Search Results (104,750)

The erosion plot method (EPM) is the most accurate method for measuring total runoff and soil loss in the field, but it is expensive, time-consuming, and tedious to use, thereby limiting the scope of soil erosion research. Alternatively, the fractional method (FM) involves measuring a portion of total runoff and soil loss to estimate the total erosion. Although the FM may be easier to use in rainforest agroecology, it has not been evaluated under vetiver grass technology (VGT). Thus, a 2-year field study was conducted to verify the efficacy of the FM under VGT by comparing soil nutrient erosion between the FM and the EPM on two slopes (5% and 10%). Three piped drums (left, central, and right) were used to collect total runoff under the EPM, while only a central piped drum was used under the FM (usual practice). The FM’s runoff and soil loss values were similar to those under the EPM (R² = 0.98–0.99; p < 0.001). Runoff nutrients (R² = 0.90; p < 0.001) and eroded nutrients (R² = 0.97; p < 0.001) from the FM were highly similar to those of the EPM on the 5% slope. Similarly, runoff nutrients (R² = 0.86; p < 0.001) and eroded nutrients (R² = 0.95; p < 0.001) from the FM were strongly similar to those of the EPM on a 10% slope. The FM accounted for 92% of the total nutrient erosion measured by the EPM under VGT management. Thus, the FM will make research more efficient, cost-effective, and attractive, particularly in large-scale water erosion studies. Full article

Forest litter plays a critical role in regulating the water balance of forest ecosystems, particularly in semi-arid regions where hydrological stability is under pressure due to climate change. This study investigates the maximum water holding capacity (MWHC) of litter layers across three ecologically distinct regions in Türkiye—Kastamonu, Kütahya, and Muğla—to evaluate how structural and physicochemical characteristics influence the maximum water holding capacity (MWHC) of litter layers. Litter samples classified into humus, fermenting debris, and needles were analyzed for MWHC, pH, electrical conductivity (EC), and total dissolved solids (TDSs). The results revealed that both the type of litter and regional ecological conditions significantly affect MWHC, with humus layers and moist environments exhibiting the highest water holding capacity. Additionally, MWHC showed moderate positive correlations with EC and TDS, highlighting the importance of chemical composition in water dynamics. The findings underscore that forest litter should be regarded as a dynamic and functional hydrological component, not merely residual biomass. This perspective is vital for sustainable watershed planning and adaptive forest management. The study supports the development of integrated management strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). Full article

Pinus taeda plantations have been facing declining productivity in South America, especially due to competition for natural resources such as light, water, and nutrients. Competition with spontaneous vegetation in the early years is one of the main constraints on growth and biomass allocation in trees. However, the best method and timing for weed control and its impact on the productivity of Pinus taeda plantations are unknown. This study aims to evaluate whether weed control increases the growth and above-ground biomass production of Pinus taeda plantations in southern Brazil. This study was conducted at two sites with five-year-old Pinus taeda plantations in southern Brazil, with each being submitted to different weed control methods. This study was conducted in randomized blocks, with nine treatments: (i) NC—no weed control, i.e., weeds always present; (ii) PC—physical weed control; (iii) CC–T—chemical weed control in the total area; (iv) CC–R—chemical weed control in rows (1.2 m wide); (v) C6m, (vi) C12m, (vii) C18m, and (viii) C24m—weed control up to 6, 12, 18, and 24 months after planting; and (ix) COC—company operational weed control. The following parameters were evaluated: the floristic composition and weed biomass, height, diameter, stem volume, needle biomass, branches, bark, and stemwood of Pinus taeda. Control of the weed competition, especially by physical means (PC), and chemical control over the entire area (CC–T) promoted significant gains in the growth and above–ground biomass production of Pinus taeda at five years of age, particularly at the Caçador site. The results reinforce the importance of using appropriate strategies for managing weed control to maximize productivity, especially before canopy closure. In addition, the strong correlation between growth variables and the total biomass and stemwood indicates the possibility of obtaining indirect estimates through dendrometric measurements. The results contribute to the improvement of silvicultural management in subtropical regions of southern Brazil. Full article

The escalating challenge of resistance to insecticides among agricultural and public health pests poses a significant threat to global food security and vector-borne disease control. This review synthesizes current understanding of the molecular mechanisms underpinning resistance, including well-characterized pathways such as target-site mutations affecting nicotinic acetylcholine receptors (nAChRs), acetylcholinesterase (AChE), voltage-gated sodium channels (VGSCs), and γ-aminobutyric acid (GABA) receptors, and metabolic detoxification mediated by cytochrome P450 monooxygenases (CYPs), esterases, and glutathione S-transferases (GSTs). Emerging resistance mechanisms are also explored, including protein sequestration by odorant-binding proteins and post-transcriptional regulation via non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Focused case studies on Aedes aegypti and Spodoptera frugiperda illustrate the complex interplay of genetic and biochemical adaptations driving resistance. In Ae. aegypti, voltage-gated sodium channel (VGSCs) mutations (V410L, V1016I, F1534C) combined with metabolic enzyme amplification confer resistance to pyrethroids, accompanied by notable fitness costs and ecological impacts on vector populations. In S. frugiperda, multiple resistance mechanisms, including overexpression of cytochrome P450 genes (e.g., CYP6AE43, CYP321A8), target-site mutations in ryanodine receptors (e.g., I4790K), and behavioral avoidance, have rapidly evolved across global populations, undermining the efficacy of diamide, organophosphate, and pyrethroid insecticides. The review further evaluates integrated pest management (IPM) strategies, emphasizing the role of biopesticides, biological control agents, including entomopathogenic fungi and parasitoids, and molecular diagnostics for resistance management. Taken together, this analysis underscores the urgent need for continuous molecular surveillance, the development of resistance-breaking technologies, and the implementation of sustainable, multifaceted interventions to safeguard the long-term efficacy of insecticides in both agricultural and public health contexts. Full article

Conventional health risk assessments do not adequately reflect short-term exposure characteristics following chemical accidents. We aimed to evaluate the efficacy of existing assessment methods and propose a more suitable risk assessment approach for short-term exposure to hazardous chemicals. We analyzed foundational studies used to derive reference concentration (RfC), reference dose (RfD), and minimal risk level (MRL) values and applied these health guidance values (HGVs) to a hypothetical chemical accident scenario. An analysis of the studies underlying each HGV revealed that, except for the RfC for formaldehyde and the RfD for toluene, all values were derived under research conditions comparable to their respective exposure durations. Given the differing toxicity mechanisms between acute and chronic exposures, MRLs that were aligned with the corresponding exposure durations supported more appropriate risk management decisions. The health risk assessment results showed that RfC/RfD-based hazard quotients (HQs) were consistently higher than MRL-based HQs across all age groups and both substances, indicating that RfC/RfD values tend to yield more conservative risk estimates. For formaldehyde, the use of RfC instead of MRL resulted in an additional 208 tiles (2.08 km²) being classified as areas of potential concern (HQ > 1) relative to the MRL-based evaluation. These findings highlighted that the selection of HGVs can significantly influence the spatial extent of areas of potential concern, potentially altering health risk determinations for large population groups. This study provides a scientific basis for improving exposure and risk assessment frameworks under short-term exposure conditions. It also serves as valuable foundational data for developing effective and rational risk management strategies during actual chemical accidents. To the best of our knowledge, this is the first study to apply MRLs to a short-term chemical accident scenario and directly compare them with traditional reference values. Full article

Sustainable energy entrepreneurs promote sustainable development by focusing more on energy efficiency. This study examines the interdependence and driving–dependent relationships among the socioeconomic factors (SEFs) influencing sustainable energy enterprises (SEEs). A mixed-methods approach is used, beginning with a literature review and expert consensus, followed by total interpretive structural modeling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC) analysis. Seven key SEFs are finalized through interviews with 12 experts. Data are then collected from 11 SEEs. The study reveals that the regulatory and institutional framework emerges as the primary driving factor influencing other SEFs, including financial accessibility, market demand, technological innovation, and infrastructure readiness. Social and cultural acceptance is identified as the most dependent factor. The study proposes future research directions by identifying the United Nations sustainable development goals (SDGs) related to the antecedents, decisions, and outcomes with theoretical linkages through the Antecedents–Decisions–Outcomes (ADO) framework. The major SDGs identified are SDG 4 (education), SDG 7 (energy), SDG 9 (industry), SDG 11 (communities), and SDG 13 (climate). The study highlights that regulatory support, funding access, skill development, and technology transfer are required areas for strategic focus. Understanding the hierarchy of SEs supports business model innovation, investment planning, and risk management. Full article

The integration of 5G technology with cloud and edge computing is redefining the digital landscape by enabling ultra-fast connectivity, low-latency communication, and scalable solutions across diverse application domains. This paper investigates the synergistic impact of 5G on cloud-to-edge architectures, emphasizing its transformative role in revolutionizing sectors such as healthcare, smart cities, industrial automation, and autonomous systems. Key advancements in 5G—including Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and Massive Machine-Type Communications (mMTC)—are examined for their role in enabling real-time data processing, edge intelligence, and IoT scalability. In addition to conceptual analysis, the paper presents simulation-based evaluations comparing 5G cloud-to-edge systems with traditional 4G cloud models. Quantitative results demonstrate significant improvements in latency, energy efficiency, reliability, and AI prediction accuracy. The study also explores challenges in infrastructure deployment, cybersecurity, and latency management while highlighting the growing opportunities for innovation in AI-driven automation and immersive consumer technologies. Future research directions are outlined, focusing on energy-efficient designs, advanced security mechanisms, and equitable access to 5G infrastructure. Overall, this study offers comprehensive insights and performance benchmarks that will serve as a valuable resource for researchers and practitioners working to advance next-generation digital ecosystems. Full article

With the expansion of offshore and subsea infrastructure in Arctic and sub-Arctic regions, concerns are rising, driven by climate change and global warming, over the risk of drifting icebergs colliding with these structures in cold waters. Traditional methods for estimating iceberg underwater height and assessing subgouge soil properties, such as costly and time-consuming underwater surveys or centrifuge tests, are still used, but the industry continues to seek faster and more cost-efficient solutions. In this study, the extra tree regression (ETR) algorithm was employed for the first time to simultaneously model iceberg drafts and subgouge soil properties in both sandy and clay seabeds. The ETR approach first predicted the iceberg draft, then simulated subgouge soil reaction forces and deformations. A total of 22 ETR models were developed, incorporating parameters relevant to both iceberg draft estimation and subgouge soil characterization. The best-performing ETR models, along with the most influential input variables, were identified through a combination of sensitivity, error, discrepancy, and uncertainty analyses. The ETR model predicted iceberg draft with a high level of accuracy (R = 0.920, RMSE = 1.081), while the superior model for vertical reaction force in sand achieved an RMSE of 43.95 with 70% of predictions within 16% error. The methodology demonstrated improved prediction capacity over traditional techniques and can serve early-stage iceberg risk management. Full article

In the context of global food security and sustainable agricultural development, the efficient recognition and precise management of agricultural insect pests and their predators have become critical challenges in the domain of smart agriculture. To address the limitations of traditional models that overly rely on single-modal inputs and suffer from poor recognition stability under complex field conditions, a multimodal recognition framework has been proposed. This framework integrates RGB imagery, thermal infrared imaging, and environmental sensor data. A cross-modal attention mechanism, environment-guided modality weighting strategy, and decoupled recognition heads are incorporated to enhance the model’s robustness against small targets, intermodal variations, and environmental disturbances. Evaluated on a high-complexity multimodal field dataset, the proposed model significantly outperforms mainstream methods across four key metrics, precision, recall, F1-score, and mAP@50, achieving 91.5% precision, 89.2% recall, 90.3% F1-score, and 88.0% mAP@50. These results represent an improvement of over 6% compared to representative models such as YOLOv8 and DETR. Additional ablation studies confirm the critical contributions of key modules, particularly under challenging scenarios such as low light, strong reflections, and sensor data noise. Moreover, deployment tests conducted on the Jetson Xavier edge device demonstrate the feasibility of real-world application, with the model achieving a 25.7 FPS inference speed and a compact size of 48.3 MB, thus balancing accuracy and lightweight design. This study provides an efficient, intelligent, and scalable AI solution for pest surveillance and biological control, contributing to precision pest management in agricultural ecosystems. Full article

The environmental problem of abandoned fishing gear (e.g., ghost nets) exists on a world scale. It impacts marine biodiversity for decades after the nets has become lost in the ocean. In Cyprus (eastern Mediterranean), ghost nets are found almost everywhere around the island, threatening marine life and human activities, such as scuba diving, fishing and navigation. To achieve meaningful outcomes for biodiversity conservation and the management of an offshore site that is particularly affected by ghost nets, the Jubilee Shoals, this issue is addressed in this study with an evidence-based approach. Pre-removal surveys were necessary to assess the nets and produce the environmental, ecological and structural data for the calculation of the Gear Removal Index (GRI). The results of a revised version of the index (GRI+) that includes species of conservation interest and invasive species were cross-checked in the field by divers with experience in marine ecology and similar removals. About 3 km of nets in total were successfully removed. The implementation of the GRI+ was an important proof-of-concept for environmental managers, aiding them to decide whether it would be necessary (or not) to perform removals and highlighting the index as a useful tool for the protection and management of Cyprus’ marine habitats. Full article

Semi-enclosed bays are greatly affected by human activities and have undergone drastic changes in their ecological environment, which requires our continuous attention. Laizhou Bay (LZB) is a typical semi-closed bay that is greatly influenced by human activities, and it is highly representative on a global scale. Investigating the multi-scale variation in nutrient concentrations in semi-enclosed bays can provide scientific support for environmental management and policy adjustments. To address the limitations of in situ data and the high cost of field surveys, this study utilizes machine learning methods to construct MODIS remote sensing models for quantitatively analyzing the concentrations of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) in the surface water of LZB, as well as the spatiotemporal factors influencing them. Among various methods tested, the Support Vector Machine Regression (SVR) algorithm demonstrated the best performance in retrieving nutrient concentrations in LZB. The R² values of the DIN and DIP retrieval results based on the SVR algorithm are 0.91 and 0.92, respectively, while the RMSE values are 5.43 and 0.08 μmol/L, respectively. The retrieval results indicate that nearshore nutrient concentrations are significantly higher than those in offshore areas. Temporally, from 2003 to 2024, the DIN concentration in l has decreased at a rate of 0.4 μmol/L/yr, while the DIP concentration has remained relatively stable. Given sufficient observation data, the proposed machine learning and remote sensing approach can be effectively applied to other bays, offering the advantages of long time series, high spatial resolution, and a low cost. Full article

As governments pursue digital transformation to improve service delivery and administrative efficiency, AI chatbots have emerged as a promising innovation in smart public administration. However, their adoption remains limited, particularly in transitioning countries where institutional, organizational, and technological conditions are complex and evolving. This study aims to empirically examine the key aspects, challenges, and strategic implications of AI chatbots’ adoption in public administration of Uzbekistan, a transitioning government in Central Asia. The study offers a novel contribution by employing an extended technology–organization–environment (TOE) framework. Data were collected through a survey among 501 public employees and partial least squares structural equation modeling was used to analyze data. The results reveal that perceived usefulness, compatibility, organizational readiness, effective accountability, and ethical AI regulation are key enablers, while system complexity, traditional leadership, resistance to change, and concerns over data management and security pose major barriers. The findings contribute to the literature on effective innovation in public administration and provide practical insights for policymakers and public managers aiming to effectively implement AI solutions in complex governance settings. Full article

Accurate parametric modeling of lithium-ion batteries is essential for battery management system (BMS) design in electric vehicles and broader energy storage applications, enabling reliable state estimation and effective thermal control under diverse operating conditions. This study presents a detailed characterization of lithium-ion cells to support advanced BMS in electric vehicles and stationary storage. A second-order equivalent circuit model is developed to capture instantaneous and dynamic voltage behavior, with parameters extracted through Hybrid Pulse Power Characterization over a broad range of temperatures (−10 °C to 45 °C) and state-of-charge levels. The method includes multi-duration pulse testing and separates ohmic and transient responses using two resistor–capacitor branches, with parameters tied to physical processes like charge transfer and diffusion. A weakly coupled electro-thermal model is presented to support real-time BMS applications, enabling accurate voltage, temperature, and heat generation prediction. This study also evaluates open-circuit voltage and direct current internal resistance across pulse durations, leading to power capability maps (“fish charts”) that capture discharge and regenerative performance across SOC and temperature. The analysis highlights performance asymmetries between charging and discharging and confirms model accuracy through curve fitting across test conditions. These contributions enhance model realism, thermal control, and power estimation for real-world lithium-ion battery applications. Full article

Plants are constantly exposed to various environmental challenges, such as drought, flooding, heavy metal toxicity, and pathogen attacks. To cope with these stresses, they employ several adaptive strategies. This review highlights the potential of plant-derived smoke (PDS) solution as a natural biostimulant for improving plant health and resilience, contributing to both crop productivity and ecological restoration under abiotic and biotic stress conditions. Mitigating effects of PDS solution against various stresses were observed at morphological, physiological, and molecular levels in plants. PDS solution application involves strengthening the cell membrane by minimizing electrolyte leakage, which enhances cell membrane stability and stomatal conductance. The increased reactive-oxygen species were managed by the activation of the antioxidant system including ascorbate peroxidase, superoxide dismutase, and catalase to meet oxidative damage caused by challenging conditions imposed by flooding, drought, and heavy metal stress. PDS solution along with other by-products of fire, such as charred organic matter and ash, can enrich the soil by slightly increasing its pH and improving nutrient availability. Additionally, some studies indicated that PDS solution may influence phytohormonal pathways, particularly auxins and gibberellic acids, which can contribute to root development and enhance symbiotic interactions with soil microbes, including mycorrhizal fungi. These combined effects may support overall plant growth, though the extent of PDS contribution may vary depending on species and environmental conditions. This boost in plant growth contributes to protecting the plants against pathogens, which shows the role of PDS in enduring biotic stress. Collectively, PDS solution mitigates stress tolerance in plants via multifaceted changes, including the regulation of physico-chemical responses, enhancement of the antioxidant system, modulation of heavy metal speciation, and key adjustments of photosynthesis, respiration, cell membrane transport, and the antioxidant system at genomic/proteomic levels. This review focuses on the role of PDS solution in fortifying plants against environmental stresses. It is suggested that PDS solution, which already has been determined to be a biostimulant, has potential for the revival of plant growth and soil ecosystem under abiotic and biotic stresses. Full article

Background/Objectives: Orchialgia following kidney donation is an underrecognized complication with reported incidence varying dramatically between retrospective (2–3%) and prospective (44–55%) studies, suggesting significant underreporting. This study aimed to determine the incidence, characteristics, and clinical relevance of orchialgia in male kidney donors within 2 years post-donation using direct patient assessment. Methods: This is a cross-sectional study of 100 male donors (64.5% response rate) from 155 eligible donors approached who underwent left laparoscopic donor nephrectomy between February 2021 and 2023. Donors completed a literature-based 15-item questionnaire at routine follow-up visits assessing testicular pain characteristics, timing, and impact. Results: Orchialgia occurred in 48% (48/100) of donors. Early onset (≤14 days) occurred in 47%, with median onset at day 2 (range 1–14). At 3-month follow-up, 37% reported persistent pain; by 1 year, only 0.8% experienced persistent pain based on our 10-year institutional database. No significant difference in incidence between altruistic (54%) and related donors (33%), though pain severity was lower in altruistic donors (mean 3.6 vs. 4.2, p = 0.04, independent t-test). Conservative management was effective in all cases; no invasive interventions were required. Conclusions: Orchialgia affects nearly half of male kidney donors when directly assessed, though it follows a benign, self-limiting course with minimal long-term clinical impact. These findings support enhanced preoperative counseling while reassuring donors about favorable outcomes. Full article