3rd TAGRAHYBRID

The Chancellor of Gümüşhane University, Prof. Oktay Yıldız addresses the attendees.

The Scientific Chair of the Congress Prof. Hayrunnisa Nadaroğlu addresses the attendees.

The Organizing Chair of the Congress Assoc. Prof. Kaan Yeşilyurt addresses the attendees.

The Local Organizing Chair and Co-Chair of the Congress Prof. Ebru Emine Demirci Şüküroğlu addresses the attendees.

When complaining about the Global Warming, we should look for all the factors that might have contributed to it. So far, we blame only the increased CO2 in the atmosphere for it. Nobody seems to look for other factors that might have contributed to the Global Warming: 1/ We are at the maximum of the Big Cycle of Solar Activity of 2,562.5 years – so we didn't create the Global Warming we just made it worse. 2/ We should also consider as contributing factor the heating effect of the microwaves used in our cellular phones, TV, internet, and everything wireless because we know that the microwaves heat - we use microwaves to cook and warm food. 3/ We should also consider the fact that to avoid severe droughts artificial rain was created by shooting into the ionosphere with a powerful microwave flux (called HARP) to create a rain of ions. When these ions pass through the clouds (created by spraying chemicals), they become nucleuses of condensations and rain falls. However, shooting with powerful microwave flux should never be done toward the Sun, because this would further increase the solar activity. Also, the use of ions from the ionosphere to create rain is depleting the ionosphere, which would lead to farther warming. Also, the ionosphere holds the atmosphere, and by losing its ionosphere, the Earth will lose its atmosphere, and become uninhabitable.

Co-crystals are crystalline structures made up of two or more components in a definite stoichiometric ratio linked through non-covalent interactions in same crystal lattice. They differ in their biological and physiochemical properties from their components. They have wide applications in drug designing and in analysis of active pharmaceutical ingredients (APIs). The US-FDA approval for co-crystals to be considered as drug intermediates has opened new vistas, both in pharmaceutical and academic research sector. Present lecture will cover the results of structural modification of antileishmanial natural product and commercially available drugs by using co-crystallization. The 21 new co-crystals of anti-leishmainal Amphotericin B has synthesized by using GRAS (Generally recognized as safe) natural and semi-synthetic compounds as coformers. A range of state-of-art modern technicheues such as powder X-ray diffraction (PXRD), FT-IR, UV-Vis, 1H-NMR spectroscopy, DSC/TGA, HPLC, SEM, DLS, and AFM analyses were used to establish co-crystal formation, thermal stability, particle morphology, size distribution, and retention time behaviour. Solubility studies revealed the promising impact of co-crystallization on solubility of AmB. All synthesized co-crystals also showed least toxicity and improved anti-leishmanial activity, against promastigotes of Leishmania major, L. tropica, and L. donovani and amstigotes of L. major. Promising results of antiviral activity further broadened the pharmacological applications of the optimized co-crystals. In conclusion the presented promising results collectively demonstrate that co-crystallization can effectively modulate the pharmaceutical performance of AmB, without altering its molecular structure.

This paper examines the transformative role of Financial Technology (FinTech) in advancing sustainable finance and Environmental, Social, and Governance (ESG) investing across the BRICS economies (Brazil, Russia, India, China, and South Africa). As emerging markets navigate the dual pressures of rapid economic growth and climate change mitigation, FinTech emerges as a critical enabler of green capital allocation. By deploying advanced technologies—including Artificial Intelligence (AI), Machine Learning (ML), big data analytics, and blockchain—FinTech platforms significantly lower informational barriers, optimize data-driven ESG scoring algorithms, and reduce transaction costs for renewable energy and sustainable development projects. Furthermore, digital financial tools enhance corporate ESG transparency, mitigating risks like greenwashing while democratizing access to green bonds and retail sustainable investment products. However, the study identifies critical bottlenecks, including regulatory fragmentation, data standardization deficits, and the carbon footprint of digital infrastructure itself. The findings suggest that while FinTech serves as a potent catalyst for sustainable transition, maximizing its potential requires cohesive, cross-border BRICS green taxonomies and robust regulatory frameworks.

Inorganic hole transport layers (HTLs) play an important role in improving charge transport and the performance of photovoltaic devices. However, their electrical and interfacial properties still need to be improved. Dopant engineering is a useful approach to modify the properties of inorganic HTLs by controlling their conductivity, defect characteristics, and charge transport. This work focuses on the use of dopants to improve inorganic HTLs, particularly copper-based materials such as CuI and CuSCN, for photovoltaic applications. The effects of dopant concentration on the structural, optical, morphological, and electrical properties of the HTLs are considered. Optimized doped HTLs can improve hole extraction, reduce charge recombination, and enhance photovoltaic performance. Overall, dopant engineering provides a simple and effective approach for developing more efficient and stable inorganic HTLs for next-generation photovoltaic devices.

The microbiome–gut–brain axis is transforming neurodegenerative research by identifying gut microorganisms as regulators of brain function and immunity. Microbial dysbiosis may increase systemic and neuroinflammation, disrupt the blood–brain barrier, alter microglial activity, and promote pathological protein aggregation. Microbiota-derived metabolites influence immune signaling, neuronal survival, synaptic function, and neurovascular integrity. The novelty of this perspective lies in integrating microbiology, immunology, metabolism, and neuroscience into a unified model of neurodegeneration. This framework may support microbiome-based biomarkers and personalized interventions, including dietary modulation, probiotics, prebiotics, and postbiotics. However, causal mechanisms and clinical reproducibility remain uncertain. Future research should combine longitudinal cohorts, multi-omics analyses, mechanistic studies, and well-designed clinical trials to translate microbiome–immune–brain interactions into effective therapies.

This study the effect of post-heat-treatment routes on the microstructure, mechanical properties, and tribological behaviour of Wire-Laser Metal Deposition (Wire-LMD) fabricated Inconel 718. Initially, the Inconel 718 wire was additively manufactured with a Meltio M450 system for fabricating large and dense metallic components with minimal material wastage. The fabricated Inconel 718 was subjected to Direct Aging (DA), Solution Treatment and Aging (STA), and Homogenization plus Solution Treatment and Aging (HSTA). The microstructural evolution was examined using optical microscopy, Field Emission Scanning Electron Microscope (FESEM), and Energy Dispersive Spectroscopy (EDS) analysis to assess phase distribution and elemental homogeneity. Vickers microhardness measurements were conducted to evaluate the strengthening response due to heat treatment. Dry reciprocating wear tests were performed used ball on disc tribometer under varying normal loads to study wear behaviour, supported by 3D profilometry and worn surface morphology analysis. The as-deposited sample exhibited columnar dendrites, elemental segregation, and Nb-rich Laves phases, resulting in lower hardness and inferior wear resistance. Heat treatment significantly modified the microstructure by promoting precipitation and dissolving deleterious Laves phases. Among the investigated conditions, the HSTA treatment resulted in the highest hardness and lowest wear rate due to improved microstructural homogeneity. The study establishes a clear correlation between heat treatment, microstructure, hardness, and wear mechanisms, highlighting the effectiveness of HSTA for enhancing the tribological performance of Wire-LMD Inconel 718.

Rapid global population growth and environmental challenges demand a shift toward a resilient circular bioeconomy. Microalgae have emerged as highly efficient, self-contained photosynthetic biofactories capable of converting sunlight, water, and carbon dioxide into primary and secondary metabolites with immense industrial value. This presentation explores the multifaceted metabolic potential of microalgae, showcasing their capacity to yield high-quality protein fractions, vital marine omega-3 polyunsaturated fatty acids, and powerful high-value pigments such as astaxanthin, beta-carotene, and fucoxanthin. Maximizing the yield of these target metabolites requires balancing cultivation strategies and innovative engineering. We highlight the comparative dynamics between scalable open ponds and closed photobioreactors, demonstrating how controlled microenvironments unlock superior metabolic control. Moving beyond traditional axenic monocultures, this talk introduces a new paradigm in microalgae biotechnology: engineering deliberate microalgae-bacterial consortia within the phycosphere. By establishing functional synergies—such as co-cultivation with lactic acid bacteria—we can accelerate biological growth, improve nutritional attributes, and biologically remove the unpleasant sensory off-flavors historically associated with algal food products. To bridge production and application, we discuss the evolution of downstream processing from toxic conventional solvents toward eco-friendly green extraction technologies like Ultrasound Assisted Extraction (UAE) and Supercritical Fluid Extraction (SFE). These innovations secure clean, high-purity bioactive recoveries without thermal or chemical degradation. Finally, we demonstrate the versatile applications of these refined microalgal products across diverse sectors, including functional foods, clean-label coloring agents, and immunity-boosting aquaculture feeds. Ultimately, this framework addresses critical production hurdles to establish a comprehensive, closed-loop operating system aligning with global Sustainable Development Goals (SDGs)

With the current industrialization and its effects on the environment has led to an alarming need of valuable products from sustainable resources. With the aim of sustainable products and environmental protection different value added products from carbon dioxide using nanobiocatalysis and bioactive biopolymer from feather biomass and biopigments from microalgae, waste marigold flower biomass and fungi have been carried out. Carbon dioxide, the current escalator of temperature and concern, was used to synthesize calcium carbonate (used in cement industries) using carbonic anhydrase isolated from Cornybaterium flavescens. Microalgae (Tetradesmus obliquus), the natural sequester of CO2 has been utilized to enhance its biomass and extract medically important compounds such as lutein, an eye protector carotenoid and the microalgal biomass was used to remove synthetic dye. Further, to combat the problems of emerging pollutants such as synthetic dyes and pharmaceutical waste products (antibiotics), laccase extracted from Pleurotus florida, a fungal isolate, was used by immobilizing it on a metal organic framework(ZIF-8, ZIF-8/GO). The use of biopolymers and biopolymer based composites has also been explored in cosmetics and pharmaceuticals industry. Poultry feathers, a major bulk waste generated by the poultry industry, were utilized as a sustainable feedstock for keratin extraction, and the recovered bioactive protein was used in value-added products, including bioplastics for packaging, hydrogels and creams for wound healing, sponges for dye removal, and topical creams for skincare applications. In a separate study, a multifunctional polymeric patch was developed using chicken feather-derived keratin and Moringa oleifera extract for potential skin repair and wound healing, while Lion’s Mane (Hericium erinaceus), Reishi(Ganoderma lucidum) mushroom extract was independently investigated as a bioactive ingredient for incorporation into a patch-based topical system. Collectively, these studies highlight the potential of sustainable bioresources and waste-derived biomaterials for developing innovative, value-added products addressing environmental remediation, healthcare, and cosmoceutical applications.

Transdermal patch technologies are being investigated as potential alternatives to traditional oral nutritional supplements, particularly in cases involving challenges such as gastrointestinal imbalances, malabsorption, or limited bioavailability. The stratum corneum, the outermost layer of the skin, poses a significant barrier to the delivery of many nutrients into the body. This review evaluates current evidence, emerging delivery strategies, and the challenges associated with the transdermal administration of nutrients. Approaches discussed include chemical penetration enhancers, nanocarriers, liposomal formulations, iontophoresis, ultrasound-assisted delivery, and microneedle-based systems. These technologies aim to enhance skin permeability and facilitate controlled nutrient release. Current findings indicate that the evidence varies significantly depending on the type of nutrient and the delivery platform employed. While human studies have focused on transdermal vitamin D administration, research on vitamin B12, vitamin K, iron, and magnesium relies largely on preclinical, in vitro, or ex vivo evidence. Microneedle-based systems are particularly promising; however, successful nutrient loading and skin penetration do not always guarantee systemic bioavailability or clinical efficacy. Key challenges include dose control, delivery efficiency, long-term safety, manufacturing standardization, and a lack of sufficient clinical data. Furthermore, wearable and smart patch technologies may offer future opportunities to integrate nutrient delivery with biomarker monitoring and personalized nutrition practices. However, further validation of these applications is required. In conclusion, while transdermal patch technologies represent an emerging field in nutritional science, their clinical role has not yet been fully defined. Well-designed human clinical studies focusing on specific nutrients are needed to determine the safety, bioavailability, and efficacy of these methods, as well as their potential contributions to personalized nutritional care.

This study investigates the performance and efficiency of a perovskite solar cell through numerical simulation. The main objective is to evaluate the electrical characteristics of the device and to determine the key parameters affecting its photovoltaic efficiency. A perovskite-based solar cell structure was modeled by defining the electrical and optical properties of the absorber layer, electron transport layer, hole transport layer, and contact materials. The effects of selected device parameters, including absorber layer thickness, defect density, carrier concentration, and material properties, were analyzed systematically. The performance of the simulated solar cell was evaluated in terms of open-circuit voltage (Voc), short-circuit current density (Jsc), fill factor (FF), and power conversion efficiency (PCE). The simulation results demonstrate that the optimization of layer properties and device parameters has a significant influence on overall cell performance. In particular, appropriate control of the absorber layer and charge transport characteristics contributes to reduced recombination losses and improved charge collection. The findings indicate that numerical simulation provides an effective approach for predicting the behavior of perovskite solar cells and identifying suitable design parameters before experimental fabrication. This study therefore contributes to the optimization of perovskite photovoltaic devices and supports the development of high-efficiency, cost-effective solar energy technologies.

Transformer overloading in densely populated urban distribution networks is a critical challenge during peak consumption hours. While traditional Flexible AC Transmission Systems (FACTS) are cost-prohibitive, Continuously Variable Series Reactors (CVSRs) offer a highly economical alternative (approximately $10/kVAr) by regulating transformer reactance—up to a maximum of 3 Ohm—via magnetic core saturation. To maximize economic benefits, it is crucial to minimize the number of CVSR devices deployed. This study investigates the optimal placement of CVSR devices across the 48 secondary network transformers of the highly meshed IEEE 342-Node Low Voltage Networked Test System (LVNTS). Four distinct analytical approaches are compared: the Shortest Path, Loading-Based, Transformer Sensitivity-Based, and Piecewise Optimization (MILP) algorithms. A co-simulation framework coupling MATLAB and OpenDSS was utilized to evaluate these algorithms under severe conditions, including a system-wide load increment and area-based load surges. The findings reveal that while graph-theory and loading-based methods offer rapid computational times, they often fail to capture the localized, non-linear dynamics of overloaded nodes accurately. Conversely, the Piecewise Optimization-Based method—formulated as a Mixed-Integer Linear Program (MILP)—demonstrated superior accuracy. By approximating non-linear power flow curves into multiple linear segments, this algorithm successfully identified the exact transformers requiring intervention and maintained all power flows strictly below the 1 MVA limit. The results indicate that utilizing piecewise sensitivity matrices for CVSR allocation provides distribution system operators with a highly precise and cost-effective strategy to alleviate congestion and defer grid upgrades.

Using rainwater as an alternative water source requires treatment approaches that reduce pollutants under real environmental conditions. In this study, a sensor-controlled treatment system based on a poly(vinyl alcohol) (PVA) nanofiber membrane doped with nut husk-derived activated carbon (NHAC) was developed to remove metals from actual rainwater and was operated in the field during rainfall events. The activated carbon was produced by chemically activating nut husks with K₂CO₃ and incorporated into PVA nanofiber membranes prepared by electrospinning. The membrane was integrated into an automated system comprising a rain sensor, an Arduino UNO control unit, and a motor-controlled cover mechanism. The system's performance was evaluated using actual rainwater samples collected in Gümüşhane province, without adding artificial metals. Elemental concentrations before and after treatment were determined using ICP-MS. Reductions were observed primarily in Fe and Pb levels, followed by decreases in Cr, Zn, Cu, Ni, and As concentrations; the water quality from the two-stage filtration process was compared against TSE standards to assess its suitability for domestic use. The device, which performed successfully under the examined field conditions, combines agricultural bio-waste-derived activated carbon with nanofiber membrane filtration and sensor-controlled automation. The findings support the viability of this configuration for treating actual rainwater. Acknowledgment: This study was supported by TÜBİTAK under the 2209-A University Students Research Projects Support Program (Project No: 1919B012513305).

Metal-semiconductor-metal (MSM) photodetectors are strong candidates for high-speed optical receivers and ultraviolet sensing owing to their planar structure, single-step lithographic fabrication, low capacitance and compatibility with field-effect transistor technology. However, MSM performance depends not only on the absorber material but also on the electrode geometry and the physics of the metal-semiconductor interface. Reducing the finger spacing increases speed but also increases shadowing, while raising the Schottky barrier height suppresses dark current. These competing effects turn device design into a multi-parameter optimization problem and make experimental exploration costly. In this work, MSM photodetectors are modeled in SCAPS-1D as an equivalent one-dimensional structure consisting of two back-to-back Schottky contacts. The Poisson, continuity and drift-diffusion equations are solved together with the Shockley-Read-Hall recombination model at 300 K, and the model is validated against experimental results reported in the literature. Absorber thickness (0.5–5 µm), contact work function (4.3–5.65 eV), doping and defect densities, bias voltage (−5 V to +5 V), temperature and interlayer thickness are systematically varied. Shadowing, carrier transit time and the RC limit specific to the interdigitated electrode structure are incorporated through analytical corrections. Dark current, photo-to-dark current ratio, quantum efficiency, responsivity, specific detectivity, noise equivalent power and 3 dB bandwidth are extracted, and the speed-efficiency trade-off is evaluated using the bandwidth-efficiency product. By comparing Si, GaAs, GaN and heterostructure options, the study aims to identify optimal design ranges for high-speed, high-responsivity and low-noise scenarios. The work is expected to provide a quantitative design guideline for experimental MSM photodetector studies without resorting to costly fabrication processes.

Background: Benzodiazepines are widely used central nervous system-active drugs, and their sensitive determination in aqueous and biological matrices requires efficient sample preparation and preconcentration techniques. Carbon nanotubes, owing to their high surface area and adsorption capacity, have potential as effective sorbents for solid-phase extraction.
Objective: This study aimed to develop a functionalized carbon nanotube-based solid-phase extraction method for the preconcentration and determination of two benzodiazepines, diazepam and lorazepam, in aqueous samples.
Methods: Single-walled carbon nanotubes were chemically functionalized with A174 silane using a sol-gel-based approach. Surface functionalization was characterized by Fourier-transform infrared spectroscopy. The extraction performance of functionalized and unfunctionalized carbon nanotubes was compared. Important extraction parameters, including desorption solvent, adsorption and desorption times, sorbent amount, pH, adsorption temperature, and solvent volume, were systematically optimized. Diazepam and lorazepam were separated and quantified using gas chromatography coupled with mass spectrometry operated in selected-ion monitoring mode.
Results: Functionalization of the carbon nanotubes with A174 silane substantially improved their extraction performance compared with unfunctionalized carbon nanotubes. Under optimized conditions, the calibration data demonstrated good linearity. For lorazepam, the correlation coefficient was 0.9993 in the 0.01–400 ppm range, with a limit of detection (LOD) of 158.64 ppb, limit of quantification (LOQ) of 475.91 ppb, and relative standard deviation (RSD) of 2.80%. For diazepam, the corresponding correlation coefficient was 0.9985, with an LOD of 24.76 ppb, LOQ of 74.26 ppb, and RSD of 3.82% over the same concentration range. Additional calibration ranges extending to 4000 ppm were also evaluated.
Conclusion: A174-silane-functionalized carbon nanotubes provided an efficient sorbent for the solid-phase extraction and preconcentration of diazepam and lorazepam. The developed procedure showed good linearity, low detection limits, satisfactory repeatability, short extraction time, and low consumption of organic solvents, indicating its potential for analytical applications involving pharmaceutical compounds in aqueous samples.

Mycotoxins, known for their high toxicity, pose significant challenges to food safety and public health. They garner attention due to their widespread occurrence in food products and their ability to exert toxic effects even at low concentrations. Among these toxins, aflatoxin B1 (AFB1) is of particular importance due to its potent hepatotoxic, mutagenic, and carcinogenic properties. Detecting AFB1 in food and feed is crucial for safeguarding consumer health. Currently, toxins can be analyzed using various techniques—such as high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC-MS), and immunological methods—that require expensive instrumentation and specialized personnel. However, technological advancements have accelerated efforts to develop simpler, faster, more sensitive, and portable analytical systems. Carbon quantum dots (CQDs) are nanomaterials suitable for high-performance sensor applications, thanks to their strong fluorescence, excellent water dispersibility, surface functional groups, and ease of modification. Deriving CQDs from renewable carbon sources, such as plants and agricultural waste, further enhances their value in the context of sustainable nanotechnology. Additionally, incorporating metal ions into the CQD structure allows for the modulation of the material's electronic and optical properties, thereby improving sensor performance. This presentation provides a comprehensive overview of our group's research on utilizing carbon quantum dots derived from plant and agricultural sources for the detection of AFB1. It has been demonstrated that CQDs derived from plant-based waste and modified with metal NPs interact with AFB1, resulting in a fluorescence change that can be utilized for the detection of the toxin. Results obtained from real food samples have further supported the potential application of these nanomaterials in the field of food safety and yielded remarkable findings.

This study investigates the antioxidant and antimicrobial potential of the methanol extract (ME) obtained from Bornmuellera cappadocica (Willd.) Cullen & T.R.Dudley, alongside the silver nanoparticles (BCAgNPs) green-synthesized using this botanical extract. The antioxidant activities of ME and BCAgNPs were examined by DPPH and ABTS radical scavenging methods, iron (III) reducing antioxidant power (FRAP) test, total phenolic substance (TPC), total flavonoid substance (TFC) and total antioxidant capacity (TAC) values. Antimicrobial activities, agar well diffusion method and minimum inhibitory concentration (MIC) values against six bacterial and one yeast strains were examined. According to the antioxidant analysis results, the TPC and TFC contents of the methanol extract were determined as 56.18 mg GAE/g and 22.65 mg QE/g, respectively, while these values for BCAgNPs were found to be 321.53 mg GAE/g and 102.88 mg QE/g, respectively. TAC was determined as 96.08 mg AAE/g in methanol extract and 581.65 mg AAE/g in BCAgNPs. In DPPH and ABTS analyses, the IC₅₀ values of ME were 2147.49 µg/mL and 1091.75 µg/mL, respectively, while these values for BCAgNPs were 148.98 µg/mL and 304.59 µg/mL. FRAP values were determined as 58.72 mg FeSO₄/g and 64.69 mg FeSO₄/g for ME and BCAgNPs, respectively. These results revealed that BCAgNPs exhibited higher antioxidant activity compared to ME. In antimicrobial assays, ME did not show any measurable antimicrobial activity. BCAgNPs created 12.23–16.63 mm inhibition zones against all test microorganisms, and the highest inhibition zone was determined in the Escherichia coli ATCC 25922 strain. MIC values are in the range of 0.078–0.315 mg/mL and the lowest MIC value was detected against Klebsiella pneumoniae ATCC 13883 strain. Moreover, BCAgNPs showed antifungal activity against Candida albicans ATCC 18804 with an inhibition zone of 14.56 mm and a MIC value of 0.149 mg/mL.

This study aimed to determine the phenolic compound profile of the methanol extract of Bornmuellera cappadocica (Willd.) Cullen & T.R.Dudley (Brassicaceae) and to comparatively evaluate the enzyme inhibitory activities of the extract and the silver nanoparticles (BCAgNPs) green-synthesized using this extract. The phenolic compound profile of the methanol extract was determined using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The enzyme inhibitory activities of the extract and BCAgNPs were assessed based on half-maximal inhibitory concentration (IC₅₀) values determined against carbonic anhydrase-II (CA-II), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and α-glucosidase enzymes. LC–MS/MS analysis revealed the quantitative presence of five phenolic compounds in the methanol extract. p-Coumaric acid was identified as the predominant phenolic compound, with a concentration of 231.911 µg/g of extract, followed by chlorogenic acid (184.613 µg/g) and resveratrol (76.381 µg/g). The total content of the identified phenolic compounds was calculated to be 559.847 µg/g of extract. The high levels of p-coumaric and chlorogenic acids, in particular, demonstrated that the extract possesses a noteworthy composition regarding hydroxycinnamic acid derivatives. In enzyme inhibition assays, the IC₅₀ values of the methanol extract against CA-II, AChE, BChE, and α-glucosidase enzymes were determined to be 1.126 mg/mL, 0.00304 mg/mL, 0.00754 mg/mL, and 0.0275 mg/mL, respectively. For BCAgNPs, the IC₅₀ values for the same enzymes were found to be 0.102 mg/mL, 0.125 mg/mL, 0.145 mg/mL, and 0.00013 ± 0.0000163 mg/mL, respectively. These results indicate that BCAgNPs exhibited higher inhibitory activity than the methanol extract against CA-II and α-glucosidase enzymes, but lower inhibitory activity against AChE and BChE enzymes. In conclusion, it was demonstrated that the B. cappadocica methanol extract contains various phenolic compounds primarily p-coumaric acid and chlorogenic acid and that both the extract and the green-synthesized silver nanoparticles exhibit varying inhibitory activities depending on the enzyme type.

Non-Newtonian calculus offers alternative frameworks for studying functions with different analytical structures. This study presents a first-order local approximation method for mixed-type functions containing classical and non-Newtonian components. In the proposed method, each component is approximated within its corresponding calculus, and the resulting approximations are combined according to the structure of the original function. The method is applied to a function containing exponential and double-exponential components. Its local behavior is compared with that of the classical first-order Taylor approximation through absolute and relative error analysis. In the example examined, the proposed method produces smaller approximation errors near the expansion point. This finding suggests that retaining the structure of the individual components can improve the local representation of mixed-type functions.

Stress concentration is the local increase in stress caused by geometric discontinuities and is quantified by the theoretical stress concentration factor. In shafts, the change in diameter at the shoulder is a typical source of stress concentration and a common site of fatigue failure. Stress concentration factors for solid shouldered shafts are well documented, but data for hollow shafts are limited. In this study, the effect of the inner diameter on the stress concentration factor in shouldered shafts under axial tension was investigated by finite element analysis using ANSYS Workbench. Two-dimensional axisymmetric linear elastic analyses were performed. A matrix of 150 geometries was analyzed for D/d = 1.05-2.0, r/d = 0.025-0.3, and di/d = 0-0.8, where D and d are the larger and smaller shaft diameters, r is the fillet radius, and di is the inner diameter of the shaft. The model was validated against published data for solid shafts. The variation of the stress concentration factor with di/d and r/d was determined, and the results were compared with those for solid shafts. The results show that the stress concentration factor increases with increasing di/d, and the parametric data obtained in this study provide design charts for hollow shouldered shafts under axial tension.

The anageometric Laplace transform has been formulated for scalar differential equations, but its use in coupled systems requires an explicit matrix-based treatment. This study applies the transform to linear systems of anageometric differential equations with constant coefficients and continuous forcing. The anageometric derivative is defined by D̃f(t) = t f′(t) for t ≥ 1, and the transform is taken with respect to the measure dt/t. Applying the derivative rule componentwise converts an initial value problem into a system of algebraic equations involving the matrix resolvent. A logarithmic change of time then yields an explicit solution formula and establishes uniqueness under the stated assumptions. Two coupled examples demonstrate the method. In a triangular system with forcing, inversion produces power-law terms together with a logarithmic term associated with a repeated transform-domain pole. In a two-component rotational system, the solutions are oscillatory functions of ln t and remain bounded. Direct substitution verifies the equations and initial conditions in both examples. The analysis shows precisely how classical linear-system tools transfer to the anageometric setting through logarithmic time. The matrix formulation also makes the effects of coupling visible in the transformed equations and in the resulting solutions. Its scope is limited to the system class and assumptions stated here; it does not claim a general solution method for nonlinear systems.

The purpose of this study was to analyze the three-dimensional stress distribution in a journal bearing using a one-way coupled Computational Fluid Dynamics (CFD) and Fluid–Structure Interaction (FSI) model. Numerical simulations were performed using ANSYS 2023 R2 software. The hydrodynamic pressure distribution was obtained under laminar, isothermal, steady-state conditions at an eccentricity ratio of 0.6, with a radial clearance of 0.04 mm, a journal speed of 1200 rpm, and a lubricant dynamic viscosity of 0.022 Pas at 70 °C. The attitude angle was determined through a two-step approach. First, a preliminary model with vertical eccentricity was simulated, and the load-carrying capacity components (Fx, Fy) were obtained by integrating the pressure over the journal surface. The attitude angle was then calculated from the arctangent of these components, and the geometry was rebuilt accordingly for the FSI analysis. The Gumbel boundary condition was applied in the divergent region. The numerical model was verified against a finite difference solution of the Reynolds equation under the same boundary condition, following the approach used in previous CFD–FSI studies. The resulting pressure field was applied as a load to the inner surface of a ZA-27 journal bearing. The full-field distribution maps of the stress components on the bearing surface, including axial, radial, tangential, maximum shear, and von Mises stresses, were determined. The CFD results revealed a pressure field concentrated in the convergent region, with a parabolic profile in the axial direction reaching a maximum at the mid-plane and decreasing towards the edges. The FSI analysis revealed that the stress field was concentrated at the periphery of the pressurized region, where the pressure gradients were highest. The tangential stresses were compressive within the pressurized region and tensile at its periphery, where the pressure gradients are largest.

Historic stone arch bridges are important cultural heritage structures that may develop different collapse mechanisms under seismic actions due to their traditional construction techniques, masonry material properties, and distinctive geometries. Evaluating the seismic behavior of these structures requires understanding how their geometric and mechanical characteristics affect their collapse capacity. This study aims to evaluate the seismic collapse capacity of historic stone arch bridges using a limit analysis approach and to investigate the influence of key parameters. Within the scope of the study, representative bridge geometries will be defined based on available inventory records, accessible visual sources, and literature data. Geometric and mechanical properties not directly specified in the available sources will be addressed through explicitly stated engineering assumptions. Following the development of the analytical model, potential collapse mechanisms and limit capacities of the bridges under seismic actions will be investigated. Furthermore, analyses conducted using different values of selected geometric and mechanical parameters will be used to evaluate changes in collapse capacity and possible variations in collapse mechanisms. The study is expected to contribute to the mechanism-based assessment of the seismic behavior of historic stone arch bridges and to improve understanding of the effects of geometric and mechanical characteristics on their collapse capacity. The findings are intended to provide a basis for preliminary seismic assessment of historic bridges with similar characteristics and for more comprehensive structural analyses in future research.

This study evaluated mineralized groundwater potential for sustaining the Ayazma Travertine using electrical resistivity tomography (ERT) and topographic data. Low-resistivity anomalies identified along three ERT profiles were interpreted together with a previously observed iron-rich mineralized water discharge near point S. Anomalies occur at profile distances of 65–90 m on E-1, 105–145 m on E-2, and 95–115 m on E-3, indicating a conductive zone within the same general area. Resistivity on E-2 decreases to approximately 7–20 Ωm. These findings identify the vicinity of point S as a priority target for exploratory drilling. The estimated primary target depth is 15–30 m; drilling to 40–50 m is recommended to investigate potentially fractured and permeable surrounding intervals. The feasibility of conveying water from the potential source to point S′ at the travertine site was also assessed preliminarily. Although point S is approximately 3 m higher than point S′ along a route of about 650 m, intervening topographic rises mean that gravity-fed conveyance cannot be established from endpoint elevations alone. Pipeline design must account for hydraulic losses and air accumulation. A siphon system may be examined, with low-head pumping considered if gravity-fed conveyance proves infeasible. The interpretation of the ERT anomalies as mineralized groundwater, sustainable source yield, and suitability of the water for travertine deposition require confirmation through drilling, discharge measurements, and hydrogeochemical analyses.

In the modeling of soil-structure interaction (SSI) using the finite element method, the dimensions of the finite soil domain and the boundary conditions can affect the calculated dynamic properties of the system. This study used the five-story reinforced concrete frame structure examined by Kamal et al. (2022) as a reference to create three-dimensional soil–structure interaction models using ANSYS software and investigated the effect of soil geometry on the system’s dynamic behavior. The soil depth was set to 45 m, the raft foundation dimensions (B×L) to 25×20 m, and the soil mesh size to 1.25 m. Bottom boundary conditions were fixed for the soil region, while viscous boundary conditions were applied to the horizontal boundaries. The plan dimensions of the soil, while remaining the same in the X direction, were modified in the Y direction by taking 2, 4, 5.5, and 6.5 times the length of the structure’s edge in the Y direction (20 m), resulting in 110×40 (Model-1), 110×80 (Model-2), 110×110 (Model-3), and 110×130 (Model-4). When the dominant periods in the X and Y directions were evaluated based on the modal analysis results, negligible differences were observed in the X direction. In the Y direction, however, the differences decreased as the dimensions increased and became negligible after Model-3. Furthermore, the models were analyzed under the effects of the Erzincan earthquake, revealing that the ground geometry had an impact on the dynamic responses. The results demonstrated that the distance of the boundaries in the soil region from the structure can influence the directional system behavior. The findings indicate that in direct ZYE analyses, the dimensions of the soil region must be evaluated not only in terms of computational cost but also to minimize boundary effects and obtain reliable dynamic system characteristics.

Historic masonry houses require a specialized approach to seismic assessment due to their use of local materials, traditional construction techniques, and distinctive structural system characteristics. The extent to which existing rapid visual screening methods represent the characteristic features of these buildings is important for reliably prioritizing the historic building stock. This study aims to critically examine the representativeness of existing methods for the seismic assessment of historic masonry houses through a parameter-based approach. To this end, international rapid visual screening methods, parameter-based seismic vulnerability assessment approaches for masonry buildings, a rapid screening method developed in Türkiye, and a regulatory framework for risk identification will be comparatively examined through a literature review. The assessment will consider the material and masonry characteristics of load-bearing walls, wall thickness, the location and dimensions of openings, the number of stories, plan and vertical irregularities, floor and roof systems, wall connections, and observable material deterioration. In addition, the extent to which the material-specific and construction-related characteristics of historic stone, brick, and adobe masonry houses are reflected in existing assessment parameters will be investigated. The study will identify the common assessment criteria, application limitations, and capacity of different methods to represent the distinctive characteristics of historic buildings. The findings are expected to contribute to the selection of appropriate methods for the preliminary seismic assessment of traditional masonry houses and to the development of assessment criteria that better reflect the characteristics of historic buildings.

In this study, magnetic magnetite nanoparticles were synthesized and modified for the covalent immobilization of lipase. Magnetic nanoparticles have attracted considerable attention due to their applications in catalysis, water treatment, biotechnology, biomedicine, and drug delivery. Magnetite nanoparticles with an approximate size of 10–20 nm were prepared using the co-precipitation method under optimized conditions. The synthesis was conducted in an alkaline medium under a nitrogen atmosphere to minimize the oxidation of Fe(II) ions and prevent the formation of unwanted iron oxide phases. The synthesized nanoparticles were characterized by infrared (IR) spectroscopy and subsequently coated with silica using a sol-gel process involving tetraethyl orthosilicate (TEOS). The silica coating protected the magnetic core and provided a suitable surface for functionalization. The nanoparticles were further modified with 3-aminopropyltriethoxysilane (APTES) to introduce amino groups and improve surface properties, facilitating enzyme attachment. Lipase was covalently immobilized onto the functionalized magnetic nanoparticles. This approach aims to improve enzyme stability, facilitate magnetic separation, and enable enzyme recovery and reuse. The high surface-to-volume ratio of nanoparticles also provides favorable conditions for enzyme loading and catalytic performance. IR spectroscopy was used to characterize the nanoparticles at different stages of synthesis and modification. Characteristic absorption bands associated with Fe–O and Si–O bonds confirmed the formation of magnetite and the silica coating, while changes in the spectra indicated successful surface functionalization and enzyme immobilization. Finally, atomic absorption spectroscopy was employed to compare free and immobilized lipase and investigate parameters affecting enzyme performance. The study highlights the potential of functionalized magnetic nanoparticles as effective supports for enzyme immobilization, offering advantages in enzyme recovery, operational stability, and reusability.

The use of carbon nanotubes as a solid phase of the extraction of both organic and inorganic compounds provides sufficient absorption capacity. It is also used as a new material in a solid-phase microextraction. Solid phase extraction of some polycyclic aromathic hydrocarbons (PAHs) (naphthalene, anthracene and pyrene) from aqueous solution using carbon nanotubes (CNT) has been investigated. In the carbon nanotubes, which have a covalently modified surface, a change in selectivity is seen. Single wall carbon nanotubes with carboxyl groups have been used as solid substrate for chemical surface-activation by the 3-(Aminopropyl) trimethoxysilane (APTMS). The sol gel technique is used to modify of carbon nanotube surfaces. Selection of the appropriate solvent for carbon nanotube dispersion and optimal operating conditions have been performed. Using the infrared spectroscopy, the characteristics of the modified surface have been studied. Gas chromatography equipped with a mass detector was used to isolate, detect and measure quantitatively naphthalene, anthracene and pyrene, and a mass detector is planned for the selected ion monitoring (SIM) mod. Parameters such as adsorbent solvent, adsorption time, adsorbent solvent, adsorbent amount, pH, absorption temperature and desorption temperature that affect the extraction efficiency were optimized. For the studied method for naphthalene, anthracene and pyrene, respectively, the limits of detections (ppb) 187.61, 51.46 and 139.45 , the limit of Quantitation (ppb) 562.83, 154.35 and 418.21, the linear dynamic range (ppm) 0. 1-4000 for all, the relative standard deviation (n=5) 4.33, 3.25 and 3.12 has been achieved.

Organophosphorus pesticides are extensively used in agricultural applications, and their residues in aquatic environments have raised significant environmental and analytical concerns. In this study, a solid-phase extraction method based on functionalized single-walled carbon nanotubes (SWCNTs) was developed for the extraction and preconcentration of diazinon and malathion from aqueous samples prior to gas chromatography–mass spectrometry (GC–MS) determination. Carboxylated SWCNTs were functionalized with different organic modifiers, including diphenylmethanol, benzyl alcohol, and cyclohexanol, and their extraction performances were comparatively evaluated. Among the investigated sorbents, diphenylmethanol-functionalized carbon nanotubes exhibited the highest extraction efficiency and were therefore selected for further optimization. The effects of several experimental parameters, including desorption solvent, extraction and desorption times, sorbent amount, sample pH, extraction and desorption temperatures, and solvent volumes, were systematically investigated. Acetonitrile showed the highest desorption efficiency for both analytes and was selected as the optimum desorption solvent. A sample pH of 7 was selected for subsequent experiments to achieve efficient extraction while minimizing possible pesticide degradation. The extracted analytes were determined by GC–MS using selected ion monitoring (SIM). Characteristic ions at m/z 125, 173, and 93 were monitored for diazinon, whereas m/z 179, 152, and 137 were used for malathion. The results demonstrated that surface functionalization of carbon nanotubes, particularly with diphenylmethanol, enhanced their extraction performance toward the investigated organophosphorus pesticides. The developed approach provides a simple and effective strategy for the extraction and preconcentration of diazinon and malathion from aqueous samples and demonstrates the potential application of functionalized carbon nanotubes as sorbents for trace pesticide analysis.

Multiservice software-defined networks (SDNs) must deliver multimedia traffic with different service requirements while maintaining acceptable delays and efficient use of limited channel capacity. This study addresses the challenge of distributing traffic flows when transmission patterns are variable and self-similar, making timely delivery difficult to assess. We develop a stochastic mathematical model of a converged SDN to evaluate probabilistic and temporal performance characteristics and formulate flow distribution in terms of network efficiency and the probability of timely message delivery. The model accounts for channel capacity and traffic self-similarity. To support intelligent traffic analysis, we classify traffic flows using the Random Forest algorithm implemented in Python's scikit-learn library. The resulting traffic classes are considered alongside the model's performance indicators to inform routing decisions. The analysis establishes a framework for relating traffic characteristics and channel constraints to the evaluation of delivery timeliness and flow allocation. It also shows how machine-learning-based traffic classification can be incorporated into the construction of SDN routing tables and network-layer packet management. These findings provide a methodological basis for jointly considering statistical traffic behavior, classification, and routing optimization rather than treating them as separate tasks. The proposed approach can support adaptive management of multiservice telecommunication networks and the delivery of multimedia services under changing traffic conditions. Further experiments are needed to quantify improvements in delay, delivery probability, and resource utilization across a range of traffic loads and service classes.

This study examined software projects completed and presented in the Computer Programming program of a vocational school in terms of the problems they addressed, their target users, and their artificial intelligence functions. This descriptive document analysis evaluated the final reports of 29 software projects deemed suitable for examination. The reports were classified by problem domain, target user, the status of the artificial intelligence function within the existing product, and the described technical mechanism. Using a rubric adapted from the Conceive–Design–Implement–Operate (CDIO) framework, we also coded how well the reports described the problem, user, design, and implementation. The projects primarily focused on business, commerce, and food services (n=6); education and learning (n=5); and healthcare services (n=4). Eight reports presented the artificial intelligence function as part of the existing product, while two reports presented it as a future development. Among the eight reports describing an existing function, four detailed model or service integration, three explained threshold or matching rules, and one did not specify a technical mechanism. Using coding adapted from CDIO, 21 reports explicitly described the problem, 22 the target user, 26 the design, and 27 the implementation. The "operate" (usage) phase was not coded because this analysis did not include records of presentation evaluations. The findings indicate that students developed software projects addressing diverse user needs and employed various technical mechanisms for the functions they labeled as "artificial intelligence." For future projects, students should clearly define the problem they aim to solve and the target user, and explain using concrete examples how user needs are reflected in design decisions and the functions developed.

In this study, Ground Penetrating Radar (GPR) was used to investigate continuous water discharge approximately 3 m below a retaining wall and assess possible leakage from a buried main wastewater pipeline or its building connections. Nine profiles (Lines 34–42) were acquired approximately parallel to the pipeline, and eleven profiles (Lines 49–59) approximately perpendicular to it at 0.30 m spacing. The sections were interpreted by comparing reflector continuity, amplitude, electromagnetic attenuation, and localized signal disruption. The parallel profiles showed strong shallow reflections and local heterogeneity, but no pronounced attenuation indicative of a major active leak. In the perpendicular profiles, disturbed reflector continuity and an altered electromagnetic response were observed near the pipeline axis between Lines 53 and 56, most clearly around Lines 54–55. Based on the assumed propagation velocity, the anomaly lies at an estimated depth of 1.0–1.5 m. The absence of widespread signal loss across adjacent profiles reduces the likelihood of a major pipeline rupture. The anomaly could reflect trench backfill heterogeneity, a low- to moderate-discharge leak at a pipe joint, or water entering the trench from a building connection. Water may also travel laterally through permeable bedding before emerging at the retaining wall, so the discharge point may not lie directly above its source. The pipeline axis near Lines 54–55 is the priority area for verification. CCTV inspection of the main pipeline and connections, controlled water injection into individual connections, and simultaneous monitoring of retaining-wall discharge are recommended. The results show how closely spaced GPR profiles can help prioritize targeted investigation of suspected underground leaks.

In modern video surveillance systems, the large area under observation and the varying distances of objects from the camera may reduce the informational value of the captured images. In particular, small and distant objects are represented by a limited number of pixels within the camera frame, making their detection and subsequent analysis more difficult. To address this problem, instead of relying solely on a camera operating in a fixed position, it is appropriate to enable the camera to automatically change its orientation according to the movement of the observed object and, when necessary, perform optical zooming. This study presents a system approach based on the detection of moving objects from image sequences, determination of their direction of movement, automatic orientation of the camera toward the detected object, and automatic optical zooming depending on the object's size within the frame. Following the initial image preprocessing stage, differences between consecutive frames are calculated to identify moving regions, while morphological processing is applied to reduce the influence of incidental image changes. For each detected object, a characteristic tracking point is determined, and the displacement of this point relative to previous frames is used to control the camera's movement. When the object's movement and its size within the image satisfy predefined conditions, optical zooming is activated. Such an approach enables distant and small objects to be maintained at a more suitable size within the image, thereby facilitating their observation and subsequent analysis.

Motion capture systems enable ergonomic risks to be assessed based on actual working conditions by recording operators’ movements during work. This study aimed to ergonomically improve a workstation where repetitive assembly operations are performed. First, a standard workstation was established, and operator movements were recorded using the Xsens system and transferred to the Siemens Process Simulate v2502 environment. Subsequently, the worktable height (94, 85, and 82 cm), the position of the parts rack, and the arrangement of material containers and work equipment on the table were examined in three separate scenarios. The scenarios were evaluated using the OWAS, RULA, and REBA methods, as well as analyses of estimated recovery time and the time-dependent variation in muscle strain. The arrangements found to be appropriate based on the analyses were combined to create an improved workstation. In the reference layout, 82.95% of the OWAS scores were classified as Category 4 and 17.05% as Category 3, whereas all scores in the improved layout were classified as Category 2. At the point when the two-handed reaching task was examined, the RULA score, which was 7 for both arms in the reference layout, decreased to 5 for the left arm and 4 for the right arm; similarly, the REBA score, which was 8 for both arms, decreased to 5 and 4, respectively. These findings indicate that digital ergonomic analyses supported by motion capture data can contribute to improving individual working conditions and developing operator-specific work standards.

Adhesive bonding is widely used in composite and polymer-based structures to join different materials due to its advantages, including low weight, uniform load transfer, and reduced stress concentrations. Since interfacial interactions and the mechanical performance of the adhesive are decisive in bonding different materials, modifying adhesives with nanosized additives is considered an effective approach to improving bonding performance. This study experimentally investigates the tensile behavior of single-lap adhesive joints (SLJ) composed of glass fiber/epoxy composite plates, produced by hand lay-up, and polylactic acid (PLA) plates fabricated using a 3D printer. The glass fiber/epoxy composite plates were manufactured using six-layer glass fiber fabric and a Hexion Epicote Resin MGSLR 635 epoxy resin with a Hexion Epicote Curing Agent MGH LH 635 hardener system. Six joint groups were prepared, representing three material combinations: glass fiber–glass fiber (GF–GF), glass fiber–PLA (GF–PLA), and PLA–PLA. Araldite® 2015-1 adhesive, modified with 0.5% by weight nano-Ag particles and unmodified, was used to bond the joints. The SLJ samples were subjected to tensile testing at a rate of 1 mm/min, and the resulting load-displacement curves were comparatively evaluated. The findings demonstrate the influence of nano-Ag reinforcement on the load-carrying capacity and deformation behavior of bonded joints with different material combinations. Experimental results revealed that adding 0.5% nano-Ag to the adhesive improved bonding performance across all sample groups. With nano-Ag modification, the maximum tensile loads of GF–GF, GF–PLA, and PLA–PLA bonds increased by 3.99%, 10.60%, and 120.98%, respectively; the largest increases in relative strength and ductility were recorded in the PLA–PLA joint group.

The 7xxx series aluminum alloy AA 7020 is widely used in engineering applications because of its low density, high strength, good corrosion resistance, and weldability. AA 7020 reaches its maximum strength in the T6 temper. Although AA 7020-T6 is readily weldable, the heat generated during welding can alter the microstructure near the weld, particularly in the heat-affected zone (HAZ), and increase its susceptibility to stress corrosion cracking (SCC). This susceptibility limits the use of welded AA 7020-T6 in corrosive environments. Electric arc spray coating (EASC) is a thermal spraying process used for corrosion protection. It is valued for its relatively low cost and broad range of applications. In this study, aluminum-based Al99.99, AlMg5, and AlZn2 coatings were applied to welded AA 7020-T6 specimens by EASC to investigate whether they could reduce SCC susceptibility. After welding, the AA 7020-T6 specimens were divided into four groups. The control specimens were left uncoated, while the three experimental groups were coated with Al99.99 (commercially pure aluminum), AlMg5, and AlZn2, respectively. SCC tests were conducted based on ISO 7539. For each group, the ductility ratio was calculated by dividing the elongation at break in the corrosive environment by the elongation at break in the dry laboratory environment. The uncoated control group exhibited the lowest SCC resistance. Among the coated groups, SCC resistance followed the order AlZn2 > Al99.99 > AlMg5.

Magnesium and its alloys are among the metallic materials attracting attention for biomedical applications due to their low densities, elastic moduli close to those of natural bone, and biodegradable properties. The micro-arc oxidation (MAO) method, used to modify the surface properties of these alloys, is an effective electrochemical surface treatment technique that enables the formation of ceramic-based oxide layers on the surface. Modifying the electrolyte composition with various additives during the MAO process enables the incorporation of different constituents into the coating structure and the development of composite oxide coatings. In this regard, cerium (Ce) is an element that attracts interest in biomaterial research due to its significant functions in biological systems. This study aims to investigate the applicability of producing cerium dioxide (CeO2)-doped composite coatings on WE43 magnesium alloy via the MAO method and the possibility of incorporating Ce-containing constituents into the coating structure. For this purpose, oxide coatings were formed on the surface of the WE43 alloy using the MAO method with undoped and CeO2-doped electrolytes. The phase structure of the resulting coatings was examined using X-ray diffraction (XRD), surface morphology by scanning electron microscopy (SEM), and elemental composition by energy-dispersive X-ray spectroscopy (EDS). SEM analyses revealed that a characteristic porous oxide coating structure formed on the WE43 alloy surface following the MAO process and that the addition of CeO2 caused changes in the coating’s surface morphology. While EDS analyses confirmed the presence of Ce in coatings produced using a CeO2-containing electrolyte, XRD analyses enabled the evaluation of the coatings’ crystalline phase structure. The results demonstrated that Ce-containing MAO composite coatings could be successfully produced on the WE43 magnesium alloy using an electrolyte containing CeO2 and that the electrolyte additive influenced the structural and morphological properties of the coating.

Contact mechanics examines the interaction of bodies using the theory of elasticity and finds applications across various engineering disciplines involving solid structures. Structural damage often results from fractures in regions with high stress concentrations, making it crucial to accurately determine contact stress distributions during the design phase. With advancements in materials science, production methods have emerged that enable tailoring material properties based on location within the material. These materials, known as Functionally Graded Materials (FGMs), are heterogeneous composites where properties vary continuously according to a specific function. This study investigates the continuous contact problem involving a two-layer system resting on an elastic half-plane, subjected to a rigid flat block load. The upper layer, with a thickness of ℎ1, is an FGM whose density and shear modulus vary exponentially. The lower layer, with a thickness of ℎ2, is homogeneous with constant material properties. All surfaces in the system are assumed to be frictionless. A rectangular rigid block applies an external load 𝑃 on the functionally graded layer. The problem is solved analytically by using elasticity theory and integral transform technics. The study considers various parameters, including density ratios (γ/ℎ1 = 1.38629, γ/h1=0.0001, γ/h=−1.38629), block width-to-height ratios (𝑎/ℎ1 =0.25, 𝑎/ℎ1 =0.5, 𝑎/ℎ1=1, 𝑎/ℎ1=2), and stiffness parameters (βh1=-1.38629, βh1=0.0001, βh1=1.38629). The contact stresses at the interfaces are determined, along with the initial separation load and the critical separation distances (λ𝑐𝑟, xcr) between the FGM and homogeneous layers. Results are presented in the form of figures, graphs, and tables.

AA2024 aluminium alloy is a widely used structural material, especially in aerospace and automotive applications, due to its high strength-to-weight ratio and low density. Also, Surface modification is required since the alloy's surface properties are insufficient under operating conditions. This study aims to investigate the feasibility of producing composite coatings containing TiC particles on AA2024 aluminium alloy via the micro-arc oxidation (MAO) method, as well as the effect of TiC addition on the morphological and structural properties of the coating. For this purpose, an undoped MAO coating was produced using a base electrolyte, while a composite MAO coating was fabricated by adding titanium carbide (TiC) particles to the electrolyte. The surface and cross-sectional morphologies of the obtained coatings were examined using scanning electron microscopy (SEM), while their elemental compositions were analysed using energy-dispersive X-ray spectroscopy (EDS). It has been observed that microcracks and pores of various sizes form on the surface of the undoped MAO coating. In the EDS analysis of the TiC-containing composite coating, Ti and C were detected with Al and O. It has been observed that adding TiC particles increases coating thickness, reduces the number and size of surface pores, and causes TiC particles to condense particularly around pores. The findings demonstrated that composite MAO coatings containing TiC particles could be successfully produced on the surface of AA2024 aluminium alloy and that the addition of TiC caused significant changes in the coating thickness and surface morphology.

Throughout human history, death has been interpreted not merely as the cessation of biological life, but as a multifaceted phenomenon shaped by concepts such as the unknown, fear, existence, the afterlife, and the quest for immortality. Human awareness of one's own mortality, combined with the lack of definitive knowledge regarding what follows death, has established it as a fundamental existential issue that societies have sought to explain and interpret throughout history. The religious, philosophical, cultural, and metaphysical approaches developed in response to this uncertainty have paved the way for viewing death not simply as an end, but within a realm of mystical meaning that opens onto diverse modes of existence, spiritual and otherworldly visions, and the pursuit of immortality. Indeed, the fear of death and the drive to explain the unknown have played a decisive role in shaping beliefs, rituals, symbols, and narratives concerning the afterlife across various eras and cultures. The individual's quest to understand death and the hereafter, alongside the desire for immortality, has persisted as a significant way of making sense of the enigma of death. Drawing upon the mystical, metaphysical, and cultural meanings death has acquired over time, this study aims to examine the mystical interpretation of death within the context of sports. It employs an interdisciplinary approach—grounded in relevant literature—to explore how fears regarding the unknown and annihilation, the concept of the afterlife, and the quest for immortality manifest within the realm of sports. This study, a conceptual review based on a literature survey, aims to provide a platform for discussing the relationship between sport and the layers of meaning that lie beyond the biological reality of death.

Traffic police officers perform a critical public service by regulating traffic, conducting roadside inspections, enforcing traffic regulations, and responding to road traffic crashes. Unlike personnel working in controlled workplace environments, they frequently carry out their duties near moving vehicles and under rapidly changing traffic and environmental conditions. Roadside enforcement and crash response operations may therefore expose officers to numerous occupational hazards. The principal hazards include uncontrolled traffic flow, high vehicle speeds, limited visibility, unsafe driver behavior, and the intrusion of vehicles into roadside inspection or crash-response zones. Exposure to these hazards may result in struck-by incidents, secondary crashes, serious injuries, or fatalities. Traffic police officers may also be exposed to excessive noise, exhaust emissions, adverse weather conditions, prolonged standing, irregular working hours, night shifts, and physically demanding postures. In addition to these physical, environmental, and ergonomic hazards, responding to severe crashes and encountering injured or deceased individuals may cause considerable psychological stress and emotional strain. These interacting factors make traffic policing a high-risk occupation requiring task-specific preventive and protective measures. Safer working conditions can be supported through standardized roadside deployment procedures, appropriate positioning of police vehicles, advance warning and traffic-calming systems, adequate lighting, high-visibility personal protective equipment, regular occupational safety training, and organizational support for psychological well-being. This paper presents an overview of the duties and working conditions of traffic police officers and discusses the principal occupational hazards associated with roadside enforcement and crash response operations. Increasing awareness of these hazards may contribute to the development of safer operational practices and more comprehensive occupational health and safety policies within traffic policing.

The safe use, storage, transportation, and disposal of chemicals used as raw materials, intermediates, final products, and auxiliary substances in the chemical industry are important for protecting the health and safety of workers, limiting environmental impacts, and ensuring production continuity. Particularly in areas where chemicals are stored, the physical and chemical properties of the substances and their compatibility with one another must be taken into consideration. Industrial racking systems used for the storage of chemicals are not merely equipment for organizing storage areas but also constitute an important engineering element in terms of occupational health and safety. Improper design, selection, or use of racking systems may result in the tipping, falling, and leakage of chemicals, as well as fire, explosion, the release of toxic gases or vapors, chemical exposure, injuries, and fatalities. Therefore, racking systems should be constructed from materials suitable for the properties of the chemicals being stored and the relevant storage conditions, provide adequate resistance to chemical leakage and potential reactions, possess appropriate fire safety characteristics, and have sufficient mechanical load-bearing capacity. In addition, securing racks against tipping and falling, designing them with seismic effects taken into consideration, and conducting regular inspections and maintenance are among the fundamental elements of safe storage. In this study, industrial racking systems used in the chemical industry were examined in terms of workplace characteristics, the physical and chemical properties of the stored chemicals, environmental conditions, fire safety, load-bearing capacity, and mechanical strength. In addition, the importance of considering the safety requirements specified in relevant legislation and standards when selecting racking systems and designing chemical storage facilities was evaluated.

The Chain of Custody (CoC) certification, developed by the Forest Stewardship Council (FSC), is a global standard aimed at ensuring the delivery of wood and forest products from sustainably managed sources to the final consumer in an unbroken and traceable manner. Structured around the FSC-STD-40-004 standard, this system mandates key criteria such as management responsibility, raw material procurement and verification, traceability control systems (transfer, percentage, and credit systems), mass balance calculations, sales declarations, and compliance with FSC Core Labour Requirements. The emergence of sustainable forestry principles as a strategic necessity in international trade has rapidly increased the demand for FSC certification within Türkiye's forest products and furniture sectors. The aim of this study is to examine the normative criteria of the FSC CoC certification system and to identify the primary academic, technical, and operational challenges encountered by manufacturing and exporting companies in Türkiye during the implementation process. Within the scope of the research, qualitative and quantitative findings were evaluated based on field audits conducted at wood processing and packaging facilities in Türkiye. The results indicate that the most frequently encountered issues in Turkish implementations include: insufficient supplies of certified domestic raw materials; missing FSC code declarations on supplier invoices and delivery notes; errors in calculating waste rates and conversion factors during production processes; and contractual and auditing shortcomings in subcontracting (outsourcing) operations. Furthermore, other critical areas of non-compliance for Small and Medium-sized Enterprises (SMEs) include FSC certification costs, a lack of personnel training, and the risk of uncertified inputs physically mixing with certified products during storage and production stages. The study presents strategic solution proposals aimed at strengthening the domestic certified raw material supply chain, with the objective of maintaining the competitiveness of Türkiye's forest industry in the global market and ensuring full compliance with international standards.

Football is a dynamic team sport that requires players to rapidly adapt to changing game conditions, anticipate one another's actions, and coordinate their individual behaviors in alignment with the team's shared goals. Within this framework, communication encompasses not merely the verbal exchange of messages between players but also cognitive and interactive processes—such as the construction of shared game knowledge, the similar perception of game situations, and the anticipation of teammates' potential actions. Research on football indicates that shared knowledge and shared mental models are linked to team coordination; furthermore, the development of shared game knowledge among players during collective training can alter the need for real-time verbal communication. Regarding defensive organization, processes such as positioning, space sharing, marking, pressing, and adjusting behavior based on a teammate's movements highlight the collective nature of defensive action, which relies on coordination among players. This study aims to conceptually examine communication among defenders in Scandinavian football within the context of defensive organization. Communication in this study will not be limited to verbal message exchanges between players but will instead be addressed within a framework comprising verbal and non-verbal interaction, shared game knowledge, shared situational awareness, and player coordination. Accordingly, the study seeks to discuss—based on relevant literature—the relationship between the necessity for collective action among defenders and intra-team communication processes within the context of Scandinavian football (encompassing Denmark, Norway, and Sweden). Designed as a conceptual study based on a literature review, this work aims to establish an interdisciplinary platform for discussing the defensive organization of football—evaluating it not merely through tactical and physical elements, but also through the processes of communication and the co-construction of meaning among players.

Geotechnical failures in basement terrains frequently result from insufficient subsurface characterisation, leading to differential settlement and structural damage. This study applies Vertical Electrical Sounding (VES) to assess geotechnical suitability at Bolorunduro and environs, Ondo State, Southwestern Nigeria, underlain by the Precambrian Basement Complex. Twenty VES stations were surveyed using the Schlumberger electrode configuration, with half-current electrode spacing (AB/2) of 1–80 m. Field data were processed by partial curve matching and inverted using IPI2Win software to generate layer models defining resistivity, thickness, and depth for each subsurface unit. Interpretation delineated three to five geo-electric layers per station — comprising topsoil, lateritic horizons, clay-rich units, weathered basement, and fresh competent basement — with curve types spanning H, HA, KH, QH, HK, A, and AH forms, reflecting lateral subsurface variability across the study area. Depth to competent basement ranged from approximately 2.7 m in the northwestern zone to over 43 m in the clay-rich eastern region, indicating significant lateral heterogeneity. Resistivity values below 100 Ω·m were diagnostic of clay-rich horizons with high plasticity and low bearing capacity, while values exceeding 1,500 Ω·m indicated competent basement suitable for heavy structural foundations. Three geotechnical suitability zones — high, moderate, and low — were delineated and integrated into a suitability map guiding pre-construction planning. The results confirm that VES is a reliable, non-invasive, and cost-effective geotechnical site investigation tool in crystalline basement terrains, providing spatially continuous subsurface characterisation that complements conventional borehole-based assessments.

Effective management of university campuses requires the integration of up-to-date spatial data on physical features with descriptive information and making this information accessible to users. Particularly at universities with campuses in different locations, enabling staff and students to access accurate information quickly depends on maintaining data within an organized and queryable system. This study aims to develop an accessible and queryable campus information system supporting smart campus applications at Gümüşhane University using unmanned aerial vehicles (UAVs) and geographic information systems (GIS). The study covers the main campus of Gümüşhane University and the Kelkit, Köse, Kürtün, Şiran, and Torul campuses. UAV images acquired from all six campuses were processed to generate orthophotos. Buildings, green spaces, parking areas, roads, recreational areas, sidewalks, stairs, sports facilities, and event areas were digitized from these orthophotos. The digitized features were organized into thematic layers, while descriptive information was incorporated into attribute tables and linked to spatial data. Thus, an information system containing spatial and descriptive information on the physical components of each campus was established. As a result, a digital inventory covering the physical components and land-use characteristics of all six campuses was created. The system enables university staff and students to access, query, monitor, and visualize information about campus features on a map. The systematic integration of spatial and descriptive data reduces the need to search across multiple sources and facilitates faster access to accurate information. It also provides a basis for area calculations, analysis of facility distributions, and comparisons among campuses. By integrating UAV-based mapping with GIS-based information management, the study supports both institutional management and user access to information. The developed infrastructure can provide a foundation for campus planning, facility management, and the future development of user-oriented smart campus applications.

The Hakkari–Yüksekova region is located within the tectonically active Eastern Anatolian–Iranian Plateau and is characterized by major structures including the Şemdinli–Yüksekova Fault Zone, Başkale Fault, and Bitlis–Zagros Thrust Belt. This study investigates the relationship between regional magnetic structure, active faults, and seismicity. The magnetic structure was evaluated using the EMAG2-v3 magnetic anomaly dataset, while seismicity was examined using earthquakes with M > 3.0 recorded between 1900 and 2026. Active faults were compiled from the 2026 Active Fault Map of Türkiye and the GEM Global Active Faults
The results reveal pronounced lateral variations in the magnetic structure and magnetic source depths across the study area. Several prominent magnetic gradients and anomaly boundaries spatially coincide with or follow the major active faults, indicating a close relationship between subsurface magnetic discontinuities and regional fault geometry. Earthquake epicenters are also concentrated mainly along and around major active fault zones. The combined evaluation of magnetic anomalies, source depths, active faults, and seismicity provides complementary constraints on the subsurface structural architecture and contributes to a better understanding of the active tectonic framework of the Hakkari–Yüksekova region.

The Guba–Khachmaz region is one of Azerbaijan’s most promising areas for the development of low- to medium-temperature geothermal resources. This study evaluates the hydrogeological characteristics, theoretical thermal capacity, and potential utilization pathways of the region’s thermal waters. Official hydrogeological data and published scientific sources were analyzed, while thermal-power scenarios were calculated using water discharge, specific heat capacity, and temperature reduction. Exploration wells drilled to depths of up to 3,000 m in the Khudat–Khachmaz area have encountered high-discharge thermal waters with temperatures generally ranging from 50 to 81°C. The officially approved operational reserve of the Khudat–Khachmaz thermal-water field is 25,700 m³/day. Based on this reserve, the estimated theoretical thermal capacity is approximately 24.9 MWt for a temperature reduction of 20°C, 37.3 MWt for 30°C, and 49.7 MWt for 40°C. These values represent theoretical heat potential rather than electricity-generation capacity. The results demonstrate that the region’s geothermal resources are more suitable for direct heat applications than for conventional electricity production. The most promising uses include greenhouse heating, space and district heating, agricultural drying, aquaculture, balneology, thermal tourism, and systems integrated with geothermal heat pumps. A cascade-use model could increase efficiency by applying the same thermal water successively for several purposes at decreasing temperature levels. Sustainable development requires continuous monitoring of temperature, discharge, pressure, and hydrochemical parameters, together with reinjection where technically feasible. The findings provide a scientific basis for selecting pilot geothermal projects and expanding renewable heat utilization in northern Azerbaijan.

The Bolu–Düzce region in northwestern Türkiye is characterized by intense tectonic and seismic activity associated with the North Anatolian Fault Zone (NAFZ). This study investigates the relationship between seismicity, active fault systems, and regional magnetic structure through an integrated analysis of earthquake and magnetic data. Seismicity is evaluated using M > 3.0 earthquakes recorded between 1900 and 2026 from the Kandilli Observatory and Earthquake Research Institute catalogue. Earthquake epicenters are mapped according to focal depth and compared with the regional active fault pattern. The magnetic structure is investigated using the EMAG2-v3 magnetic anomaly dataset, which was processed using magnetic data enhancement and spectral analysis techniques to characterize regional magnetic variations and estimate magnetic source depths. The results show that seismicity is predominantly concentrated along and around the principal branches of the NAFZ. Magnetic anomalies exhibit distinct spatial variations across the study area, while enhanced anomaly patterns delineate structural boundaries and lineaments that locally correspond to active fault traces and zones of concentrated seismicity. Variations in magnetic source depths also indicate lateral changes in the subsurface magnetic structure. The integrated interpretation of seismic and magnetic data provides complementary constraints on the tectonic architecture of the Bolu–Düzce region and contributes to a better understanding of active deformation along the western NAFZ.

This study evaluates iron ore prospectivity in Itakpe and its environs, North-Central Nigeria, through the integration of high-resolution aeromagnetic data with the Analytical Hierarchy Process (AHP) within a GIS environment. High-resolution aeromagnetic data were processed to enhance magnetic anomalies and delineate subsurface geological features. Processing techniques included Reduction to the Equator (RTE) to center anomalies over their sources, residual magnetic anomaly separation to isolate near-surface sources, and derivative-based filters including First Vertical Derivative (FVD), Total Horizontal Derivative (THD), Tilt Derivative (TDR), and Analytical Signal (AS) to highlight edges, contacts, and high-magnetization zones associated with ferruginous bodies. Spectral analysis using Fourier transform was applied to estimate depths to magnetic sources, distinguishing shallow from deep-seated anomalies. Detailed structural interpretation revealed a network of faults, fractures, and lithological contacts controlling iron mineralization, with lineament density analysis further identifying zones of intense deformation favorable for ore emplacement. To quantitatively assess prospectivity, four key thematic layers; Analytical Signal, First Vertical Derivative, Lineament Density, and Geology were selected based on their relevance to iron ore controls. These layers were weighted using AHP pairwise comparison matrix with consistency ratio validation, and integrated through weighted overlay analysis in ArcGIS to generate a final prospectivity map. The resulting map classified the study area into very low, low, moderate, and high mineral potential zones. High prospectivity zones exhibit strong correlation with banded iron formations, high analytical signal amplitudes, shallow depth to magnetic sources, and high lineament density, confirming that mineralization is dominantly lithologically and structurally controlled. The study demonstrates that the synergy of aeromagnetic data processing and AHP-GIS modeling offers an effective, cost-efficient, and reproducible framework for regional mineral exploration, providing a reliable decision-support tool for future detailed exploration and sustainable resource development in Itakpe and analogous Basement Complex terrains across Nigeria, and to informed policy formulation in mineral exploration.

Sri Lanka's gem industry still relies largely on traditional exploration knowledge. Scientific studies have focused on floodplain and valley-fill alluvial deposits, and high-energy landforms such as plunge pools remain poorly examined. Plunge pools are scour basins at the base of waterfalls and may trap dense minerals such as gemstones; nevertheless, has not been tested in Sri Lankan gem-bearing rivers. This study assessed gemstone deposition potential in plunge pools of the upper Gala Oya River, Uva Province. The river rises on the Dorapoda mountain range (937 m) near Highland–Vijayan Complex boundary. Ten plunge pools were georeferenced, and waterfall height, pool depth, diameter, flow velocity and elevation were recorded. Two sand samples, one proximal and one distal to the waterfall, were collected from each pool, concentrated by panning and sieved. The 150 µm heavy mineral fraction was examined under a gemmological microscope, and grain counts were used to calculate the percentage of each variety. Relationships with pool parameters were tested using Pearson correlation, proximal–distal differences using paired t-tests, and spatial gem potential was mapped in ArcGIS using inverse distance weighting. Garnet was dominant (29.4–50.3%), followed by tourmaline (17.5–31.9%), yellow sapphire (2.8–9.6%) and zircon (0.6–4.5%). Yellow sapphire correlated strongly with pool depth (r = 0.89, p < 0.001) and moderately with diameter (r = 0.64, p = 0.045), while garnet declined with increasing elevation (r = −0.74, p = 0.015). Waterfall height and flow velocity showed no significant relationships, and no variety differed significantly between proximal and distal samples, so proximity to the waterfall is not a reliable exploration indicator. Despite the limited sample size and shallow sampling depth, the findings suggest that pool depth and size are practical morphological criteria for targeting yellow sapphire potential in plunge pools, while garnet potential is better explained by elevation. This supports low-impact, science-based gem exploration.

Land surface temperature (LST) is an important indicator for examining spatial variations in surface thermal conditions and their changes over time. Satellite observations enable consistent assessments of surface thermal patterns across extensive areas, while cloud-based processing facilitates the analysis of historical imagery through a standardized workflow. This study assessed summer LST patterns across Gümüşhane Province, Türkiye, between 1985 and 2025 using Landsat imagery and the Google Earth Engine (GEE) platform. Nine individual years (1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2025) were investigated at five-year intervals. Landsat Collection 2 Level-2 surface temperature products were processed within the provincial boundaries. For each selected year, imagery acquired between June and August was filtered, and cloud-contaminated pixels and cloud shadows were excluded using quality assurance bands. Surface temperature values were converted to degrees Celsius, and summer mean LST maps were generated independently for each year. A consistent spatial extent and processing framework were applied to support comparisons. Valid observation counts and spatial data coverage were also examined to assess the reliability of the seasonal composites. The analysis compared provincial temperature statistics and the spatial distribution of relatively warmer and cooler surfaces. Differences between successive selected years and between 1985 and 2025 were mapped to identify areas exhibiting pronounced thermal changes. The resulting maps and statistical summaries provided a basis for evaluating summer surface temperature variability over the forty-year study period. Comparisons focused on the selected summer periods, allowing spatial differences and changes between observation years to be examined within a common seasonal context. The approach established a reproducible framework for monitoring surface thermal conditions in Gümüşhane. The outputs provided baseline information for regional environmental assessment, spatial planning, and subsequent investigations of the relationships between LST, land cover, and topography.

Wettability is a key concept in petroleum engineering, referring to the ability of a fluid (such as oil) to adhere to and maintain contact with the surface of reservoir rock. Wettability alteration is a complex concept, and various methods and techniques may be employed depending on the specific conditions and characteristics of each reservoir and the oil it contains. In general, it may be affected by several factors like reservoir pressure, reservoir temperature and reservoir fluid composition. In general, changes in wettability can involve the factors like pressure, temperature and fluid content composition. By considering the changes in oil wettability, petroleum engineers can implement various strategies and techniques in reservoir engineering and production operations to mitigate the adverse effects of wettability or leverage wettability changes to enhance oil production. In this paper, reservoir rock wettability analysis of a studied geological formation will be explained and discussed by using available data from several reservoir selected cores.

Corrosion of marine steel structures remains one of the major challenges in shipbuilding and offshore engineering, leading to significant maintenance costs, reduced operational reliability, and environmental concerns. The development of advanced protective coatings with improved durability and corrosion resistance is therefore an important research direction. Nanomodification of conventional coating systems has recently attracted considerable attention due to its potential to enhance both mechanical and protective properties. The purpose of this study was to investigate the effectiveness of nanomodified PF-115 alkyd coatings for sustainable corrosion protection of marine steel exposed to aggressive marine and petrochemical environments. Four coating formulations were prepared, including a reference PF-115 coating and three nanomodified systems containing nano-calcium carbonate (CaCO₃), zinc oxide (ZnO), and copper(I) oxide (Cu₂O) nanoparticles. The coatings were applied to steel substrates under identical laboratory conditions, producing dry film thicknesses within the recommended protective range. The experimental program included laboratory exposure under simulated marine and petrochemical conditions. The coatings were evaluated in terms of corrosion resistance, coating integrity, adhesion, and overall protective performance. Comparative analysis demonstrated that the incorporation of nanoparticles significantly improved the protective characteristics of the coatings compared with the unmodified PF-115 formulation. The combined use of nano-CaCO₃, ZnO, and Cu₂O provided the highest corrosion resistance and improved long-term coating stability under aggressive environmental conditions. The nanomodified coatings also exhibited enhanced barrier properties, reducing coating degradation during prolonged exposure. The obtained results confirm that nanomodification is an effective approach for improving the performance of conventional alkyd protective coatings intended for marine applications. The proposed coating systems may contribute to extending the service life of marine steel structures, reducing maintenance requirements, and supporting sustainable corrosion protection strategies in the maritime industry. The findings demonstrate the practical potential of nanotechnology for developing next-generation protective coatings for shipbuilding and related engineering applications.

H13 hot-work tool steel is widely preferred in hot forging, extrusion, and die-casting applications due to its high hardness, good thermal fatigue resistance, and dimensional stability at elevated temperatures; however, its wear resistance and surface durability under severe thermal and mechanical loading remain limited, necessitating protective surface coatings. In this study, Cr/CrN/CrAlN and Cr/CrN/CrAlCN multilayer coatings were deposited on H13 substrates using the Closed Field Unbalanced Magnetron Sputtering (CFUBMS) technique. The structural, mechanical, adhesion, and tribological properties of both coating systems were comparatively investigated at room temperature (25 °C) and at 400 °C, 600 °C, 800 °C, and 1000 °C. Microstructural and phase characterization was performed using XRD, SEM, and EDS, while mechanical properties were evaluated by nanoindentation and microhardness measurements. Adhesion strength at the coating-substrate interface was assessed by scratch testing, and tribological performance was compared through friction coefficient and wear rate values obtained from ball-on-disk tests at different temperatures.The results show that both the CrAlN and CrAlCN top layers form protective oxide layers at elevated temperatures, enhancing oxidation resistance and tribological stability, with the carbon-containing CrAlCN layer providing additional lubricating effect and lower friction coefficients up to moderate temperatures. As temperature increased, the dominant wear mechanism shifted from adhesive to oxidative/abrasive wear for both coatings. The CrN interlayer mitigated stress transitions between the Cr bonding layer and the top layers, improving adhesion strength and delaying interlayer delamination at high temperatures. Even at 1000 °C, both coatings largely retained their structural integrity, attributed to the dense, low-porosity microstructure achieved by CFUBMS.Cr/CrN/CrAlN and Cr/CrN/CrAlCN coatings produced by CFUBMS represent effective surface engineering solutions for enhancing the wear resistance and service life of H13 tool steel in high-temperature applications such as hot forging and extrusion dies.

The F1 Halo component, mandated to protect drivers' heads, is manufactured from Grade 5 titanium (Ti-6Al-4V) per FIA Standard 8869-2018, yet strict weight limits make every kilogram critical to vehicle performance. This study investigates whether carbon fiber reinforced polymer (CFRP) composites can offer a lighter alternative to titanium without compromising FIA safety requirements. Six candidate materials, including standard-modulus T700 and high-modulus M46J, were defined in Ansys Material Designer using fabric-epoxy systems with 0°, ±10°, and ±30° shear angles; the Halo geometry was imported as an STL file and simplified through surface wrapping. Two static load cases reflecting FIA standards, with combined vertical and lateral forces of 116 kN/46 kN and 122 kN/46 kN, were applied to each material, and maximum displacement and principal stress were compared against titanium. Results obtained at the 0° fiber orientation show that M46J experiences 6.6% higher stress than titanium but achieves substantially lower deformation than IM7 carbon, reducing displacement by 24% in Test 1 and 19% in Test 2, while still meeting FIA displacement and permanent-deformation criteria. These findings indicate that high-modulus carbon fiber composites can meet FIA static safety requirements while reducing Halo system weight by up to 60%, offering a promising alternative for motorsport structural design. Since only static linear loading was examined, dynamic impact tests and the brittle fracture and delamination behavior specific to composites were excluded from this analysis; unlike titanium's ductile behavior, the potential for sudden and unpredictable fracture in composites should be regarded as an important limitation of these findings. Future work should extend this analysis to dynamic crash simulations, incorporate failure criteria such as Tsai-Wu and Puck and validate the findings through physical prototype testing.

In recent years, we are increasingly seeing composite materials in the field of biomaterials, driven by esthetic, chemical, and mechanical demands associated with living tissue structures. From the perspective of materials engineering, desired new material forms can be created by combining the superior properties of the constituent materials that make up composite materials. The aim of this study is to conduct research on the use of composite materials as biomaterials by analyzing existing studies in the literature. Within the scope of the study, the keywords "composite material" and "biomaterial" were listed using the Web of Science database with various Boolean search operators. Analyses were conducted by examining the bio composite materials and testing methods identified in the specific studies. These analyses aimed to evaluate the mechanical, aesthetic, and chemical behaviors of composite materials used in the living body. Future studies aim to conduct experiments using specific methods and laboratory set up on bio composite materials that have been frequently preferred in recent years. In this way, the aim is to predict the behavior of bio composite materials implanted in the human body over time, therefore contributing to the establishment of satisfactory treatment processes.

Machine-tool spindles are critical components whose performance directly affects machining accuracy, product quality, and service life. Contact and sliding between the spindle surface and its supporting components during operation can lead to wear, consequently reducing spindle service life and adversely affecting machining quality. AISI 7131 steel is commonly used for machine-tool spindle applications due to its suitable mechanical properties and response to surface heat treatment. In the present study, the microstructure, hardness, microhardness, and wear behavior of AISI 7131 steel and carburized structural steel were investigated and compared. Samples of AISI 7131 and structural steel were carburized at 920 °C for 5 h, followed by hardening and tempering at 200 °C. Dry sliding wear tests were performed using a block-on-ring configuration under a load of 150 N and a sliding speed of 3.7 m/s for 40 min. Metallographic examination, hardness and microhardness measurements, and scanning electron microscopy (SEM) were employed to characterize the microstructure and surface properties of the samples. The results showed that the carburized AISI 7131 steel exhibited higher hardness and microhardness and superior wear resistance compared with the carburized structural steel. After 40 min of wear testing, the mass losses of the carburized AISI 7131 steel, carburized structural steel, and untreated AISI 7131 steels were 0.0126, 0.0382, and 0.0196 g, respectively. Microstructural observations revealed the formation of a martensitic surface layer in the carburized AISI 7131, which was attributed to its higher hardenability resulting from the presence of alloying elements, particularly manganese and chromium. In contrast, the carburized structural steel exhibited lower hardenability and a lower degree of martensitic transformation in the surface region. Overall, the results indicate that carburized AISI 7131 steel provides superior wear resistance and is a more suitable candidate for machine-tool spindle applications where high surface hardness and extended service life are required.

Surface degradation, wear debris generation, and metal ion release are major factors limiting the long-term performance of metallic biomedical implants. Nitrogen-based ceramic coatings, particularly titanium nitride (TiN), titanium carbonitride (TiCN), and titanium aluminum nitride (TiAlN), have attracted growing interest as surface modification strategies because they can enhance implant surface performance without substantially altering bulk mechanical behavior. This paper provides a general overview of the microstructure, surface morphology, phase composition, and mechanical properties of these coatings, along with their corrosion behavior and biocompatibility-related surface characteristics, with particular attention to how coating type and nitrogen content influence coating–substrate adhesion, surface roughness, and corrosion resistance. The literature indicates that TiN, TiCN, and TiAlN coatings can form dense, adherent, and chemically stable surface layers that, owing to their high hardness and chemical inertness, improve wear and corrosion resistance and may act as diffusion barriers limiting the release of potentially harmful metal ions in physiological environments. Nitrogen-based coatings are therefore promising candidates for improving the surface performance of biomedical implants, especially where wear resistance, corrosion protection, and biocompatibility are required. However, long-term osseointegration, cytotoxicity, and clinical performance remain insufficiently understood, and further in vitro and in vivo studies are needed.

Titanium and titanium alloys are frequently preferred as biomaterials due to their unique properties. However, since the living body comprises a complex structure capable of constant change, doubts may always arise regarding the adequacy of material strength. Many new experimental methods are being developed to predict the time-dependent behavior of material strengths within the living body. In this study, the angular chewing behavior of a pure titanium material designed according to international standards within dental implant structures will be analyzed using the Finite Element Method using ANSYS. Within the scope of the study, the stress distributions induced in the pure titanium screw component by a 50 N biting force applied at a 80 degree horizontal angle during the chewing motion of the human jaw were analyzed through chewing simulation test. The regions of stress accumulation were observed in the implant screw body in conjunction with angular bite forces. This result has been analyzed as a mathematical indication that various damage mechanisms may develop in the implant screw section due to cyclic loading. In future studies, modeling the mathematically designed chewing motion mechanism in a laboratory setting, conducting in vitro tests, and analyzing the obtained results will contribute to the overall analysis.

Thermoelectric cooling (TEC) systems offer several advantages, including compact size, absence of moving parts, quiet operation, and environmentally friendly operation without conventional refrigerants. In this study, the cooling performance of a thermoelectric module was experimentally investigated for two different applications: refrigeration and air conditioning. In the refrigeration configuration, the TEC module was used to cool a thermally insulated mini-refrigerator box, and the temperature variation inside the box was monitored. In the air-conditioning configuration, air was passed through the cooling section, and the inlet and outlet air temperatures were measured to determine the cooling effect. The cooling capacity and coefficient of performance (COP) were calculated separately for both configurations based on their respective thermal loads and electrical power consumption.

Transient heat transfer in a U-tube geothermal borehole heat exchanger embedded in saturated sand was investigated numerically. The energy equation was solved by the finite element method on a two-dimensional cross-section of the borehole (fluid, pipe wall, grout and sand), following the setup of the COMSOL Multiphysics Heat Transfer module. Geometry, thermal properties and heat load (57.7 W/m for 52 h) were taken from the laboratory reference data set of Beier et al. [6]. After 52 h the borehole-wall temperature (30.09 °C) differs by only 0.1% from the infinite line-source analytical solution, and refining the mesh changes the response by less than 0.03%. The borehole thermal resistance was 0.206 m·K/W for the nominal pipe spacing (53 mm) and 0.175 m·K/W for an effective spacing of 68.8 mm, i.e. errors of 19.1% and 1.4% relative to the experimental value of 0.173 m·K/W. The ground conductivity estimated from the fluid-temperature slope (2.43 W/m·K) deviates by 13.9% from the measured 2.82 W/m·K. A parametric study showed that grout conductivity is the most influential parameter: raising it from 0.5 to 2.0 W/m·K lowers the borehole resistance by about 62%.

The energy generation performance of photovoltaic (PV) systems is significantly influenced by environmental operating conditions, in addition to the technical characteristics of the system components. Environmental factors such as solar irradiance, ambient and cell temperature, relative humidity, wind, dust and atmospheric aerosols, cloud cover, and precipitation can affect the electrical performance of PV systems to varying degrees. In this study, the primary environmental factors affecting PV system performance were examined based on the literature, and their impacts on PV power generation and efficiency were evaluated. The literature indicates that solar irradiance is a fundamental determinant of PV power generation, whereas an increase in cell temperature has a detrimental effect, particularly on electrical efficiency. Dust and atmospheric aerosol accumulation on panel surfaces can cause electrical performance losses; additionally, relative humidity has been found to influence PV performance through its effects on atmospheric conditions and surface dust accumulation. Although wind can positively contribute to performance by lowering panel temperatures, it also plays a role in particle transport and surface soiling. Precipitation stands out as a significant natural cleaning mechanism, particularly for removing dust accumulated on panel surfaces. Overall, the literature demonstrates that PV system performance can vary significantly depending on environmental conditions and that considering various environmental factors collectively is crucial for understanding performance under actual operating conditions. This study aims to provide a literature-based assessment of the importance of environmental conditions during the design, performance evaluation, and operation of PV systems.

Heat transfer problems in layered and multi-material systems involve discontinuous thermal conductivity, which makes the temperature gradient jump across material interfaces and challenges physics-informed neural networks (PINNs) represented by a single smooth network. This study implements a single-network PINN and a domain-decomposed extended PINN (XPINN) for transient heat conduction in a two-layer composite wall within a reproducible PyTorch-based Python framework, and compares both against an independent finite volume reference. The framework includes interface losses for temperature, flux and residual continuity, together with gradient-norm-based adaptive loss weighting. It is shown analytically that a loss function without interface conditions admits a spurious stationary solution that has zero loss and coincides with the initial profile, and the error measures of this solution reproduce the reported results of the single-network PINN. For a conductivity ratio of 0.2, the single-network PINN yields a relative L2 error of 19.9% and an interface flux mismatch of 2.00, whereas the XPINN reduces these values to 1.57% and 0.044. As the conductivity ratio decreases from 1 to 0.05, the error ratio between the two approaches increases from 1.0 to 8.3. Adaptive weighting reduced the flux mismatch by about 22% but did not improve the relative L2 error in the single-seed experiment. The results show that interface continuity conditions must be included explicitly in the loss function and that a low loss value alone is not a measure of accuracy. >> This study is supported by Ataturk University Coordinatorship of Scientific Research under project # FBA-2026-17685

In this study, the effects of the number of turbulators (1, 5, 9), fluid type (water, ethylene glycol, ammonia), absorber surface coating (standard, Black 2.0, Black 3.0), and fluid mass flow rate (50, 100, 150 kg/h) on the thermal performance of a flat-plate solar collector (FPSC) were investigated using both numerical (ANSYS-Fluent, CFD) and experimental methods. The Response Surface Method (RSM) was employed for experimental design and the determination of optimum parameters, while Analysis of Variance (ANOVA) was performed separately for the numerical and experimental datasets to compare the results. In the experimental study, halogen floodlights were used to simulate solar radiation, and a pyranometer, T-type thermocouples, and a flow meter were used for measurements; an uncertainty of ±1.06% in efficiency was determined using the Kline-McClintock method. In both models, fluid type was identified as the most influential parameter regarding the outcome variable (contributing 56.48% and 53.83%, respectively); however, while the effects of flow rate and the number of turbulators were found to be statistically insignificant (P>0.05) in the numerical model, they were significant (P<0.05) in the experimental model. The maximum thermal energy was calculated as 96.91 W (at 100 kg/h) in the numerical model, whereas it was measured as 132.51 W (at 150 kg/h) in the experimental study, and a systematic deviation ranging from 4% to 37% was observed between the two methods. Consequently, a configuration comprising a mass flow rate of 150 kg/h, 9 turbulators, ammonia as the working fluid, and a Black 3.0-coated collector has been identified as the experimentally validated point of maximum performance. The findings demonstrate that designs based solely on numerical optimization can yield misleading results in the absence of experimental validation.

In recent years, thermoelectric cooling (TEC) systems have found widespread use, especially in applications requiring low cooling capacity. Their simple structures without moving parts, low power requirements, and ease of maintenance make these systems advantageous compared to traditional vapor-compression refrigeration cycles. In this study, the air conditioning performance of a thermoelectric module was experimentally investigated. In the installation, by keeping the air flow rate delivered to the cabin constant, the cooling performances of the simple (reference) and radiator-added configurations were comparatively analyzed. In this context, the inlet and outlet temperatures of the ambient air passing through a thermally insulated cooling cell were measured instantaneously. In light of the obtained experimental data, the coefficient of performance (COP) values for both configurations were calculated and evaluated separately based on the system's thermal load and electrical power consumption.

In photovoltaic (PV) systems, a significant portion of solar radiation converts into heat rather than electricity; this raises the cell temperature and reduces electrical efficiency. This study aimed to lower PV cell temperature and generate additional electricity via Peltier modules by integrating a combination of aluminum metal foam and Peltier modules (thermoelectric modules) onto the underside of the panel. Experiments were conducted outdoors in Erzurum using a full factorial experimental design involving three parameters: two Peltier types (12706 and 12710), three metal foam arrangements (perpendicular, diagonal, and parallel to the flow), and three fan speeds (0.5, 1.4, and 2 m/s). In reference experiments without fins, the panel temperature rose from 21°C to 62°C, resulting in an approximately 20% decrease in efficiency. The highest thermal efficiency with the developed system was achieved using the 12706 series Peltier and the diagonal foam arrangement at an air speed of 2 m/s (level 10); this value was 19.47% higher than that of the 12710 series in the same arrangement. The highest electrical efficiency was obtained with the 12710 series Peltier and the parallel foam arrangement at an air speed of 2 m/s; this value was 41.4% higher than the best result achieved by the 12706 series. Additionally, it was determined that the 12710 series Peltier modules generated, on average, 4.21% more electrical power than the 12706 series. The findings indicate that metal-foam-enhanced thermoelectric cooling is an effective method for maintaining the efficiency of PV panels in hot climate conditions and generating additional electrical power for the system.

Microbial infections are among the major factors that impair wound healing, and the increasing prevalence of bacterial resistance to antibiotics has highlighted the need to develop novel wound dressings with antimicrobial properties. The incorporation of antimicrobial nanomaterials into biocompatible polymer matrices represents a promising approach to improving wound dressing performance. The aim of this study was to prepare and evaluate the antimicrobial properties of a wound dressing containing silver quantum dots, zinc oxide quantum dots, and chitosan polymer. In this study, silver and zinc oxide quantum dots were synthesized, and chitosan was used as the polymeric matrix to prepare the composite wound dressing. To characterize the physicochemical and structural properties of the synthesized nanomaterials and the prepared wound dressing, Fourier-transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) analysis, and X-ray diffraction (XRD) were performed. The results of these analyses confirmed the formation of silver and zinc oxide quantum dots. The antimicrobial activity of the prepared wound dressing was also evaluated against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Enterococcus species using the agar diffusion assay and determination of the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). The results demonstrated that the prepared wound dressing exhibited antimicrobial activity against some of the tested bacteria. Overall, the findings indicate the potential of the composite wound dressing containing silver quantum dots, zinc oxide quantum dots, and chitosan to inhibit certain bacteria. These findings may provide a basis for further research into the development of nanostructured wound dressings with antimicrobial properties.

Rosehip (Rosa canina L.) is a medicinal fruit rich in phenolic compounds, and their recovery depends on solvent polarity and extraction technique. This study compared maceration with maceration followed by ultrasound-assisted extraction (UAE) using dimethyl sulfoxide (DMSO), methanol–water and ethyl acetate. Dried, deseeded fruit powder was extracted under identical conditions, with ultrasonication as the only additional step in the combined method. Total phenolic and flavonoid contents were determined, and antioxidant capacity was assessed by DPPH, ABTS and FRAP assays. Antimicrobial activity was evaluated by agar well diffusion and minimum inhibitory concentration against Gram-positive bacteria, Gram-negative bacteria and Candida albicans, and cholinesterase inhibition was measured by Ellman's method. Differences were analysed by ANOVA with Duncan's test (P < 0.05). DMSO combined with UAE gave the highest phenolic and flavonoid contents (P < 0.05) and the highest DPPH and ABTS activities, whereas methanol–water with UAE ranked next and showed the highest FRAP value. Ultrasonication increased antioxidant capacity in all solvents, with the highest absolute values in the polar solvents, while ethyl acetate maceration was lowest in every antioxidant assay (P < 0.05). All extracts inhibited C. albicans and Bacillus cereus, and several extracts were active against every tested organism, with no consistent advantage of ultrasonication. Ethyl acetate extracts showed the lowest minimum inhibitory concentrations, and the ethyl acetate ultrasound extract was the strongest inhibitor of both acetylcholinesterase and butyrylcholinesterase despite its weak antioxidant profile.DMSO with UAE was the most effective system for recovering antioxidant compounds, and polar solvents benefited most from ultrasonication, whereas the less polar ethyl acetate extracts showed stronger antimicrobial and anticholinesterase effects. Solvent and technique should therefore be selected according to the target activity, and chromatographic profiling is needed to identify the compounds responsible.

Osteosarcoma is a highly aggressive malignancy with limited therapeutic advancements, often characterized by overexpression of murine double minute 2 (MDM2) and functional suppression of p53. Diosmin, a citrus-derived flavonoid, exhibits broad pharmacological properties, yet its molecular role in MDM2-p53 regulation remains unexplored. This study investigates the anti-cancer potential of diosmin in osteosarcoma via modulation of the MDM2-p53 signaling axis. Human SJSA-1 osteosarcoma cells were treated with diosmin and assessed for viability, apoptosis (Annexin V/Propidium iodide (PI)), and cell cycle dynamics via flow cytometry. Western blot analysis was used to evaluate the expression of MDM2, p53, and caspase-3. Mechanistic validation employed ZVAD (a caspase inhibitor), MG132 (a proteasome inhibitor), and MDM2 siRNA. MDM2 ubiquitination was examined in vitro. Molecular docking and 100 ns molecular dynamics simulations assessed diosmin-MDM2 interactions. Diosmin induced dose-dependent cytotoxicity (IC₅₀ = 27.91 μM), G2-M arrest, and apoptosis. It suppressed MDM2, stabilized p53, and activated caspase-3, effects reversed by ZVAD and potentiated by MG132. MDM2 knockdown mimicked diosmin's effect and co-treatment showed no additive effect, indicating a shared pathway. Diosmin enhanced MDM2 ubiquitination, and showed favorable MDM2 binding affinity (−8.6 kcal/mol) and complex stability. Diosmin effectively disrupts the MDM2-p53 axis, inducing apoptotic cell death and tumor suppression in osteosarcoma. These findings highlight diosmin as a promising natural candidate for MDM2-targeted cancer therapy.

Neurological disorders cause substantial motor, sensory, and cognitive disability, while conventional pharmacological treatments often provide incomplete symptom control. Neuromodulation devices offer additional therapeutic options by altering neural activity through electrical or magnetic stimulation. However, their clinical effectiveness varies across diseases, patient populations and Technologies. These technologies include deep brain stimulation (DBS), transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), and responsive neurostimulation (RNS). These approaches differ in invasiveness, anatomical targets, stimulation delivery, and requirements for monitoring and programming. Implantable systems enable targeted or sustained stimulation, whereas noninvasive devices permit stimulation without intracranial electrode implantation. Clinical utility nevertheless depends on the specific disorder, patient characteristics, and strength of supporting evidence. In Parkinson’s disease, DBS addresses selected motor symptoms, while adaptive systems adjust stimulation according to recorded neural signals. In drug resistant epilepsy, VNS, DBS, and RNS provide options for selected patients; RNS detects abnormal electrophysiological activity and delivers stimulation through a closed loop system. For stroke rehabilitation, greater improvement in upper limb motor function when implanted VNS was paired with rehabilitation than with sham stimulation. TMS and tDCS are also investigated for neurological rehabilitation, although outcomes vary across protocols and indications. Overall, neuromodulation represents a clinically relevant intersection of neuroscience and biomedical device engineering. Translation requires careful patient selection, standardized outcome assessment, appropriate safety monitoring, and distinction between established applications and investigational techniques. Future advances should prioritize individualized targeting, biomarkers, and adequately powered comparative trials to clarify durable benefits and optimize device integration into multidisciplinary neurological care. This review aims to examine major neuromodulation technologies, summarize their clinical applications, and identify current limitations and future research priorities.

Creatine is one of the most popular supplements for enhancing muscular performance; however, the combined effect of creatine with resistance training on structural muscle changes has been less investigated. This study aimed to examine the effect of 8 weeks of resistance training and creatine supplementation on quadriceps muscle cross-sectional area (CSA) and jump power. Sixty male subjects aged 20–30 years were randomly assigned to 4 groups of 15: control, training, supplement, and training+supplement. The training program consisted of 3 sessions per week at 70–85% 1RM. The supplement group received 5 g of creatine monohydrate daily. Muscle CSA was measured by ultrasound, and jump power was assessed using the Sargent jump test. The training+supplement group is expected to show the greatest increase in muscle CSA and jump height, due to the synergistic effect of creatine on protein synthesis and phosphocreatine storage. Combining resistance training with creatine supplementation may lead to improvements in both the anatomical structure and physiological function of muscle

Neurological disorders represent a global health challenge, contributing to disability, mortality, and reduced quality of life. Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, stroke, and neurodevelopmental disorders involve interactions among genetic, metabolic, inflammatory, vascular, environmental, and lifestyle factors. Increasing attention has therefore focused on nutrition as a modifiable determinant of brain health and neurological outcomes. Smart Nutrition is a data-driven approach integrating nutritional science, artificial intelligence (AI), machine learning, and digital health technologies to develop personalized and adaptive dietary strategies. By combining dietary records with clinical characteristics, metabolic biomarkers, microbiome profiles, and lifestyle data, this approach seeks to identify individual nutritional needs and predict responses to dietary interventions. Particular attention is given to Mediterranean, DASH, MIND, and ketogenic dietary patterns, alongside omega-3 fatty acids, B vitamins, polyphenols, and microbiota-directed dietary fibers. Their potential relationships with neuroinflammation, oxidative stress, mitochondrial function, the gut–brain axis, cognitive resilience, and neurological disease management are discussed. Selected published studies are considered to illustrate how AI and machine learning have been applied to dietary pattern optimization, nutrition-related neurological risk prediction, digital dietary assessment, and prediction of responses to nutritional interventions. These applications may support a transition from generalized dietary advice toward more individualized, evidence-informed strategies. However, observational associations should not be interpreted as causal effects, and promising predictive models do not necessarily demonstrate clinical benefit. Limitations involving data quality, heterogeneous populations, algorithmic bias, interpretability, privacy, and insufficient prospective validation remain substantial. Interdisciplinary collaboration and clinical trials are essential before AI-supported nutritional recommendations can be implemented. Overall, Smart Nutrition provides a promising framework for connecting nutrition, neurological science, and digital technologies while preserving the central role of clinical judgment and robust evidence in patient care. This study will discuss nutrition-based approaches to neurological diseases and evaluates the contribution of Smart Nutrition and AI to personalized neurological care.

Chronic Hepatitis B Virus (HBV) infection remains a major global health challenge due to its persistence and progression to severe liver diseases. This study develops and analyzes a mathematical model to investigate the long-term dynamics of chronic HBV transmission. The disease-free and endemic equilibrium points, together with the basic reproduction number $\mathfrak{R}_0$, are derived and analyzed. Stability analysis establishes that the disease-free equilibrium is locally asymptotically stable when $\mathfrak{R}_0<1$, whereas the endemic equilibrium exists and remains stable for $\mathfrak{R}_0>1$, indicating a transcritical bifurcation at $\mathfrak{R}_0=1$. Sensitivity analysis identifies the key parameters influencing disease transmission and persistence. Furthermore, an optimal control framework incorporating vaccination, treatment, and immune enhancement is formulated to determine cost-effective intervention strategies. Numerical simulations validate the theoretical results and demonstrate that the proposed control measures significantly reduce chronic HBV prevalence, providing useful insights for effective disease management and public health policy.

In recent decades, the rapid development of nanoscience and nanotechnology has significantly increased interest in the fundamental and applied properties of semiconductor nanostructures. In low-dimensional systems such as quantum wells, quantum wires, quantum dots, and other nanostructures with characteristic dimensions comparable to the electron de Broglie wavelength or the exciton Bohr radius, the phenomenon of quantum confinement arises, in contrast to bulk semiconductor materials. Quantum confinement leads to the reconstruction of the electronic density of states, alteration of charge-carrier transport properties, and reorganization of optical transitions.

The objective of this work is to analyze, within a unified physical framework, the influence of quantum confinement on the energy spectrum and the electronic density of states in semiconductor nanostructures of different dimensionalities, to identify the limitations of existing theoretical models, and to establish the conceptual foundation for the development of a generalized theoretical model capable of providing a continuous description of energy spectrum transformation in semiconductor nanostructures.

The mathematical form of the density of states (DOS) depends on the dimensionality of the system, the nature of its energy spectrum, and the spatial localization of the electron wave functions. In three-dimensional bulk crystals, the density of states follows a square-root dependence on energy. In two-dimensional systems, it exhibits a step-like behavior, whereas in one-dimensional structures, Van Hove singularities emerge. In zero-dimensional quantum dots, the complete discretization of the energy spectrum results in a density of states determined by discrete quantum energy levels.
From this perspective, the investigation of the electronic density of states extends far beyond the calculation of discrete energy levels. The principal objective is to determine how quantum confinement transforms the energy spectrum, how this transformation modifies the analytical structure of the density of states, and how these changes are manifested in the macroscopic transport and optical properties of semiconductor nanostructures.

During the final stage of field exploitation, a decline in oil production is observed due to reservoir energy depletion, changes in the pressure regime, reservoir rock heterogeneity, increasing water cut, and the clogging of pore channels.Significant volumes of residual oil reserves remain in such reservoirs.Accurately assessing the current state of the reservoir-well system and forecasting the outcomes of the technological measures to be implemented are of great importance for the efficient recovery of these reserves. The aim of the study is to forecast the dynamics of changes in oil production based on mathematical models following the application of a nanotechnology-based method to the productive reservoir of an oil field at the final stage of exploitation.To this end, a fourth-degree polynomial regression model, and the Segmented (Modified) Arps model were applied to evaluate the production dynamics of the selected well. The polynomial regression model made it possible to determine the trend in the actual production data.The model results have shown that production does not exhibit a consistent trend over the years, with sharp increases and decreases observed during certain periods.Arps model makes it possible to account not only for the classic production decline phase but also for the phases of increase and stabilization that occur following technological intervention.Such an approach more accurately represents the actual production dynamics in long-term forecasting. Nanotechnology-based treatment of the reservoir–well system has also been considered promising for recovering residual oil reserves.The application of nanosystems makes it possible to improve the flow of residual oil from the reservoir to the wellbore and increase current oil production.The results of the study indicate that an integrated mathematical and hydrodynamic modeling approach enables the assessment of future production dynamics, the selection of optimal parameters for technological interventions.

Mobile gaming addiction has emerged as a significant behavioural problem which could be investigated mathematically through modelling techniques akin to those used for transmission of diseases in a population. In this paper, we propose a Takagi-Sugeno fuzzy fractal-fractional model to describe the dynamics of PUBG Mobile addiction via a system of five compartments: susceptible, exposed, addicted, treated, and recovered players. The nonlinear interaction that gives rise to the emergence of addicted players is modelled by means of an exact sector-based Takagi-Sugeno model, maintaining the original nonlinear system in the given state domain. This model is further generalized to a fractal-fractional system with two independent orders to incorporate memory and fractality effects in the system dynamics. The mathematical characteristics of the proposed model are explored through results on existence and uniqueness, positivity, boundedness, and Ulam-Hyers stability. For numerical solution of the fractal-fractional model, a piecewise Lagrange interpolation technique is utilized. To calibrate the model, an eighteen-months series of PUBG Mobile daily active user data from January 2024 to June 2025 is analysed. The proposed model is then estimated by fitting the model directly to the actual data by jointly optimizing the model rate parameters along with the two orders of the derivatives. The resulting fractal–fractional fuzzy framework is compared to the classical and fractional models using the same real dataset. It is evident from the numerical findings that the fractal–fractional model performs better with respect to the observed data and captures the slowly changing nature of the PUBG Mobile users.

This paper is devoted to the asymptotic analysis of a system of singularly perturbed integral equations with a piecewise-smooth matrix kernel. The presence of a small parameter multiplying the unknown function leads to a singular perturbation problem, in which the limiting equation may not adequately describe the behavior of the solution. The main objective is to construct an asymptotic approximation of the solution as the perturbation parameter tends to zero. For this purpose, a regularization method based on the Dirac delta function is employed. The proposed approach enables the integral operator to be transformed into a form suitable for systematic asymptotic analysis. Under appropriate smoothness and spectral assumptions on the kernel matrices, an asymptotic representation of the solution is constructed. The results provide a framework for investigating singularly perturbed integral systems with discontinuous kernels and contribute to the development of regularization techniques for nonlocal problems.

This study focuses on the development and MATLAB implementation of a four-node quadrilateral (Q4) finite element for the free bending vibration analysis of isotropic plates. A Mindlin–Reissner plate formulation is adopted so that transverse displacement and two independent rotations are considered at each node. The element formulation includes bending and transverse shear deformation, and a consistent mass formulation is used for dynamic analysis. The element equations are formulated in natural coordinates using bilinear Q4 shape functions, Jacobian transformation, numerical integration, and global finite element assembly. The transverse free vibration behavior of a uniform rectangular-cross-section structure fixed at its left edge is investigated. The natural frequencies are calculated by solving the generalized eigenvalue problem obtained for the global system. The results are also validated using ANSYS software. To further validate the numerical model, experimental modal testing was conducted on polyester specimens with three different thicknesses: 8 mm, 12 mm, and 16 mm. The experimental results exhibit good agreement with the numerical predictions across all three specimen thicknesses.

Fractal structures occur naturally in mathematics, physics, engineering, and many complex systems. Since classical calculus is formulated primarily on smooth spaces, a natural question arises: How can calculus be developed directly on a fractal set? In this talk, we introduce fractal calculus, a local framework for differentiation and integration on fractal supports. The approach is based on a fractal measure and an associated staircase coordinate, which encode the intrinsic geometry of the underlying set. This leads to the (F^\alpha)-derivative and (F^\alpha)-integral, where the order (\alpha) has a geometric interpretation related to the dimension of the fractal support. We emphasize the distinction between fractal calculus and conventional fractional calculus. While fractional calculus is commonly associated with nonlocal operators and memory effects, fractal calculus is designed to describe local differential and integral operations with respect to the geometry of a fractal set. The classical calculus is recovered in the limiting case (alpha=1). Several examples and applications will be presented, including fractal differential equations and models arising in mathematical physics and applied mathematics. We conclude by discussing current challenges and future directions in the development of analysis and differential equations on fractal structures.

The escalating prevalence of metabolic disorders, diabetes, and obesity has significantly shifted dietary patterns toward low-calorie and sugar-free food formulations. However, the reduction or complete replacement of sucrose with alternative sweeteners—such as polyols, stevia, and high-intensity sweeteners—imposes severe structural limitations on the food matrix, including gel network weakening, reduced plastic viscosity, phase separation, and impaired sensory attributes. In this context, naturally occurring mineral compounds, particularly hydrated phyllosilicates (clay minerals), have emerged as multifunctional texture modifiers and innovative processing aids. Owing to their layered/fibrous crystal structures, high specific surface area, cation exchange capacity (CEC), distinctive rheological behavior, and selective adsorption capabilities, clay minerals are widely utilized as food-grade technological additives and processing aids. Conventional applications encompass the refining and bleaching of edible oils, beverage clarification, mycotoxin detoxification (notably aflatoxins), and the stabilization and textural enhancement of suspension systems. Concurrently, the burgeoning market for sugar-free products introduces technological hurdles regarding rheological profile adjustments, physical stability, mouthfeel optimization, and lipid migration-induced fat bloom. This review comprehensively synthesizes the functional roles of food-grade bentonite/montmorillonite, kaolin, palygorskite/sepiolite, talc, and hydrotalcites, emphasizing their formulation utility in sugar-free systems, especially chocolate and confectionery matrices. Furthermore, essential safety criteria and quality control parameters—including mineralogical purity, heavy metal thresholds, microbial limits, and chronic exposure risk assessments—are critically addressed. The compiled evidence underscores that the targeted selection of clay species, rational surface functionalization, and stringent adherence to food-grade standards facilitate the formulation of next-generation sugar-free products exhibiting superior physical stability and enhanced sensory performance.

Ethiopia's Green Legacy Initiative (GLI) is one of Africa's most ambitious large-scale Nature-based Solutions. This study applied the Multiscale Hydrologic Ecosystem Services Proxy (MS-HES Proxy) Framework to evaluate the ecohydrological impacts of GLI across multiple spatial scales—from basin to plot level—within the Rift Valley Lakes Basin (RVLB). The approach integrated key indicators as proxies for ecosystem services: basin-scale Normalized Difference Vegetation Index (NDVI) for vegetation greenness, subbasin-scale curve number (CN) analysis for hydrological regulation and plot-scale Landscape Functionality Analysis (LFA) combined with the Shannon–Wiener Index to assess soil functionality, nutrient cycling and biodiversity. Results showed notable improvements across scales. NDVI increased from 0.48 to 0.53, indicating enhanced vegetation cover, whereas CN declined from 82.62 to 81.60, reflecting reduced runoff and improved flood regulation. At the field scale, soil stability rose from 35% (control) to 50% under GLI and 77.5% with soil and water conservation (SWC); infiltration nearly tripled (16.9% to 65%–68.9%); and nutrient cycling improved from 9%–14% to 46%–69%, reaching 100% under GLI + SWC. Biodiversity (H′) increased from 0.77 to 1.75 under GLI + SWC, peaking at 2.26. The results demonstrate a clear ecosystem-service pathway: restoring soil stability and hydrological function enhances regulating and supporting services, which in turn strengthen provisioning and cultural benefits. Overall, the study signifies a shift from tree planting towards multifunctional ecosystem restoration. Strengthening community-based watershed stewardship and long-term ecosystem management is essential to sustain GLI's ecological and socioeconomic benefits.

Biomass ash (BA) represents a promising secondary resource for the restoration of degraded soils, provided that its application rate is optimized and its nutrient limitations are addressed. This study evaluated the potential of BA to improve soil properties and plant performance by first conducting controlled pot experiments and subsequently validating selected treatments under field conditions. In the pot experiments, BA was applied as a sole amendment at rates of 1, 2.5, 5, and 7.5% (w/w) to assess its effects on soil chemical and biological properties and plant growth. Biomass ash increased soil pH, electrical conductivity, and the availability of P, K, Ca, and Zn. Low application rates (1% and 2.5%) improved soil properties and enhanced plant biomass, whereas higher rates adversely affected both soil conditions and plant growth. Nitrogen deficiency was identified as a major limitation of BA applied alone. Based on these findings, a field experiment was established on a brownfield soil using lower BA rates (1% and 2.5%), applied alone or in combination with digestate, with Miscanthus × giganteus (M×g) as the test crop. During the first year of the field experiment, some of soil parameters, particularly pH, did not differ significantly among treatments, which is consistent with the limited short-term response often observed under field conditions. However, nutrient concentrations, especially K and P, increased in the amended treatments. At the brown harvest, the BA 2.5%, Digestate, BA 1% + Digestate, and BA 2.5% + Digestate treatments all produced significantly higher biomass than BA 1%, with the highest mean recorded for BA 2.5% + Digestate. These results suggest that low-dose BA, particularly when combined with other organic amednments, has potential for improving soil nutrient status and supporting M×g performance; however, longer-term field monitoring is needed to determine the persistence and practical significance of these effects under field conditions.

Rapid industrialization, mining operations, fertilizer manufacturing, and dye synthesis have led to the extensive discharge of heavy metals and synthetic colorants into natural ecosystems. Due to their severe toxicity, environmental persistence, and non-biodegradability, these pollutants pose critical hazards to human health and ecological integrity. Conventional remediation strategies are frequently limited by high operational costs, intensive energy consumption, and the generation of secondary toxic sludge. Consequently, the pervasive contamination of aquatic and terrestrial matrices with heavy metals, synthetic dyes, and persistent organic compounds necessitates the development of cost-effective, sustainable, and indigenous remediation technologies. Clay minerals, characterized by their natural abundance, low cost, high specific surface area, substantial cation exchange capacity (CEC), and chemical stability, have emerged as highly efficient, eco-friendly adsorbents. Both pristine and surface-modified clays serve as viable, regenerative alternatives to commercial resins and activated carbon for effluent decontamination and toxic ion sequestration. In waste containment engineering and soil remediation, compacted bentonite liners and clay–cement stabilization/solidification (S/S) matrices exhibit ultra-low hydraulic conductivity, preventing leachate percolation and immobilizing hydrocarbon and metal contaminants via physicochemical entrapment. Furthermore, surface engineering techniques—such as acid activation, organoclay synthesis via surfactant intercalation, and nanocomposite fabrication—significantly enhance adsorption capacity and selectivity toward multi-pollutant systems. Overall, pristine and modified clay minerals offer a robust, sustainable, and green platform for environmental protection and waste management, provided that challenges regarding spent-adsorbent regeneration, safe disposal, and long-term desorption risks are effectively addressed.

Land surface temperature (LST) is a key indicator of urban thermal environments. However, studies of its drivers often rely on linear models or black-box machine learning, and rarely address nonlinearity, interpretability, and spatial autocorrelation together. This study proposes to analyze the factors controlling LST in Ho Chi Minh City using Landsat 8/9 imagery, combined with spectral indices (NDVI, NDBI, MNDWI, albedo), topography, and urban characteristics (built-up fraction, road density, population density, distance to water). The approach has two complementary branches: (1) gradient-boosted trees (XGBoost) with SHapley Additive exPlanations (SHAP) to quantify variable importance, nonlinear responses, and effect thresholds; and (2) a generalized additive model (GAM) with a spatial smooth term to account for residual spatial structure and to estimate spatially varying effects. Models will be evaluated using spatial block cross-validation to avoid optimistic bias from spatial autocorrelation, and residuals will be checked with Moran’s I. The study will compare SHAP-based and GAM-based interpretations to assess their consistency, and will derive thresholds for vegetation cover, proximity to water, and built-up density to support urban heat mitigation planning.

The global shift toward natural cosmetic and personal care products has expanded the utilization of clay minerals as active ingredients and multifunctional texture modifiers in skin, hair, and beauty formulations. Clay minerals are hydrous phyllosilicates characterized by unique physicochemical attributes, such as high specific surface area, cation exchange capacity (CEC), adsorption potential, biocompatibility, and chemical inertness. These properties have established them as essential components in modern cosmetic and dermatological products. The efficacy of these minerals in skin and hair care is derived from the physicochemical interactions between the clay surface and the skin microenvironment, facilitating the removal of sebum, sweat, and environmental pollutants. The layered architecture of smectites and the exceptional adsorption capacity of fibrous clays allow for the development of innovative formulations with advanced properties, including deep cleansing, oil control, anti-inflammatory action, and targeted active ingredient delivery. However, ensuring consumer safety necessitates the implementation of stringent geological purification protocols, rigorous heavy metal analysis, the exclusion of asbestiform fibers and free crystalline silica, and pH adjustment to ensure compatibility with the skin’s natural physiological acidity. When subjected to standardized purification and targeted surface modification, clay minerals represent highly efficient and safe options for enhancing the quality of therapeutic and aesthetic skin and hair care products.

The unique physicochemical properties of hybrid hydrogels create broad opportunities for their application in oil and gas engineering. In particular, these systems can be effectively utilized for formation water shut-off, selective plugging of high-permeability channels, profile control, and reservoir permeability restoration. The present study focuses on the swelling mechanisms of a xanthan/polyacrylamide-based hydrogel in various aqueous mediums, including buffer and saline solutions. The well-defined three-dimensional network was obtained in alkaline medium at a xanthan:PAAm mass ratio of 1:3 when the crosslinker concentration was in the range of 0.15–0.4 wt%. The swelling of the hydrogel increased with temperature, shows enhanced polymer chain mobility and accelerated water diffusion, and was systematically investigated in DW and physiological saline at 293-343 K. At all temperatures, the swelling degree increased with time, indicating a diffusion-controlled water uptake process followed by network relaxation. This behavior suggests that higher temperatures promote polymer chain mobility, reduce hydrogen bonding, and enhance solvent diffusion into the hydrogel network. In 0.9% NaCl solution also exhibited a clear temperature dependence; however, the overall swelling degree was lower than that observed in DW. The reduced swelling in saline medium can be attributed to the ionic strength effect, where Na⁺ ions partially screen the negatively charged functional groups of xanthan, thereby decreasing electrostatic repulsion and osmotic pressure within the network. The equilibrium swelling of the Xanthan/PAA hydrogel exhibited a temperature dependence in both DW and NaCl solution. In DW, the swelling capacity increased with temperature, indicating an endothermic and entropy-driven process due to enhanced chain mobility of the polymer network. The slight deviation observed at intermediate temperatures may be attributed to structural rearrangements and hydrogen-bond reorganization within the hydrogel matrix. In NaCl medium demonstrated more complex, non-monotonic behavior due to the competition between thermo activation and ionic screening effects.

The increasing contamination of water resources by petroleum-derived pollutants, synthetic dyes, and toxic organic compounds has created an urgent need for efficient, versatile, and environmentally sustainable remediation technologies. Carbon-based materials have emerged as promising platforms for environmental applications owing to their tunable surface, high surface area, porous structures, chemical stability, and ability to serve as supports for catalytically active species. In this contribution, our recent studies on the design and application of carbon-based materials for water remediation are highlighted. Carbonaceous materials with tailored surface properties were employed for the efficient removal of petroleum-related contaminants and a variety of organic dyes from aqueous media, demonstrating the importance of surface functionality, porosity, and pollutant–surface interactions in adsorption performance. In a complementary approach, carbon-based substrates were utilized for the immobilization of metal nanoparticles, providing heterogeneous catalytic systems with enhanced efficiency and reusability for the transformation of nitroaromatic pollutants into more valuable products. These studies demonstrate that rational engineering of carbon-based materials can provide multifunctional platforms capable of addressing different classes of water pollutants through adsorption and catalytic transformation. The combination of high adsorption capacity, effective nanoparticle stabilization, catalytic activity, and recyclability highlights the potential of carbon-based materials as versatile and sustainable materials for advanced environmental remediation.

The development of efficient, sustainable, and recyclable heterogeneous catalysts for multicomponent reactions is of considerable importance in view point of green and modern organic synthesis. In this study, nitrogen-doped carbon nanofibers (N-CNFs) were used as an efficient green catalyst for the Biginelli multicomponent reaction, providing a straightforward and environmentally friendly approach to synthesizing dihydropyrimidinone derivatives. The N-doped carbon nanofibers were prepared and characterized using appropriate spectroscopic and microscopic techniques, and their catalytic activity was evaluated in the condensation of aldehydes, β-ketoesters, and urea derivatives. The catalytic system afforded the desired products in good to excellent yields under mild reaction conditions. The enhanced catalytic performance of the N-CNFs can be attributed to the presence of nitrogen-containing surface functionalities, which provide catalytically active sites and facilitate the activation of the reaction components. Furthermore, the heterogeneous nature of the catalyst enables its facile separation from the reaction mixture and potential reuse in subsequent reaction cycles.

An early assessment estimated 10.36 million tonnes/year of plastic waste in the five littoral countries: Russia 7.15 million tonnes, Iran 1.8 million, Kazakhstan 950,000, Azerbaijan 290,000, and Turkmenistan 170,000 tonnes. About 425,000 tonnes/year were generated in coastal areas, with 58,000–155,000 tonnes/year entering the Caspian Sea. The 2019 Tehran Convention report lists coastlines of 955 km for Azerbaijan, 1,000 km for Iran, 2,320 km for Kazakhstan, and 1,200 km for Turkmenistan, while Russia has a longer coastline. In 2024, 4.07 million people lived in Azerbaijan’s Caspian coastal zone: Baku (2.35 million), Absheron (434,000), and Sumgait (428,000), indicating anthropogenic pressure. Wastewater, petroleum products, and other pollutants may enter the marine ecosystem. Marine plastics undergo aging, embrittlement, cracking, and fragmentation under temperature, solar/UV radiation, oxygen, ozone, ionizing radiation, water pressure, waves, mechanical forces, salinity, pH, and microorganisms. Waves, sand, gravel, and rocks accelerate abrasion and surface damage, while water pressure, salinity, pH, and microorganisms influence surface processes.
This study investigates plastic properties, packaging liquids, seawater parameters, chemical interactions, and surface chemical/mechanical changes caused by external factors. Post-consumer PP, PS, and PET were characterized using XRF, FTIR spectroscopy, mechanical testing (tensile strength, elongation at break, Young’s modulus), and seawater analysis. Surface, physicochemical, chemical, and photochemical changes induced by gamma irradiation, ozone, and UV irradiation were investigated. Results may improve understanding of plastic degradation and microplastic formation in the Caspian Sea.The work is conducted within IAEA Technical Cooperation Project RER7016, “Enhancing Coastal Management in Fresh and Saltwater Bodies by Using Nuclear Analytical Techniques, Including the Monitoring of Microplastics.”

In this study, the methanolic extract of the aerial parts of Anthemis talyschensis was used to synthesize silver nanoparticles (AgNPs) via a simple and rapid biological method. The synthesized nanoparticles were characterized using UV-Vis spectroscopy; their shape, size, and morphology were examined via Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM); and their structure, size, and composition were analyzed using X-ray diffraction (XRD). TEM analysis revealed the formation of silver nanoparticles with diameters ranging from 30 to 50 nm and an average diameter of 41.8 nm. SEM analysis indicated the formation of silver nanoparticles with a size of 43.0 nm. XRD patterns and analyses confirmed the formation of crystals with a face-centered cubic (fcc) geometry. Interpretation of FT-IR spectra indicated that active functional groups present in the plant extract were the primary agents responsible for the reduction of silver ions (Ag+) into silver nanoparticles. This study demonstrates that utilizing the extract from the aerial parts of Anthemis talyschensis offers a robust and cost-effective method for producing silver nanoparticles from silver ions. Producing silver nanoparticles through this approach is highly significant and valuable, given that the process is both rapid and environmentally friendly.

Bismuth telluride is a layered crystal with unique properties utilized in thermoelectrics and various sensors; it is a topological insulator and a promising material for spintronics. Of practical interest is the type of transport that achieves the maximum charge transfer density with maximum phonon scattering, which makes it possible to increase the thermoelectric figure of merit of the material by reducing thermal conductivity. It is known that in layered crystals, a portion of the super-stoichiometric excess and impurities forms nanostructural elements within interlayer spaces and defect cavities; in our case, the formation of nanocomposites in the form of superstructures was observed in doped Bi2Te3. The diverse nature of charge transport in a crystal—composed of phases with differing conduction characteristics and featuring an ordered structure of quintet-block arrays interspersed with layers of nano-inclusions and islands—significantly influences overall charge transport; this process is governed by the interplay between the crystal's continuous energy spectrum and the energy spectra and wave functions of localized states, the distribution of electron density across the material's thickness, band discontinuities at interfaces, and the rates of charge carrier emission and trapping at localized levels. Structural arrangement features significantly influence the mechanical properties of the crystals—a factor crucial for producing strengthened materials intended for use under high mechanical loads. We obtained strengthened Bi2Te3 crystals doped with various impurities (Cu; Cu+In; Ni; Fe, B, Zn) that exhibited a 15% increase in thermoelectric efficiency.

Silk fibroin has attracted considerable interest as a sustainable biopolymer for flexible electronics, biointegrated sensors, dielectric layers, and frequency-selective devices because of its biocompatibility, mechanical flexibility, film-forming ability, and solution processability. However, pristine fibroin is generally characterized by high electrical resistance and broad non-Debye relaxation behavior, which restrict its use in applications requiring controlled charge transport and frequency-dependent electrical performance. Incorporating metal-oxide nanoparticles into fibroin represents an effective strategy for modifying its dielectric properties through the formation of additional charge-transport pathways and electrically active interfaces. Among these nanofillers, TiO₂ is particularly attractive because of its chemical stability, high dielectric response, and sensitivity to defect engineering. Neutron irradiation can modify the defect structure and electronic properties of TiO₂ by generating or stabilizing Ti³⁺/oxygen-vacancy centers and producing transmutation-related dopants. Therefore, this study investigates the impedance relaxation and charge-transport behavior of silk fibroin composites containing pristine and neutron-modified TiO₂ nanoparticles. At higher TiO₂ loading, however, stronger Maxwell–Wagner–Sillars polarization and increased interfacial heterogeneity may broaden or partially slow the relaxation response. Neutron modification changes this balance by increasing the electrical activity of the TiO₂ nanofillers. Irradiation-induced Ti³⁺/oxygen-vacancy centers can serve as donor-like states and support defect-assisted or small-polaron hopping between neighboring titanium sites. Neutron-transmutation-generated vanadium dopants may provide an additional contribution to carrier density and local electronic conductivity. Consequently, charge exchange across the fibroin–TiO₂ interface becomes more efficient, the interfacial resistance decreases, and the characteristic impedance relaxation shifts toward higher frequencies. The response of the nanocomposites is therefore determined by the combined effects of thermally activated motion in the fibroin matrix, filler concentration, Maxwell–Wagner–Sillars polarization, and the defect structure of the TiO₂ nanoparticles. This interpretation provides a consistent physical framework for understanding how neutron-modified nanofillers can be used to regulate the macroscopic electrical behavior of flexible biopolymer composites.

Interface defects in perovskite solar cells (PSCs) are recognized as a major source of non-radiative recombination, which adversely affects device performance. In this study, the impact of interface defect density on the performance of a lead-free FTO/TiO₂/KSnI₃/Cu₂O/Au perovskite solar cell was investigated using the SCAPS-1D simulation platform. The simulation model was initially validated against a previously reported device, yielding a power conversion efficiency (PCE) of 8.87%, which closely matches the reported value of 8.88%. To evaluate the influence of interface defects, the defect densities at the TiO₂/KSnI₃ and KSnI₃/Cu₂O interfaces were independently varied from 10¹⁰ to 10²⁰ cm⁻³. The results revealed a pronounced difference in defect sensitivity between the two interfaces. Increasing the defect density at the TiO₂/KSnI₃ interface led to substantial reductions in open-circuit voltage (Voc) and overall efficiency, whereas the KSnI₃/Cu₂O interface exhibited relatively stable performance across a broader defect-density range. The optimum defect densities were identified as 1 × 10¹⁰ cm⁻³ for the TiO₂/KSnI₃ interface and 1 × 10¹⁴ cm⁻³ for the KSnI₃/Cu₂O interface. Under these optimized conditions, the device achieved a Voc of 1.1679 V, Jsc of 15.34 mA cm⁻², FF of 79.49%, and PCE of 14.24%, representing an efficiency enhancement of approximately 60% compared with the reference device. As all other device parameters were kept constant throughout the study, the observed improvement can be attributed solely to the reduction of interface-assisted recombination losses. These findings indicate that the TiO₂/KSnI₃ interface is the primary recombination pathway in the device and underscore the critical role of ETL/absorber interface engineering in improving the performance of lead-free KSnI₃ perovskite solar cells.

This study investigates the temperature-dependent dielectric relaxation of bromobenzene in two structurally different nonpolar solvents, benzene and n-hexane, with the aim of elucidating the role of solvent structure and intermolecular interactions in the dynamics and thermodynamics of dipole reorientation. The complex dielectric permittivity, including its real (ε′) and imaginary (ε″) components, was experimentally determined in the microwave range at a wavelength of λ = 12.8 mm over the temperature interval of 193–293 K. The temperature dependence of the dielectric relaxation time (τ) was established for both binary systems, allowing the effect of the molecular environment on relaxation dynamics to be assessed. Within the framework of absolute reaction-rate theory, the activation free energy (ΔF), enthalpy (ΔH), and entropy (ΔS) of the relaxation process were determined. The results demonstrate a pronounced dependence of the relaxation dynamics on the molecular structure of the solvent. Comparison of the bromobenzene–benzene and bromobenzene–n-hexane systems reveals systematic differences in the relaxation behavior and thermodynamic activation parameters, reflecting the distinct intermolecular environments surrounding the bromobenzene molecules. The novelty of this study lies in establishing a direct relationship between solvent molecular structure, dielectric relaxation dynamics, and the thermodynamic parameters governing dipole reorientation. The analysis shows that the energy barrier and degree of molecular ordering during relaxation are determined not only by the properties of bromobenzene but also by the structural organization and intermolecular interactions of the surrounding solvent. These findings provide new insight into solvent effects on dielectric relaxation in nonpolar binary molecular systems.

Based on the perovskite material, lead-based perovskite solar cells exhibit outstanding photovoltaic properties, but their toxicity poses environmental and health issues that hinder sustainable commercialization. In this study, a lead-free cesium titanium chloride based perovskite solar cell is proposed and optimized with numerical simulation and hybrid optimization. The structure of the device is made of FTO/CdS/Cs₂TiCl₆/CdTe/Au. The baseline device's average open-circuit voltage, short-circuit current density, fill factor and power conversion efficiency were 1.014 V, 20.32 mA/cm², 88.06%, and 18.14% respectively. The influence of absorber thickness, doping density of the absorber, defect density of the absorber, and transport layer thickness on the performance of the device were investigated using parametric analysis. Multiple photovoltaic responses were considered using Grey Relational Analysis, simulation runs were reduced using the Taguchi method and L9 orthogonal array. The optimized Taguchi–Grey Relational Analysis result was an efficient of 23.45%, which was better than the baseline. An optimized efficiency of 24.25% was obtained after further optimization using the Genetic Algorithm. Based on these results, it can be concluded that the proposed hybrid optimization method can be used to optimize the simulated performance of lead-free perovskite solar cells prior to real fabrication.

Compression ratio is one of the most important design parameters of compression-ignition engines, directly affecting the combustion process, engine performance, fuel consumption, and emissions. In this study, the effect of compression ratio on the performance of a single-cylinder Ruston & Hornsby 1YWA diesel engine was investigated using the GT-SUITE software. First, a one-dimensional engine model was developed in the GT-SUITE environment based on the engine’s geometric and operating specifications, including cylinder bore, piston stroke, displacement volume, direct fuel injection system, and operating conditions. The model results were then validated against reliable data available in the scientific literature in terms of the variation in in-cylinder pressure. Subsequently, the effects of three compression ratios, 16, 17, and 18, over an engine speed range of 1000–2000 rpm were evaluated with respect to performance parameters, including in-cylinder pressure and temperature, brake mean effective pressure (BMEP), brake-specific fuel consumption (BSFC), and brake-specific carbon monoxide (CO) emissions. The simulation results showed that increasing the compression ratio increased the peak pressure and temperature within the combustion chamber, improved the combustion process, and increased the brake mean effective pressure. Furthermore, an increase in compression ratio resulted in a reduction in both brake-specific fuel consumption and carbon monoxide emissions at all engine speeds, indicating improved thermal efficiency and more complete combustion of the fuel. Investigation of the effect of engine speed showed that increasing engine speed increased the peak in-cylinder pressure and temperature, whereas BMEP exhibited a decreasing trend and BSFC showed an increasing trend. Overall, a compression ratio of 18:1 provided the most favorable performance in terms of improving efficiency and reducing fuel consumption and CO emissions. The results of this study demonstrate that optimization of the compression ratio can be an effective approach for improving the performance of single-cylinder diesel engines and reducing energy consumption.

Naturally aspirated engines provide adequate performance in urban and highway driving conditions where high power and acceleration are not required. However, when greater acceleration and power are needed, mechanical supercharging can be used to increase engine torque and power. This study investigates the effects of mechanical supercharging on a four-cylinder engine. First, the engine was modeled in GT-Suite, and the simulation results were compared with experimental data. After the model was validated, a mechanical supercharger with an intercooler was incorporated into the engine model. Engine power, torque, brake-specific fuel consumption (BSFC), and emissions of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) were then compared between the naturally aspirated and supercharged configurations. The results indicate that supercharging can substantially increase torque and power, with only modest increases in fuel consumption and some emissions. The greatest increases occurred at 6000 rpm: torque rose from 113 to 208 N·m, while power increased from 95 to 175 hp. On average, brake-specific HC emissions, brake-specific CO emissions, and BSFC increased by 5.4%, 3.7%, and 3.65%, respectively, whereas brake-specific NOx emissions decreased by an average of 10.58%.

Valve springs are critical components of internal combustion engines that are subjected to cyclic loading during engine operation. Therefore, investigating their mechanical behavior is of considerable importance. In this study, the static behavior of the K4M engine valve spring was investigated using the finite element method (FEM). First, the geometry and dimensions of the actual spring were measured, and its three-dimensional model was developed using SolidWorks. The developed model was then transferred to the ANSYS Workbench environment for static structural analysis. The spring material was assumed to be SAE 6150 (50CrV4/51CrV4), and its mechanical behavior was evaluated under different compressive loads ranging from 150 to 250 N. The main parameters considered in the analysis were the maximum shear stress and maximum deformation, and the effects of increasing the applied load on these parameters were evaluated. The results showed that both the maximum shear stress and deformation increased with increasing compressive load. At a load of 250 N, the maximum deformation and maximum shear stress were approximately 24.83 mm and 259.54 MPa, respectively. The obtained results can be used to evaluate the mechanical performance and support the design and analysis of the K4M engine valve spring.

Urban rail systems stand out as strategic infrastructures for urban mobility, since, depending on their implementation, they promote accessibility, improve quality of life and reduce environmental impacts, with emphasis on mitigating vehicular traffic and atmospheric pollution resulting from the use of fossil fuels. faced with the need to decarbonize the transportation sector, the electrification of modes, combined with the incorporation of renewable sources of energy, emerges as an alternative to reduce emissions of pollutants and greenhouse gases. This article aims to analyze strategies for integrating renewable sources into subway systems in developed and developing countries, evaluating, from a comparative perspective, the business models adopted, the location of energy generation and the resilience of the systems in the face of operational disturbances. The research is characterized as qualitative, exploratory-descriptive in nature, based on an analysis of scientific literature. The multiple case study method was adopted with a comparative approach between three experiences: two international case studies (REDWAN, 2024 and Viswambharan et al., 2018) and one national case study (São Paulo Metro, 2025). The data were systematized using an analytical matrix composed of pre-defined criteria, covering the type of energy source, generation location, business model, resilience and main advantages and disadvantages identified in each context. The findings reveal different degrees of technological and institutional maturity between cases, demonstrating that the energy transition in metro transport transcends the technological dimension and requires a structural debate on energy sovereignty, operational resilience and socio-environmental equity, aspects that, in the Brazilian context, remain underexplored and lack greater regulatory transparency.

The purpose of this article is to analyze the recent rise of China and South Korea as global leaders in the production and export of electric vehicles by examining the industrial policies these nations have implemented in the sector. This definition of electric vehicles includes all vehicles (passenger cars, buses, trucks, utility vehicles, etc.) and propulsion types that are not exclusively combustion-based, such as battery electric vehicles (BEVs), conventional hybrids (HEVs), plug-in hybrids (PHEVs), and fuel cell vehicles (FCEVs). The study explores the rapid growth in the production of and demand for EVs worldwide, with special attention paid to the growing popularity of this type of vehicle in the Brazilian market and China’s emergence as its main supplier. It then discusses the general context of the development strategy that guides industrial policy initiatives in East Asian countries based on the concept of “developmental environmentalism.” This approach explains how these national energy transitions function as strategies to continue their development trajectories, ensuring these nations’ dominance over the production chains relevant to electrification. The study then analyzes in greater detail the national industrial policy cases for the automotive sector and the electric vehicle production chains in China and South Korea, respectively. Thus, the authors aim to contribute to an understanding of the economic planning aspects of vehicle electrification in the sector’s current frontrunners. This understanding is relevant for the formulation of Brazilian projects aimed at responding to and catching up in this segment.

The rapid integration of artificial intelligence (AI) into education presents a critical challenge: institutions lack scalable, theoretically grounded tools to assess students' underlying cognitive and epistemic dispositions toward knowledge and technology. Understanding these dispositions is essential for personalizing learning and identifying potentially maladaptive patterns. This study addresses this gap by developing and applying a machine learning-based framework to evaluate two novel constructs in higher education students: Epistemic Orientation Index (EOI) and Mental Polarity Index (MPI). The EOI measures a student's position on a continuum from knowledge replication (viewing knowledge as fixed) to knowledge generation (viewing knowledge as evolving). The MPI assesses cognitive degradation and polarity shifts. To operationalize these indices, a supervised machine learning model was trained on a purpose-built database of textual phrases, each independently rated by experts for its alignment with EOI and MPI constructs. This trained model was then applied to analyze student-generated text data. The key findings demonstrate that the model successfully classifies students' epistemic and mental polarity profiles, revealing significant variability across the student population. This approach enables the automated identification of students who may benefit from pedagogical interventions tailored to their specific orientation, particularly those exhibiting patterns associated with cognitive rigidity or negative polarity. The significance of this research lies in providing a scalable, automated assessment tool that bridges theoretical models of cognition with practical educational applications. It offers a foundation for developing personalized teaching methodologies and early identification of students who may be at risk of disengagement or cognitive stagnation, thereby contributing to more adaptive and responsive higher education systems.

Accurate prediction of bone fracture probability and identification of areas susceptible to damage is an important challenge in biomechanics and medical engineering. This study aimed to develop a framework for bone fracture risk assessment, combining Finite Element Analysis (FEA) and Explainable Machine Learning (XAI). By applying loading conditions related to standing and walking postures, stress distribution, stress concentration areas, and bone mechanical behavior are investigated using the finite element method. Fracture mechanics approach is also used to simulate surface cracks with different geometries and positions to determine the stress intensity factor at the crack tip and investigate crack growth. The modeling results show that bone geometry, bone elastic modulus, load application, and crack location and size are important factors affecting the mechanical response and vulnerability of the femur. A decrease in bone elastic modulus, which can indicate a decrease in bone quality, causes a significant increase in tensile stress in some conditions. Fracture mechanics analysis also shows that the location of cracks in different bone regions has a direct impact on the stress intensity factor of the first mode and, consequently, the probability of crack propagation and failure. In the second stage, numerical outputs from the finite element analysis, including tensile and compressive stresses, displacement, stress intensity factor, crack size and location, and mechanical parameters, are used as input variables to develop machine learning models. Using explainable machine learning methods, the relative contribution of each input parameter is determined. Thus, unlike purely predictive models, the proposed framework can explain the mechanical and geometric factors affecting the model's decision. The proposed framework can be used for personalized assessment of bone fracture risk and identification of critical areas. Combining FEA with explainable machine learning enables the connection between the mechanical behavior of bone and data-driven prediction.

This research explores a theoretical foundation for an intelligent machine capable of human-like reasoning through relational geometry, context, and self-reference. It proposes a framework for Quantum-Relational Artificial Intelligence based on Self-Referential Focal Relations (SRFR). The main idea is to represent information not simply as separate objects or states, but through the relationships between an observer and an object. The proposed information structure includes four elements: the relation between the subject and the object, the possibility of this relation, its necessity, and its temporal context. Inspired by Lotfi A. Zadeh’s possibility theory, possibility and necessity are used to describe incomplete knowledge without forcing it into a single probability value. In the proposed relational geometry, self-reference means that the relation itself becomes part of the information. The subject, the object, and their relation form one connected configuration. As a result, the system considers not only what is observed, but also how it is observed and from what relational position. The observer is therefore not an external label added to the information; the observer’s relation to the object is part of the information itself. The framework brings together Zadeh’s possibility theory, fuzzy relations, evidence-based reasoning, and ideas inspired by quantum information. It provides a way to describe an informational state through the object, the observer, their relation, and the surrounding context. This is a theoretical framework for further developing intelligent systems that can work with incomplete, uncertain, and changing knowledge. Future work will focus on developing rules for updating relational states, algorithms for interactions between SRFR nodes, and comparisons with probabilistic and neural approaches. The goal is to investigate whether relational geometry can provide a foundation for machines capable of more human-like forms of reasoning. This research is to connect human-like reasoning, relational geometry, ideas of quantum theory, and self-reference within one framework.

This study investigates how an artificial intelligence (AI)-DevSecOps framework can support the modernization of major-specific ICT education and the alignment of course content with contemporary industry requirements. A comparative case study was conducted for the “Computer Networks” course at the University of Central Asia using teaching materials from the fall semesters of the 2022/2023 and 2025/2026 academic years. A corpus-based lexical analysis was performed using a 444-term computer-networking glossary as specialized vocabulary. The number of glossary terms with non-zero occurrences increased from 97 to 173, corresponding to a 1.78-fold increase in the breadth of specialized terminology represented in the course materials. The framework also incorporated cybersecurity-related subtopics into a 15-week sequence and supported the iterative development of presentations, practical assignments, and quizzes with generative AI and DevSecOps practices. The findings indicate substantial expansion of course-content coverage; however, the study does not establish a causal effect on student learning or employment outcomes. The results suggest that an AI-DevSecOps approach can support curriculum modernization by combining AI-assisted content development, practical cybersecurity activities, and continuous alignment with industry-oriented ICT competencies.

Food waste in school catering represents a major environmental, ethical, and economic challenge. This study investigated food waste in two Tunis private primary schools operating under a centralized logistics model (reheating and service only, with three rapid shifts). It aimed to diagnose baseline waste causes and evaluate a short-term, gamified pedagogical intervention. The study targeted pupils from the 3rd to 6th grades (mean: 191/service). Phase 1 consisted of precise daily waste weighing during 10 days, and 224 face-to-face parental interviews. Phase 2 was a 10-day campaign combining empathy-based education (a cartoon anthropomorphizing a strawberry's lifecycle, followed by a discussion), and social gamification (a "Zero Waste Table Captains" inter-table competition with merit points). The baseline diagnosis revealed critical thresholds being exceeded: kitchen surplus stood at 14.4% (Vaz limit: 3%), plate waste reached 39% (Aragão limit: 10%), and the overall Waste/Consumption Index peaked at 64.23% (106g/pupil; Ferrara threshold: 15%). Raw salads were initially the most rejected item (163%), while bread was well-preserved (2.41%). The parental survey highlighted a structural paradox: 91% viewed waste as an ethical/religious transgression, yet only 29% systematically educated their children about it. This gap was aggravated by oversized portions and rushed shifts. Following the campaign, the overall index achieved a 58% reduction, dropping sharply to 26.88% for the waste/consumption index (49g/pupil, a 54% decrease in mass). Post-intervention food typologies revealed an important drop in salad waste to 25.30%. Conversely, cereal dishes remained critical, with pasta at 38.72% and couscous at 96.22%. The intervention successfully triggered a behavioral shift, particularly regarding vegetable acceptance. However, high waste in cereal products shows that behavioral nudging must be paired with operational updates to tackle rigid, oversized portion sizes.
Acknowledgments: The authors want to thank Bouebdelli Education Group for their valuable support throughout this research project.

Gulazik is a traditional meat-based food prepared from meat, kurut (dried fermented curd), and talkan (roasted grain flour). This study investigated the effects of meat species (beef, horsemeat, and mutton) and oven-drying temperatures (50 °C, 75 °C, and 100 °C) on the physicochemical quality attributes and lipid oxidation dynamics of standardized Gulazik formulations containing 65% dried meat, 10% kurut, and 25% talkan. Dry matter content and water activity ranged from 93.03% to 95.11% and from 0.33 to 0.38, respectively, with drying temperature significantly affecting both parameters. All aw values remained below 0.60, indicating low susceptibility to microbial growth. pH values ranged from 5.58 to 6.12, with horsemeat dried at 100 °C exhibiting the lowest value (5.58), while titratable acidity ranged from 0.26% to 0.45%. Color analysis showed a significant decline in lightness (L: 43.49 – 60.60) with increasing temperature, likely associated with Maillard reaction and myoglobin denaturation. Redness (a) values remained near neutral, whereas yellowness (b*: 22.74 – 31.51) dominated the visual profile. Mutton samples had the highest crude fat content (14.21 – 16.99%),with lower values observed at 100 °C, whereas the fat content of beef and horsemeat samples increased with temperature, likely due to moisture loss. Horsemeat exhibited the highest lipid oxidation, with thiobarbituric acid substances (TBARS) values reaching 5.23 mg MDA/kg at 50 °C. The lower TBARS values observed at 100 °C may reflect malondialdehyde loss or its involvement in secondary reactions, including interactions with Maillard reaction products and proteins. Overall, meat species and drying temperature significantly influenced the physicochemical quality and oxidative stability of Gulazik. The low water activity achieved across all treatments indicates favorable conditions for microbiological stability, while the marked differences in lipid oxidation among meat species and drying temperatures highlight the importance of optimizing processing conditions to maintain product quality.

The aim of this study was to identify expert opinions and consensus regarding food safety-related components within the One Health approach and to provide recommendations for evaluating food safety within a One Health framework. The study was conducted using a two-round Modified Delphi Consensus Method. The study group consisted of academic staff from the Faculties of Medicine, Dentistry, Nursing, Education, Veterinary Medicine, Health Sciences, Agriculture, Science, and Economics and Administrative Sciences at a public university in Türkiye. A total of 108 participants took part in the first Delphi round and 64 in the second round. Data were collected electronically using semi-structured forms and evaluated using the median, interquartile range (IQR), and consensus percentage. Consensus was defined as a median ≥4, IQR ≤1, and consensus percentage ≥80%. Within the scope of this study, Delphi items considered directly or closely related to food safety were examined through a secondary analysis. The Delphi process demonstrated consensus on the integrated consideration of various One Health components related to food safety. These components included human health and nutrition, zoonotic diseases and their epidemiology, the human-animal-plant-environment-ecosystem interface, sustainable food and water safety, environmental health and ecotoxicological risks, ocean health, and antimicrobial resistance. In addition, learning methods and assessment and evaluation methods for addressing food safety-related topics within the One Health approach were identified based on expert consensus, indicating their potential to contribute to innovative practices and new approaches in food safety education. In conclusion, this Delphi consensus provides a framework for addressing food safety multidimensionally within the One Health umbrella and for advancing food safety education in alignment with this approach.

Damage to the electrical grid and disruptions to transportation networks during disasters lead to significant losses in cold-chain-dependent food products. Items such as dairy products, fresh fruits and vegetables, meat, and baby food spoil rapidly when appropriate temperature conditions cannot be maintained. This situation results in both the waste of aid resources and a compromise in the food security of the affected population. In current disaster logistics practices, refrigeration infrastructure relies heavily on diesel generators, a reliance that increases dependence on fuel supplies and exacerbates negative environmental impacts. This study aims to examine the design principles and operational suitability of renewable energy-powered mobile cold storage units intended to reduce food loss in disaster zones. The study proposes evaluating modular cold storage units—supported by solar energy and battery storage systems—based on criteria such as capacity, energy efficiency, portability, and setup time. The methodology combines a systematic literature review with a comparative analysis of selected disaster cases, focusing particularly on the 2023 Kahramanmaraş earthquakes. Additionally, site selection factors, specifically the pre-positioning of storage units within disaster zones and their proximity to demand points are addressed. The study is expected to demonstrate that these systems can mitigate food spoilage, reduce fuel dependency, and strengthen logistical continuity. However, limitations such as high initial investment costs, seasonal variations in energy efficiency, and operational capacity constraints will also be discussed. It is anticipated that the study will contribute to the United Nations (UN) Sustainable Development Goals—specifically the goals of Zero Hunger, Affordable and Clean Energy, and Responsible Consumption and Production—in alignment with these objectives. Consequently, it aims to offer policy and implementation recommendations directed at these goals.

In this study, the phytosynthesis of silver nanoparticles was carried out using the hydromethanolic extract of the fruit of the pumpkin plant (Cucurbita moschata), and their physicochemical characteristics were investigated using TEM, SEM, FT-IR, UV/Vis, and XRD techniques. The results of transmission electron microscopy (TEM) showed that the average size of the obtained silver nanoparticles was approximately 38 nm. Scanning electron microscopy (SEM) also showed that the size of the silver nanoparticles ranged from 33 to 50 nm. The results of X-ray diffraction (XRD) analysis indicated that the nanoparticles were spherical in shape, with a face-centered cubic (FCC) structure and a size of 32.8 nm. FT-IR spectroscopic analysis of the plant extract before and after nanoparticle synthesis revealed the presence of functional groups that may be involved in nanoparticle formation. The phytosynthesis of silver nanoparticles using C. moschata is an efficient, cost-effective, inexpensive, and environmentally friendly synthetic method and can serve as an alternative to conventional synthesis methods.

Abstract
Carbon nanotubes (CNTs) have attracted considerable attention as sorbent materials for the extraction and preconcentration of organic and inorganic compounds because of their high surface area and adsorption capacity. In this study, a solid-phase extraction method based on functionalized carbon nanotubes was developed for the extraction and determination of two benzodiazepines, diazepam and lorazepam, from aqueous samples. Single-walled carbon nanotubes (SWCNTs) were chemically functionalized with carboxyl groups, and their surface was further modified using Silane A174 through a sol–gel process. The functionalized sorbent was characterized by Fourier-transform infrared (FTIR) spectroscopy. Gas chromatography coupled with mass spectrometry (GC–MS) was employed for the separation and quantitative determination of the target analytes in selected-ion monitoring (SIM) mode. Experimental parameters affecting the extraction efficiency, including pH, extraction and desorption solvents, extraction time, sorbent amount, and adsorption and desorption temperatures, were systematically optimized. Under the optimized conditions, the proposed method exhibited satisfactory extraction performance for both benzodiazepines. The limits of detection were 26.74 and 475.91 ppb, while the limits of quantification were 158.64 and 76.24 ppb for lorazepam and diazepam, respectively. The results indicate that functionalized CNTs can serve as suitable sorbents for the extraction and preconcentration of benzodiazepines from aqueous samples.

Chronic wounds, due to infection and biofilm formation, are among the major challenges in wound care. The combination of chitosan, silver nanoparticles, and bioactive compounds of thyme may provide a suitable approach for developing an antimicrobial wound dressing. This study aimed to synthesize and evaluate the physicochemical and antimicrobial properties of a polymeric wound dressing containing chitosan, silver nanoparticles, and thyme essential oil. Silver nanoparticles were synthesized, and the wound dressing was prepared. The physicochemical characteristics of the samples were evaluated using XRD, FTIR, EDS, FESEM, DLS, and BET. The antimicrobial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Enterococcus faecalis was assessed using MIC, MBC, and AATCC 100 assays. The XRD pattern showed a phase consistent with Ag₂O, with a crystallite size of 26 nm. FTIR analysis revealed the functional groups of chitosan and the Ag–O bond. The silver content determined by EDS was 19.99 wt%. FESEM analysis showed a rough, layered surface with small pores. The average particle size determined by DLS was approximately 165 nm, with a Z-average of 211.8 nm and a PDI of 0.701. The zeta potential was −48.5 mV, and the BET specific surface area was 2.36 m²/g. The MIC and MBC results demonstrated inhibitory and bactericidal activities of the samples. According to the AATCC 100 test, the reductions in Pseudomonas aeruginosa and Enterococcus faecalis were 100%, while the reductions in Escherichia coli and Staphylococcus aureus were 99.67% and 6.25%, respectively. The prepared wound dressing demonstrated suitable physicochemical properties and considerable antimicrobial activity and may be a potential candidate for antimicrobial applications in wound dressings.