Search Results (3,768)

The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex nonlinear relationships and spatial dependencies among factors influencing EVCS locations. To address this research gap and better understand the spatial impacts of urban activities on EVCS placement, this study presents a spatially aware machine learning (SAML) method that combines a multi-layer perceptron (MLP) model with a spatial loss function to optimize EVCS sites. Additionally, the method uses the Shapley additive explanation (SHAP) technique to investigate nonlinear relationships embedded in EVCS placement. Using the city of Wuhan as a case study, the SAML method reveals that parking site (PS), road density (RD), population density (PD), and commercial residential (CR) areas are key factors in determining optimal EVCS sites. The SAML model classifies these grid cells into no EVCS demand (0 EVCS), low EVCS demand (from 1 to 3 EVCSs), and high EVCS demand (4+ EVCSs) classes. The model performs well in predicting EVCS demand. Findings from ablation tests also indicate that the inclusion of spatial correlations in the model’s loss function significantly enhances the model’s performance. Additionally, results from case studies validate that the model is effective in predicting EVCSs in other metropolitan cities. Full article

2,5-bis(hydroxymethy)lfuran (BHMF), a renewable compound with extensive industrial applications, can be obtained by selective hydrogenation of the C=O group of 5-hydroxymethylfurfural (HMF), a platform molecule derived from lignocellulosic biomass. In this work, we perform kinetic modeling of the selective liquid-phase hydrogenation of HMF to BHMF over a Cu/SiO₂ catalyst prepared by precipitation–deposition (PD) at a constant pH. Physicochemical characterization, using different techniques, confirms that the Cu/SiO₂–PD catalyst is formed by copper metallic nanoparticles of 3–5 nm in size highly dispersed on the SiO₂ surface. Before the kinetic study, the Cu/SiO₂-PD catalyst was evaluated in three solvents: tetrahydrofuran (THF), 2-propanol (2-POH), and water. The pattern of catalytic activity and BHMF yield for the different solvents was THF > 2-POH > H₂O. In addition, selectivity to BHF was the highest in THF. Thus, THF was chosen for further kinetic study. Several experiments were carried out by varying the initial HMF concentration (C⁰_HMF) between 0.02 and 0.26 M and the hydrogen pressure (P_H2) between 200 and 1500 kPa. In all experiments, BHMF selectivity was 97–99%. By pseudo-homogeneous modeling, an apparent reaction order with respect to HFM close to 1 was estimated for a C⁰_HMF between 0.02 M and 0.065 M, while when higher than 0.065 M, the apparent reaction order changed to 0. The apparent reaction order with respect to H₂ was nearly 0 when C⁰_HMF = 0.13 M, while for C⁰_HMF = 0.04 M, it was close to 1. The reaction orders estimated suggest that HMF is strongly absorbed on the catalyst surface, and thus total active site coverage is reached when the C⁰_HMF is higher than 0.065 M. Several Langmuir–Hinshelwood–Hougen–Watson (LHHW) kinetic models were proposed, tested against experimental data, and statistically compared. The best fitting of the experimental data was obtained with an LHHW model that considered non-competitive H₂ and HMF chemisorption and strong chemisorption of reactant and product molecules on copper metallic active sites. This model predicts both the catalytic performance of Cu/SiO₂-PD and its deactivation during liquid-phase HMF hydrogenation. Full article

Phthalocyanines (Pcs) are well-established photosensitizers in photodynamic therapy, valued for their strong light absorption, high singlet oxygen generation, and photostability. Recent advances have focused on covalently conjugating Pcs, particularly zinc phthalocyanines (ZnPcs), with a wide range of small bioactive molecules to improve selectivity, efficacy, and multifunctionality. These conjugates combine light-activated reactive oxygen species (ROS) production with targeted delivery and controlled release, offering enhanced treatment precision and reduced off-target toxicity. Chemotherapeutic agent conjugates, including those with erlotinib, doxorubicin, tamoxifen, and camptothecin, demonstrate receptor-mediated uptake, pH-responsive release, and synergistic anticancer effects, even overcoming multidrug resistance. Beyond oncology, ZnPc conjugates with antibiotics, anti-inflammatory drugs, antiparasitics, and antidepressants extend photodynamic therapy’s scope to antimicrobial and site-specific therapies. Targeting moieties such as folic acid, biotin, arginylglycylaspartic acid (RGD) and epidermal growth factor (EGF) peptides, carbohydrates, and amino acids have been employed to exploit overexpressed receptors in tumors, enhancing cellular uptake and tumor accumulation. Fluorescent dye and porphyrinoid conjugates further enrich these systems by enabling imaging-guided therapy, efficient energy transfer, and dual-mode activation through pH or enzyme-sensitive linkers. Despite these promising strategies, key challenges remain, including aggregation-induced quenching, poor aqueous solubility, synthetic complexity, and interference with ROS generation. In this review, the examples of Pc-based conjugates were described with particular interest on the synthetic procedures and optical properties of targeted compounds. Full article

This study addresses the complex challenges associated with flexible mattress (soft mattress) installation in the sharply curved and deep-water sections of the Yangtze River, particularly in the Yaozui revetment reconstruction project. Under extreme hydrodynamic conditions—water depths exceeding 30 m and velocities over 2.5 m/s—the risk of structural failures such as displacement, flipping, or tearing of the mattress becomes significant. To improve construction safety and stability, the study integrates numerical modeling and on-site strain monitoring to analyze the mechanical response of flexible mattresses during deployment. A three-dimensional finite element model based on the catenary theory was developed to simulate stress distributions under varying flow velocities and angles, revealing stress concentrations at the mattress’s upper edge and reinforcement junctions. Concurrently, a real-time monitoring system using high-precision strain sensors was deployed on critical shipboard components, with collected data analyzed through a remote IoT platform. The results demonstrate strong correlations between mattress strain, flow velocity, and water depth, enabling the identification of high-risk operational thresholds. The proposed monitoring and early-warning framework offers a practical solution for managing construction risks in extreme riverine environments and contributes to the advancement of intelligent construction management for underwater revetment works. Full article

Ujimqin sheep, known for its distinctive multi-vertebrae phenotypes (T13L7, T14L6, and T14L7) and economic value, has garnered significant attention. However, conventional phenotypic detection methods suffer from low efficiency and high costs. In this study, based on a key SNP locus (ABCD4 gene, Chr7:89393414, C > T) identified through a genome-wide association study (GWAS), a TaqMan-MGB (minor groove binder) genotyping system was developed. the objective was to establish a high-throughput and efficient molecular marker-assisted selection (MAS) tool. Specific primers and dual fluorescent probes were designed to optimize the reaction system. Standard plasmids were adopted to validate genotyping accuracy. A total of 152 Ujimqin sheep were subjected to TaqMan-MGB genotyping, digital radiography (DR) imaging, and Sanger sequencing. the results showed complete concordance between TaqMan-MGB and Sanger sequencing, with an overall agreement rate of 83.6% with DR imaging. For individuals with T/T genotypes (127/139), the detection accuracy reached 91.4%. This method demonstrated high specificity, simplicity, and cost-efficiency, significantly reducing the time and financial burden associated with traditional imaging-based approaches. the findings indicate that the TaqMan-MGB technique can accurately identify the T/T genotype at the SNP site and its strong association with the multi-vertebrae phenotypes, offering an effective and reliable tool for molecular breeding of Ujimqin sheep. Full article

Novel solid strong base catalysts have attracted considerable attention in fine chemical synthesis owing to their unique advantages. In this work, a magnetic solid strong base catalyst with controlled morphology and porous carbon shell structure was successfully fabricated using low-cost carbon sources combined with Fe₃O₄ nanoparticles. KOH was used to introduce strong basic sites through ultrasonic-assisted impregnation. The carbon shell acted as a protective barrier to suppress detrimental interactions between basic species and the support while maintaining structural integrity after high-temperature activation without morphology degradation. The obtained K/C/Fe₃O₄ catalyst exhibits excellent catalytic performance and near-ideal superparamagnetic behavior. In the transesterification reaction for dimethyl carbonate (DMC) synthesis, the K/C/Fe₃O₄ catalyst provides superior performance than conventional solid base catalysts and maintains stable activity over six consecutive cycles. Notably, efficient solid–liquid separation was achieved successfully via magnetic separation, demonstrating practical applicability for the K/C/Fe₃O₄ catalyst. Full article

Land use conversion to perennial cropland often degrades the soil structure and fertility, particularly under Mediterranean climatic conditions. This study assessed spatial and temporal dynamics of soil properties and tree responses to 3-year repeated mature compost additions in a citrus orchard. Digital soil mapping revealed strong baseline heterogeneity in texture, CEC, and Si pools. Compost application markedly increased total organic C and N levels, aggregate stability, and pH with noticeable changes after the first amendment, whereas a limited C storage potential was found following further additions. NDVI values of tree canopies monitored over a 3-year period showed significant time-dependent changes not correlated with the soil fertility variables, thus suggesting that multiple interrelated factors affect plant responses. The non-crystalline amorphous Si/total amorphous Si (_iSi:Si_amor) ratio is here proposed as a novel indicator of pedogenic alteration in disturbed agroecosystems. These findings highlight the importance of tailoring organic farming strategies to site-specific conditions and reinforce the value to combine C and Si pool analysis for long-term soil fertility assessment. Full article

The mountainous rivers of Central Asia host diverse ichthyofauna threatened by increasing anthropogenic pressures, particularly water pollution, abstraction, and hydropower development. This study provides valuable morphometric and ecological data for Schizothorax eurycephalus (snow trout) and Triplophysa ferganaensis (stone loach) in the Shakhimardan River basin, Uzbekistan. S. eurycephalus exhibited positive allometric growth, while T. ferganaensis showed negative near-isometric growth. The mean Fulton’s Condition Factor was 1.0 for S. eurycephalus and 0.7 for T. ferganaensis, with site-specific variations. Strong correlations among morphometric parameters, particularly length–height relationships, support non-invasive monitoring techniques. Dietary analysis revealed S. eurycephalus was predominantly herbivorous, with around 70% algae consumption. Early sexual maturity was observed in S. eurycephalus males, whereas T. ferganaensis showed no clear maturity signs, but swollen bellies suggested ongoing or recent reproductive activity. These baseline morphometric and ecological data establish a solid foundation for future ecological assessments, conservation strategies, and the design and monitoring of mitigation measures to address anthropogenic impacts in this vulnerable region. Full article

This study presents a numerical and experimental evaluation of axial load transfer mechanisms in deep foundations constructed in stratified cohesive soils in İzmir, Türkiye. A full-scale bi-directional static load test equipped with strain gauges was conducted on a barrette pile to investigate depth-dependent mobilization of shaft resistance. A finite element model was developed and calibrated using field-observed load–settlement and strain data to replicate the pile–soil interaction and deformation behavior. The analysis revealed a shaft-dominated load transfer behavior, with progressive mobilization concentrated in intermediate-depth cohesive layers. Sensitivity analysis identified the undrained stiffness (E_u) as the most influential parameter governing pile settlement. A strong polynomial correlation was established between calibrated E_u values and SPT N₆₀, offering a practical tool for preliminary design. Additionally, strain energy distribution was evaluated as a supplementary metric, enhancing the interpretation of mobilization zones beyond conventional stress-based methods. The integrated approach provides valuable insights for performance-based foundation design in layered cohesive ground, supporting the development of site-calibrated numerical models informed by full-scale testing data. Full article

Because artificially cemented granular (ACG) materials employ diverse combinations of aggregates and binders—including cemented soil, low-cement-content cemented sand and gravel (LCSG), and concrete—their stress–strain responses vary widely. In LCSG, the binder dosage is typically limited to 40–80 kg/m³ and the sand–gravel skeleton is often obtained directly from on-site or nearby excavation spoil, endowing the material with a markedly lower embodied carbon footprint and strong alignment with current low-carbon, green-construction objectives. Yet, such heterogeneity makes a single material-specific constitutive model inadequate for predicting the mechanical behavior of other ACG variants, thereby constraining broader applications in dam construction and foundation reinforcement. This study systematically summarizes and analyzes the stress–strain and volumetric strain–axial strain characteristics of ACG materials under conventional triaxial conditions. Generalized hyperbolic and parabolic equations are employed to describe these two families of curves, and closed-form expressions are proposed for key mechanical indices—peak strength, elastic modulus, and shear dilation behavior. Building on generalized plasticity theory, we derive the plastic flow direction vector, loading direction vector, and plastic modulus, and develop a concise, transferable elastoplastic model suitable for the full spectrum of ACG materials. Validation against triaxial data for rock-fill materials, LCSG, and cemented coal–gangue backfill shows that the model reproduces the stress and deformation paths of each material class with high accuracy. Quantitative evaluation of the peak values indicates that the proposed constitutive model predicts peak deviatoric stress with an error of 1.36% and peak volumetric strain with an error of 3.78%. The corresponding coefficients of determination R² between the predicted and measured values are 0.997 for peak stress and 0.987 for peak volumetric strain, demonstrating the excellent engineering accuracy of the proposed model. The results provide a unified theoretical basis for deploying ACG—particularly its low-cement, locally sourced variants—in low-carbon dam construction, foundation rehabilitation, and other sustainable civil engineering projects. Full article

Surface and sub-surface atomic configurations are critical for catalysis as they host the active sites governing electrochemical processes. This study employs density functional theory (DFT) calculations and Monte Carlo simulations combined with the cluster-expansion approach to investigate atom distribution and Pt segregation in Pt-Fe alloys across varying Pt/Fe ratios. Our simulations reveal a strong tendency for Pt atoms to segregate to the surface layer while Fe atoms enrich the sub-surface region. Crucially, the calculations predict the stability of a periodic Pt₂Fe alloy surface model, characterized by specific defect structures, at low platinum content and low annealing temperatures. Electronic structure analysis indicates that forming this Pt₂Fe surface alloy lowers the d-band center of Pt atoms, weakening CO adsorption and thereby enhancing resistance to CO poisoning. Although defect-induced strains can modulate the d-band center, crystal orbital Hamilton population (COHP) analysis confirms that such strains generally strengthen Pt-CO interactions. Therefore, the theoretical design of Pt₂Fe alloy surfaces and controlling defect density are predicted to be effective strategies for enhancing catalyst resistance to CO poisoning. This work highlights the advantages of periodic Pt₂Fe surface models for anti-CO poisoning and provides computational guidance for designing efficient Pt-based electrocatalysts. Full article

Class D β-lactamases (DBLs) represent a major threat to antibiotic efficacy by hydrolyzing β-lactam drugs, including last-resort carbapenems, thereby driving antimicrobial resistance in Gram-negative bacteria. The enzymes share a structurally conserved two-domain α/β architecture with seven active-site motifs and three flexible extended loops (the P-loop, Ω-loop, and newly designated B-loop) that surround the active site. While each of these loops is known to influence enzyme function, their coordinated roles have not been fully elucidated. To investigate the significance of their interplay, we compared the sequences and crystal structures of 40 DBLs from clinically relevant Gram-negative pathogens and performed molecular dynamics simulations on selected representatives. Combined structural and dynamical analyses revealed a strong correlation between B-loop architecture and carbapenemase activity in the pathogens Klebsiella and Acinetobacter, particularly regarding loop length and spatial organization. These findings emphasize the B-loop’s critical contribution, in concert with the P- and Ω-loops, in tuning active site versatility, substrate recognition, catalytic activity, and structural stability. A deeper understanding of how these motifs and loops govern DBL function may inform the development of novel antibiotics and inhibitors targeting this class of enzymes. Full article

The prevention of biofilm formation and algal biodeterioration on building materials, particularly on cultural heritage sites, is a growing concern. Due to regulatory restrictions on conventional algicidal biocides in Europe, natural alternatives such as essential oils are gaining interest for their potential use in heritage conservation. This study evaluates the anti-algal activity of Salvia officinalis and Equisetum arvense (essential oils, hydrolates, and extracts) against a mixed culture of five green algae species (Bracteacoccus minor, Stichococcus bacillaris, Klebsormidium nitens, Chloroidium saccharophilum, and Diplosphaera chodatii). The plant materials were processed using hydrodistillation and solvent extraction, followed by chemical characterization through gas chromatography–mass spectrometry (GC-MS). Biological efficacy was assessed by measuring algal growth inhibition, changes in biomass colour, chlorophyll a concentration, and fluorescence. S. officinalis yielded higher extract quantities (extraction yield: 23%) than E. arvense and contained bioactive compounds such as thujone, camphor, and cineole, which correlated with its strong anti-algal effects. The essential oil of S. officinalis demonstrated the highest efficacy, significantly inhibiting biofilm formation (zones of inhibition: 15–94 mm) and photosynthetic activity at 0.5% concentration (reduction in chlorophyll a concentration 90–100%), without causing visible discolouration of treated surfaces (∆E < 2). These findings highlight the potential of S. officinalis essential oil as a natural, effective, and material-safe algicidal biocide for the sustainable protection of cultural heritage sites. Full article

The fraction of absorbed photosynthetically active radiation (FAPAR) stands as a pivotal parameter within the Earth system, quantifying the energy exchange between vegetation and solar radiation. Accordingly, there is an urgent need for comprehensive validation studies to accurately quantify uncertainties and improve the reliability of FAPAR-based applications. This study validated five global FAPAR products, MOD15A2H, MYD15A2H, VNP15A2H, GEOV2, and GEOV3, over four boreal forest sites in North America. Qualitative quality flags (QQFs) and quantitative quality indicators (QQIs) of each product were analyzed. Time series high-resolution reference FAPAR maps were developed using the Harmonized Landsat and Sentinel-2 dataset. The reference FAPAR maps revealed a strong agreement with the in situ FAPAR from AmeriFlux (correlation coefficient (R) = 0.91; root mean square error (RMSE) = 0.06). The results revealed that global FAPAR products show similar uncertainties (RMSE: 0.16 ± 0.04) and moderate agreement with the reference FAPAR (R = 0.75 ± 0.10). On average, 34.47 ± 6.91% of the FAPAR data met the goal requirements of the Global Climate Observing System (GCOS), while 54.41 ± 6.89% met the threshold requirements of the GCOS. Deciduous forests perform better than evergreen forests, and the products tend to underestimate the reference data, especially for the beginning and end of growing seasons in evergreen forests. There are no obvious quality differences at different QQFs, and the relative QQI can be used to filter high-quality values. To enhance the regional applicability of global FAPAR products, further algorithm improvements and expanded validation efforts are essential. Full article

Lanthanide rare earth elements possess significant promise for material applications owing to their distinctive optical and magnetic characteristics, as well as their versatile coordination capabilities. This study introduced a lanthanide-functionalized magnetic nanocellulose composite (NNC@Fe₃O₄@La(OH)₃) for effective phosphorus/nitrogen (P/N) ligand separation. The hybrid material employs the adaptable coordination geometry and strong affinity for oxygen of La³⁺ ions to show enhanced DNA-binding capacity via multi-site coordination with phosphate backbones and bases. This study utilized cellulose as a carrier, which was modified through carboxylation and amination processes employing deep eutectic solvents (DES) and polyethyleneimine. Magnetic nanoparticles and La(OH)₃ were subsequently incorporated into the cellulose via in situ growth. NNC@Fe₃O₄@La(OH)₃ showed a specific surface area of 36.2 m²·g⁻¹ and a magnetic saturation intensity of 37 emu/g, facilitating the formation of ligands with accessible La³⁺ active sites, hence creating mesoporous interfaces that allow for fast separation. NNC@Fe₃O₄@La(OH)₃ showed a significant affinity for DNA, with adsorption capacities reaching 243 mg/g, mostly due to the multistage coordination binding of La³⁺ to the phosphate groups and bases of DNA. Simultaneously, kinetic experiments indicated that the binding process adhered to a pseudo-secondary kinetic model, predominantly dependent on chemisorption. This study developed a unique rare-earth coordination-driven functional hybrid material, which is highly significant for constructing selective separation platforms for P/N-containing ligands. Full article