Search Results (11,261)

Accurate runoff forecasting is essential for effective water resource management, hydropower operation, and flood risk mitigation. In this study, daily inflow runoff in the Xin’an River Basin, eastern China, was simulated using four ensemble learning models: Gradient Boosting Decision Tree (GBDT), XGBoost, CatBoost, and Stacking. Among them, the CatBoost model achieved the best performance, with a correlation coefficient (CC) exceeding 0.97, Nash–Sutcliffe efficiency (NSE) above 0.95, and reduced RMSE and MAE compared with the currently operational hydrological model. To extend the forecast lead times, two hydro–meteorological coupled models were developed by integrating the CatBoost model with a single numerical weather prediction model (EC) and a dynamically weighted multi-model ensemble precipitation forecast system (OCF). The coupled models were evaluated for lead times up to 240 h. The forecast skill value was highest within 96 h, with CC values above 0.80 and NSE around 0.50. The OCF-coupled model demonstrated improved reliability for lead times of 48–96 h, whereas the EC-driven forecasts performed better within the first 48 h. Case studies during the 2021–2022 flood seasons confirmed that the coupled framework accurately reproduced flood evolution and peak discharge dynamics, demonstrating its practical value for medium-range runoff forecasting in humid river basins. Full article

Like most of the North Atlantic marine coastal area, the seawater temperature in the English Channel (EC) is showing an increase that began in the middle of the 1980s. Similarly, during the same period, there has been an increase in human activities (extraction of aggregates, harbour sediment dredging and spoil disposal, Offshore Wind Farms). This point of view examines and analyses the changes in biodiversity of benthic species and communities from the EC under climatic and anthropogenic pressures during the four last decades. Four main changes have been recorded: (1) additions to the checklist of benthic species, due to new prospections; (2) changes in the structure of benthic communities, due to human activities; (3) an increase in diversity due to the arrival of non-indigenous species, some of which have effects on the structure of benthic communities; and (4) eastward progression of temperate species, while some boreal species tend to disappear. Situated in temperate mid-latitudes bordering the North-eastern Atlantic, the EC is an excellent open laboratory to observe and understand the impact of climatic change and human activities on marine coastal ecosystems. Today, the increase in seawater temperature and the introduction of non-native species appear to be the main factors that explain the changes in benthic diversity in the EC. Full article

To investigate the effect of phenolic hydroxyl group number on the interaction between catechins and a plant-derived protein carrier, four catechins with varying hydroxyl numbers—epicatechin (EC), epicatechin gallate (ECG), epigallocatechin (EGC), and epigallocatechin gallate (EGCG)—were investigated. The new plant-derived edible dock protein (EDP) was selected as a carrier matrix. EDP, when employed as a protein delivery carrier, possessed a hydrophobic amino acid content of 45%. This structural feature enabled it to provide more hydrophobic cavities for small molecule compounds, thereby facilitating better binding with them. The results indicated that the order of loading capacity of catechins within EDP was EGCG (9.7%) > ECG (9.1%) > EGC (8.8%) > EC (7.1%). This sequence was consistent with the number of hydroxyl groups in catechin: EGCG (8) > ECG (7) > EGC (6) > EC (5). Among the four catechins, EGCG had the highest binding constant (Ka = 2.6 × 10³ L/mol), leading to the largest quenching of EDP. During self-assembly, hydrogen bonding, hydrophobic and electrostatic interactions were the main driving forces, and the interaction between EGCG and EDP was the strongest. This study indicated that the hydroxyl group number of polyphenolic compounds can determine its binding affinity with proteins. Full article

Energy Communities (ECs) have emerged as a key instrument for promoting local renewable energy integration and citizen participation in the energy transition. While their economic performance largely depends on the ability to generate savings through self-consumption and internal energy trading, their long-term viability is strongly influenced by how these savings are distributed among heterogeneous participants. Despite extensive literature on cost allocation methods, there remains a lack of integrated, data-driven approaches that clearly disentangle the sources of savings in ECs and examine how different allocation methods perform under realistic operating conditions. This paper presents a simulation-based analytical framework to quantify the economic savings generated within Energy Communities and to analyse how a set of widely used cost allocation methods distribute these savings among participants. The approach explicitly separates savings due to renewable self-consumption from those arising from internal trading in a Local Energy Market and explores allocation outcomes across a broad range of community configurations. Extensive simulations based on both synthetic and real-world consumption and price data are used to examine community-level savings, individual outcomes, surplus distribution patterns between Net Consumers and Net Producers, and computational tractability. The results show that internal energy trading consistently increases community-level savings, although its contribution is typically modest relative to self-consumption and strongly dependent on contextual factors such as renewable penetration, demand heterogeneity, and price conditions. The analysis highlights important trade-offs between savings generation, surplus distribution, and computational feasibility, underscoring the relevance of context-aware selection of allocation mechanisms. Overall, the proposed approach provides a transparent and reproducible tool for analysing the economic performance of Energy Communities under practical constraints. Full article

Deep learning has become a key approach for automated sea ice mapping in the AI4Arctic Sea Ice Challenge dataset, yet most studies focus on accuracy metrics and rarely evaluate whether predicted probabilities are reliable for operational use. This paper investigates calibration-aware training for multi-task sea ice segmentation of sea ice concentration (SIC), stage of development (SOD), and floe size (FLOE) using the U-Net model. We train the network with cross-entropy (CE) and augment the objective with focal loss, Brier loss, and an entropy-regularization term to reduce overconfidence and improve calibration. Experiments follow a scene-level Monte Carlo cross-validation protocol on the ready-to-train AI4Arctic Sea Ice Challenge dataset (AI4Arctic) dataset and are evaluated using $R^2$ for SIC, F1 for SOD and FLOE, a weighted combined score, and expected calibration error (ECE) and reliability diagrams. Results show that calibration-aware loss functions improve test performance relative to the CE loss, and the full objective (CE + Brier + focal + entropy) achieves the highest combined score of $84.73\%$ and reduces FLOE ECE to 0.044. Qualitative comparisons further indicate cleaner spatial structures and fewer scattered errors, particularly for FLOE. Overall, the proposed loss design improves both segmentation quality and confidence reliability, supporting more trustworthy sea ice products for decision-making. Full article

Background: The emergence of carbapenem-resistant enterobacteriaceae (CRE) co-harboring the mcr-1.1 gene and carbapenemase-encoding genes poses a severe threat to public health. Urban wastewater treatment plants (WWTPs) act as natural reservoirs and hotspots for the dissemination of antimicrobial resistance genes (ARGs). This study aimed to elucidate the molecular characteristics of CRE carrying mcr-1.1 in urban WWTPs. Methods: Samples were collected from the influent of urban WWTPs in Fengxian, Shanghai, from April 2024 to March 2025. mcr-1.1-positive Escherichia coli (E. coli) isolates were screened using real-time PCR, and their antimicrobial susceptibility was determined via the broth microdilution method. Plasmid conjugation assays were performed with E. coli C600 as the recipient strain. Whole-genome sequencing (WGS) was carried out to analyze the molecular characteristics of mcr-1.1-positive E. coli isolates. Results: A total of 312 samples were collected, and 5 (1.6%) mcr-1.1-positive E. coli isolates were identified. All isolates were multidrug-resistant (MDR) but susceptible to tigecycline (TIG). WGS of strain EC0176 (sequence type 156 [ST156], enteroaggregative E. coli [EAEC]) detected the presence of bla_NDM-5, bla_TEM-1, bla_CTX-M-55, and mcr-1.1 as well as related virulence genes. Further analysis revealed that pEC0176 was an IncHI2-type plasmid co-harboring mcr-1.1, bla_NDM-5, arr-3, aph(4)-Ia, aph(3′)-Ia, aac(3)-IVa, and mph(A). The plasmid pEC0176 harbored similar backbones as p20014-MCR, p2017.03.02CC_1, pSC2017167-mcr-256k, pEC17CM13_MCR and pGDE043-mcr1, including the type IV secretion system (T4SS) and IncHI-type conjugal transfer genes. Conjugation experiments confirmed that pEC0176 could be horizontally transferred into E. coli C600, with an average transfer efficiency of 3.3 × 10⁻². Phylogenetic analysis showed that the MCR-1 protein of EC0176 is closely related to that of two human-derived E. coli strains from China (GenBank accession: AVR64822.1 and WP_076611062.1). Conclusions: To our knowledge, this is the first report of E. coli ST156 carrying an IncHI2-type plasmid co-harboring mcr-1.1 and bla_NDM-5 from urban WWTPs in Fengxian, Shanghai. Our findings underscore the severe status of bacterial antimicrobial resistance and emphasize the necessity of enhancing antimicrobial resistance surveillance in urban WWTPs. Full article

Phosphogypsum (PG) has the potential to elevate phosphorus levels in compost; however, it may also retard the composting maturation process, and its underlying mechanism for phosphorus activation remains unclear. In this study, sawdust was mixed with pig manure or chicken manure at a ratio of 1:4 (m:m, fresh weight) and added 10% PG as the treatment group, and added no PG as control treatment. The entire composting process lasts for 60 days. During the composting process, temperature was monitored daily, pH, electrical conductivity (EC), germination index (GI), phosphorus and its distribution were measured to monitor the composting process, and bacterial communities and predict phosphate-solubilizing genes and bacteria through the KEGG database. Pearson correlation analysis between phosphate-solubilizing bacteria and phosphorus components was conducted. The results demonstrated that (1) PG supplementation delayed the temperature rise and humification during composting, yet the final compost maturity was maintained (GI ≈ 90%). (2) PG addition increased the abundance of the ppx-gppa and phoR genes in pig manure compost, while enhancing the phnE and phoP genes in chicken manure compost. (3) In pig manure composting, Dietzia and Clostridium sensu stricto_1 were identified as key bacteria responsible for phosphorus activation, and promoting their growth favored phosphorus mobilization. (4) In chicken manure compost, Lactobacillus and Pseudomonas played crucial roles in phosphorus activation, though inhibiting their growth was found to enhance phosphorus availability. Overall, PG addition promoted phosphorus activation in compost, significantly increasing the NaHCO₃-P content in both pig manure and chicken manure composts (by 9.36 and 17.86 percentage points, respectively). Full article

In recent years, microplastics (MPs) pollution in agricultural soils has increased markedly, largely due to the improper management of plastic mulch films used to improve crop growing conditions. In this context, the present study evaluated the use of biochar (BC) as a soil amendment for mulch-derived MPs-contaminated soils in a radish (Raphanus sativus L.) crop under greenhouse conditions. A pot experiment was established in soils contaminated with MPs (0.5% w/w) and amended with four BC rates (w/w): 0% (Control), 1% (BC1), 3% (BC3), and 5% (BC5). Soil physicochemical indicators were assessed, together with germination, leaf, and radish bulb growth parameters. The experiment was conducted under greenhouse conditions until the radishes reached commercial maturity. Most of the soil’s physicochemical indicators, such as hydrogen potential (pH), electrical conductivity (EC), water holding capacity (WHC), total organic carbon (TOC), organic matter (OM), total nitrogen (TN), ammonium (N–NH₄⁺) and nitrates (N–NO₃⁻), showed significant differences between treatments (p < 0.05), with the exception of the carbon-nitrogen ratio (C/N), which did not vary significantly (p ≥ 0.05). No significant differences were observed among treatments (p ≥ 0.05) for germination indicators. For leaf traits, dry biomass was significantly lower in BC1 than in the other treatments (p < 0.05). For radish bulb traits, fresh weight was significantly higher in BC3 (p < 0.05) compared with the other treatments. Similarly, total plant fresh weight showed significant differences among treatments, with BC3 exhibiting the highest value (p < 0.05). Overall, the BC3 treatment provided the greatest improvement in radish development in MPs-contaminated soil. However, further research involving different types of MPs, BCs, or other crop species is needed to more comprehensively assess the impact of BC on agricultural soils contaminated with MPs. Full article

Mass timber elements such as glued laminated timber (Glulam) and cross-laminated timber (CLT) have become increasingly prominent in sustainable construction due to their structural efficiency and reduced environmental impact. However, fire performance remains a critical consideration for structural safety. This paper presents a comparative assessment of experimentally measured and code-predicted fire performance parameters for Glulam and CLT, including charring rate, effective charring depth, zero-strength layer (ZSL) thickness, and residual mechanical properties. The evaluation covers major international fire design standards: Eurocode 5 (EC5), the Australian Standard (AS/NZS 1720.4), the Swedish Handbook (Swedish), American Wood Council (AWC TR10), and the Canadian Standard (CSA O86). Across all Glulam datasets, charring rate predictions agreed with tests within approximately ±20%, while AS/NZS 1720.4 consistently over predicted charring and effective char depth by around 40%. In contrast, CLT demonstrates greater variability, primarily due to adhesive degradation, delamination, and lamella orientation, which influence heat transfer and post-fire capacity. CLT data exhibited higher scatter, with effective charring depth showing standard deviations of approximately 30 to 40%, ZSL thickness averaging about 2.5 times the typical 7 mm assumption, and residual stiffness commonly reducing to around 20 to 25% of initial values after standard fire exposure. Overall, findings suggest that current standards adequately address Glulam performance but require refinement to capture the complex fire response of CLT. Continued experimental research and targeted code development, particularly within the Australian Standard, are essential to improve reliability and confidence in performance-based fire design for mass timber structures. Full article

Background/Objectives: The discovery of antimalarial compounds with novel mechanisms of action and distinct rates of kill (RoK) is essential to address emerging drug resistance in Plasmodium falciparum. Natural product libraries represent a valuable and chemically diverse source of potential new antiplasmodial scaffolds. This study aimed (i) to evaluate a modified bioluminescence relative rate-of-kill (mBRRoK) assay as a rapid triage platform for screening large compound libraries with previously unknown antiplasmodial activity, enabling simultaneous assessment of potency and RoK, and (ii) to identify novel compounds with potent and selective in vitro erythrocytic activity. Methods: A fixed two-concentration mBRRoK screen was applied to 1165 compounds from the PhytoQuest natural product library. Antiplasmodial activity and RoK profiles were assessed over 48 h using two genetically distinct luciferase-expressing P. falciparum strains (Dd2^luc and NF54^luc) with distinct drug resistance backgrounds. Reproducibility was evaluated across biological replicates. Selected hits underwent secondary profiling, including EC₅₀ determination and HepG2 cytotoxicity assessment to establish potency and selectivity. Results: The primary screen identified 36 lead compounds demonstrating potent activity within 48 h, encompassing both fast- and slow-acting phenotypes. Activity was reproducible and largely strain-independent across both parasite lines. Secondary profiling prioritised four compounds (100657, 101158, 101160, and 101173) with nanomolar-to-micromolar antiplasmodial potency and favourable selectivity indices relative to mammalian cell cytotoxicity. Conclusions: The mBRRoK assay provides a robust and scalable framework for integrating potency and pharmacodynamic assessment in early antimalarial discovery. This strategy enabled efficient prioritisation of selective natural product-derived leads with distinct killing profiles, supporting their progression toward further optimisation and preclinical development. Full article

With the proliferation of Internet of Things (IoT) deployments and mobile sensing systems, reversible data hiding in encrypted images (RDHEI) has emerged as a cornerstone technology for secure cloud-based sensor data management. RDHEI ensures data confidentiality while enabling bit-to-bit restoration of original visual assets. However, conventional RDHEI methods often struggle to optimize the trade-off between high embedding capacity (EC) and the fidelity requirements of sensor-acquired content. This paper proposes an advanced RDHEI framework based on Adaptive Predicted Value Computation and Pixel Classification (APVCPC). The core contribution is a context-aware prediction engine that adaptively selects optimal estimation functions based on local texture complexity, significantly enhancing prediction accuracy in heterogeneous image regions. Subsequently, a content-driven pixel classification paradigm categorizes pixels into loadable (Lpxls) and non-loadable (NLpxls) sets using a dynamic threshold, maximizing the utilization of spatial redundancy. The proposed scheme further supports separable data extraction and image decryption, providing flexible access control for diverse user privileges in secure sensing scenarios. Experimental results on standard benchmarks and the BOW-2 database demonstrate that APVCPC achieves a superior average embedding rate exceeding 2.0 bpp and ensures perfect reversibility, significantly outperforming state-of-the-art techniques in terms of both capacity and security. Full article

Background: Metastatic melanoma is an extremely aggressive malignancy with limited therapeutic options, despite advances in targeted and immunotherapy. MicroRNAs are key post-transcriptional regulators of gene expression and play a critical role in tumor adaptation, invasion, and metastasis. The aim of our study was to identify dysregulated miRNAs which may serve as novel biomarkers and therapeutic targets. Materials and Methods: The study was conducted on FFPE samples from metastatic melanoma (n = 15), compared to healthy skin tissue (n = 6). BRAF V600E/Ec mutation status was established by Real-Time qPCR. Expression miRNA analysis was performed, using digital counting of 827 miRNAs on the NanoString platform, with data normalization and fold change calculations. Results: Following normalization and quality control metrics, 58 differentially expressed miRNAs were identified in BRAFwt melanoma samples: 6 overexpressed and 52 inderexpressed miRNAs. In BRAFmut melanoma, 37 microRNAs were differentially expressed: 11 overexpressed and 26 underexpressed. Four miRNAs showed elevated expression in both melanoma groups. Among them, miR-146a-5p and miR-4286 demonstrated the highest elevation, especially in BRAFmut tumors. We focused further on their targeted genes. Conclusion: This study demonstrates significant alterations in the miRNA expression profile in metastatic melanoma and highlights the potential of miR-146a-5p and miR-4286 as key regulators of tumor biology. Full article

Background: Cardiovascular diseases (CVDs) are the leading global cause of mortality, with vascular calcification (VC) as a major predictor of adverse outcomes. Although vascular smooth muscle cells (VSMCs) are established contributors, the role of endothelial cells (ECs), particularly via the endothelial–mesenchymal transition (EndMT) and exosome signaling, remains less defined. Objective: This study investigated whether the gut microbiota-derived metabolite Trimethylamine-N-oxide (TMAO) induces EndMT in ECs and whether exosomes from TMAO-treated ECs regulate the VSMC phenotype and calcification. Methods: Human umbilical vein endothelial cells (HUVECs) were exposed to TMAO at physiological and pathological levels (10–50 µM). EndMT markers were analyzed by Western blotting and qPCR. Exosomes were isolated, characterized, and applied to HAVSMCs in graded doses. Osteogenic and contractile markers, β-catenin signaling, and calcification were quantified. Exosomal miR-30 and miR-222 were studied. Results: TMAO triggered dose-dependent EndMT, decreasing CD31/VE-cadherin and increasing α-SMA, N-cadherin, and vimentin. Exosomes from TMAO-treated ECs reprogrammed VSMCs, downregulating contractile proteins and upregulating RUNX2, OPN, TNAP, and β-catenin, causing calcium accumulation. These exosomes displayed elevated miR-222 and reduced miR-30, changes that activated β-catenin signaling and promoted the osteogenic reprogramming of VSMCs. Conclusions: Pathophysiological TMAO levels induce EndMT and mediate the formation of exosomes, which drive the osteogenic reprogramming and calcification of VSMCs. Full article

Keishikaryukotsuboreito (KKT) is a Kampo formula prescribed for neuropsychiatric symptoms, whereas Keishito (KT), despite including most of the constituent herbs, is not indicated for such conditions, suggesting distinct biological actions. We examined whether KT and KKT modulate nerve growth factor (NGF)-induced neurite outgrowth in PC12 cells. Cells were stimulated with NGF in the presence or absence of KT or KKT, and neurite extension was quantified. The involvement of NGF receptor signaling was assessed using the Trk inhibitor K-252a. KKT, but not KT, enhanced NGF-induced neurite outgrowth in a concentration-dependent manner without affecting basal morphology. Pharmacological analysis showed that KKT increased the maximal NGF-induced neurite response (E_max) without altering NGF potency (EC₅₀). K-252a completely abolished NGF-induced neurite extension and KKT-mediated enhancement, indicating that the effect was entirely dependent on NGF–TrkA signaling. These findings demonstrate that KKT selectively augments NGF-elicited neuronal differentiation and suggest translational relevance as a neurotrophic strategy. Full article

The interfacial and functional properties of water-soluble protein (WP) from honeybee pupa are highly sensitive to environmental conditions, which govern its applicability in food systems. This study investigated the effects of pH (3–11), ionic strength (0–1 M NaCl), and sucrose concentration (0–1 M) on the colloidal behavior, surface hydrophobicity, sulfydryl exposure, functional properties, and interfacial characteristics of WP. These findings provide valuable reference data for future processing of bee pupa protein. Acidic conditions (pH 3) resulted in a high surface hydrophobicity (H₀). Conversely, alkaline conditions enhanced protein interfacial activity. Specifically, the foaming capacity (FC) increased significantly with pH, reaching 90.88% at pH 11, which was approximately 2.5 times higher than that at pH 5 (35.10%). Moderate ionic strength (≤0.05 M NaCl) exerted minimal effects on particle size, while high salt levels (≥0.5 M) promoted aggregation via salting-out, increasing H₀ from 219.91 (0 M) to 459 (1 M). Sucrose had little impact on particle size but significantly altered system viscosity. Interfacial measurements confirmed that moderate ionic strength (0.05 M NaCl) combined with sucrose addition (0.05 M) improved protein spreadability, yielding low contact angles of 9.60° and 9.93°, respectively. From the perspective of oil–water interfacial tension, increased pH and moderate sucrose concentrations reduce interfacial tension, promoting protein adsorption, whereas high salt and high sugar concentrations inhibit surfactant activity. Functional property evaluations indicated that alkaline conditions enhance foaming and emulsifying activity. Under conditions near pH 5, both foam and emulsion stability were optimal (foam stability ~99.95%), while the emulsifying capacity (~64.83%) was achieved at pH 11. As ion concentration increases, EC decreases. Sucrose concentration has no significant effect on emulsifying properties. These findings provide a quantitative reference for the tailored processing of honeybee pupa protein as a functional ingredient in food systems. Full article