Search Results (28,436)

Nanoparticle-modified concrete can exhibit improved mechanical performance, yet its residual compressive strength (Fc) after fire-like thermal exposure is difficult to predict because the response depends on both mixture design and heating conditions. Building on recent advances in explainable machine learning (ML) for cementitious materials, this study compiles 218 literature datapoints of post-heating Fc from 100 mm concrete cubes incorporating carbon nanotubes (CNTs) and nano-alumina (NA), exposed to 20–800 °C for up to 2 h. Seven input variables are used: cement-to-total aggregate ratio, CNT-to-cement ratio, NA-to-cement ratio, coarse-to-fine aggregate ratio, water-to-cement ratio, peak temperature, and exposure duration at temperature. Two particle-swarm-optimized ensemble regression models, Extreme Gradient Boosting (XGB-PSO) and Random Forest (RF-PSO), were developed and evaluated using a 70/30 train–test split with K-fold cross-validation on the training set. SHAP, individual conditional expectation (ICE), and partial dependence plots (PDPs) were employed to study the individual and combined effects of each input parameter on Fc prediction. The results demonstrated that the XGB-PSO model provides the best predictive performance (training R² = 0.9983; testing R² = 0.9434; testing MAE = 1.3168 MPa). Model interpretability was assessed using SHAP, ICE, and PDP analyses, revealing that temperature and exposure duration dominate strength loss, while CNTs and NA contribute positively within dose-dependent regimes. The highest predicted strengths occur for CNTs of 0.05% to 0.15% and NA of 0.65 to 2.71% (by cement mass) under moderate temperature exposure. A Python-based graphical user interface is provided to support rapid what-if assessment of CNT–NA mixtures under elevated-temperature scenarios. Full article

Deep learning-powered Street View Imagery (SVI) analytics provides a critical mechanism for smart city perception within the framework of Sustainable Development Goal 11 (SDG 11), effectively bridging the gap left by traditional remote sensing in fine-grained street-level observation. Over the years, deep learning-based semantic segmentation of urban streetscapes has become the dominant paradigm. However, when scaling to megacity measurements, current research faces the dual bottlenecks of “computational redundancy” and the “geographical domain shift” caused by the blind application of pre-trained models based on Western datasets. To address these challenges, this study is the first to systematically quantify the performance trade-off between Multi-Task Learning (MTL) and Single-Task Learning (STL) in megacity scenarios. Using this as a baseline, we constructed and validated a “low-computation, high-robustness” framework for streetscape semantic perception and spatial measurement. Relying on an integrated ResNeXt101-FPN MTL architecture and an ultra-low-cost fine-tuning strategy to overcome geographical domain shift, we extracted and analyzed the spatial heterogeneity of five core semantic elements—vegetation, sky, building, road, and vehicle—across the road network within Beijing’s 5th Ring Road. The results indicate the following: (1) We explicitly defined the computation-accuracy trade-off of MTL and STL in megacity perception. While utilizing only 1/5 of the parameters of STL, the MTL framework achieved a 5.34-fold increase in inference speed with a negligible 0.1% loss in overall mean Intersection over Union (mIoU); however, a 27.13% decrease in boundary segmentation accuracy was observed. (2) We established a low-cost, localized correction paradigm to overcome domain shift. Utilizing a minimal annotation cost (only 200 local images) significantly improved cross-domain adaptability, boosting the overall mIoU by 8.92% and significantly mitigating the geographical domain shift problem. (3) Multi-dimensional measurement and spatial analysis revealed a significant spatial decoupling pattern in Beijing’s streetscapes. The visual proportion of vegetation exhibited a pronounced “north-high, south-low” spatial differentiation, whereas built environment elements (e.g., building and road) displayed a typical “center-periphery” concentric gradient. This objectively reflects the spatial inequality of urban street greenery resources and the monocentric development characteristics of the built environment. The proposed framework therefore serves as a low-cost, AI-driven computational paradigm for smart city perception in resource-constrained regions. Furthermore, the revealed spatial heterogeneity offers data-driven insights for formulating sustainable urban renewal policies aligned with SDG 11. Full article

The optimization of new cropland allocation is crucial for promoting the efficient use of cropland resources and safeguarding food security. However, existing studies primarily take suitability as the optimization objective and lack the consideration of stable utilization potential, which may lead to subsequent unstable use. To address this gap, this study quantified the stable utilization potential of new cropland using a machine learning model and integrated it with the ant colony optimization (ACO) model to develop a spatial allocation framework. This framework was validated in Guangdong Province, China, a region characterized by diverse resource endowments and pronounced regional heterogeneity. The results indicated that, under the specified objective-weighting scheme and compared with the business-as-usual (BAU) scenario, the optimized scenario achieved regional cropland quantity balance. It also increased the average stable utilization potential of new cropland and overall utility by 34.84% and 12.74%, respectively, while reducing the mean cost and mean ecological benefit loss per unit area by 10.22% and 41.36%, respectively. Overall, under the specified constraints, the proposed framework offers a promising approach for new cropland planning and provides a basis for governments and land management authorities to improve future allocation practice. Full article

Vitiligo is a chronic, acquired autoimmune disorder characterized by white skin patches resulting from the loss of epidermal melanocytes. Vitiligo may arise through multiple mechanisms, including genetic susceptibility, oxidative stress, autoimmune dysfunction, and environmental factors. Treatment strategies have focused on inhibiting melanocyte loss and stimulating repigmentation. Mitogen-activated protein kinase (MAPK) pathways regulate various cellular processes, including differentiation, survival, and inflammatory responses. The dysregulated MAPK pathways play distinct roles in the development of vitiligo through a complex interplay of melanogenesis, oxidative stress, and autoimmune responses within different cells, thereby leading to melanocyte damage. Thus, therapeutic targeting of MAPK pathways has the potential to mitigate oxidative stress-induced damage and inhibit the exaggerated autoimmunity, thereby controlling disease progression and supporting repigmentation. This review provides an overview of MAPK signaling across the multicellular network in vitiligo pathogenesis and summarizes agents that may provide new perspectives for therapeutic intervention. Full article

As a high-value horticultural crop, melon cultivation requires substantial labor input for plant architecture management. Dwarf architecture is a desirable trait for melon breeding, as it simplifies plant management and enables higher planting density. In this study, we identified a spontaneous dwarf mutant, HMN-d, derived from a cantalupensis melon HMN. Compared to HMN, HMN-d exhibited a 70% reduction in plant height with unchanged node number. BSA-seq mapped the mutation to a single 1.86 Mb interval on chromosome 7 containing CmER, a known regulator of melon height. A novel loss-of-function allele, Cmer-2, introducing a premature stop codon, was identified in this region of HMN-d. Linkage analysis using 1455 F₂ individuals via KASP marker developed from the Cmer-2 variant revealed complete co-segregation with the dwarf phenotype. Allelism analysis further demonstrated that Cmer-2 is allelic to Cmer-1, a previously identified loss-of-function allele of CmER. CmER knockout lines generated by gene editing recapitulated the dwarf phenotype, directly confirming that loss of CmER function is sufficient to cause dwarfism. Collectively, these findings establish Cmer-2 as the causal variant underlying the dwarf phenotype and provide valuable genetic resources for melon plant architecture improvement and for dissecting the mechanisms of height regulation. Full article

Efficient electricity distribution in rural areas is strongly affected by seasonal agricultural energy demand, particularly in irrigation-intensive regions where electricity consumption increases substantially during summer periods. Conventional transformer operation strategies in such rural grids often fail to adapt to seasonal load variability, leading to unnecessary idle operation, increased technical losses, and reduced infrastructure efficiency. Existing approaches generally rely on static assumptions or simulated data, limiting their ability to represent real irrigation-driven seasonal load asymmetry. To address this issue, this study proposes a data-driven multi-objective seasonal transformer scheduling framework using a bio-inspired Artificial Immune System (AIS) algorithm. The model was developed using two years of empirical hourly SCADA load data and transformer operation records obtained from a real 380/154 kV TEİAŞ transmission substation in Central Anatolia, Türkiye. Hourly SCADA measurements were used for seasonal load characterization and objective-function evaluation, while transformer scheduling decisions were defined at the seasonal operational level. The proposed AIS-based scheduling strategy reduced annual technical energy losses by approximately 5.4 GWh, decreased operational costs by 10.81 million TL (≈360,000 USD), and lowered carbon emissions by about 2270 metric tons of CO₂ compared with conventional static transformer operation. The study presents a proof-of-concept framework integrating empirical SCADA measurements with AIS-assisted seasonal transformer scheduling for practical utility-scale operational planning in irrigation-dominated rural electricity networks. Full article

Plant-parasitic nematodes (PPNs) rank among the most economically destructive soilborne pathogens worldwide, causing annual crop losses estimated at USD 125–175 billion. Traditional management of plant parasitic nematodes has depended significantly on synthetic nematicides; however, increasing regulatory constraints, environmental pollution, and the rise of resistant nematode populations have generated an urgent need for sustainable alternatives. Humic substances (HS), comprising humic acids, fulvic acids, and humins derived primarily from leonardite and lignite, represent biologically active components of soil organic matter. Their different functional groups, like carboxylic, phenolic, and carbonyl groups, have direct nematicidal and nematostatic effects by stopping eggs from hatching, slowing down juvenile development, and lowering infectivity. They also indirectly improve soil structure, nutrient bioavailability, and the composition of the rhizosphere microbiome. Plant growth-promoting rhizobacteria (PGPR), particularly Bacillus spp. and Pseudomonas spp., suppress PPN populations through antibiotic biosynthesis, cuticle-degrading hydrolytic enzymes, nematostatic volatile organic compounds, and elicitation of induced systemic resistance (ISR). This review methodically analyzes the individual and synergistic processes by which HS and PGPR inhibit PPNs and enhance plant growth. Humic compounds strongly promote PGPR rhizosphere colonization, augmenting microbial metabolic activity and bioinoculant stability, hence producing combinatorial suppressive effects unattainable by either input independently. The combined HS-PGPR approach is reliable and environmentally sustainable for comprehensive nematode control, requiring multidisciplinary research to achieve global sustainable agriculture. Full article

Periodontitis is a biofilm-associated inflammatory disease that still requires effective local non-antibiotic antibacterial strategies. In this study, we developed a protonated defect-engineered atomic-layered graphitic carbon nitride nano-system (PVCN) for visible light photodynamic antibacterial therapy. Defect engineering was used to improve visible light absorption and photodynamic activity, while protonation introduced a positively biased surface potential to strengthen bacteria–material interactions and enhance interfacial antibacterial efficacy. Under visible light irradiation, PVCN showed increased ROS production, stronger bacterial adhesion, and rapid killing activity against both Staphylococcus aureus and Escherichia coli, with bactericidal efficiency above 95%. PVCN also disrupted S. aureus biofilms and induced membrane damage, intracellular content leakage, and metabolic suppression. Atomic force microscopy and omics analyses further supported enhanced bacterial adsorption as an important contributor to the improved antibacterial efficacy of PVCN. In vitro assays demonstrated preliminary cytocompatibility and hemocompatibility. In a ligature-induced mouse periodontitis model, PVCN reduced bacterial burden, alleviated inflammation, and attenuated alveolar bone loss. These results support PVCN as a promising photodynamic antibacterial material with preliminary therapeutic potential in experimental periodontitis, and highlight bio-interface regulation as a useful strategy for designing efficient carbon nitride-based photodynamic antibacterial materials. Full article

Background/Objectives: Gastrojejunal–ileal interposition with bipartition and sleeve gastrectomy (GJIB-SG) is a novel metabolic procedure developed to combine functional foregut exclusion with hindgut stimulation while preserving duodenal continuity and endoscopic biliary access. This study evaluated the medium-term glycemic, weight-loss, and nutritional safety outcomes of GJIB-SG in patients with obesity and long-standing type 2 diabetes (T2D). Methods: A retrospective single-center cohort of 30 consecutive patients with obesity and T2D who underwent GJIB-SG between January 2016 and August 2019 and reached at least 60 months of postoperative follow-up was analyzed at baseline and at 12, 24, 36, 48, and 60 months. Longitudinal data were analyzed by repeated-measures ANOVA with Greenhouse–Geisser correction and Bonferroni-adjusted pairwise comparisons. Diabetes remission was classified using the 2021 American Diabetes Association consensus definition (A1C < 6.5%, medication-free). Results: Mean body weight decreased from 102.4 ± 13.6 kg preoperatively to 73.5 ± 7.6 kg at 60 months (p < 0.001; mean %TWL 27.4%, mean %EWL 99.4%). Mean A1C decreased from 9.4 ± 1.6% to 6.0 ± 1.4% at 60 months (p < 0.001). Complete medication-free remission was achieved by 70.0% of patients at 12 months and 44.8% at 60 months; cumulatively, 25 of 30 (83.3%) achieved complete remission at one or more intervals, and 3 patients (10.0%) never achieved A1C < 6.5%. Triglycerides, total cholesterol, and LDL cholesterol decreased by 56%, 39%, and 35%, respectively. No protein–energy malnutrition or hypoalbuminemia occurred; however, a late rise in parathyroid hormone and a return of 25-OH vitamin D toward preoperative insufficient values by 60 months indicate the need for sustained micronutrient surveillance. One cardiovascular death at 24 months was not considered procedure related. Conclusions: In this single-center cohort, GJIB-SG was associated with durable weight loss, sustained glycemic improvement with cumulative complete remission in 83.3% of patients, and absence of severe nutritional complications over 60 months. Prospective comparative studies with longitudinal mixed-effects analysis are warranted to define the role of GJIB-SG within the metabolic–surgical armamentarium. Full article

Natural ecosystems are facing threats from natural and anthropogenic stressors. Wetlands are among the most delicate natural ecosystems and are particularly vulnerable to the impacts of urbanization. One of the intended purposes of the wetlands is to mitigate the impact of urbanization (e.g., stormwater), but we often lack a comprehensive understanding of their capacity in doing so. Determination of water balance is essential in understanding the efficacy of a wetland when it comes to treating excess stormwater. This study therefore considers the Sparrovale Wetland in Victoria, Australia, to assess its performance in mitigating the impacts of urbanization in the surrounding catchment areas. A 1D model (HYDRUS-1D) was previously developed by the authors based on extensive field and laboratory measurements on one side (north) of the wetland. It was crucial to understand the two-dimensional water balance dynamics in the Sparrovale Wetland to utilize its full potential for managing excessive stormwater. This study therefore employed the HYDRUS-2D model (based on HYDRUS-1D) supported by extended, spatially explicit in situ measurements. The model was run (with additional input of inflow added to the rainfall) on the average Van Genuchten parameters obtained from the previously developed HYDRUS-1D model and the extended determination of the parameters. The model performance in simulating measured water content was good for both the south (average RMSE = 0.013 m³/m³) and the north side (average RMSE = 0.028 m³/m³). The model was also used to simulate surface water levels in the wetland and showed a good agreement (RMSE = 0.1 m AHD and R² = 0.72) with in situ surface water level measurements. This developed model was used to determine the water balance dynamics (infiltration, evapotranspiration, soil water storage, surface and bottom boundary flux) in the Sparrovale Wetland. Our results indicate that evapotranspiration is the major factor controlling the water flux losses in the Sparrovale Wetland, while the role of infiltration was minimal, which might be attributed to the dominant soil type (clay) and shallow groundwater levels in the Sparrovale Wetland. Insights provided by this study might be helpful in optimizing the performance of the Sparrovale Wetland in managing the excess stormwater arising from the surrounding catchments. Full article

Phytopathogenic bacteria and fungi significantly reduce fruit and vegetable yields, resulting in substantial economic losses. Conventional management relies on synthetic agrochemicals; however, their intensive use poses risks to human health, environmental integrity, and biodiversity. Snake venoms have evolved under selective pressure, developing specialized components with potent antimicrobial properties as part of a defense mechanism against prey-borne microorganisms. This study evaluated the inhibitory potential of Micrurus venoms against pathogens of agricultural interest and developed bioactive gelatin-based films incorporated with purified L-amino acid oxidases (LAAOs) as a novel biocontrol strategy. Venoms from M. ancoralis, M. mipartitus, and M. dumerilii exhibited significant growth inhibition against Xanthomonas and Fusarium strains. The primary active component was identified as LAAO through biological activity and mass spectrometry. Biofilms were formulated by incorporating M. ancoralis venom and its purified LAAO into a gelatin matrix. Physicochemical and microbiological characterization, alongside in situ assays on strawberries, demonstrated that the functionalized biofilms retained potent antimicrobial activity. Furthermore, LAAO incorporation did not significantly alter the physicochemical properties of the fruit but effectively extended shelf life by reducing weight loss and maintaining sensory appearance. These findings highlight the biotechnological potential of elapid venom components in the development of alternatives for phytopathogen control and active food packaging. Full article

Gelatin methacrylate (GelMA) hydrogels are promising carriers for bioactive agents like curcumin (Cur) and adenosine diphosphate (ADP) in wound healing. However, existing GelMA-based systems fail to achieve both rapid hemostasis and sustained anti-inflammatory effects. In this study, we developed a Cur/ADP GelMA hydrogel, and evaluated its anti-inflammatory, regenerative, hemostatic, and biocompatible properties. Proton nuclear magnetic resonance (¹H-NMR) analysis showed that a 65% degree of substitution of GelMA is optimal for wound dressings. Scanning electron microscopy revealed a uniform pore size, aiding inflammatory exudate removal. The Cur/ADP GelMA hydrogel exhibited strong adhesion, stability, and antibacterial activity, reducing E. coli and S. aureus proliferation by 85% and 72%, respectively. Hemostatic effects were observed, with blood loss reduced to 238 ± 23 mg compared to 559 ± 18 mg in the untreated group. The ELISA results showed reduced pro-inflammatory cytokines (TNF-α, IL-1β, IL-6) and increased IL-10. In vivo studies demonstrated 98% wound closure by day 14, enhanced granulation tissue formation, and a 70% thicker epidermis compared to controls. Mechanistically, ADP accelerates platelet activation and clot formation, while Cur modulates the inflammatory microenvironment, enabling synergistic hemostasis and immune regulation, thus promoting accelerated wound healing. Full article

Sarcopenia is an age-related syndrome characterized by the progressive loss of skeletal muscle mass, strength, and function, significantly impairing older adults’ independence and quality of life. Given their anti-inflammatory, antioxidant, and metabolic regulatory properties, n-3 polyunsaturated fatty acids (n-3 PUFAs) have emerged as a promising nutritional strategy to mitigate this muscle degeneration. This review systematically synthesizes existing evidence regarding the association between n-3 PUFAs and sarcopenia. To capture the relevant literature, we searched PubMed, Web of Science, CNKI, and Wanfang Data using a combination of subject headings and free-text terms. We supplemented primary search terms—such as “n-3 polyunsaturated fatty acids,” “omega-3 fatty acids,” “sarcopenia,” and “muscle mass”—with mechanism-related keywords like “inflammation,” “muscle satellite cells,” and “oxidative stress.” We also manually screened the reference lists of the included literature. Our inclusion criteria encompassed interventional studies, observational studies, and high-quality reviews, while excluding conference abstracts, duplicate publications, and studies with incomplete data. This review first outlines the established biological mechanisms linking n-3 PUFAs to the pathological progression of sarcopenia, specifically detailing how these fatty acids improve muscle satellite cell function, suppress inflammation and oxidative stress, and ameliorate metabolic disorders. Next, we critically evaluate recent clinical studies and reviews, analyzing sources of study heterogeneity such as variations in sample size, intervention dose and duration, outcome measures, and baseline participant characteristics. We also highlight current research hotspots—including specialized pro-resolving mediators (SPMs), the gut–organ axis, combined interventions, and precision nutrition strategies—while emphasizing the functional differences between EPA and DHA to guide future intervention designs. Current evidence indicates that while n-3 PUFA supplementation can improve muscle strength and physical performance in older adults, its effects on muscle mass remain inconsistent. Addressing key research gaps, particularly the lack of standardized core outcome measures and unclear dose–response relationships, is critical. Ultimately, future research must prioritize developing high-bioavailability formulations, conducting personalized trials based on baseline n-3 PUFA status, and deepening investigations into inter-organ networks to translate these nutritional insights into effective sarcopenia prevention and management strategies. Full article

Biodiversity, as the foundation of life on Earth, sustains the balance of ecosystems and supports human sustainable development. However, the current accelerated decline in biodiversity poses ecological threats that require urgent attention. This research based on the perspective of ethnic ecological wisdom, explores the customary practices of biological conservation among the Miao ethnic group in Southwest China, the Tao ethnic group on Orchid Island (Lanyu), Taiwan, and the Maasai ethnic group on the East African Plateau. By conducting in-depth case studies, combined with literature review and data validation, it investigates their practical value and implementation pathways in biodiversity conservation. By analyzing the ecological conservation wisdom models of the Miao, Tao and Maasai ethnic groups, it is found that the core species populations in each region have shown a positive growth trend since the gradual integration of traditional ethnic customary laws with modern ecological protection systems and practices. Drawing on the extensive experience accumulated in integrating customary law into ecological governance across the three cases, this study proposes a three-dimensional optimization pathway: at the policy level, construct a mechanism integrating customary law and diversified ecological compensation; at the community level, implement a model featuring benefit sharing, patrol mediation and digital management; and at the cultural level, strengthen the development and dissemination of ethnic ecological conservation wisdom through multidisciplinary talent training and IP-based communication of exemplary customary law outcomes. We aspire to slow the rate of global biodiversity loss and achieve a bright future of harmonious coexistence between humans and nature. Full article

When poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is employed as the hole transport layer in visible/near-infrared photodetectors, the extraction and transport of holes are hindered by the accumulation of the PSS insulating phase at the interface. This accumulation results in an increase in contact resistance and creates a potential barrier for hole injection. This study introduces a self-assembled monolayer, (2-(9H-carbazol-9-yl)ethyl)phosphonic acid (2PACz), to modify PEDOT:PSS, effectively optimizing the interface of the hole transport layer. Such improvements lead to a reduction in recombination losses during charge transfer, a lower dark current, and improved energy level alignment in the device, thereby boosting the performance of visible/near-infrared photodetectors. The fabricated double hole layer photodetector exhibits a low dark current of (1.4 ± 0.6) × 10⁻⁵ A at −1 V bias and a switching ratio of up to 7.62 × 10⁵ at 0 V bias. The device achieves a responsivity of 0.31 A/W and a high specific detection rate of 3.23 × 10¹² Jones at a wavelength of 780 nm, which corresponds to the peak responsivity, showcasing enhanced detection capabilities. In comparison to a reference device based on PEDOT:PSS, the response speed, cutoff frequency, and linear dynamic range of the double hole layer device have been enhanced by 400%, 213%, and 81%, respectively, thereby better aligning with practical application requirements. This research presents a novel approach for the development of high-performance organic visible/near-infrared photodetectors. Full article