Search Results (96,969)

Spent automotive catalysts represent an important secondary resource for platinum group metals, offering environmental and economic advantages over primary mining. This review evaluates bioleaching-based recovery strategies of these metals as sustainable alternatives to conventional pyrometallurgical and hydrometallurgical processing. The cyanogenic bioleaching using Chromobacterium violaceum, Pseudomonas fluorescens, and Bacillus megaterium, and acidophilic bioleaching using Acidithiobacillus spp. for washcoat degradation and base-metal removal are discussed through the one-step, two-step, spent-medium, and decoupled systems. The analysis shows progressive improvement of recovery as process separation increases. Sequential pretreatment involving ultrasound-assisted acid leaching, thermal oxidation, and pressure-enhanced processing improved recovery by removing competing base metals and increasing PGM accessibility. Kinetic analyses indicate that diffusion through the porous catalyst support matrix becomes the dominant rate-controlling mechanism at high conversion, which impacts reactor design. Despite sustainability potential, industrial implementation remains constrained by low pulp density, cyanide stability, reactor productivity, and scale-up limitations. Routes to commercialisation require feasibility studies of process designs that integrate viable process flow diagrams combining pretreatment, biological lixiviant generation, intensified bioleaching, and downstream metal purification. Full article

Nitrogen dioxide (NO₂) drives ozone and secondary aerosol formation and harms human health. Chongqing, a mountainous megacity of 32 million people, lacks a fine-scale satellite assessment of its NO₂ evolution. We analyzed tropospheric NO₂ vertical column density (VCD) over Chongqing for 2019–2024. The analysis used Sentinel-5P TROPOMI observations. We computed monthly, seasonal, and annual composites at 5.5 km resolution. Trends were quantified with the Theil–Sen slope and, at the pixel level, the Seasonal Mann–Kendall (SMK) test applied to the full 72-month series. A MODIS land-cover mask separated urban built-up from non-urban pixels. NO₂ concentrated in the central districts and along the Yangtze valley. The core exceeded the mountainous counties by a factor of 3 to 4. TROPOMI resolved the Wanzhou and Yongchuan–Jiangjin hotspots as separate features. The record was divided into three phases. The 2020 lockdown produced the minimum, 31% below the prior February. Rebound emissions produced the 2021 maximum of 5.6 × 10¹⁵ molecules cm⁻² under near-normal dispersion conditions, with ERA5 (the European Centre of Medium-range Weather Forecasts Reanalysis v.5) showing the January 2021 boundary layer 4.3% deeper than its climatological norm. Thereafter the regional mean stabilized: the area-weighted SMK slope was +0.042 × 10¹⁵ molecules cm⁻² yr⁻¹ and not significant (p = 0.14), because emission controls in the core and rising county emissions canceled in the average. Trends diverged sharply in space. The nine core districts declined (median urban Sen slope −0.11 × 10¹⁵ molecules cm⁻² yr⁻¹), whereas 41% of peripheral pixels rose significantly (p < 0.05). The urban-to-rural ratio narrowed from 3.0 in 2019 to 2.3 in 2024 (annual means). This convergence was robust to the built-up threshold (30–50%). Industrial relocation and county urbanization explain the peripheral rise. The results support extending vehicle and industrial emission standards from the core to the receiving counties. Full article

Municipal solid waste landfill leachate represents one of the most environmentally challenging liquid effluents in modern waste management; however, its high nitrogen and phosphorus content renders it a potentially valuable nutrient source for microalgal phycoremediation. Here, Chlorella sp. and Scenedesmus sp. were cultivated for 15 days in CHU-10 standard medium and 50% (v/v) municipal landfill leachate from Nauta, Peru, and characterized across 33 biochemical variables, 14 physicochemical parameters, and 32 metal ions and trace elements. A sequential competitive multivariate pipeline comprising principal component analysis (PCA), hierarchical cluster analysis (HCA), permutational multivariate analysis of variance (PERMANOVA), and linear discriminant analysis (LDA) was applied to both the biochemical and bioremediation datasets. Leachate supplementation increased peak biomass density by 26.6–28.3% and elevated total protein by 56.9% in Chlorella sp. and 73.4% in Scenedesmus sp., while reducing total lipids by 37–46% and suppressing polyunsaturated fatty acid production. Both species achieved net biological removal efficiencies (NBRE) exceeding 86% for ammonium and ammonia; toxic elements, including Cd (~96%), Al (~92%), As (~90%), and Pb (~90%), were removed at higher NBRE than macro- and micronutrient categories. LDA achieved 100% leave-one-out cross-validation accuracy for species classification from both physicochemical and 32-element NBRE profiles. These findings indicate two complementary valorization directions, contingent on further biomass safety verification: leachate-grown Scenedesmus sp. shows a favorable combination of protein enrichment and nutrient removal for single-cell protein production integrated with bioremediation, while Chlorella sp. in standard medium shows a more favorable fatty acid profile for nutraceutical applications. Because leachate-grown biomass also accumulates inorganic and trace-element constituents from the medium, its suitability for protein or nutraceutical use requires direct heavy-metal characterization of the harvested biomass, independent of the demonstrated removal efficiency from the liquid phase. Full article

Background/Objectives: Performance measurement and management is a key administrative function; however, its application to child and adolescent healthcare services remains poorly mapped in the international literature. This study attempts a systematic bibliometric mapping of the field. To the best of our knowledge, previous bibliometric studies in pediatric and related healthcare fields have primarily focused on specific clinical or service domains, whereas the intersection of performance measurement and management with child and adolescent healthcare services has not been specifically mapped. The novelty of the present study lies in addressing this intersection through an integrated bibliometric assessment of its thematic, temporal, and geographical structure. Methods: A bibliometric analysis was performed on the Scopus database, with a query that combined a proximity operator (W/10) and Boolean logic, yielding 643 documents (1990–2026). After metadata cleaning and application of an occurrence threshold (≥15), 111 keywords were analyzed with VOSviewer (network, overlay, density, targeted analysis, bibliographic coupling of countries). Results: Research production increased strongly since 2010, peaking in 2025. Four thematic clusters emerged—quality of care, clinical outcomes, administrative framework, emergency/operational care—with the term “quality of health care” as the central hub-bridge. The administrative cluster was linked to older publications relative to the clinical/operational clusters. Country-level bibliographic coupling identified distinct geographical patterns in cited-reference similarity, including a predominantly European cluster, a transcontinental cluster dominated by the United States and Canada, and a separate Australian cluster. The term “performance measurement” itself did not meet the inclusion threshold, reflecting the methodological effect of the selected occurrence threshold rather than the absence of the concept from the literature. Conclusions: The retrieved literature was strongly concentrated in clinical and health-related subject areas, while explicitly administrative and managerial perspectives appeared comparatively limited. This pattern indicates a potential research gap that warrants further investigation rather than confirming the absence of managerial performance frameworks in the broader field. Full article

Although many studies had been conducted on soil microbial communities in forest ecosystems before this one, how the diversity and network complexity of soil microbial communities evolved throughout the succession of karst forests remained unclear. We collected soil samples from three vegetation successional stages (grassland stage, shrub stage and arbor stage) in Maolan National Nature Reserve, Guizhou Province, China, and applied high-throughput sequencing technology to explore soil microbial diversity, community composition, co-occurrence network characteristics and their internal correlations. The results showed that the succession process significantly affected soil microbial diversity (p < 0.05). Bacterial diversity increased by 12.33% as succession proceeded, whereas fungal diversity declined by 37.50%. The dominant microbial communities exhibited obvious stage-specific characteristics. For bacteria, Bacillaceae served as a universally dominant taxon. Paenibacillaceae and Thermoactinomycetaceae were enriched in the grassland (CD) stage, and the relative abundance of Streptosporangiaceae reached its maximum in the arbor (QM) stage. For fungi, Trimorphomycetaceae and Hypocreaceae were ubiquitous dominant groups. Aspergillaceae possessed the highest relative abundance in the CD stage, while Clavicipitaceae peaked in relative abundance in the QM stage. The complexity of bacterial co-occurrence networks rose with succession, whereas fungal network complexity decreased. Both positive and negative linkages in bacterial networks increased over succession, while both types of connections in fungal networks declined. Soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP) and N/P ratio exerted the strongest influences on bacterial communities and bulk density; SOC and TN were the key drivers structuring fungal assemblages. Micromonosporaceae and Xanthobacteraceae showed significant positive correlations with TP and N/P ratio (p < 0.05), whereas Thermoactinomycetaceae and Oscillospiraceae presented significant negative correlations with these two indicators (p < 0.01). Clavicipitaceae had strong positive correlations with SOC and TN (p < 0.01), and Herpotrichiellaceae together with Aspergillaceae displayed significant negative correlations with SOC and TN (p < 0.05). This study clarified the regulatory effects of karst forest secondary succession on soil microbial communities and provided theoretical evidence for the ecological restoration of karst regions. Full article

With the rapid transition of the global energy structure, large-scale clean energy integration has become a major trend in power system development. Nevertheless, the intermittency and stochastic fluctuation of renewable power generation threaten the secure operation of power systems. With high power density and millisecond-level response capability, supercapacitors act as key technical support for frequency stabilization and grid frequency fluctuation suppression. This paper reviews research advances in the application of supercapacitors to power system frequency regulation. It presents the classification and energy storage mechanisms of supercapacitors, analyzes their technical advantages in frequency regulation, and summarizes key research progress involving control strategies, topologies and capacity optimization schemes. Three typical application scenarios are illustrated: standalone frequency regulation, coordinated thermal-storage frequency regulation, and auxiliary frequency regulation for renewable power plants. Considering future requirements for frequency regulation, potential research directions are put forward to provide references for follow-up related studies. Full article

AIS trajectories in and around ports are often incomplete because of transmission interruptions, reception failures, and infrastructure outages. In this paper, we investigate whether the Data-driven AIS Trajectory Interpolation method (DAISTIN), which reconstructs missing trajectory segments using a graph derived from historical AIS observations, can be improved by retaining local directional information that is otherwise discarded when observations are sampled to form the graph. To this end, we introduce two extensions, xDAISTIN and xDAISTOUT. The originality of the proposed approach lies in extending DAISTIN by enriching each sampled graph node with neighbourhood-level directional information from nearby historical AIS observations. Specifically, local vessel headings are encoded cyclically and modelled using kernel density estimators, allowing candidate graph transitions to be evaluated using local movement probabilities rather than only the heading of the sampled point. The methods are evaluated on real-world AIS data from the Port of Antwerp by introducing synthetic gaps into held-out trajectories and measuring how well they are reconstructed by the methods. Using 36,748 moving sub-trajectories from 5488 vessel trips, we compare the proposed methods against DAISTIN, linear interpolation, and several directed, undirected, probabilistic, and shortest-path graph variants. Across graph sizes from 100 k to 180 k nodes, DAISTIN and its undirected variant reconstructed $48.48$–$84.61\%$ and $72.35$–$91.23\%$ of missing segments, respectively, compared to $88.02$–$96.42\%$ and $91.36$–$99.13\%$ for xDAISTIN and its variants, and $65.75$–$85.17\%$ and $72.12$–$97.80\%$ for xDAISTOUT and its variants. Compared with undirected DAISTIN at 180 k nodes, undirected xDAISTIN at 180 k nodes achieved significantly lower mean SPD, DFD, and HD (all Holm-adjusted, $p<0.001$), by approximately $14\%$, $43\%$, and $36\%$, respectively. These findings demonstrate that preserving neighbourhood-level directional behaviour during graph construction can substantially improve the interpolation completion rate and reconstruction accuracy in complex port environments. Full article

Background/Objectives: Paget’s disease of bone (PDB) and osteoporosis are chronic metabolic bone disorders characterized by disrupted bone remodeling and increased skeletal fragility; however, the underlying mechanism of PDB remains poorly understood. Artificial intelligence (AI) has emerged as a transformative tool in medical imaging, enabling automated feature extraction and improved diagnostic classification of skeletal disorders. This study aimed to investigate whether AI could distinguish subtle variations in bone morphology between PDB and osteoporotic bone. Methods: C57BL/6 mice femurs were scanned by µCT: 16 optineurin-knockout mice with a PDB phenotype (20–26 months), 25 genetically matched wild-type Aging mice (20–26 months), and 15 ovariectomized (OVX) mice with osteoporotic bone phenotype (4.5 months). Two AI algorithms were investigated: a machine learning (ML) model using 22 µCT-derived features trained with a Random Forest (RF) classifier, and a deep learning (DL) model using a 3D convolutional neural network (3D-CNN) trained on raw µCT images. Leave-one-out cross-validation was applied to evaluate model robustness. Results: Significant differences in volumetric, density, and morphological parameters of cortical and trabecular bone were observed between PDB and osteoporosis (p < 0.05). The RF algorithm achieved 90% accuracy in distinguishing PDB from both aging- and OVX-induced osteoporosis and provided feature importance rankings that improved model interpretability. The 3D-CNN achieved classification accuracies of 70% for PDB vs. OVX and 68% for PDB vs. aging, demonstrating the feasibility of an image-based DL approach. Conclusions: AI-based RF and 3D-CNN models demonstrated promising performance in differentiating PDB from osteoporosis using µCT-derived bone features. These findings suggest potential for using AI to assist with analyzing skeletal images in the diagnosis of metabolic bone disorders. Full article

GaN power devices used in high-power-density converters face significant thermal-management challenges because substantial heat is generated within a compact active region and transferred through the device–Printed Circuit Board (PCB) interface. This study investigates the influence of PCB dielectric-material selection on the coupled thermal and electrical behavior of a 48 V/12 V GaN half-bridge converter. Flame Retardant 4 (FR4), Hydrocarbon ceramic laminate material RO4000 series (4003) (RO4003), and polybenzoxazole (PBO) were compared using a reduced steady-state thermal-resistance network, three-dimensional finite-element simulations in Ansys Icepak, parasitic-capacitance extraction in Ansys Q3D, and switching simulations in LTspice. Both analytical and numerical models produced the same thermal-performance ranking, with PBO providing the lowest junction temperature. Under identical geometry, power dissipation, and boundary conditions, the Finite Elements Method (FEM) results showed a reduction in the maximum junction temperature from 225 °C for FR4 to 159 °C for PBO. The extracted layout-associated capacitances were also reduced by approximately 30–38% with PBO relative to FR4. This decrease produced a slight reduction in the switching-node falling time and lowered the calculated transistor loss from 3.118 W to 3.102 W. The results show that PCB dielectric selection is primarily a thermal-design parameter, while its electrical influence remains modest under the investigated operating conditions. Full article

Complex surfaces exhibit hierarchical morphological organizations that cannot be fully described by conventional roughness parameters alone. In this study, a fractal–statistical framework is proposed to elucidate the substrate-controlled morphological evolution of 2,6-diphenyl anthracene (DPA) thin films deposited on chemically modified dielectric substrates, including hexamethyldisilazane (HMDS), octyltrimethoxysilane (OTMS), octadecyltrichlorosilane (OTS), and bare silicon dioxide (SiO₂). A multidimensional morphological descriptor vector (M_DPA) is introduced by integrating ISO 25178 areal surface parameters (H_ISO), fractal dimension (D_f), texture direction parameters (T_d), power spectral density (PSD), and scale-sensitive fractal analysis (SSFA) descriptors to quantify amplitude-based, spatial-frequency, and scale-dependent morphological information. Atomic force microscopy (AFM) topographies of 5 nm and 50 nm thick films were analyzed using complementary approaches, including ISO 25178 areal surface parameters, texture direction analysis, peak statistics, morphological envelope fractal analysis, two-dimensional Fourier analysis, power spectral density (PSD), and scale-sensitive fractal analysis (SSFA). The results demonstrate that substrate chemistry governs not only the amplitude of surface roughness but also the lateral organization, spatial frequency distribution, and scale-dependent fractal complexity of DPA morphologies. The fractal dimension analysis revealed substrate-dependent variations in surface complexity, with values ranging from 2.11 to 2.45 for 5 nm films and from 2.19 to 2.52 for 50 nm films. PSD analysis identified distinct substrate-induced modifications in spectral organization, while SSFA revealed significant changes in smooth–rough crossover scales, maximum complexity scales, and fractal surface complexity during film growth. In particular, OTMS promoted the strongest hierarchical organization for thicker films, exhibiting the highest scale-sensitive fractal complexity, whereas OTS generated highly developed but less hierarchically correlated rough structures. The integrated fractal–spectral methodology establishes quantitative relationships between substrate functionalization and multiscale surface evolution, demonstrating that morphological complexity cannot be described solely by conventional height parameters. This framework provides a robust approach for characterizing hierarchical thin-film architectures and can be extended to other organic semiconductor systems where substrate-driven morphological control is critical. Full article

Urban agglomerations concentrate human populations, economic activities, and land development, but gains in land-use efficiency do not necessarily progress synchronously with improvements in human-development capability. This study examines the coordination and mismatch between population high-quality development (PHQD)—referring specifically to the high-quality development of the human population—and land green use efficiency (LGUE) across 131 cities in six major Chinese urban agglomerations from 2011 to 2023. PHQD is measured using the entropy-weighted TOPSIS method. LGUE is measured using a non-oriented global super-efficiency slacks-based measure (SBM) model with undesirable outputs. People–land coordination is assessed using a modified coupling coordination degree (MCCD) model combined with a relative development index (RDI). Kernel density estimation, Dagum Gini decomposition, and Geodetector are applied to analyze distribution dynamics, disparities, and spatially stratified associations. MCCD rose from 0.311 to 0.419, although most cities remained at relatively low coordination levels. PHQD-lagging was the dominant mismatch type in 2023, involving 98 of 131 cities. Overall MCCD inequality declined from 0.138 to 0.103, while transvariation replaced between-group differences as the largest disparity component. Economic development had the strongest explanatory power, and all pairwise interaction q values exceeded the corresponding single-factor q values. Sustainable urban transformation therefore requires coordinated investment in human capital and public services alongside continued improvements in resource- and environmentally constrained land-use efficiency. Full article

Background: Generative artificial intelligence (GenAI) has attracted significant attention in supply chain management (SCM) due to its potential to improve data-driven decision-making and operational performance. However, existing studies mainly focus on individual GenAI models or specific supply chain applications, lacking a comprehensive understanding of how different GenAI architectures support decision-making across the supply chain. Methods: This study conducts a systematic literature review using the PRISMA framework to examine the applications of Generative Adversarial Networks (GANs), Transformers, Variational Autoencoders (VAEs), and flow-based models within a six-level supply chain decision-making framework. A total of 692 peer-reviewed publications were analyzed using bibliometric methods, including keyword co-occurrence, temporal and density analyses, and Supervised Embedding Visualization. Results: Current research is concentrated on Transformer and GAN applications, particularly in data analytics, optimization, forecasting, manufacturing, transportation, logistics, and quality management. The analyses also reveal major research themes, the evolution of GenAI in SCM, and limited attention to sustainability, cybersecurity, resilience, and reverse logistics. Conclusions: This study provides a comprehensive overview of GenAI applications in SCM, identifies key research gaps, and offers a foundation for future research while helping practitioners evaluate opportunities and limitations of GenAI for supply chain decision-making. Full article

Rapid urbanization has increasingly posed risks of inducing land subsidence in newly developed urban districts, posing growing threats to infrastructure safety. This study focuses on a selected rectangular area within the Shannan New District of Huainan City. Based on 94 Sentinel-1A images acquired from 2023 to 2025, the SBAS-InSAR technique was employed to obtain high-density spatiotemporal surface deformation data. The discrete monitoring points were mapped onto a 100 × 100 regular grid according to their spatial coordinates, with null-value cells retained. A spatial attention mechanism was then embedded into the Convolutional Long Short-Term Memory (ConvLSTM) network to construct a Spatial Attention–ConvLSTM (SA-ConvLSTM) model for spatiotemporal prediction, which was systematically compared with LSTM, CNN-LSTM (Convolutional Neural Network combined with Long Short-Term Memory), and standard ConvLSTM. The results demonstrate that SA-ConvLSTM achieves optimal prediction performance on the temporal hold-out test set, with a root mean square error of 2.09 mm and a coefficient of determination (R²) of 0.77. For subsidence hotspot identification, the intersection over union (IoU) reaches 0.56, and the F1-score reaches 0.72—substantially improving from 0.25 for standard ConvLSTM, confirming that the spatial attention mechanism effectively enhances the model’s capability to focus on key deformation areas. Rolling predictions of the deformation field for 2026 (12 time steps, each covering one Sentinel-1A acquisition interval of approximately 12 days) yield an estimated deformation trend ranging from −16.58 to 0.28 mm over the 12-step forecast period (approximately 144 days). This integrated framework provides a methodological reference for subsidence risk identification and mitigation in the Shannan New District. Full article

This work examines a new methodology for the nonlinear electrohydrodynamic interfacial stability of dielectric viscoelastic liquids to enhance the predictive accuracy of microfluidic and biological applications. It tackles the intricacies of nonlinear coupled dynamics, encompassing interfacial deformation and viscoelastic stress influences. This study examines nonlinear stability, as linear stability has previously been thoroughly scrutinized. The interacting fluids are distinguished by differences in density, dielectric permittivity, permeability, viscoelastic parameters, surface tension, and their dynamic response at the perturbed interface. To simplify the mathematical organization, viscous potential flow theory is adopted. Further reduction is achieved by coupling linearized governing partial differential equations with the applicable nonlinear interfacial boundary conditions. This formulation leads to a nonlinear Mathieu oscillator, which governs the evolution of interface displacement. By adopting a non-perturbative approach, the achieved nonlinear ordinary differential equation is transformed into an equivalent linear one. Numerical solutions to the derived stability conditions reveal that the fundamental stability behavior remains qualitatively identical to both the real and complex coefficients associated with nonlinear characteristic equations describing the movement of interfacial displacement. The findings demonstrate that the Darcy number negatively influences the stability region, whereas kinematic viscosities, the Weber number, and Ohnesorge number facilitate the system’s stabilizing impact. Full article

The Jinsha River Basin on the eastern margin of the Qinghai–Xizang (Tibetan) Plateau is one of the most landslide-prone regions globally. The Batang reach (from Suwalong Township to Changbo Township) lies in the core of the Jinsha River Suture Zone, characterized by complex geological conditions and frequent landslide disasters. To address the limitations of traditional monitoring methods—including difficulty in full-area coverage, high costs, and low efficiency in mountainous canyon terrain—a systematic study of landslide monitoring was conducted using Sentinel-1A SAR data and Interferometric Synthetic Aperture Radar (InSAR) technology. The results demonstrate that SBAS-InSAR, via short-baseline combinations, achieves a monitoring point density of 697 points/km² (6.28 times that of PS-InSAR), offering significant advantages in mountainous canyon areas with dense vegetation and fragmented rock masses. Using this technical framework, a total of 38 active landslides were identified in the study area, including 5 newly detected rapidly deforming hazards, 17 with river blockage risk, and 10 with the potential to bury buildings. The maximum downslope deformation rate reaches −89.56 mm/yr for the landslide near Suwalong Hydropower Station. Landslides are concentrated within 500 m of faults, in weak rock zones, on steep slopes with gradients greater than 30°, and near road-cutting projects. Temporally, landslide deformation shows an evident correlation with rainfall; approximately 70% of annual cumulative deformation occurs within the rainy season. Engineering activities including hydropower station impoundment appear to be associated with elevated deformation rates of local landslides. This study provides a scientific basis for the safety of major infrastructure corridors (e.g., the Sichuan–Tibet Railway) and regional disaster prevention and mitigation. Full article