Search Results (13,422)

By addressing the challenges of management difficulties, insufficient integration of driver analysis, and single-dimensional analysis in the governance of illegal land use and illegal construction (collectively referred to as the “Two Illegalities”) under rapid urbanization, this study designs and implements a GIS-based governance system using Xiamen City as the study area. First, we propose a standardized data-processing workflow and construct a comprehensive management platform integrating multi-source data fusion, spatiotemporal visualization, intelligent analysis, and customized report generation, effectively lowering the barrier for non-professional users. Second, utilizing methods integrated into the platform, such as Moran’s I and centroid trajectory analysis, we deeply analyze the spatiotemporal evolution and driving mechanisms of “Two Illegalities” activities in Xiamen from 2018 to 2023. The results indicate that the distribution of “Two Illegalities” exhibits significant spatial clustering, with hotspots concentrated in urban–rural transition zones. The spatial morphology evolved from multi-core diffusion to the contraction of agglomeration belts. This evolution is essentially the result of the dynamic adaptation between regional economic development gradients, urbanization processes, and policy-enforcement synergy mechanisms. Through a modular, open technical architecture and a “Data-Technology-Enforcement” collaborative mechanism, the system significantly improves information management efficiency and the scientific basis of decision-making. It provides a replicable and scalable technical framework and practical paradigm for similar cities to transform “Two Illegalities” governance from passive disposal to active prevention and control. Full article

This study focuses on the transfer of architectural facade styles. Using the node-based visual deep learning platform ComfyUI, the system integrates the Flux Redux and Flux Depth models to establish a modular workflow. This workflow achieved style transfer of building facades guided by deep perception, encompassing key stages such as style feature extraction, depth information extraction, positive prompt input, and style image generation. The core innovation of this study lies in two aspects: Methodologically, a modular low-code visual workflow has been established. Through the coordinated operation of different modules, it ensures the visual stability of architectural forms during style conversion. In response to the novel challenges posed by generative AI in altering architectural forms, the evaluation framework innovatively introduces a “semantic inheritance degree” assessment system. This elevates the evaluation perspective beyond traditional “geometric similarity” to a new level of “semantic and imagery inheritance.” It should be clarified that the framework proposed by this research primarily provides innovative tools for architectural education, early design exploration, and visualization analysis. This workflow introduces an efficient “style-space” cognitive and generative tool for teaching architectural design. Students can use this tool to rapidly conduct comparative experiments to generate multiple stylistic facades, intuitively grasping the intrinsic relationships among different styles and architectural volumes/spatial structures. This approach encourages bold formal exploration and deepens understanding of architectural formal language. Full article

As a critically important global food crop, wheat has been increasingly threatened by the frequent occurrence of extreme high-temperature events, which impairs its growth and development, resulting in reduced seed-setting rate, compromised grain quality and diminished yield. Therefore, identifying heat-tolerant genes and enhancing thermotolerance through molecular breeding are essential strategies for wheat improvement. In this study, we retrieved spatial transcriptomic data from the public database PRJNA427246, which captured gene expression profiles in flag leaves and grains of the heat-sensitive wheat cultivar Chinese Spring (CS) under 37 °C heat stress at time points of 0 min, 5 min, 10 min, 30 min, 1 h, and 4 h. Weighted Gene Co-expression Network Analysis (WGCNA) was used to construct co-expression networks for flag leaf and grain transcriptomes. One highly significant module was identified in each tissue, along with 35 hub genes that showed a strong temporal association with heat stress progression. Notably, both modules contained the previously characterized thermotolerance gene TaMBF1c, suggesting that additional heat-responsive genes may be present within these modules. Simultaneous analysis of the expression data from four groups (encompassing different tissues and high-temperature treatments) for the 35 core genes revealed that genes from the TaHSP20 family, TaMBF1c family, and other related genes exhibit coordinated expression patterns in terms of the temporal dynamics and tissue distribution of stress responses. Additionally, 27 genes of the small heat shock protein (HSP20) family are predicted to be involved in the endoplasmic reticulum-associated degradation (ERAD) pathway. They assist in clearing misfolded proteins induced by stress, thereby helping to maintain endoplasmic reticulum homeostasis and cellular functions under stress conditions. Finally, the expression levels of three core genes, TaHSP20-1, TaPCDP4, and TaMBF1c-D, were validated by qRT-PCR in two wheat cultivars with distinct thermotolerance: S116 (Zhehuamai 2008) and S128 (Yangmai 33). These findings provide new insights into the molecular mechanisms underlying heat tolerance in wheat and offer valuable genetic resources for breeding thermotolerant varieties. Full article

China boasts abundant cultivated resources of pitahaya, with Guizhou Province being one of its core producing areas. Quality differences in red-fleshed pitahaya among local producing areas have not been fully clarified, and a standardized quantitative evaluation system for these differences remains lacking. This study seeks to identify the key factors influencing regional variations in quality and establish a comprehensive evaluation standard. In this study, 15 samples of red-fleshed pitahaya were collected from four major producing areas in Guizhou and used as research materials. Based on 15 quality characteristic indicators of the fruits, an analysis of quality differences and establishment of an evaluation system were carried out using multivariate statistical analysis. The results showed that 14 of the 15 quality indicators exhibited significant differences among pitahaya samples from different producing areas (p < 0.05), with the a* value being the sole exception. Cluster analysis classified the 15 samples into four groups. Principal component analysis (PCA) extracted four principal components, with a cumulative variance contribution rate of 81.07%, which clearly identified betacyanin, betaxanthin, 1,1-diphenyl-2-picrylhydrazyl (DPPH) free-radical scavenging rate, vitamin C, fruit shape index, and transverse diameter as the core evaluation indicators. This study systematically clarifies the differences in quality characteristics and the internal correlations among quality indicators of red-fleshed pitahaya from different major producing areas in Guizhou. It further provides an important scientific basis for pitahaya variety breeding, cultivation regulation, and market positioning in this region and fills the research gap existing in the field of comprehensive quality evaluation of pitahaya. This is of significant practical importance for promoting the standardized upgrading of local specialty fruit industries, enhancing the market competitiveness of products, and facilitating the high-quality development of the agricultural economy. Full article

This study presents a robust framework for optimizing the site selection of Electric Vehicle Charging Stations (EVCS) in Qatar by integrating a Geographic Information System (GIS) with a Multi-Criteria Decision-Making (MCDM) model. The core innovation lies in the enhancement of the conventional Analytic Hierarchy Process (AHP) with a Removal Sensitivity Analysis (RSA). This unique integration moves beyond traditional, subjective expert-based weighting by introducing a transparent, data-driven methodology to quantify the influence of each criterion and generate objective weights. The Analytic Hierarchy Process (AHP) was used to evaluate fourteen criteria related to accessibility, economic and environmental factors that influence EVCS site suitability. To enhance robustness and minimize subjectivity, a Removal Sensitivity Analysis (RSA) was applied to quantify the influence of each criterion and generate objective, data-driven weights. The results reveal that accessibility factors, particularly proximity to road networks and parking areas exert the highest influence, while environmental variables such as slope, CO concentration, and green areas have moderate but spatially significant impacts. The integration of AHP and RSA produced a more balanced and environmentally credible suitability map, reducing overestimation of urban sites and promoting sustainable spatial planning. Environmentally, the proposed framework supports Qatar’s transition toward low-carbon mobility by encouraging the expansion of clean electric transport infrastructure, reducing greenhouse gas emissions, and improving urban air quality. The findings contribute to achieving the objectives of Qatar National Vision 2030 and align with global efforts to mitigate climate change through sustainable transportation development. Full article

To enhance PharmD student leadership and advocacy skills, combat the paucity of trained pre-health advisors for pharmacy admissions, augment community relationships, and increase pharmacy admissions volume, we designed, implemented, and assessed PAALS, a Pre-health Academic Advising and Leadership System. PAALS was grounded in Astin’s Theory of Student Involvement and evaluated using the RE-AIM implementation science framework. RE-AIM measured outcomes across Reach, Effectiveness, Adoption, Implementation, and Maintenance as indicators of PAALS’s scale, fidelity, sustainability, and institutional embedding. Analysis of PAALS using the RE-AIM framework demonstrated the following outcomes: (1) Reach: 42 P1-P3 PharmD students participated as mentors; external partnerships expanded from 2 to 8 regional high schools and community programs; and more than 25 mentored learners successfully matriculated into the PharmD program. (2) Effectiveness: students enacted sustained leadership, advocacy, and mentoring roles. (3) Adoption: voluntary uptake of mentoring and governance roles by PharmD students occurred with repeated engagement by external partner institutions. (4) Implementation: Core program components were delivered consistently using existing institutional resources. (5) Maintenance: PAALS remained operational across five academic years despite student turnover, with leadership succession and institutional embedding sustained across cohorts. Our findings demonstrate that student-led advising and advocacy ecosystems address critical gaps in pharmacy-specific pre-health advising models. Full article

As the global transportation sector accelerates toward net-zero targets, the rapid deployment of alternative fuels like hydrogen, ammonia, and batteries introduces complex and novel safety challenges. This study systematically maps the intellectual structure of safety and risk research on zero-emission transportation systems to evaluate field maturity and identify critical knowledge gaps. We conducted a comprehensive bibliometric analysis of 151 core publications retrieved from the Web of Science from 2000 to 2025. By integrating quantitative performance analysis with qualitative science mapping techniques, the results identify that the domain is nascent and rapidly expanding, and a distinct inflection in publication occurred in 2020. However, science mapping reveals a fragmented intellectual structure. Among the four identified research clusters, two dominant streams emerge as the primary drivers of the field. The first is a “motor theme” focused on lithium-ion battery reliability and thermal runaway, while the second is a “basic theme” focused on hydrogen dispersion and toxicity risks. The analysis exposes a blind spot regarding the lack of cross-modal research addressing the physical safety interactions between different fuel systems operating in the shared infrastructure. Finally, this study proposes a future research agenda focusing on gathering real-world accident data and using system-theoretic approaches to manage integrated alternative fuel risks. Full article

Fe-Ni-based alloys have attracted attention due to their potential for applications such as transmission line de-icing, where the core requirements include a Curie temperature near the freezing point and sufficient saturation magnetization. Accordingly, this study designed an Fe-29Ni-2Cr-1.5Mn (at.%) alloy with a Curie temperature around the freezing point, aiming to investigate the correlation between microstructural evolution and magnetic properties after cold rolling and annealing. The alloy was cold-rolled by 65% and subsequently annealed at 873 K for 0 to 60 min. The study reveals systematic evolutions in the alloy’s microstructure and magnetic properties. During the initial annealing stage, recovery substructures predominantly formed within the deformed grains, accompanied by a reduction in dislocation density and lattice constant. In the later annealing stage, the recrystallized fraction increased, although complete recrystallization was not achieved. Texture analysis indicates that the intensity of the Cube texture strengthened from 0.48 to 1.13. Correspondingly, the saturation magnetization and Curie temperature increased by approximately 9.76% and 10.25%, respectively, in the early annealing period, and then stabilized thereafter. The early-stage improvement in properties is likely related to stress relief and lattice distortion relaxation during the recovery stage. The calculated magnetocrystalline anisotropy constant of this alloy at 273 K is K₁ = 126 ± 18 J/m³, indicating that the <100> direction is its easy magnetization axis. This study provides insights into optimizing the magnetic properties of this alloy through controlled annealing. Full article

The sustainable valorization of lignocellulosic biomass offers a promising route for developing low-cost photothermal materials for solar water purification. This study investigates natural fibers from Opuntia ficus-indica, Agave sisalana, and cellulose sponge, which were chemically purified through alkaline–peroxide pretreatment and subsequently functionalized with biochar via immersion and crosslinking-assisted deposition. Structural analyses (SEM, FTIR, XRD, CHNS/O) confirmed the transition from heterogeneous lignocellulosic matrices to cellulose-rich scaffolds and finally to hierarchical composites in which crystalline cellulose cores are coated with amorphous carbon structures containing aromatic domains typically formed during biomass carbonization. The NaOH/urea/citric acid crosslinking system significantly improved biochar adhesion, producing uniform and mechanically stable photothermal layers. Under 500 W m⁻² illumination, the biochar-modified fibers exhibited rapid thermal response and enhanced surface heating, resulting in increased water evaporation rates, with cellulose sponge achieving the highest performance (1.12–1.25 kg m⁻² h⁻¹). Water-quality analysis of the condensate showed >97% TDS removal, complete rejection of hardness, fluoride, nitrates, arsenic, and barium, and turbidity <0.2 NTU, meeting NOM-127-SSA1-2021 standards. Overall, the findings demonstrate that biochar-functionalized natural fibers constitute a scalable, environmentally benign strategy for efficient solar-driven purification, supporting their potential for sustainable clean-water technologies in resource-limited settings. Full article

Polylactic acid (PLA) is a promising biodegradable polymer whose widespread application is hindered by inherent brittleness. Polyethylene glycol (PEG) is a common plasticizer, but the effects of intermediate molecular weights, such as 4000 g/mol, on the coupled thermal, mechanical, and rheological properties of PLA remain insufficiently understood. This study presents a comprehensive analysis of PLA plasticized with 0–20 wt% PEG 4000, employing differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and rheology. DSC confirmed excellent miscibility and a significant glass transition temperature (T_g) depression exceeding 19 °C for the highest concentration. A complex, non-monotonic evolution of crystallinity was observed, associated with the formation of different crystalline forms (α′ and α). Critically, DMA revealed that the material’s thermo-mechanical response is dominated by its thermal history: while the plasticizing effect is masked in highly crystalline, as-cast films, it is unequivocally demonstrated in quenched amorphous samples. The core finding emerges from a targeted rheological investigation. An anomalous increase in melt viscosity and elasticity at intermediate PEG concentrations (5–15 wt%), observed at 180 °C, was systematically shown to vanish at 190 °C and in amorphous samples. This proves that the anomaly stems from residual crystalline domains (α′ precursors) persisting near the melting point, not from a transient molecular network. These results establish that PEG 4000 is a highly effective PLA plasticizer whose impact is profoundly mediated by processing-induced crystallinity. This work provides essential guidelines for tailoring PLA properties by controlling thermal history to optimize flexibility and processability for advanced applications, specifically in melt-processing for flexible packaging. Full article

In recent years, the rapid development of commercial satellite projects, such as low-Earth orbit (LEO) communication and remote sensing constellations, has driven the satellite industry toward low-cost, rapid development, and large-scale deployment. Commercial off-the-shelf (COTS) components have been widely adopted across various commercial satellite platforms due to their advantages of low cost, high performance, and plug-and-play availability. However, the space environment is complex and hostile. COTS components were not originally designed for such conditions, and they often lack systematically flight-verified protective frameworks, making their reliability issues a core bottleneck limiting their extensive application in critical missions. This paper focuses on COTS solid-state drives (SSDs) onboard the Jilin-1 KF satellite and presents a full-lifecycle reliability practice covering component selection, system design, on-orbit operation, and failure feedback. The core contribution lies in proposing a full-lifecycle methodology that integrates proactive design—including multi-module redundancy architecture and targeted environmental stress screening—with on-orbit data monitoring and failure cause analysis. Through fault tree analysis, on-orbit data mining, and statistical analysis, it was found that SSD failures show a significant correlation with high-energy particle radiation in the South Atlantic Anomaly region. Building on this key spatial correlation, the on-orbit failure mode was successfully reproduced via proton irradiation experiments, confirming the mechanism of radiation-induced SSD damage and providing a basis for subsequent model development and management decisions. The study demonstrates that although individual COTS SSDs exhibit a certain failure rate, reasonable design, protection, and testing can enhance the on-orbit survivability of storage systems using COTS components. More broadly, by providing a validated closed-loop paradigm—encompassing design, flight verification and feedback, and iterative improvement—we enable the reliable use of COTS components in future cost-sensitive, high-performance satellite missions, adopting system-level solutions to balance cost and reliability without being confined to expensive radiation-hardened products. Full article

Geothermal energy is a crucial component of climate adaptation and sustainability transitions, as it provides a dependable, low-carbon source of baseload power that can accelerate sustainable energy transitions and enhance climate resilience. Yet, in East Africa—one of the world’s most promising geothermal regions, with the East African Rift—a unique climate-energy opportunity zone—the harnessing of geothermal power remains slow and uneven. This study examines the contextual conditions that facilitate the successful and sustainable development of geothermal power in the region. Drawing on semi-structured interviews with 17 experienced professionals who have worked extensively on geothermal projects across East Africa, the analysis identifies how technical, institutional, managerial, and relational circumstances interact to shape outcomes. The findings indicate an interdependent configuration of success conditions, with structural, institutional, managerial, and meta-conditions jointly influencing project trajectories rather than operating in isolation. The most frequently emphasised enablers were resource confirmation and technical design, leadership and team competence, long-term stakeholder commitment, professional project management and control, and collaboration across institutions and communities. A co-occurrence analysis reinforces these insights by showing strong patterns of overlap between core domains—particularly between structural and managerial factors and between managerial and meta-conditions, highlighting the mediating role of managerial capability in translating contextual conditions into operational performance. Together, these interrelated circumstances form a system in which structural and institutional foundations create the enabling context, managerial capabilities operationalise this context under uncertainty, and meta-conditions sustain cooperation, learning, and adaptation over time. The study contributes to sustainability research by providing a context-sensitive interpretation of how project success conditions manifest in geothermal development under climate transition pressures, and it offers practical guidance for policymakers and partners working to advance SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action) in Africa. Full article

Reproductive performance in livestock and poultry is a core determinant of economic efficiency in the animal industry. While traditional research has primarily focused on genetics, endocrinology, and immune regulation, emerging microbiome studies reveal that commensal microbiota within the gut and reproductive tracts play an underestimated yet pivotal role in host reproductive health. This review systematically synthesizes recent advances regarding the relationship between the microbiome and reproductive functions in major livestock species (cattle, pigs, sheep, and chickens). We first delineate the theoretical basis and mechanisms of the “gut-reproductive axis,” highlighting cross-system communication mediated by microbial metabolites, including short-chain fatty acids (SCFAs), indoles, and bile acids. Subsequently, we provide an in-depth comparative analysis of the microecological features of both female (vagina/uterus) and male (semen/epididymis) reproductive systems, examining their impacts on fertility, sperm quality, and pregnancy outcomes. Furthermore, we explore the molecular and systemic mechanisms governing microbial regulation of reproduction, encompassing the modulation of the hypothalamic-pituitary-gonadal (HPG) axis, the balance of local mucosal immunity and inflammation, and epigenetic regulation. Finally, we address current challenges—such as causal validation and the scarcity of multi-species databases—and propose future directions, including spatial multi-omics, AI-integrated analysis, and microbial intervention strategies. Ultimately, this review aims to offer a theoretical foundation and translational insights for elucidating reproductive regulatory networks and developing microbiome-driven precision strategies to enhance reproductive performance. Full article

Measuring the spray parameters and providing feedback on the quality of the spraying is critical to ensuring that the spraying material reaches to the appropriate region. A novel software entitled DropSense was developed to determine spray parameters quickly and accurately compared to DepositScan, ImageJ 1.54d and Image-Pro 10 software. Water-sensitive papers (WSP) were used to determine spray parameters such as deposit coverage, total deposits counted, D_V10, D_V50, D_V90, density, deposit area and relative span values. Upon execution of the developed software, these parameters were displayed on the computer screen and then saved in an Excel spreadsheet file at the end of the image analysis. A conveyor belt system with three different belt speeds (4, 5 and 6 km h⁻¹) and four nozzle types (AI11002, TXR8002, XR11002, TTJ6011002) were used for carrying out the spray experiments. The novel software was developed in the LabVIEW programming language. Compared WSP image results related to the mentioned spray parameters were statistically evaluated. The results showed that the DropSense software had superior speed and ease of use in comparison to the other software for the image analysis of WSPs. The novel software showed mostly similar or more reliable performance compared to the existing software. The core technical innovation of DropSense lay in its integration of advanced morphological operations, which enable the accurate separation and quantification of overlapping droplet stains on WSPs. In addition, it performed fully automated processing of WSP images and significantly reduced analysis time compared to commonly used WSP image analysis software. Full article

Background: Type 2 diabetes mellitus (T2DM) and periodontitis are highly prevalent immune-inflammatory diseases that interact bidirectionally. However, how early-onset T2DM, periodontitis, and adverse lifestyle behaviors collectively remodel the gingival plaque microbiome at the ecological network level remains poorly understood in Indian populations. Methods: A cross-sectional 16S rRNA gene (V3–V4) sequencing study was conducted on supragingival and subgingival plaque from 60 adults (30–40 years) recruited in Mumbai. Participants were categorized as healthy (H, n = 10), periodontitis (P, n = 10), T2DM (n = 20), and T2DM with periodontitis (T2DM_P, n = 20). Comprehensive demographic, anthropometric, metabolic, periodontal, dietary, lifestyle, and oral hygiene data were collected. Sequence data were processed using QIIME2–DADA2, followed by diversity, differential abundance, and genus-level co-occurrence network analyses (Spearman |r| ≥ 0.6, FDR < 0.05; core prevalence ≥ 70%). Results: α-diversity showed no marked depletion across groups, whereas Bray–Curtis β-diversity revealed significant global separation, with maximal dissimilarity between H and T2DM_P. Healthy individuals with favorable lifestyle behaviors harbored scaffold-forming taxa such as Corynebacterium matruchotii, Lautropia mirabilis, and Capnocytophaga spp. In contrast, P and T2DM_P groups showed enrichment of proteolytic, inflammation-adapted genera including Porphyromonas, Tannerella, Treponema, Fretibacterium, Peptostreptococcus, and Selenomonas. Network analysis revealed a shift from commensal-rich modular networks to densely connected, keystone-centered disease modules. Conclusion: Early-onset T2DM and periodontitis, particularly under adverse lifestyle behaviors, reorganize plaque microbial composition and interaction architecture rather than depleting diversity, highlighting plaque-based keystone taxa and networks as targets for microbiome-informed risk stratification and integrated medical–dental–lifestyle interventions. Full article