Search Results (2,468)

Neurodegenerative disorders, including Alzheimer’s disease (AD), are a growing problem in aging society. The amyloid cascade hypothesis has recently been questioned, and therapies based on it have not yielded the expected results. However, the role of amyloid-β (Aβ) in AD pathogenesis cannot be rejected. It appears that some of the key players in the pathogenesis of the disease are the soluble amyloid-β oligomers. Soluble amyloid-β oligomers have neurotoxic effects by disrupting intracellular Ca²⁺ homeostasis and impairing mitochondrial function. The glymphatic system is an important pathway for the removal of soluble amyloid forms from the brain. The decline in the activity of this system is observed in aging brains, which is correlated with the occurrence of Alzheimer’s disease, primarily among the elderly population. Therefore, the question arises as to whether the glymphatic system could be another potential target for therapeutic interventions in Alzheimer’s disease. In this regard, it is imperative to pay attention to the factors that contribute to the pathogenesis of Alzheimer’s disease and also impact the glymphatic system, such as sleep, physical activity, alcohol consumption, and supplementation with polyunsaturated fatty acids. The question remains whether the glymphatic system will become the key to treating Alzheimer’s disease. Full article

While acetic acid has proven effective as a mild acidic treatment for removing adhered mortar from recycled concrete aggregate (RCA) surfaces, its potential for dissolving damage to the surface of the original natural coarse aggregate (NCA) within the RCA and its impact on the resultant concrete properties require careful consideration. This investigation systematically evaluates the effects of varying concentrations of dilute acetic acid solutions, commonly used in RCA treatment protocols, through a multi-methodological approach that includes comprehensive physical characterization, stylus and 3D optical profilometry, scanning electron microscopy (SEM), and nanoindentation analysis. The results show that even dilute acid solutions have an upper concentration limit, as excessive acid concentration, specifically 0.4 M, induces significant textural dislocations on NCA surfaces, creating millimeter-scale erosion pits that increase aggregate water absorption by 18.5%. These morphological changes significantly impair concrete workability and reduce compressive strength performance. Furthermore, microstructural analysis reveals a 45.24% expansion in interfacial transition zone (ITZ) thickness, accompanied by notable reductions in elastic modulus and microhardness characteristics. In practical RCA treatment applications, for RCA containing limestone-based NCA, it is recommended to use acetic acid concentrations between 0.1 and 0.3 M to avoid substantial physical and microstructural degradation of aggregates and concrete. Full article

UAV-based inspections are an effective way to ensure railway safety and have gained significant attention. However, images captured during complex weather conditions, such as rain, snow, or fog, often suffer from severe degradation, affecting image recognition accuracy. Existing algorithms for removing rain, snow, and fog have two main limitations: they do not adaptively learn features under varying weather complexities and struggle with managing complex noise patterns in drone inspections, leading to incomplete noise removal. To address these challenges, this study proposes a novel framework for removing rain, snow, and fog from drone images, called WeatherClean. This framework introduces a Weather Complexity Adjustment Factor (WCAF) in a parameterized adjustable network architecture to process weather degradation of varying degrees adaptively. It also employs a hierarchical multi-scale cropping strategy to enhance the recovery of fine noise and edge structures. Additionally, it incorporates a degradation synthesis method based on atmospheric scattering physical models to generate training samples that align with real-world weather patterns, thereby mitigating data scarcity issues. Experimental results show that WeatherClean outperforms existing methods by effectively removing noise particles while preserving image details. This advancement provides more reliable high-definition visual references for drone-based railway inspections, significantly enhancing inspection capabilities under complex weather conditions and ensuring the safety of railway operations. Full article

Dye residues from the textile industry constitute a critical wastewater problem. This study aimed to evaluate the removal capacity of methylene blue (MB) in aqueous media, using an adsorbent formulated from activated and sonicated nanoclay (NC) and microatomized Nostoc sphaericum (ANS). NC was obtained by acid treatment, followed by activation with 1 M NaCl and sonication, while ANS was obtained by microatomization in an aqueous medium. NC/ANS was mixed in a 4:1 weight ratio. The NC/ANS synergistic adsorbent was characterized by the point of zero charge (PZC), zeta potential (ζ), particle size, FTIR spectroscopy, and scanning electron microscopy (SEM). NC/ANS exhibited good colloidal stability, as determined by pH_PZC, particle size in the nanometer range, and heterogeneous morphology with functional groups (hydroxyl, carboxyl, and amide), removing between 72.59 and 97.98% from an initial concentration of 10 ppm of MB, for doses of 20 to 30 mg/L of NC/ANS and pH of 5 to 8. Optimal adsorption conditions are achieved at pH 6.8 and 32.9 mg/L of adsorbent NC/ANS. It was observed that the pseudo-first-order (PFO) and pseudo-second-order (PSO) kinetic models best described the adsorption kinetics, indicating a predominance of the physisorption process, with adsorption capacity around 20 mg/g. Isotherm models and thermodynamic parameters of adsorption, ΔS, ΔH, and ΔG, revealed that the adsorption process is spontaneous, favorable, thermodynamically stable, and occurs at the monolayer level, with a regeneration capacity of 90.35 to 37.54% at the fifth cycle. The application of physical activation methods, such as sonication of the clay and microatomization of the algae, allows proposing a novel and alternative synergistic material from organic and inorganic sources that is environmentally friendly and promotes sustainability, with a high capacity to remove cationic dyes in wastewater. Full article

In this work, the biosorption potential of Spirulina sp. as an effective and eco-friendly biosorbent for the removal of Ni(II) and Pb(II) ions from aqueous solutions was investigated. Detailed characterization of the biosorbent was carried out, including surface morphology, chemical composition, particle size, zeta potential, crystallinity, zero-point charge, and functional group analysis. Batch tests were performed to determine the kinetic constants and adsorption equilibrium of the studied ions. The adsorption behavior of Spirulina sp. was described using six adsorption isotherms. The best fit was obtained for the Redlich-Peterson and Langmuir isotherms, indicating that monolayer adsorption occurred. The maximum biosorption capacities for Ni(II) and Pb(II) were 20.8 mg·g⁻¹ and 93.5 mg·g⁻¹, respectively, using a biosorbent dose of 10 g·L⁻¹, initial metal concentrations ranging from 50 to 5000 mg·L⁻¹, at pH 6, 20 °C, and a contact time of 120 min. Low values of the mean free energy of adsorption (E) in the Dubinin–Radushkevich and Temkin model (0.3 and 0.1 kJ·mol⁻¹ for Pb(II) and 0.35 and 0.23 kJ·mol⁻¹ for Ni(II)) indicate the dominance of physical processes in the ion binding mechanism. The adsorption of Pb(II) ions was more effective than that of Ni(II) ions across the entire range of tested concentrations. At low initial concentrations, the removal of Pb(II) reached 94%, while for Ni(II) it was 80%. Full article

The strategic construction of heterojunctions through a simple and efficient strategy is one of the most effective means to boost the photocatalytic activity of semiconductor materials. Herein, a thiazole-linked covalent organic framework (TZ-COF) with large surface area, well-ordered pore structure, and high stability was developed. To further boost photocatalytic activity, the TZ-COF was synthesized in situ on the surface of Cu₂O through a simple multicomponent reaction, yielding an encapsulated composite material (Cu₂O@TZ-COF-18). In this composite, the outermost COF endows the material with abundant redox active sites and mass transfer channels, while the innermost Cu₂O exhibits unique photoelectric properties. Notably, the synthesized Cu₂O@TZ-COF-18 was proven to have the heterojunction structure, which can efficiently restrain the recombination of photogenerated electron–hole pairs, thereby enhancing the photocatalytic performance. The photocatalytic degradation of tetracycline demonstrated that 3-Cu₂O@TZ-COF-18 had the highest photocatalytic efficiency, with the removal rate of 96.3% within 70 min under visible light, which is better than that of pristine TZ-COF-18, Cu₂O, the physical mixture of Cu₂O and TZ-COF-18, and numerous reported COF-based composite materials. 3-Cu₂O@TZ-COF-18 retained its original crystallinity and removal efficiency after five cycles in photodegradation reaction, displaying high stability and excellent cycle performance. Full article

Flocculants are indispensable in water and wastewater treatment, enabling the aggregation and removal of suspended particles, colloids, and emulsions. However, the conventional development and application of flocculants rely heavily on empirical methods, which are time-consuming, resource-intensive, and environmentally problematic due to issues such as sludge production and chemical residues. Recent advances in machine learning (ML) have opened transformative avenues for the design, optimization, and intelligent application of flocculants. This review systematically examines the integration of ML into flocculant research, covering algorithmic approaches, data-driven structure–property modeling, high-throughput formulation screening, and smart process control. ML models—including random forests, neural networks, and Gaussian processes—have successfully predicted flocculation performance, guided synthesis optimization, and enabled real-time dosing control. Applications extend to both synthetic and bioflocculants, with ML facilitating strain engineering, fermentation yield prediction, and polymer degradability assessments. Furthermore, the convergence of ML with IoT, digital twins, and life cycle assessment tools has accelerated the transition toward sustainable, adaptive, and low-impact treatment technologies. Despite its potential, challenges remain in data standardization, model interpretability, and real-world implementation. This review concludes by outlining strategic pathways for future research, including the development of open datasets, hybrid physics–ML frameworks, and interdisciplinary collaborations. By leveraging ML, the next generation of flocculant systems can be more effective, environmentally benign, and intelligently controlled, contributing to global water sustainability goals. Full article

Thermal wick-debinding, commonly used in low-pressure injection molding, remains challenging due to complex interactions between binder transport, capillary forces, and thermal effects. This study presents a numerical simulation of binder removal kinetics by coupling Darcy’s law with the Phase Transport in Porous Media interface in COMSOL Multiphysics. The model was validated and subsequently used to study the influence of key debinding parameters. Contrary to the Level Set method, which predicts isolated binder clusters, the Multiphase Flow in Porous Media method proposed in this work more accurately reflects the physical behavior of the process, capturing a continuous binder extraction throughout the green part and a uniform binder distribution within the wicking medium. The model successfully predicted the experimentally observed decrease in binder saturation with increasing debinding temperature or time, with deviation limited 3–10 vol. % (attributed to a mandatory brushing operation, which may underestimate the residual binder mass). The model was then used to optimize the debinding process: for a temperature of 100 °C and an inter-part gap distance of 5 mm, the debinding time was minimized to 7 h. These findings highlight the model’s practical utility for process design, offering a valuable tool for determining optimal debinding parameters and improving productivity. Full article

Current work investigates the fabrication and performance of nanocomposite membranes, modified with varying concentrations of hybrid nanostructures comprising titanium nanowires coated with iron nanoparticles (TiO₂ NWs-Fe₂O₃), for the removal of Naphthol Blue Black (NBB) dye from industrial wastewater. A series of analytical tools were employed to confirm the successful modification including scanning electron microscopy and EDX analysis, porosity and hydrophilicity measurements, Fourier-transform infrared spectroscopy, and X-Ray Diffraction. The incorporation of TiO₂ NWs-Fe₂O₃ has enhanced membrane performance significantly by increasing the PWF and improving dye retention rates of nanocomposite membranes. At 0.7 g of nanostructure content, the modified membrane (M8) achieved a PWF of 93 L/m²·h and NBB dye rejection of over 98%. The flux recovery ratio (FRR) analysis disclosed improved antifouling properties, with the M8 membrane demonstrating a 73.4% FRR. This study confirms the potential of TiO₂ NWs-Fe₂O₃-modified membranes in enhancing water treatment processes, offering a promising solution for industrial wastewater treatment. These outstanding results highlight the potential of the novel PES-TiO₂ NWs-Fe₂O₃ membranes for dye removal and present adequate guidance for the modification of membrane physical properties in the field of wastewater treatment. Full article

The rapidly changing dynamics of the digital age reshape the addiction relationship that high school students establish with technology. While smartphones remove boundaries in terms of communication and access to information, their usage triggers a source of anxiety and nomophobia. The increase in students’ anxiety levels because of their over-reliance on mobile phone use leads to significant behavioral changes in their mental health, academic performance, social interactions and financial dependency. This study examined the nomophobia levels of high school students according to selected socio-demographic indicators. Using the relational screening model, the multistage sampling technique was used to select a sample of 884 participants: 388 from Science High School and 496 from Anatolian High School (459 female, 425 male, Mage = 16.45 ± 1.14 year). Independent sample test and One-way ANOVA were applied. Depending on the homogeneity assumption of the data, Welch values were considered, and Tukey tests were applied as a second-level test from post hoc analyses. Comprehensive analyses of nomophobia levels revealed that young individuals’ attitudes towards digital technology differ significantly according to their demographic and behavioral characteristics. Variables such as gender, physical activity participation, grade level and duration of smartphone use are among the main factors affecting nomophobia levels. Female individuals and students who do not participate in physical activity exhibit higher nomophobia scores. Full article

The discharge of oily wastewater threatens the ecosystem and human health, and the efficient treatment of oily wastewater is confronted with problems of high mass transfer resistance at the oil-water-solid multiphase interface, significant light shielding effect, and easy deactivation of photocatalysts. Although traditional physical separation methods avoid secondary pollution by chemicals and can effectively separate floating oil and dispersed oil, they are ineffective in removing emulsified oil with small particle sizes. To address these complex challenges, photocatalytic technology and photocatalysis-based improved technologies have emerged, offering significant application prospects in degrading organic pollutants in oily wastewater as an environmentally friendly oxidation technology. In this paper, the degradation mechanism, kinetic mechanism, and limitations of conventional photocatalysis technology are briefly discussed. Subsequently, the surface interface modulation functions of metal doping and heterojunction energy band engineering, along with their applications in enhancing the light absorption range and carrier separation efficiency, are reviewed. Focus on typical studies on the separation and degradation of aqueous and oily phases using photocatalytic membrane technology, and illustrate the advantages and mechanisms of photocatalysts loaded on the membranes. Finally, other new approaches and converging technologies in the field are outlined, and the challenges and prospects for the future treatment of oily wastewater are presented. Full article

The geometric design of flow channels in bipolar plates is one of the critical features of proton exchange membrane fuel cells (PEMFCs), as it determines the power output of the fuel cell and has a significant impact on its performance and durability. The function of the bipolar plate is to guide the transfer of reactant gases to the gas diffusion layer and catalytic layer inside the PEMFC, while removing unreacted gases and gas–liquid byproducts. Therefore, the design of the bipolar plate flow channel is directly related to the water and thermal management of the PEMFC. In order to improve the comprehensive performance of PEMFCs and ensure their safe and stable operation, it is necessary to design the flow channels in bipolar plates rationally and effectively. This study addresses the limitations of existing bipolar plate flow channels by proposing a new coupling of serpentine and radial channels. The distribution of oxygen, water concentrations, and temperature inside the channel is simulated using the multi-physics simulation software COMSOL Multiphysics 6.0. The performance of this novel design is compared with conventional flow channels, with a particular focus on the pressure drop and current density to evaluate changes in the output performance of the PEMFC. The results show that the maximum current density of this novel design is increased by 67.36% and 10.43% compared to straight channel and single serpentine channels, respectively. The main contribution of this research is the innovative design of a new coupling of serpentine and radial channels in bipolar plates, which improves the overall performance of the PEMFC. This study provides theoretical support for the design of bipolar plate flow channels in PEMFCs and holds significant importance for the green development of energy. Full article

The use of Internet of Things (IoT) for sports innovation has transformed the way athletes train, compete, and recover in any sports activity. This study performs a bibliometric analysis to examine research trends, collaborations, and publications in the realm of IoT and Sports. Our analysis included 780 Scopus articles and 150 WoS articles published during 2012–2025, and duplicates were removed. We analyzed and visualized the bibliometric data using R version 3.6.1, VOSviewer version 1.6.20, and the bibliometrix library. The study provides insights from a bibliometric analysis, showcasing the allocation of topics, scientific contributions, patterns of co-authorship, prominent authors and their productivity over time, notable terms, key sources, publications with citations, analysis of citations, source-specific citation analysis, yearly publication patterns, and the distribution of research papers. The results indicate that China and India have the leading scientific production in the development of IoT and Sports research, with prominent authors like Anton Umek, Anton Kos, and Emiliano Schena making significant contributions. Wearable technology and wearable sensors are the most trending topics in IoT and Sports, followed by medical sciences and artificial intelligence paradigms. The analysis also emphasizes the importance of open-access journals like ‘Journal of Physics: Conference Series’ and ‘IEEE Access’ for their contributions to IoT and Sports research. Future research directions focus on enhancing effective, lightweight, and efficient wearable devices while implementing technologies like edge computing and lightweight AI in wearable technologies. Full article

Background and Objective: Temperature management is key for reliable operation of permanent magnet synchronous motors (PMSMs). The lumped-parameter thermal network (LPTN) is fast and interpretable but struggles with nonlinear behavior under high power density. We propose OLTEM, a physics-informed deep model that combines LPTN with a thermal neural network (TNN) to improve prediction accuracy while keeping physical meaning. Methods: OLTEM embeds LPTN into a recurrent state-space formulation and learns three parameter sets: thermal conductance, inverse thermal capacitance, and power loss. Two additions are introduced: (i) a state-conditioned squeeze-and-excitation (SC-SE) attention that adapts feature weights using the current temperature state, and (ii) an enhanced power-loss sub-network that uses a deep MLP with SC-SE and non-negativity constraints. The model is trained and evaluated on the public Electric Motor Temperature dataset (Paderborn University/Kaggle). Performance is measured by mean squared error (MSE) and maximum absolute error across permanent-magnet, stator-yoke, stator-tooth, and stator-winding temperatures. Results: OLTEM tracks fast thermal transients and yields lower MSE than both the baseline TNN and a CNN–RNN model for all four components. On a held-out generalization set, MSE remains below 4.0 °C² and the maximum absolute error is about 4.3–8.2 °C. Ablation shows that removing either SC-SE or the enhanced power-loss module degrades accuracy, confirming their complementary roles. Conclusions: By combining physics with learned attention and loss modeling, OLTEM improves PMSM temperature prediction while preserving interpretability. This approach can support motor thermal design and control; future work will study transfer to other machines and further reduce short-term errors during abrupt operating changes. Full article

Three-dimensional printing is commonly used to fabricate provisional dental restorations. Studies have reported that changes in printing orientation affect the physical and mechanical properties of 3D-printed polymeric provisional restorations; however the findings have been inconsistent. Therefore, this systematic review and meta-analysis aims to analyze the articles evaluating the influence of printing orientation on the physical and mechanical properties of 3D-printed polymeric provisional dental restorations. Recommendations provided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to structure and compose the review. The PICO (Participant, Intervention, Comparison, Outcome) question ordered was: ‘Do 3D-printed provisional dental restorations (P) printed at various orientations (except 0°) (I) exhibit similar physical and mechanical properties (O) when compared to those printed at a 0° orientation (C)?’. An electronic search was conducted on 28 and 29 April 2025, by two independent researchers across four databases (MEDLINE/PubMed, Scopus, Cochrane Library, and Web of Science) to systematically collect relevant articles published up to March 2025. After removing duplicate articles and applying predefined inclusion and exclusion criteria, twenty-one articles were incorporated into this review. Self-designed Performa’s were used to tabulate all relevant information. For the quality analysis, the modified CONSORT scale was utilized. The quantitative analysis was performed on only fifteen out of twenty-one articles. It can be concluded that the printing orientation affects some of the tested properties, which include fracture strength (significantly higher for specimens printed at 0° when compared to 90°), wear resistance (significantly higher for specimens printed at 90° when compared to 0°), microhardness (significantly higher for specimens printed at 90°and 45° when compared to 0°), color stability (high at 0°), and surface roughness (significantly higher for specimens printed at 45° and 90° when compared to 0°). There were varied outcomes in terms of flexural strength and elastic modulus. Full article