Search Results (1,843)

This study presents a starch-modified calcined-ZnAl layered double-hydroxide (S-C-ZnAl-LDH) nanocomposite as a multifunctional nanofiller for poly(vinylidene fluoride) (PVDF) efficiently performing, simultaneously, ultrafiltration membrane filtration and efficient adsorbent for the recovery of Acid Blue dye-contaminated water. The synergistic effects of starch modification and thermal activation on nanofiller structure, interfacial compatibility, and membrane performance were systematically investigated through a comparison with pristine ZnAl-LDH, calcined ZnAl-LDH, starch-modified ZnAl-LDH, and calcined starch-modified ZnAl-LDH. SEM, TEM, and XRD analyses confirmed the formation of hierarchical layered nanosheet architectures with a uniform dispersion of crystalline ZnAl domains within a partially amorphous starch matrix, promoting enhanced polymer–nanofiller interfacial interactions Adsorption performance was influenced by solution pH, initial dye concentration, and temperature. Nonlinear kinetic analysis showed that the PFO model described the kinetic data better. However, the overall kinetic modeling findings suggest that Acid Blue 92 adsorption is governed by a combination of physicochemical interactions, suggesting a complex adsorption mechanism was involved. The starch-modified nanocomposite exhibited excellent regeneration stability, retaining approximately 88–90% of its adsorption capacity after five adsorption–desorption cycles. More importantly, the incorporation of S-C-ZnAl-LDH into PVDF membranes significantly enhanced membrane functionality, increasing water flux and permeance by 42.9% and 25%, respectively, while improving Acid Blue rejection by 35.7% to approximately 98%. These improvements are attributed to enhanced membrane hydrophilicity, optimized nanofiller dispersion, and favorable polymer–filler interfacial interactions that facilitate water transport while maintaining high separation efficiency. This work demonstrates an effective strategy for integrating renewable bio-based modifiers with layered nanomaterials to engineer advanced polymeric films exhibiting enhanced permeability, selectivity, durability, and reusability, providing a sustainable platform for multifunctional membrane technologies in water purification and environmental protection. Full article

This work presents a numerical investigation of an asymmetric Pt/HfSiON/Ti metal–insulator–metal (MIM) tunnel diode for long-wave infrared (LWIR) rectenna applications at 28.3 THz (10.6 μm). HfSiON is investigated as the tunneling dielectric owing to its favorable electronic properties, thermal stability, and compatibility with nanoscale device fabrication. The electrical transport and rectification characteristics are evaluated using the full Simmons quantum-mechanical tunneling model implemented in MATLAB release 2025b. The analysis encompasses the current density–voltage (J–V) and current–voltage (I–V) characteristics, zero-bias dynamic resistance, current asymmetry, nonlinearity, responsivity, and temperature dependence. Under AC excitation, the Pt/HfSiON/Ti diode exhibits a calculated rectified current density of 1.78 × 10² A/cm² at zero DC bias, while a current density of 6.32 × 10⁵ A/cm² is obtained at an applied voltage amplitude of ±0.5 V. The asymmetric electrode configuration, arising from the difference in the work functions of Pt and Ti, results in a calculated asymmetry of 2.5 × 10⁴. At zero DC bias, the diode exhibits a zero-bias dynamic resistance of 3.85 × 10⁵ Ω and a zero-bias responsivity of approximately 10 V⁻¹. The calculated rectification characteristics show only weak sensitivity to temperature over the investigated range, indicating that the transport response is predominantly governed by quantum-mechanical tunneling rather than thermally activated processes. These results demonstrate the potential of HfSiON as a tunneling dielectric for nanoscale MIM rectifiers and indicate that the asymmetric Pt/HfSiON/Ti architecture provides strong nonlinear rectification and favorable zero-bias response for LWIR rectenna and energy-harvesting applications. Full article

Coal self-heating in longwall goaf areas results from strongly coupled gas flow, heat transfer, mass transport, and chemical reactions occurring within a porous medium containing residual coal. This study presents a mathematical and numerical model for analysing these transient and non-isothermal processes with spatially variable permeability based on in-situ mining data. The model accounts for gas filtration through the porous goaf, heat and mass transfer between the gas and solid phases, heterogeneous coal oxidation, homogeneous gas-phase reactions, continuous methane emission, and the possibility of nitrogen inertisation. The governing equations form a strongly coupled non-linear system and are solved using the finite volume method. Numerical simulations were performed for U-type and Y-type ventilation layouts. The results provide spatial distributions of methane, oxygen, and carbon monoxide concentrations, gas temperature, solid-phase temperature, pressure, and gas velocity. The simulations demonstrate that ventilation configuration affects oxygen penetration, gas composition, and temperature development within the goaf. In particular, the Y-type ventilation system promotes deeper oxygen ingress into the porous zone, which may increase the extent of regions susceptible to coal self-heating. The proposed approach provides a framework for analysing coupled thermal and transport phenomena associated with spontaneous coal combustion and for assessing the influence of ventilation conditions on the development of thermal hazards in longwall goaf areas. Full article

As cities strive to reduce carbon emissions, the way they are physically structured plays an important role in shaping travel patterns and energy use. Compact urban form is preferred as a strategy for sustainable urbanisation worldwide. However, compactness of an urban area is multidimensional, and the role of each dimension in shaping carbon emissions from transport remains insufficiently understood in the Indian context. This study addresses that gap by examining five dimensions of urban form—density, shape, contiguity, spatial concentration, and fragmentation—for 27 Indian cities. Each dimension is examined in relation to carbon emissions using three complementary methods, namely quadratic regression, generalised additive model, and segmented regression. Results show that shape is the strongest and most robust linear predictor, with irregular urban forms linked to higher emissions. Density shows a negative relationship, suggesting lower emissions at higher densities. Fragmentation shows a non-linear pattern, with a threshold at 0.785 (95% bootstrap confidence interval: 0.594–0.829). After correction for multiple comparisons, this pattern is considered as suggestive rather than confirmed. Contiguity and spatial concentration display no consistent effects. These findings indicate that strategies focused on reducing shape irregularity along with densification may offer effective pathways for emission reduction from transport in Indian cities. Full article

Dairy cold-chain network planning requires coordinated decisions under demand variability, product perishability, and environmental constraints. To address these interrelated challenges, this study formulates an order-driven multi-objective mixed-integer nonlinear programming (MINLP) model for the tactical planning of a three-echelon dairy cold-chain network. The model coordinates distribution-center selection, inventory, transportation allocation, vehicle configuration, and refrigeration decisions to minimize total cost, transportation-related carbon emissions, and the quantity- and importance-weighted average freshness-loss rate. Demand variability is represented through service-level-based safe demand, whereas product freshness is evaluated using Weibull-based shelf-life reliability and inventory–transportation exposure. Transportation congestion is further incorporated to capture its effects on travel time, refrigeration emissions, and freshness deterioration. NSGA-II is employed to generate Pareto solutions, with entropy-weighted TOPSIS used for compromise-solution selection and MOEA/D serving as the benchmark algorithm. Numerical results indicate that NSGA-II achieves favorable convergence performance and comparable solution diversity relative to MOEA/D, while small-scale mixed-integer approximation tests support the quality of the obtained solutions. Multi-scale experiments demonstrate stable computational performance as network size increases. Sensitivity and scenario analyses further reveal distinct effects of service levels, shelf-life characteristics, and road capacity on economic, environmental, and freshness performance. The proposed framework provides tactical decision support for coordinating demand-responsive supply, low-carbon operations, and freshness preservation in dairy cold-chain networks. Full article

Against the backdrop of China’s dual-carbon goals—peaking carbon emissions by 2030 and achieving carbon neutrality by 2060—capacity optimization in the steel industry can no longer rely solely on aggregate output reduction. Instead, governance must shift toward a multidimensional approach that combines scale control, structural adjustment, and coordinated regional allocation. This study develops a quantifiable and interpretable assessment model for capacity-adjustment pressure. Monthly provincial crude steel output is used as a high-frequency proxy for capacity utilization and production adjustment. Additive time-series decomposition is applied to extract three components from monthly output—trend, residual, and volatility—which respectively represent structural evolution, short-term deviations, and exposure to shocks. The model further incorporates multidimensional variables, including downstream steel demand, resource and transport constraints, scrap steel ratio, and policy constraints. On this basis, a two-stage hybrid assessment framework is developed. In the first stage, extreme gradient boosting (XGBoost) is used to learn nonlinear relationships and derive data-driven feature importance. In the second stage, a composite pressure index is constructed and transformed into a standardized 0–100 score through a robust rank-based mapping mechanism. Dual thresholds are then used to generate three policy recommendations: maintaining current capacity, structural optimization, and capacity reduction. The results show that production trends and volatility intensity are the primary drivers of capacity-adjustment pressure, while pronounced spatial heterogeneity requires highly localized strategies. The classification assigns 25 provinces to maintaining current capacity, 3 to structural optimization, and 3 to targeted capacity reduction. Finally, integrating SHapley Additive exPlanations (SHAP) enhances model interpretability and provides a quantitative basis for shifting from indiscriminate capacity suppression toward differentiated, region-specific capacity governance, thereby supporting the sustainable low-carbon development of the global steel industry. Full article

Background/Objectives: Streptococcus suis is an important zoonotic pathogen responsible for severe infections in animals and humans, and the emergence of diverse strains has reduced the effectiveness of conventional antimicrobial therapies. Since there is no broadly protective vaccine, there is a need for new vaccination strategies that focus on conserved antigens from a variety of strains. This study aimed to design and evaluate a multi-epitope vaccine candidate against diverse S. suis strains using an integrated pangenome-guided reverse vaccinology approach. Methods: To design a multi-epitope vaccine (MEV) candidate against diverse S. suis, an integrated computational framework was employed, incorporating pangenome analysis, subtractive proteomics, reverse vaccinology, immunoinformatics, structural modeling, molecular docking, molecular dynamics simulation, immune simulation, and in silico cloning. The conserved core proteins were systematically screened for essential, non-homologous, antigenic, non-allergenic and non-toxic vaccine candidates for epitope prediction. Results: A total of 7421 gene families, including 1169 conserved core genes, were identified through pangenome analysis of 24 complete S. suis genomes. Three computationally prioritized candidate proteins were identified through sequential subtractive proteomics: sucrose phosphorylase, peptidoglycan hydrolase PcsB and an RND transporter-associated adaptor protein, annotated in the source database as an RND efflux transporter periplasmic adaptor subunit. We selected eight cytotoxic T-lymphocyte (CTL) epitopes, five helper T-lymphocyte (HTL) epitopes, and three linear B-cell epitopes with favorable predicted immunological properties to develop a 397-amino acid multi-epitope vaccine construct that contains the S. suis 50S ribosomal protein L7/L12 adjuvant with rationally designed peptide linkers. The vaccine construct exhibited favorable physicochemical properties, predicted structural stability, and high antigenicity scores. The predicted combined HLA population coverage of the selected CTL and HTL epitopes was 90.77% across the populations included in the analysis. Immune simulation predicted patterns consistent with humoral and cellular immune activation, including sustained IgG production, elevated IFN-γ and IL-2 secretion, efficient antigen clearance, and generation of immunological memory, whereas molecular docking and molecular dynamics simulations characterized the predicted interaction and conformational behavior of the MEV–TLR1/TLR2 complex. Codon optimization (CAI = 0.996) and in silico cloning into the pET-30a(+) expression vector supported the potential feasibility of recombinant expression in Escherichia coli. Conclusions: In this study, a rationally designed multi-epitope vaccine candidate against diverse S. suis strains was developed using an integrated pangenome-guided reverse vaccinology approach. Based on these computational analyses, the proposed vaccine candidate showed favorable predicted immunogenicity, predicted structural quality, predicted HLA population coverage, and expression feasibility, providing a foundation for future experimental validation and development of a vaccine against diverse S. suis. Full article

Despite the rising interest in examining factors associated with body mass index (BMI), little longitudinal evidence can be found regarding its associations with the built environment (BE) and commute, which are closely related to sustainable urban development. Employing two rounds of nationwide survey data in China, this research assesses the links between BE, commute, and BMI in both cross-sectional and longitudinal ways. The findings indicate that non-motorized commute duration is negatively associated with BMI in both analyses. Switching from non-motorized to motorized modes is positively associated with BMI change, whereas switching in the opposite direction is negatively associated with BMI change. Among BE factors, increases in density, diversity, and green coverage are negatively associated with BMI change. Additionally, the research highlights the role of urbanization and suggests a nonlinear association with BMI that is consistent with an inverted-U pattern. The findings highlight the potential relevance of non-motorized commuting to overweight prevention and sustainable mobility. This research provides implications for integrating transport planning, public health, and sustainable urban development. Full article

The Qinghai–Xizang (Formerly Tibet) Plateau, known as the Roof of the World, is an important ecological security barrier for Asia and globally; its natural environment is fragile and challenging to repair after destruction. Prior to the 21st century, waste management in China primarily relied on unregulated direct dumping. To investigate the environmental impacts of open dumpsites in high-altitude regions, this study focused on a representative dumpsite in the northern Xizang region. The aim was to characterize the occurrence and distribution patterns of heavy metals (HMs) in its surrounding soil, conduct source apportionment, and perform comprehensive risk assessment. The results showed low levels of mercury (Hg) and excessive levels of all other HMs. In addition, all HMs had the highest content in the residual fraction and the lowest content in the weak-acid fraction, which is less bioavailable. The Absolute Principal Component Score–Multiple Linear Regression (APCS-MLR) and Positive Matrix Factorization (PMF) results showed that the dumpsite contributed the most to cadmium (Cd); agricultural sources contributed the most to zinc (Zn); Hg mainly came from atmospheric transport and traffic sources; Pb was mainly derived from traffic and natural sources; and copper (Cu), nickel (Ni), chromium (Cr), and arsenic (As) mainly came from the dumpsite and natural sources. In addition, this research found that this dumpsite poses a relatively high HM risk to human health; oral and respiratory routes are the main non-carcinogenic routes, As and Cr contribute more to the adult and child groups, and As contributes the most to carcinogenic risk. The calculation results of the pollution assessment method indicate that the pollution of the natural environment from this dumpsite is at a low level, and immediate remediation measures are urgently needed to achieve site decontamination. Full article

This paper investigates a nonlinear chemotaxis model involving diffusion and chemically directed transport. A detailed Lie symmetry analysis is carried out for different parameter cases, and the corresponding determining equations are derived explicitly to classify the admitted Lie point symmetries. Using the obtained symmetry generators, several similarity reductions are constructed, including time-invariant, space-invariant, scaling, and traveling-wave reductions, with the reduced ordinary differential systems derived step by step. In particular, traveling-wave transformations reduce the governing PDE system to ordinary differential equations, from which several exact wave profiles are obtained, including multi-wave, breather-type, and kink-rational interaction solutions. The analytical structure and graphical behavior of these solutions are examined with the term soliton used only when the corresponding localization properties are satisfied. In addition, conservation-law approaches are employed to explore the structural properties of the model. Finally, the method of lines is used to obtain numerical approximations, allowing for a comparison with the analytical profiles and illustrating the influence of model parameters on the cell-density and chemical-concentration dynamics. Full article

Spray application in spatially heterogeneous three-dimensional crop canopies is constrained by inadequate within-canopy deposition, off-target losses, and poor matching between operating parameters and target structure. This review synthesizes the technological evolution of intelligent agricultural spraying equipment from the perspectives of airflow-assisted transport, demand-based dose allocation, target sensing, actuation control, system integration, and performance evaluation. Air-assisted spraying has expanded transport regulation from hydraulic output alone to coordinated airflow–droplet–canopy interactions. Variable-rate and prescription approaches subsequently linked dose allocation to measurable spatial differences in canopy structure and target distribution. Ultrasonic sensing, light detection and ranging (LiDAR), red–green–blue depth (RGB-D) imaging, machine vision, and multimodal perception have increased the spatial and semantic resolution of target representation. Pulse width modulation (PWM), fuzzy control, and data-driven methods have improved nozzle-level actuation and compensation for nonlinear hydraulic dynamics. However, closed-loop actuator or navigation should not be conflated with closed-loop control of application quality: deposition, drift, and biological efficacy are still evaluated mainly after operation and are rarely used as real-time feedback variables. Current limitations arise less from the absence of individual sensing or control technologies than from weak coupling among canopy representation, spray transport, multivariable actuation, and performance feedback. Future development should prioritize transferable multiscale models and explicit coordination of liquid flow, airflow, droplet size, speed, and equipment state. Scenario-specific architectures must connect sensing, decision-making, actuation, and evaluation without sacrificing field robustness. Full article

Normalization of entropy generation provides a dimensionless and physically consistent framework for comparing irreversibility mechanisms under different operating conditions, while log-space third-order polynomial regression enables accurate representation of nonlinear coupled transport behavior over wide parameter ranges. Accordingly, this study investigates entropy generation associated with double-diffusive mixed convection in an oblique vented chamber filled with a nano-encapsulated phase change material suspension under local thermal non-equilibrium (LTNE) conditions in a porous medium. The governing equations are formulated by incorporating the effects of inlet and outlet sizes through the Reynolds number to provide a more realistic representation of the physical configuration. The dimensionless governing equations are discretized using the finite volume method based on the control-volume approach. The resulting entropy generation, heat transfer, and mass transfer characteristics, including the average fluid Nusselt and Sherwood numbers, are normalized and correlated using log-space third-order polynomial regression models. An effective RSM approach is employed to perform a sensitivity analysis of the key operating parameters. The results reveal that, for all inlet and outlet configurations, the normalized average fluid Nusselt number increases with increasing nanoparticle volume fraction. Moreover, both the normalized average Sherwood number and normalized fluid entropy generation increase with the Soret coefficient, demonstrating its pronounced influence on double-diffusive transport and irreversibility within the LTNE porous chamber. Full article

Richards’ equation (RE) describes transient water flow in variably saturated porous media and plays a fundamental role in hydrological, agricultural, and environmental modelling. Its inherent nonlinearity, potential degeneracy, and sensitivity to hydraulic parameterization make accurate numerical solutions a persistent challenge. This review offers a systematic comparative analysis of numerical methods for the RE across three key dimensions: spatial discretization, primary variable formulation, and iterative linearization strategy. Finite Difference, Finite Element, and Finite Volume methods are evaluated for their theoretical properties and performance under demanding conditions such as sharp infiltration fronts and heterogeneous parameter fields. Meshless methods are also assessed for their geometric flexibility and accuracy. Iterative linearization schemes are compared in terms of convergence, robustness, and computational cost. The analysis is structured around three performance metrics: numerical stability, computational efficiency, and mass conservation. Mass conservation is found to depend critically on both the primary variable formulation and the discretization framework, with mixed and finite volume approaches offering the strongest guarantees. The review concludes that no universally optimal solver exists; method selection must be tailored to specific soil conditions, boundary conditions, and computational constraints. Key open challenges include convergence under extremely dry conditions, multiscale heterogeneity, and coupled flow-transport processes. Full article

Emission reduction remains the foundation of air-pollution control, yet the relationship between reduced emissions and improved ambient air quality is frequently non-proportional. This mismatch is not an exception to atmospheric behavior but a consequence of coupled chemical, meteorological, transport, and removal processes. Here, we critically synthesize global evidence for nonlinear air-quality responses to emission controls, with particular attention to fine particulate matter (PM_2.5) and ozone (O₃). We distinguish five response forms that are directly relevant to policy: near-linear, sublinear, superlinear, threshold, and sign-reversal behavior. Ozone provides the clearest example because the response to nitrogen oxides (NOx) and volatile organic compounds (VOCs) depends on the prevailing photochemical regime and can change as emissions decline. PM_2.5 responses are likewise nonlinear because precursor controls alter atmospheric oxidation capacity, gas-particle partitioning, aerosol water, and interactions among nitrate, sulfate, ammonium, and secondary organic aerosol. Aerosol reductions can further modify photolysis and boundary-layer processes, linking PM_2.5 control to O₃ production. Regional transport and background concentrations attenuate or redistribute the benefits of local controls, while meteorological variability changes both chemical sensitivity and the realized concentration response. These mechanisms imply that sustainable air-quality management cannot be evaluated solely by tonnes of emissions avoided. Instead, policy performance should be assessed along the complete pathway from emission reduction to ambient concentration, exposure, health, climate, ecosystem, equity, and economic outcomes. We propose a sustainability-oriented framework in which control strategies are evaluated for atmospheric effectiveness, multipollutant coherence, spatial equity, climate compatibility, and robustness across changing chemical and meteorological regimes. The evidence supports adaptive, coordinated, and regionally integrated control portfolios rather than fixed single-pollutant reduction ratios. Full article

The prefectures and cities along the Yunnan–Vietnam border constitute a key cultural corridor connecting China and ASEAN. Under the dual pressures of globalization and modernization, the regional cultural landscape is undergoing profound structural transformation. This study takes 194 traditional villages and 942 municipal-level and above intangible cultural heritage (ICH) items in Honghe, Wenshan, and Pu’er as the research objects. Kernel density estimation, the standard deviation ellipse, and the gravity center model were employed to identify their spatial distribution patterns, while the spatial mismatch index and GeoDetector were used to examine their spatial coupling relationship and influencing mechanisms. The results indicate the following: (1) traditional villages exhibit a single-core clustered distribution concentrated in the Ailao Mountains-Honghe River Basin of Honghe Prefecture, whereas ICH displays a one-core-two-cluster pattern with relatively weak agglomeration, and the gravity centers of the two heritage systems are separated by 61.21 km; (2) a significant systematic spatial mismatch exists between traditional villages and ICH, with Honghe characterized as a high negative mismatch region, while Pu’er and Wenshan represent positive mismatch regions; (3) their spatial relationship is jointly shaped by nonlinear interactions among natural geographical, socioeconomic, and historical-cultural factors, forming an interaction mechanism dominated by the ecological constraints of hydrothermal conditions and topography together with the spatial organizational effects of border ports and transportation networks. This study reveals the spatial reorganization pattern of cultural heritage elements in the three prefectures and cities along the Yunnan–Vietnam border and provides a scientific basis for the coordinated conservation and spatial optimization of traditional villages and intangible cultural heritage. Full article