Search Results (3,549)

Background: This study aimed to assess the impact of methacrylate-functionalized polyhedral oligomeric silsesquioxanes dispersed in nanosilica (MA/Ns-POSS) on the mechanical properties of light-curable dental resins and composites. The primary goal was to evaluate how different concentrations of MA/Ns-POSS (0.5–20 wt.%) affect the hardness, flexural strength, modulus, diametral tensile strength, polymerization shrinkage stress, and degree of conversion of these materials. Methods: A mixture of Bis-GMA, UDMA, TEGDMA, HEMA, and camphorquinone, with a tertiary amine as the photoinitiator, was used to create resin and composite samples, incorporating 45 wt.% silanized silica for the composites. Hardness (Vickers method, HV), flexural strength (FS), and flexural modulus (E_f) were assessed using three-point bending tests, while diametral tensile strength (DTS) polymerization shrinkage stresses (PSS), and degree of conversion (DC) analysis were analyzed for the composites. Results: The results showed that resins with 10 wt.% MA/Ns-POSS exhibited the highest E_f and FS values. Composite hardness peaked at 20 wt.% MA/Ns-POSS, while DTS increased up to 2.5 wt.% MA/Ns-POSS but declined at higher concentrations. PSS values decreased with increasing MA/Ns-POSS concentration, with the lowest values recorded at 15–20 wt.%. DC analysis also showed substantial improvement for 15–20 wt.% Conclusion: Incorporating MA/Ns-POSS improves the mechanical properties of both resins and composites, with 20 wt.% showing the best results. Further studies are needed to explore the influence of higher additive concentrations. Full article

Cellulose acetate (CA), commercially produced from natural cellulose, is one of the promising candidates to solve the microplastic issue. In this study, attempts were made to prepare CA microparticles by means of melt extrusion of incompatible polymer blends comprising CA with plasticizer (triacetin (TA)) and polyvinyl alcohol (PVA) followed by selective removable of TA and PVA. As implied by semi-theoretical equation previously established by Wu (Wu’s equation), particle size decreased with increasing shear rate or decreasing viscosity ratio of polymers. CA microparticles with a controlled size of 2–8 μm, narrow particle size distribution, and smooth surface were successfully obtained. Efforts were made to determine the numerical solution of Wu’s equation to compare them with observed particle size. To this end, interfacial tension between dispersed and matrix phases to be incorporated in the equation was determined by group contribution methods. The root mean squared error (RMSE) between the observed and calculated particle size was unsatisfactorily large, 4.46 μm. It was found that one of the possible reasons for the limited prediction accuracy was migration of TA from the dispersed to matrix phase affecting the viscosity ratio. Further efforts will be required to achieve a better prediction. Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. Full article

Peroxisome proliferator-activated receptor alpha (PPARα) is a key regulator of lipid metabolism, making its agonists valuable therapeutic targets for various diseases, including chronic peripheral neuropathy. Existing PPARα agonists face limitations such as poor selectivity, sub-optimal bioavailability, and safety concerns. We previously demonstrated that A190, a novel, potent, and selective PPARα agonist, effectively alleviates chemotherapy-induced peripheral neuropathy and CFA-induced inflammatory pain as a non-opioid therapeutic agent. However, A190 alone has solubility and permeability issues that limits its oral delivery. To overcome this challenge, in this study, four new-generation ester prodrugs of A190; A190-PD-9 (methyl ester), A190-PD-14 (ethyl ester), A190-PD-154 (isopropyl ester), and A190-PD-60 (cyclic carbonate) were synthesized and evaluated for their enzymatic bioconversion and chemical stability. The lead candidate, A190-PD-60, was further formulated as a microemulsion (A190-PD-60-ME) and optimized via Box–Behnken design. A190-PD-60-ME featured nano-sized droplets (~120 nm), low polydispersity (PDI < 0.3), and high drug loading (>90%) with significant improvement in artificial membrane permeability. Crucially, pharmacokinetic evaluation in rats demonstrated that A190-PD-60-ME reached a 16.6-fold higher Cmax (439 ng/mL) and a 5.9-fold increase in relative oral bioavailability compared with an A190-PD-60 dispersion. These findings support the combined prodrug-microemulsion approach as a promising strategy to overcome oral bioavailability challenges and advance PPARα-targeted therapies. Full article

Atomic force microscopy (AFM)-based nanoindentation enables investigation of the mechanical response of biological materials at a subcellular scale. However, quantitative estimates of mechanical parameters such as the elastic modulus (E) remain unreliable because the influence of sample roughness on E measurements at the nanoscale is still poorly understood. This study re-examines the interpretation of roughness from a more rigorous perspective and validates an experimental methodology to extract roughness at each nanoindentation site—i.e., the local roughness γ_s—with which the corresponding E value can be accurately correlated. Cortical regions of a murine tibia cross-section, characterized by complex nanoscale morphology, were selected as a testbed. Eighty non-overlapping nanoindentations were performed using two different AFM tips, maintaining a maximum penetration depth of 10 nm for each measurement. Our results show a slight decreasing trend of E versus γ_s (Spearman’s rank correlation coefficient ρ = −0.27187). A total of 90% of the E values are reliable when γ_s < 10 nm (coefficient of determination R² > 0.90), although low γ_s values are associated with significant dispersion around E (γ_s = 0) = E₀ = 1.18 GPa, with variations exceeding 50%. These findings are consistent with a qualitative tip-to-sample contact model that accounts for the pronounced roughness heterogeneity typical of bone topography at the nanoscale. Full article

Data-driven approaches and calibration techniques for mathematical models, starting from observed data, are attracting more and more interest in the field of civil engineering. Among them, evolutionary polynomial regression (EPR) is an artificial intelligence (AI) technique that combines genetic algorithms (GAs) and regression strategies. However, the difficulties and uncertainties inherent in the method have pointed out how the implementation of proper computational methods together with the use of recent and qualified databases of experimental data are essential to carry out reliable formulations. In this framework, this paper explores a new robust EPR approach able to remove potential outliers and leverage points often occurring in biased dataset and simultaneously accounting for the effects of probabilistic uncertainties. Uncertainties are incorporated in the EPR methodology by adopting the direct perturbation method. In particular, it is shown the importance to set the parameters representative of experimental and analytical dispersions on the basis of the characteristics of the database in terms of homogeneity. With this purpose, two different case-studies are analyzed, dealing with the shear capacity of RC beams without stirrups and the compressive strength of cement-based mortar specimens, respectively. Finally, the best capacity equations are selected and discussed. Full article

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM₁₀ and PM_2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article

We investigated the spatial structure and colony itinerancy of Audouin’s gull (Ichthyaetus audouinii) adult breeders across multiple breeding sites in the central Mediterranean Sea during 25 years of fieldwork. Using cluster analysis of marked individuals from different years and sites, we identified five spatial breeding units of increasing hierarchical scale—Breeding Sites, Colonies, Districts, Regions and Marine Sectors—which reflect biologically meaningful boundaries beyond simple geographic proximity. To determine the most appropriate scale for monitoring local populations, we applied multievent capture–recapture models and examined variation in survival and site fidelity across these units. Audouin’s gulls frequently change their location at the Breeding Site and Colony levels from one year to another, without apparent survival costs. In contrast, dispersal beyond Districts boundaries was found to be rare and associated with reduced survival rates, indicating that breeding Districts represent the most relevant biological unit for identifying local populations. The survival disadvantage observed in individuals leaving their District likely reflects increased extrinsic mortality in unfamiliar environments and the selective dispersal of lower-quality individuals. Within breeding Districts, birds may benefit from local knowledge and social information, supporting demographic stability and higher fitness. Our findings highlight the value of adopting a District-based framework for long-term monitoring and conservation of this endangered species. At this scale, demographic trends such as population growth or decline emerge more clearly than when assessed at the level of singular colonies. This approach can enhance our understanding of population dynamics in other mobile species and support more effective conservation strategies aligned with natural population structure. Full article

Selenium (Se) is an essential trace element involved in antioxidant redox regulation, thyroid hormone metabolism, and cancer prevention. Among its different forms, elemental selenium (Se⁰), particularly at the nanoscale, has gained growing attention in food, feed, and biomedical applications due to its lower toxicity and higher bioavailability compared to inorganic selenium species. However, the detection of Se⁰ in real samples remains challenging as current analytical methods are time-consuming, labour-intensive, and often unsuitable for rapid analysis. In this study, we developed a method for rapidly measuring Se⁰ using carbon nanodots (CNDs) produced from the Maillard reaction between glucose and glycine. The fabricated CNDs were water-dispersible and strongly fluorescent, with an average particle size of 3.90 ± 1.36 nm. Comprehensive characterisation by transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), fluorescence spectroscopy, and Raman spectroscopy confirmed their structural and optical properties. The CNDs were employed as fluorescent probes for the selective detection of Se⁰. The sensor showed a wide linear detection range (0–12.665 mmol L⁻¹), with a low detection limit (LOD) of 0.381 mmol L⁻¹ and a quantification limit (LOQ) of 0.465 mmol L⁻¹. Validation with spiked real samples—including ultra-pure water, tap water, and soft drinks—yielded high recoveries (98.6–108.1%) and low relative standard deviations (<3.4%). These results highlight the potential of CNDs as a simple, reliable, and environmentally friendly sensing platform for trace-level Se⁰ detection in complex food and beverage matrices. Full article

Over efficient photocatalysts, CO₂ photoreduction typically converts CO₂ into low-carbon chemicals, which serve as raw materials for downstream synthesis processes. Here, an efficient composite photocatalyst heterojunction (Cu₂O-u/g-C₃N₄) has been fabricated to reduce CO₂. Graphitic carbon nitride (g-C₃N₄) was synthesized via thermal polymerization of urea at 550 °C, while pre-dispersed Cu₂O derived from urea pyrolysis (Cu₂O-u) was prepared by thermal reduction of urea and CuCl₂·2H₂O at 180 °C. The heterojunction Cu₂O-u/g-C₃N₄ was subsequently constructed through hydrothermal treatment at 180 °C. This heterojunction exhibited a bandgap of 2.10 eV, with dual optical absorption edges at 485 nm and above 800 nm, enabling efficient harvesting of solar light. Under 175 W mercury lamp irradiation, the heterojunction catalyzed liquid-phase CO₂ photoreduction to formic acid, acetic acid, and methanol. Its formic acid production activity surpassed that of pristine g-C₃N₄ by 3.14-fold and TiO₂ by 8.72-fold. Reaction media, hole scavengers, and reaction duration modulated product selectivity. In acetonitrile/isopropanol systems, formic acid and acetic acid production reached 579.4 and 582.8 μmol·h⁻¹·g_cat⁻¹. Conversely, in water/triethanolamine systems, methanol production reached 3061.6 μmol·h⁻¹·g_cat⁻¹, with 94.79% of the initial conversion retained after three cycles. Finally, this work ends with the conclusions of the CO₂ photocatalytic reduction to formic acid, acetic acid, and methanol, and recommends prospects for future research. Full article

Enhanced Geothermal Systems (EGS) require thermochemically stable proppant materials capable of sustaining fracture conductivity under harsh subsurface conditions. This study systematically investigates the response of commercial proppants to coupled thermo-hydro-chemical (THC) effects, focusing on chemical stability and microstructural evolution. Four proppant types were evaluated: an ultra-low-density ceramic (ULD), a resin-coated sand (RCS), and two quartz-based silica sands. Experiments were conducted under simulated EGS conditions at 130 °C with daily thermal cycling over a 25-day period, using diluted site-specific Utah FORGE geothermal fluids. Static batch reactions were followed by comprehensive multi-modal characterization, including scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), X-ray diffraction (XRD), and micro-computed tomography (micro-CT). Proppants were tested in both granular and powdered forms to evaluate surface area effects and potential long-term reactivity. Results indicate that ULD proppants experienced notable resin degradation and secondary mineral precipitation within internal pore networks, evidenced by a 30.4% reduction in intragranular porosity (from CT analysis) and diminished amorphous peaks in the XRD spectra. RCS proppants exhibited a significant loss of surface carbon content from 72.98% to 53.05%, consistent with resin breakdown observed via SEM imaging. While the quartz-based sand proppants remained morphologically intact at the macro-scale, SEM-EDS revealed localized surface alteration and mineral precipitation. The brown sand proppant, in particular, showed the most extensive surface precipitation, with a 15.2% increase in newly detected mineral phases. These findings advance understanding of proppant–fluid interactions under low-temperature EGS conditions and underscore the importance of selecting proppants based on thermo-chemical compatibility. The results also highlight the need for continued development of chemically resilient proppant formulations tailored for long-term geothermal applications. Full article

A novel type of multifunctional hybrid membranes combining modified chitosan, functionalized multi-walled carbon nanotubes (MWCNTs), and rare earth element ion-imprinted polymers (REEIIPs) were designed and characterized. The synthesized materials were characterized by thermogravimetric analysis (TGA), scanning electron microscopy (SEM), vibrating sample magnetometry (VSM), X-ray diffraction (XRD), X-ray micro-tomography, and Fourier transform infrared spectroscopy (FTIR). The hybrid membranes were also studied in terms of their mechanical and rheological properties. The key element of the proper preparation of hybrid membranes using the casting method in an external magnetic field was to synthesize membrane components with appropriate magnetic properties. It was found that they showed tunable weak ferromagnetic properties, and the increase in modified nanotube addition caused the rise in the membrane’s saturation magnetization, which for Nd-selective hybrid membranes reached 0.44 emu/g. Also, the increase in thermooxidative stability was noted after introducing functionalized nanotubes into polymer matrices, which, in the case of Gd-selective membranes, were stable even up to 730 °C. The rise in the modified MWCNT addition and selection of appropriate REE ion-imprinted polymers improved mechanical (Rm and E values increase even twice) and rheological parameters (almost double growth of E′ and E″ values) of the tested membranes. Synthesized hybrid membranes showed a high rejection of matrix components and an increase in retention ratio with rising MWCNT-REEIIP addition, ultimately reaching 94.35%, 92.12%, and 90.11% for Nd, Pr, and Gd, respectively. The performed analysis confirmed homogeneous dispersion, phase compatibility, network integration, formation of a complex 3D microstructure, and improved operational stability of created hybrid membranes, which is significant for their future applications in Nd, Pr, and Gd recovery from coal fly ash extracts. Full article

Large language models (LLMs), built upon Transformer architectures, have demonstrated remarkable performance in a wide range of natural language processing tasks. However, their practical deployment—especially in long-context scenarios—is often hindered by the computational and memory costs associated with managing the key–value (KV) cache during inference. Optimizing this process is therefore crucial for improving LLM efficiency and scalability. In this study, we propose a novel entropy-guided KV caching strategy that leverages the distribution characteristics of attention scores within each Transformer layer. Specifically, we compute the entropy of attention weights for each head and use the average entropy of all heads within a layer to assess the layer’s contextual importance. Higher-entropy layers—those exhibiting broader attention dispersion—are allocated larger KV cache budgets, while lower-entropy (sink-like) layers are assigned smaller budgets. Instead of selecting different key–value tokens per head, our method selects a common set of important tokens per layer, based on aggregated attention scores, and caches them uniformly across all heads within the same layer. This design preserves the structural integrity of multi-head attention while enabling efficient token selection during the prefilling phase. The experimental results demonstrate that our approach improves cache utilization and inference speed without compromising generation quality. For example, on the Qwen3 4B model, our method reduces memory usage by 4.18% while preserving ROUGE score, and on Mistral 0.1v 7B, it reduces decoding time by 46.6%, highlighting entropy-guided layer analysis as a principled mechanism for scalable long-context language modeling. Full article

The fabrication and application of single-site heterogeneous reaction centers are new frontiers in chemistry. Single-site heterogeneous reaction centers are analogous to metal centers in enzymes and transition-metal complexes: they are charged and decorated with ligands and would exhibit superior reactivity and selectivity in chemical conversion. Such high reactivity would also result in significant response, such as a band gap or resistance change, to approaching molecules, which can be used for sensing applications. As a proof of concept, the electronic structure and reaction pathways with NO and NO₂ of Au(I) fragments dispersed on phosphorene (Pene) were investigated with first-principle-based calculations. Atomic-deposited Au atoms on Pene (Au₁-Pene) have hybridized Au states in the bulk band gap of Pene and a decreased band gap of 0.14 eV and would aggregate into clusters. Passivation of the Au hybrid states with -OH and -CH₃ forms thermodynamically plausible HO-Au₁-Pene and H₃C-Au₁-Pene and restores the band gap to that of bulk Pene. Inspired by this, HO-Au₁-Pene and H₃C-Au₁-Pene were examined for detection of NO and NO₂ that would react with -OH and -CH₃, and the resulting decrease of band gap back to that of Au₁-Pene would be measurable. HO-Au₁-Pene and H₃C-Au₁-Pene are highly sensitive to NO and NO₂, and their calculated theoretical sensitivities are all 99.99%. The reaction of NO₂ with HO-Au₁-Pene is endothermic, making the dissociation of product HNO₃ more plausible, while the barriers for the reaction of CH₃-Au₁-Pene with NO and NO₂ are too high for spontaneous detection. Therefore, HO-Au₁-Pene is not eligible for NO₂ sensing and CH₃-Au₁-Pene is not eligible for NO and NO₂ sensing. The calculated energy barrier for the reaction of HO-Au-Pene with NO is 0.36 eV, and the reaction is about thermal neutral, suggesting HO-Au-Pene is highly sensitive for NO sensing and the reaction for NO detection is spontaneous. This work highlights the potential superior sensing performance of transition-metal fragments and their potential for next-generation sensing applications. Full article

The global plastic crisis has generated significant interest in repurposing waste plastics as asphalt modifiers, presenting both environmental and engineering advantages. This study offers a comprehensive review of the applications of waste plastics in asphalt, focusing on their types, modification mechanisms, incorporation techniques, and environmental impacts, alongside proposed mitigation strategies. Commonly utilized plastics include polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), and polyethylene terephthalate (PET), each affecting asphalt performance differently—enhancing high-temperature stability and fatigue resistance while exhibiting varying levels of compatibility and environmental risks. The incorporation techniques, namely wet and dry processes, differ in terms of efficiency, cost, and environmental footprint: the wet process enhances durability but requires more energy, whereas the dry process is more cost-effective but may lead to uneven dispersion. Environmental concerns associated with these practices include toxic emissions (such as polycyclic aromatic hydrocarbons and volatile organic compounds) during production, microplastic generation through abrasion and weathering, and ecological contamination of soil and water. Mitigation strategies encompass optimizing plastic selection, improving pre-treatment and compatibilization methods, controlling high-temperature processing, and monitoring the spread of microplastics. This review highlights the need for balanced adoption of waste plastic-modified asphalt, emphasizing sustainable practices to maximize benefits while minimizing risks. Full article