Search Results (22,960)

Drought significantly reduces global crop yields and agricultural productivity. This study aims to isolate drought-tolerant PGPR strains and evaluate their effects, both individually and in combination with salicylic acid (SA), on cowpea plants growth, physiological traits, antioxidant enzymes, and mineral content under both drought stress and non-stress conditions. Among fifteen bacterial isolates, AO7, identified as Streptomyces diastaticus subsp. ardesiacus PX459854 through 16S rRNA sequencing, demonstrated significant plant growth promotion in cowpea under gnotobiotic conditions. On the other hand, varying salicylic acid concentrations (0.5, 1.0, and 2.0 mM) was exposed to assess the plant growth of cowpea plants in a gnotobiotic system. A pot experiment in 2023 used a split-plot design with treatments for irrigation (unstressed and stressed) and different soaking treatments (control, S. diastaticus, salicylic acid (2 mM), and a combination). After 60 days, the combination treatment enhanced growth metrics, outpacing the control under stress. The microbial community in the T4 treatment exhibited the highest counts, while T8 (combination, stressed) showed lower counts but the highest chlorophyll content at 6.32 mg g⁻¹ FW. Notable increases in proline and significant changes in enzyme activities (PO, PPO, CAT, and APX) were observed, particularly in treatment T8 under stress, indicating a positive response to both treatments. Mineral content of cowpea leaves varied with soaking treatments of S. diastaticus and SA (2.0%) especially under drought stress which the highest values were 1.72% N, 0.16% P, and 2.66% K with treatment T8. Therefore, T8 (combination, stressed) > T6 (S. diastaticus, stressed) > T7 (salicylic acid, stressed) > T5 (control, stressed) for different applications under stressed conditions and T4 (combination, unstressed) > T2 (S. diastaticus, unstressed) > T3 (salicylic acid, unstressed) > T1 (control, unstressed) for the other applications under normal conditions. Thus, using S. diastaticus and SA (2.0%) in combination greatly enhanced the growth dynamics of cowpea plants under drought stress conditions. Full article

Critical transmission lines frequently traverse geologically complex mountainous regions, where harsh environments and variable climatic conditions pose significant geohazard risks. Utilizing 163 Sentinel-1A scenes (January 2018 to October 2023), we employed Multi-Temporal InSAR (MT-InSAR) to derive the deformation field along the transmission corridor. Time-series analysis of the Lingshao (LS) line towers, interpreted through the principles of mining subsidence, revealed the mechanisms behind their differential tilt. Simultaneously, time-series deformation at the tower footings was input to a deep learning model for 365-day prediction; the accuracy and practical applicability of which were rigorously assessed. The results demonstrate that (1) a unidirectional subsidence funnel within the transmission corridor deformation field, in the absence of zonal settlement features, strongly indicates the presence of a goaf beneath the line; (2) the integrated approach combining time-series InSAR with the settlement trough method proves feasible for monitoring transmission tower tilt, as validated through field verification; (3) the magnitude and direction of tower tilt correlate directly with their position in the mining-induced subsidence basin, showing convergent tilt in tensile zones, divergent tilt in compressive zones, and uniform settlement in neutral zones; (4) for the eight selected typical tower footings, predicted deformation values ranged from −284.6 mm to −186.3 mm, showing excellent agreement with measurements through correlation coefficients of 0.989–0.999 and Root Mean Square Error (RMSE) values of 0.54–2.17 mm. The framework enables proactive hazard avoidance during line routing and provides early warning for tower defects, significantly enhancing power infrastructure resilience in mining-affected regions. Full article

With the global trend towards “carbon neutrality,” the use of electric vehicles is becoming increasingly widespread, leading to new impacts on urban spaces. In the process of allocating resources for urban charging stations, there are widespread issues such as a singular planning approach and inadequate adaptation to actual travel demands. Therefore, this study adopts a method of integrating multi-source data to optimize the planning and layout of public electric vehicle charging facilities in Macau, striving to achieve breakthroughs in theoretical methods and key technologies. The study obtained a determination coefficient of R² = 0.43 through quantitative analysis, which is within a reasonable range of fitting spatial syntax and charging facility layout. This indicates that there is a moderate positive correlation between the distribution of charging facilities and core indicators such as road network integration and accessibility—about 43% of layout differences can be explained by spatial syntax indicators, and the remaining 57% of differences reserve space for optimizing multiple factors such as population density and parking lot distribution. On this basis, this study compares the layout experience of medium to high-density cities such as Hong Kong and Singapore, and combines the common characteristics of old parishes on Macau Island and new urban areas on outlying islands to explore innovative sustainable development technology paths that are suitable for Macau. This study not only summarizes the key factors and optimization breakthroughs that affect the spatial distribution of charging facilities in Macau, providing basic data and methodological strategies for charging facility planning, but also helps Macau save energy and reduce emissions, build a green city through layout optimization, provide practical reference for the development of land reclamation areas, and provide reference for carbon neutrality and smart city construction in the Guangdong Hong Kong Macau Greater Bay Area. Full article

Managing bacterial infections and the spread of microbial resistance is one of the most critical and complex tasks of modern healthcare infrastructures. Antiseptics and disinfectants such as biocides play a significant role in controlling microbial resistance by reducing the microbial load on surfaces, skin, and environments, thereby limiting the opportunity for pathogens to proliferate and develop resistance. Herein, we tested the different interactions of quaternary ammonium compound (QAC)-based biocide compositions in pursuit of a better antimicrobial performance. An extensive microbiological analysis was conducted for 12 selected compositions of various combinations of mono-QACs, bis-QACs, and alcohols on 17 strains of bacteria of the ESKAPEE group and fungi, including 11 clinical highly resistant varieties, highlighting synergistic or additive dynamics. The evaluation showed noticeable improvements in activity, with up to 16-fold MBC and 32-fold MBEC reductions for alcohol-based compositions of lead QAC. Moreover, synergistic interactions were detected and confirmed via an optimized checkerboard assay for pyridinium QAC combinations against planktonic Gram-positive S. aureus with a fractional inhibitory concentration index (FICI) and fractional bactericidal concentration index (FBCI) of 0.39–0.5 and Gram-negative A. baumannii biofilms. The studied biocides demonstrated the long-term preservation of antimicrobial efficiency without resistance development during a 40-day period and do not induce QAC-associated cross-resistance for four commercially available antibiotics with similar mechanisms of action. Full article

As critical ecosystems, coastal zones necessitate the identification of their ecosystem service values, trade-off/synergy patterns, spatiotemporal evolution, and driving factors to inform scientific decision-making for sustainable ecosystem management. This study selected the coastal zone of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the research region. By incorporating land-use types such as mangroves, tidal flats, and aquaculture areas, we analyzed land-use changes in 1990, 2000, 2010, and 2020. The InVEST model was employed to quantify six key ecosystem services (ESs): annual water yield, urban stormwater retention, urban flood risk mitigation, soil conservation, coastal blue carbon storage, and habitat quality, while spatial correlations among them were examined. Furthermore, Spearman’s rank correlation coefficient was used to assess trade-offs and synergies between ecosystem services, and redundancy analysis (RDA) combined with the geographically and temporally weighted regression (GTWR) model were applied to identify driving factors and their spatial heterogeneity. The results indicate that: (1) Cultivated land, forest land, impervious surfaces, and water bodies exhibited the most significant changes over the 30-year period; (2) Synergies predominated among most ecosystem services, whereas habitat quality showed trade-offs with others; (3) Among natural drivers, the normalized difference vegetation index (NDVI, positive effect) and evapotranspiration were critical factors. The proportion of impervious surfaces served as a key land-use change driver, and the nighttime light index emerged as a primary socioeconomic factor (negative effect). The impacts of drivers on ecosystem services displayed notable spatial heterogeneity. These findings provide scientific support for managing the supply-demand balance of coastal ecosystem services, rational land development, and sustainable development. Full article

This article examines augmented plurals in Russian, mostly focusing on those in -ĭj- (e.g., pero/perʲja ‘feather.sg/pl’). The accentual behavior of -ĭj-plurals is sensitive to animacy: while inanimates show stem-final stress, animates appear with inflectional stress. This is explained by different constituent structures: while for inanimates, -ĭj- combines with the stem, animate stems require complex suffix formation so as to not create neuter animates, which are not tolerated in Russian. The position of the accent is then derived from the usual assumptions about Russian stress and the hypothesis that -ĭj- is accented but unaccentable. Other plural augments are also discussed. Full article

This study investigates the Mode II fracture behavior of bamboo–coir–rubber (BCR) hybrid composite panels developed as sustainable alternatives for wood-based panels used in structural applications. The composites were fabricated using alternating bamboo and coir layers within a polypropylene (PP) thermoplastic matrix, with styrene–butadiene rubber (SBR) incorporated as an additive at 0–30 wt.% to enhance interlaminar toughness. Commercial structural plywood was tested as the benchmark. Mode II interlaminar fracture toughness (G_IIc) was evaluated using the ASTM D7905 End-Notched Flexure (ENF) test, supported by optical monitoring to study crack monitoring and Scanning Electron Microscopy (SEM) for microstructural interpretation. Results demonstrated a steady increase in G_IIc from 1.26 kJ/m² for unmodified laminates to a maximum of 1.98 kJ/m² at 30% SBR, representing a 60% improvement over the baseline and nearly double the toughness of plywood (0.7–0.9 kJ/m²). The optimum performance was obtained at 20–25 wt.% SBR, where the laminated retained approximately 85–90% of their initial flexural modulus while exhibiting enhanced energy absorption. Increasing the initial notch ratio (a₀/L) from 0.2 to 0.4 caused a reduction of 20% in G_IIc and a twofold rise in compliance, highlighting the geometric sensitivity of shear fracture to the remaining ligament. Analysis of Variance (ANOVA) confirmed that the increase in G_IIc for the 20–25% SBR laminates relative to plywood and the unmodified composite is significant at p < 0.05. SEM observations revealed rubber-particle cavitation, matrix shear yielding, and coir–fiber bridging as the dominant toughening mechanisms responsible for the transition from abrupt to stable delamination. The measured toughness levels (1.5–2.0 kJ/m²) position the BCR panels within the functional range required for reusable formwork, interior partitions, and transport flooring. The combination of renewable bamboo and coir with a thermoplastic PP matrix and rubber modification hence offers a formaldehyde-free alternative to conventional plywood for shear-dominated applications. Full article

The increasing use of blockchain smart contracts has introduced new security challenges, as small coding errors can lead to major financial losses. While rule-based static analyzers remain the most common detection tools, their limited adaptability often results in false positives and outdated vulnerability patterns. This study presents a comprehensive comparative analysis of machine learning (ML) and deep learning (DL) methods for smart contract vulnerability detection using the BCCC-SCsVuls-2024 benchmark dataset. Six models (Random Forest, k-Nearest Neighbors, Simple and Deep Multilayer Perceptron, and Simple and Deep one-dimensional Convolutional Neural Networks) were evaluated under a unified experimental framework combining RobustScaler normalization and Principal Component Analysis (PCA) for dimensionality reduction. Our experimental results from a five-fold cross-validation show that the Random Forest classifier achieved the best overall performance with an accuracy of 89.44% and an F1-score of 93.20%, outperforming both traditional and neural models in stability and generalization. PCA-based feature analysis revealed that opcode-level features, particularly stack and memory manipulation instructions (PUSH, DUP, SWAP, and RETURNDATASIZE), were the most influential in defining contract behavior. Full article

With the continuous expansion of urban metro systems, balancing passenger experience and operational efficiency has become a central concern in contemporary public transportation design. However, most existing metro service studies continue to focus on perceptual comfort or isolated usability tasks and lack an integrated, behavior-centered perspective that accounts for the full travel chain and diverse user groups. This study develops the Bi-directional Service Behavioral Experience Model (BSBEM), which systematically integrates one-way navigation behaviors and interactive operational behaviors within a unified dual-path framework to identify behavioral patterns and experiential disparities across user groups. Based on the People–Touchpoints–Environments–Messages–Services–Time–Emotion (POEMSTI) behavioral observation framework, this study employs a mixed-method approach combining video-based behavioral coding, usability testing, and subjective evaluation. An empirical study conducted at Beidajie Station on Xi’an Metro Line 2 involved three representative passenger groups: high-frequency commuters, urban leisure travelers, and special-care passengers. Multi-source data were collected to capture temporal, spatial, and interactional dynamics throughout the travel process. Results show that high-frequency commuters demonstrate the highest operational fluency, urban leisure travelers exhibit greater visual dependency and exploratory pauses, and special-care passengers are most affected by accessibility and feedback latency. Further analysis reveals a positive correlation between route complexity and interaction delay, highlighting discontinuous information feedback as a key experiential bottleneck. By jointly modeling one-way and interactive behaviors and linking group-specific patterns to concrete metro touchpoints, this research extends behavioral evaluation in metro systems and offers a novel behavior-based perspective along with empirical evidence for inclusive, adaptive, and human-centered service design. Full article

Despite growing interest in positive-energy and net-zero-energy buildings (NZEBs), few studies have addressed the integration of biobased construction with building-integrated photovoltaics (BIPV) under hot–dry climate conditions, particularly in Morocco and North Africa. This study fills this gap by presenting a simulation-based evaluation of energy performance and renewable energy integration strategies for a residential building in the Fes-Meknes region. Two structural configurations were compared using dynamic energy simulations in DesignBuilder/EnergyPlus, that is, a conventional concrete brick model and an eco-constructed alternative based on biobased wooden materials. Thus, the wooden construction reduced annual energy consumption by 33.3% and operational CO₂ emissions by 50% due to enhanced thermal insulation and moisture-regulating properties. Then multiple configurations of the solar energy systems were analysed, and an optimal hybrid off-grid hybrid system combining rooftop photovoltaic, BIPV, and lithium-ion battery storage achieved a 100% renewable energy fraction with an annual output of 12,390 kWh. While the system incurs a higher net present cost of $45,708 USD, it ensures full grid independence, lowers the electricity cost to $0.70/kWh, and improves occupant comfort. The novelty of this work lies in its integrated approach, which combines biobased construction, lifecycle-informed energy modelling, and HOMER-optimised PV/BIPV systems tailored to a hot, dry climate. The study provides a replicable framework for designing NZEBs in Morocco and similar arid regions, supporting the low-carbon transition and informing policy, planning, and sustainable construction strategies. Full article

This study presents an expert system designed to generate Bitcoin investment strategies based on cryptocurrency market indicators. Historical BTC daily closing prices from 2015 to 2021 were processed to build the system’s predictive foundation. Multilayer perceptron (MLP) neural networks with various configurations were then employed to forecast both price levels and directional movements in Bitcoin’s value. These networks were trained using supervised learning techniques and assessed through multiple evaluation metrics. The configuration achieving the lowest RMSE and highest trend prediction accuracy was subsequently used to implement a capital management system capable of executing long, short, and combined trading positions in the Bitcoin market. An all-or-nothing investment scheme was applied and benchmarked against a traditional Buy & Hold (B&H) strategy. The proposed system achieved up to +68% profitability in the combined long/short configuration while reducing maximum drawdown by more than 40%. In addition, an expert supervisory layer was integrated, incorporating market indicators such as stop-loss, take-profit, and market withdrawal rules based on maximum adverse excursion (MAE) and maximum favorable excursion (MFE). Although this supervisory layer slightly reduced profitability in some scenarios, it enhanced risk control and capital protection during highly volatile periods. Overall, the proposed framework demonstrates that neural network–driven trading strategies, when combined with supervisory expert rules, can significantly outperform a passive Buy & Hold approach, offering a reproducible and fully automated solution for Bitcoin capital management. Full article

The Trump administration signalled a shift toward protectionism in U.S. trade policy, imposing tariffs on imports from both strategic partners and competitors, which generated renewed uncertainty in international trade relations and the future of existing frameworks such as the African Growth and Opportunity Act (AGOA) and the Generalised System of Preferences (GSP). Earlier analysis has shown that a Free Trade Agreement (FTA) between the Southern African Customs Union (SACU) and the United States can be trade-creating and lead to improved macroeconomic outcomes in SACU countries. However, these positive effects decline over time, with varying impacts across different industries, influenced by initial tariff levels and export orientation relative to the US. This paper examines whether there are economic and strategic incentives for SACU to negotiate a more beneficial agreement than a simple across-the-board elimination of ad valorem import tariffs. Using a dynamic computable general equilibrium (CGE) model, the paper examines the outcomes if cereals, poultry, dairy products, red meat, and sugar products—often classified as sensitive due to their labour intensity, food security implications, and exposure to import competition—were to retain some level of protection under a SACU–US Free Trade Agreement. The results suggest that while the FTA boosts key macroeconomic indicators in the short run, gains taper off over time. Crucially, real wages and employment remain stagnant, and terms of trade deteriorate, raising questions about the inclusivity and sustainability of such a deal. Shielding vulnerable sectors initially enhances SACU’s exports and supports some industry growth, particularly in agriculture. However, without broader reforms and export diversification, long-term competitiveness remains weak. A nuanced FTA design, combined with structural support policies, is essential to unlock lasting and inclusive trade benefits. Full article

This study details the design, synthesis, and evaluation of a novel series of fourteen 2-((1H-1,2,4-triazol-5-yl)thio)-N-benzylidene-N-arylacetohydrazide hybrid compounds. The primary objective was to investigate their potential as antimicrobial agents and assess their cytotoxicity. A systematic approach combining in silico screening and experimental validation was employed. The initial in silico analysis, using SwissADME, identified compounds with favorable drug-like properties. Subsequently, all fourteen compounds were synthesized and characterized using various spectroscopic methods. Their antibacterial efficacy was evaluated in vitro against Gram-negative (Klebsiella aerogenes) and Gram-positive (Enterococcus sp.) bacteria through growth kinetics and colony-forming unit (CFU) assays. Cytotoxicity was assessed using MTT assays on HEK (human embryonic kidney) cell lines. The compound, 2-((1H-1,2,4-triazol-3-yl)thio)-N′-(2-fluorobenzylidene)-N-phenylacetohydrazide emerged as the most promising candidate, demonstrating broad-spectrum antibacterial activity. These findings highlight the potential of 2-((1H-1,2,4-triazol-5-yl)thio)-N-benzylidene-N-arylacetohydrazide hybrids as a scaffold for developing new antimicrobial agents. Furthermore, this study suggests possible environmental applications for these compounds in antimicrobial resistance (AMR) management. Full article

In this modern era, attention has been devoted to blind super-resolution design, which improves image restoration performance by combining self-attention networks and explicitly introducing degradation information. This paper proposes a novel model called Kernel Adaptive Swin Transformer (KAST) to address the ill-posedness in image super-resolution and the resulting irregular difficulties in restoration, including asymmetrical degradation problems. KAST introduces four key innovations: (1) local degradation-aware modeling, (2) parallel attention-based feature fusion, (3) log-space continuous position bias, and (4) comprehensive validation on diverse datasets. The model captures degraded information in different regions of low-resolution images, effectively encodes and distinguishes these degraded features using self-attention mechanisms, and accurately restores image details. The proposed approach innovatively integrates degraded features with image features through a parallel attention fusion strategy, enhancing the network’s ability to capture pixel relationships and achieving denoising, deblurring, and high-resolution image reconstruction. Experimental results demonstrate that our model performs well on multiple datasets, effectively verifying the effectiveness of the proposed method. Full article

This study evaluated the seasonal greenhouse gas (GHG) emissions and carbon assimilation of Bambusa edulis under four soil amendment treatments—control (C), biochar (B), fertilizer using vermicompost (F), and biochar plus fertilizer (B + F)—in a coastal shelterbelt system in south-western Taiwan. Over a 12-month period, CO₂ and N₂O fluxes and photosynthetic carbon uptake were measured. The control (C) treatment served as the baseline, exhibiting the lowest greenhouse gas (GHG) emissions and carbon assimilation. Its summer N₂O emissions were 39.54 ± 20.79 g CO₂ e m⁻², and its spring carbon assimilation was 13.2 ± 0.84 kg CO₂ clump⁻¹. In comparison, the amendment treatments significantly enhanced both emissions and carbon uptake. The fertilizer-only (F) treatment resulted in the highest levels, with peak summer N₂O emissions increasing by 306.5% (to 160.73 ± 96.22 g CO₂ e m⁻²) and spring carbon assimilation increasing by 40.2% (to 18.5 ± 0.62 kg CO₂ clump⁻¹). An increase in these values was also observed in the combined biochar and fertilizer (B + F) treatment, although the magnitude was less than that of the F treatment alone. In the B + F treatment, summer N₂O emissions increased by 130.3% (to 91.1 ± 62.51 g CO₂ e m⁻²), while spring carbon assimilation increased by 17.4% (to 15.5 ± 0.36 kg CO₂ clump⁻¹). Soil CO₂ flux was significantly correlated with atmosphere temperature (r = 0.63, p < 0.01) and rainfall (r = 0.45, p < 0.05), while N₂O flux had a strong positive correlation with rainfall (r = 0.71, p < 0.001). The findings highlight a trade-off between nutrient-driven productivity and GHG intensity and demonstrate that optimized organic and biochar applications can enhance photosynthetic carbon gain while mitigating emissions. The results support bamboo’s role in climate mitigation and carbon offset strategies within nature-based solution frameworks. Full article