Search Results (11,303)

River and lake health assessment has evolved from a purely ecological concept to a multidimensional framework integrating ecosystem integrity and social service functions. Based on a comprehensive dataset of 1412 papers (1991–2024), this study combines bibliometric mapping with a systematic review to track the evolution of biological monitoring and assessment methodologies. Quantitative analysis of keywords reveals that while traditional focuses on heavy metals, fish, and sediments remain dominant, there is a significant shift towards integrated frameworks where biological indicators (e.g., benthic macroinvertebrate integrity and fish retention) are increasingly coupled with social services. We critically review three assessment paradigms: single-factor bio-indicators, biological predictive models such as RIVPACS and AUSRIVAS, and multi-factor comprehensive models. The study identifies critical gaps in ecological connectivity and the management of transboundary lakes under climate change. Consequently, we propose a strategic roadmap leveraging the National Ecological Connectivity Optimization Platform and mandatory “health audits” for transboundary waters to ensure the long-term sustainability of aquatic biodiversity. This review provides a scientific basis for balancing biodiversity conservation with sustainable water resource utilization. Full article

Forests play a critical role in Earth’s ecosystem, yet monitoring their long-term, large-scale spatiotemporal dynamics remains a significant challenge. This study addresses this gap by developing an integrated framework to map annual forest distribution in Hunan, China, from 1999 to 2023 at a high resolution of 30 m. Our methodology combines multi-temporal satellite imagery (Landsat 5/7/8/9) with key environmental variables, including digital elevation models, temperature, and precipitation data. To efficiently reconstruct historical maps, training samples were automatically derived from a reliable 2023 forest product using a transferable logic, drastically reducing manual annotation effort. Comprehensive evaluations demonstrate the robustness of our approach: (1) Qualitative analyses reveal superior spatial detail and temporal consistency compared to existing global forest maps. (2) Rigorous quantitative validation based on ∼9000 reference samples confirms high and stable accuracy (∼92.4%) and recall (∼91.9%) over the 24-year period. (3) Furthermore, comparisons with government forestry statistics show strong agreement, validating the practical utility of the data. This work provides a valuable, accurate long-term dataset that forms a scientific basis for critical downstream applications such as ecological conservation planning, carbon stock assessment, and climate change research, thereby highlighting the transformative potential of multi-source data fusion and automated methods in advancing geospatial monitoring. Full article

The growing miniaturization of electronic systems and the expansion of sustainable, autonomous IoT technologies emphasize the need for efficient, ultra-low-power energy harvesting devices. This study evaluates fifteen devices from five industry leaders for use in small-scale autonomous seed germination systems. Its novelty lies in applying a competitive profile matrix within a flexible multicriteria evaluation framework based on the simple additive weighting (SAW) method that uses a comprehensive set of competitive technology factors (CTFs). The results demonstrate that a transparent and structured methodology can generate prioritized lists of suitable energy harvesters while accounting for technical, economic, and environmental trade-offs. The study also shows that device rankings depend on the scope and objectives of the project. If these change, then the CTF selection, classification, and weighting adjust accordingly. Therefore, the relevance of this study lies in the adaptability, replicability, and audibility of the proposed framework, which supports the selection of informed technology for autonomous, IoT-based germination systems and other technological projects. Full article

Background and Objectives: Sternocleidomastoid (SCM) dysfunction is commonly implicated in several musculoskeletal conditions. Accordingly, shear-wave elastography has been used to characterize SCM stiffness in asymptomatic and clinical cohorts. However, the only reproducibility study available reported limited reliability, so clinical interpretations should be made with caution. Therefore, this study revisits key methodological aspects of that protocol to assess intra-examiner reliability and includes two examiners with different levels of expertise to evaluate inter-examiner reliability. Materials and Methods: A longitudinal observational study was conducted, recruiting twenty-five asymptomatic participants. Two examiners with different experience levels participated in this study after following structured training. For each side, images were obtained in immediate succession in the sequence experienced–novice–experienced–novice (with side order randomized), using an ROI spanning full muscle thickness, stabilizing approximately 10 s before freezing to record Young’s modulus and shear-wave speed. Results: Inter-examiner agreement was good–excellent: single-measurement ICCs were 0.77–0.86, improving to 0.79–0.87 when averaging two trials, which also reduced the standard error of measurement (SEM) and minimal detectable changes (MDCs). Between-examiner mean differences were small and nonsignificant (p ≥ 0.068). Intra-examiner reliability was excellent (ICC ≈ 0.93–0.94) with small absolute errors. Precision was high (SEM ~5–6 kPa; 0.22 m/s), and MDCs were ~15–16 kPa and ~0.60 m/s, with no trial-to-trial bias (all p ≥ 0.311). Conclusions: The revised protocol showed excellent intra-examiner repeatability and good–excellent inter-examiner reliability with minimal bias. Averaging two acquisitions improved precision, while a single operator optimized longitudinal stability. Full article

Freshwater fish habitat simulation is a vital technology for assessing the state and dynamics of aquatic ecosystems under changing environments. Based on a comprehensive dataset spanning 1991–2024, this study constructs a domain knowledge map by integrating co-citation analysis, keyword burst detection, and social network metrics. The bibliometric results quantitatively identify leading contributors and trace the field’s exponential growth. Complementing this, a critical technical review reveals a significant paradigm shift in modeling methodologies: moving from traditional univariate suitability curves to advanced multivariate and artificial intelligence (AI)-based frameworks. Despite these advancements, our analysis highlights critical gaps in addressing habitat connectivity and broad environmental stressors. To overcome these limitations, we propose a novel framework that integrates landscape pattern indices with circuit theory to quantify habitat patch arrangement and ecological flows. Furthermore, we advocate for future research to explicitly incorporate climate change scenarios (e.g., thermal regime shifts) and geomorphological processes. This study offers both a macroscopic overview of the discipline’s evolution and a roadmap for developing robust, ecosystem-based management tools. Full article

Soil erosion is largely driven by climate change and land use dynamics. The objective of this study is to assess the dynamic variation in erosion under the combined effects of precipitation and land use change in the Tigrigra watershed, located in the mountainous region of the Middle Atlas. The RUSLE (Revised Universal Soil Loss Equation) model is used in the methodological approach to estimate soil loss based on various parameters such as precipitation, soil, topography, land cover, and conservation practices. Geographic Information Systems (GIS) and remote sensing tools are essential for applying this method. In addition, the CA-Markov model (cellular automata), which models and predicts land use changes over time, is used to project future land cover scenarios that influence soil erosion dynamics. The research focuses on four previous periods (1991–2000, 2001–2010, 2011–2015, and 2016–2023), as well as a future period (2024–2050), considering two climate scenarios, RCP 2.6 and RCP 4.5. Precipitation data from local weather stations and the CMIP5 climate model were used to calculate the R factor (precipitation erosivity). Land cover analysis was performed using Landsat satellite images (30 m resolution) integrated into the CA-Markov model to calculate the C factor (land cover management). The results show that erosion has gradually decreased over both past and future periods, mainly due to variations in precipitation and vegetation cover. It should be noted that the period from 1991–2000 to 2016–2023 shows higher erosion compared to the future periods, with a maximum value of 17.83 t/ha/year recorded between 1991 and 2000. For the future period 2024–2050, a continuous decrease in erosion is observed under both scenarios, with an average value of 15.30 t/ha/year for the RCP2.6 scenario and 15.86 t/ha/year for the RCP4.5 scenario, with erosion remaining slightly higher under RCP4.5. Overall, erosion decreases across both historical (1991–2023) and projected (2024–2050) periods due to reduced rainfall erosivity. The northern part of the basin is particularly prone to erosion due to the low vegetation cover. The results indicate that areas susceptible to erosion require conservation measures to reduce soil loss. Implementing sustainable agricultural practices is crucial for maintaining long-term soil health and preventing degradation. However, some limitations of the study, such as the lack of data on conservation practices and daily precipitation, might affect the overall robustness of the findings. Full article

Background/Objectives: Obesity is a multifactorial condition and a major public health challenge. Conventional treatment centers on caloric restriction, which is often unsustainable and may cause stigma and psychoemotional harm. This study aimed to describe the methodology and assess the effects of a multicomponent nutritional intervention not focused on caloric restriction on psychoemotional outcomes. Women were selected as the target population because of the higher prevalence of obesity-related psychoemotional distress, body dissatisfaction, and weight-related stigma in this group, as well as their greater vulnerability to the psychosocial impacts of weight-focused interventions. Methods: This randomised, parallel, open-label trial included 89 obese women from primary care in Viçosa, Brazil. The participants were allocated into three groups: Group 1 (Control), which received a personalised hypocaloric diet (from 500 to 1000 kcal/day); Group 2 (NutrirCom (NutrirCom is a multicomponent, person-centred nutritional intervention protocol that is not focused on caloric restriction, conceived by a group of researchers at the Federal University of Viçosa for the care of women with obesity in Primary Health Care. It integrates nutritional, psychoemotional, behavioural, and social strategies, with an emphasis on promoting eating autonomy, mental health, and quality of life through a humanised, integrated, and sustainable approach, aiming to enhance the effectiveness of health care delivery and clinical practice)), which received 10 individual NutrirCom-based sessions; and Group 3 (NutrirCom + Social Support), which combined individual NutrirCom sessions with monthly group meetings for social support. Randomisation was stratified by body mass index via Excel^® with concealed allocation. The six-month intervention assessed changes in stress, anxiety, depression, and self-compassion, along with anthropometric and metabolic markers. Results: All groups presented reductions in waist circumference, fasting glucose, and total body fat, with increased lean mass. Anxiety remained unchanged in Group 1 but decreased significantly in Groups 2 (p = 0.002) and 3 (p = 0.005). Only Group 2 showed a significant reduction in depression symptoms (p = 0.023). Self-compassion improved significantly in groups 2 and 3. Conclusions: NutrirCom is a low-cost, scalable, and human-centered intervention that integrates emotional, social, and nutritional aspects of care. This approach shows promise as a sustainable strategy for obesity treatment in primary health care. Registration: Brazilian Registry of Clinical Trials (ReBEC) (no. RBR-87wb8x5). Full article

Among existing preference elicitation methods, the trade-off method offers an advantage over others in mitigating the influence of probability weighting on preferences, as it does not require assuming a specific form for the probability weighting function. However, when accounting for the dependence of probability weighting on the choice-set outcome range (CSOR), the conventional trade-off method may lead to improper elicitation of preferences due to its inability to control the CSOR. In order to concurrently circumvent the impacts of the CSOR and probability weighting on preferences in the elicitation procedure, we introduce the Range-Fixed Trade-off Method (RFTM) and provide its full derivation and concrete implementation steps under the framework of rank-dependent utility theory (RDU). The RFTM not only retains the advantages of the conventional trade-off method but also evades the effects of the CSOR on preferences by fixing the CSOR. The results of empirical investigations into the efficacy of RFTM indicate that, compared to the existing trade-off method, utility functions derived from RFTM exhibit a lower degree of risk aversion. This result is compatible with existing experimental observations and conclusions, thus implying that RFTM can effectively elicit individual preferences, thereby preventing or mitigating the bias in preferences arising from CSOR variations in the conventional trade-off approach. Furthermore, the experimental results demonstrate that the probability weighting function remains nonlinear even within a fixed CSOR. This indicates that, under the premise of preferences depending on the CSOR, non-expected utility theories still hold promising development prospects in the future. In summary, RFTM not only provides a more effective and reliable approach for preference elicitation but also makes it feasible to study the impact of changes in the CSOR on preferences, thereby providing methodological support for the future development of CSOR-dependent non-expected utility theories. Full article

This paper aims to understand the teaching and learning practices and perceptions regarding the subject of Differential and Integral Calculus 1 (DIC1) based on the current French model, as implemented at Université Claude Bernard Lyon 1 (LYON 1), and the Brazilian model, as observed at the Federal University of Technology—Paraná (UTFPR). Five tutorial groups were studied at LYON 1. At UTFPR, four classes of DIC1 were analyzed. Teaching activities were observed, and teachers responded to a questionnaire regarding the frequency with which they implemented certain activities and their beliefs about which activities contribute most to student learning. Students responded to the same questionnaire, reflecting on how often their instructors employed these activities and which ones they believed were most beneficial for learning. There was general agreement between teachers and students about the instructional methodologies used in class; however, discrepancies emerged between observed practices, stated methodologies, and the activities considered essential for learning. In engineering programs, the time allocated to problem-solving—individually or on the board—emerged as a key aspect that may inspire changes and improvements in the Brazilian model. In contrast, group work and mathematical software may serve as avenues for improvement in the French model. Full article

Plant immunity research is being reshaped by integrative multi-omics approaches that connect transcriptomic, proteomic, and interactomic data to build systems-level views of plant–pathogen interactions. This review outlines the scope and methodological landscape of these approaches, with particular emphasis on how transcriptomic and proteomic insights converge through network-based analyses to elucidate defense regulation. Transcriptomics captures infection-induced transcriptional reprogramming, while proteomics reveals protein abundance changes, post-translational modifications, and signaling dynamics essential for immune activation. Network-driven computational frameworks including iOmicsPASS, WGCNA, and DIABLO enable the identification of regulatory modules, hub genes, and concordant or discordant molecular patterns that structure plant defense responses. Interactomic techniques such as yeast two-hybrid screening and affinity purification–mass spectrometry further map host–pathogen protein–protein interactions, highlighting key immune nodes such as receptor-like kinases, R proteins, and effector-targeted complexes. Recent advances in machine learning and gene regulatory network modeling enhance the predictive interpretation of transcription–translation relationships, especially under combined or fluctuating stress conditions. By synthesizing these developments, this review clarifies how integrative multi-omics and network-based frameworks deepen understanding of the architecture and coordination of plant immune networks and support the identification of molecular targets for engineering durable pathogen resistance. Full article

On 7 January 2025, an Mw7.1 earthquake struck Dingri County, Tibet, causing severe damage in a high-altitude, sparsely instrumented region where traditional damage assessment methods are limited. To address this, we developed an integrated "source simulation–nighttime light validation" framework. First, a kinematic source model (constrained by InSAR and teleseismic data) and the Unified Seismic Tomography models for continental China lithosphere 2.0 (USTClitho2.0) velocity model were used with the curved-grid finite difference method to simulate high-resolution ground motion and intensity fields. Second, NASA Black Marble (VNP46A2) nighttime light data, processed with the Block-Matching and 3D filtering (BM3D) algorithm, were analyzed to compute pixel-level radiance changes and township-level total nighttime light loss rates (TNLR). The results reveal a high spatial consistency between simulated high-intensity zones and areas of significant light loss. For instance, Mangpu Township, within a simulated high-intensity zone, exhibited a TNLR of 44.7%. This demonstrates that nighttime light remote sensing can effectively validate physical simulations in areas lacking dense seismic networks. Our framework provides a novel, complementary methodology for rapid and reliable post-earthquake damage assessment in high-mountain, data-sparse regions. Full article

Non-invasive vagus nerve stimulation (nVNS) is gaining attention as a promising approach to modulate emotional, cognitive, and autonomic processes. This exploratory study analyzed the short-term effects of manual vagal maneuver (MVM), applied to the left or the right side of the neck (carotid region), on emotional regulation, cognitive performance, and cardiac autonomic activity in healthy young females. Sixty participants, divided equally into three groups (left MVM, right MVM, and control), completed attentional tasks under their respective conditions. Heart rate variability (HRV), cardiac coherence, self-reported emotional states, and task performance were measured. The preliminary findings of this pilot study offer mixed evidence: while both stimulation groups seem to show significant improvements in attentional performance, only left-sided MVM was associated with increased cardiac coherence and elevated perceived emotional dominance. No significant changes were observed in HRV indices across groups, highlighting potential limitations of current physiological markers in capturing subtle autonomic modulation. These preliminary findings from a pilot study suggest that, in young healthy women, stimulation—particularly on the left side—may have a potential to enhance cognitive and affective functioning, even though no detectable changes were observed in conventional HRV metrics. Given the small sample size and other important methodological limitations, such as the single-session design, these results should be interpreted with caution, and replication in larger, more rigorous studies is necessary. Full article

The automotive industry faces radical technological change, driven by the adoption of electrification, automation, and digitalization. As a leading industrial hub with key OEMs and suppliers, such as Volkswagen, Southeast Lower Saxony is disproportionately impacted by this structural transformation. As a consequence of these trends, the region’s automotive base faces economic uncertainties, local regulatory lag, and technological disruptions. In this study a scenario planning methodology is conducted, to identify three potential mobility futures for 2035: a Best-Case scenario, where innovation and favorable policies enable a stable growth environment for the local automotive industry; a Trend scenario, marked by incremental yet uneven progress, while maintaining the current status quo; and a Worst-Case scenario, defined by economic stagnation and regulatory impediments, leading to a slow degradation of the regional automotive industry. The scenarios are then evaluated based upon their impact and probability of occurrence, while individual impact factors were also prepared and categorized to support future decision-making on a topical basis. This study offers an overview of potential scenarios for the Southeast Lower Saxon automotive industry, supporting the strategic decision-making. Full article

The total cavopulmonary anastomosis (Fontan procedure), a palliative procedure for single-ventricle congenital heart disease, improves survival but is associated with progressive multiorgan complications and high long-term morbidity. Prior blood-based proteomic studies in adults have been limited to targeted antibody-based panels or focused on methodological comparisons. Systemic molecular alterations in younger, clinically heterogeneous patients, particularly in untargeted pathways, remain incompletely characterized. Serum samples from 48 Fontan patients and 48 age- and sex-matched healthy controls were analyzed using mass spectrometry with TMT labeling. 2228 proteins were quantified, of which 124 were significantly differentially abundant (fold change > 1.5 or <0.67, FDR-adjusted p < 0.05). Network analysis identified three major functional clusters: extracellular matrix (ECM) organization (predominantly increased), actin cytoskeleton organization, and platelet-related pathways (both predominantly decreased). Stratified analyses showed reduced ECM protein abundance in high-risk patients, suggesting a shift from active remodeling toward a more established fibrotic state, and uniquely elevated cytochrome b5 reductase 3 (CYB5R3), implicating altered redox homeostasis, nitric oxide metabolism, and cellular aging. Overall, our findings extend prior targeted analyses, reveal potential biomarkers such as CYB5R3 and underscore the complexity of the Fontan circulation, with implications for risk stratification and therapeutic targeting. Full article

Hair dyes are widely used across all socioeconomic groups and regions worldwide. However, some studies indicate that these products contain substances known to be toxic to a wide variety of organisms. Moreover, dyeing practices generate effluents that may carry the toxicity of hair dyes into the environment. Due to these facts, there is great concern about the impacts these products may have on the environment, as well as on the health of their users and professionals in the field of cosmetology. This scoping review analyzed 184 publications from major databases (PubMed, SciELO, Scopus, Google Scholar, and MEDLINE). Ultimately, 126 scientific studies published between 1981 and 2024 were included based on methodological rigor and their relevance to the One Health framework. According to the literature, the components of hair dyes can induce adverse responses in biological systems, ranging from reversible topical irritations to severe systemic effects. Among the studies evaluated, more than half reported significant toxicological or genotoxic associations related to oxidative dye components such as p-phenylenediamine and its derivatives. These compounds are frequently associated with various types of human cancers, including breast, prostate, bladder, skin, ocular cancers, and brain tumors. In addition to their effects on humans, hair dyes exhibit ecotoxicity, which may threaten the maintenance of ecosystems exposed to their residues. The reported environmental impacts result from effluent emissions after successive hair washes that release unreacted dye residues. Due to the low biodegradability of these compounds, conventional wastewater treatment methods are often ineffective, leading to environmental accumulation and changes in aquatic ecosystems, soil fertility, and trophic balance. Data on the toxicity of hair dye effluents remain scarce and sometimes contradictory, particularly regarding the effects of their transformation products and metabolites. Overall, the evidence underscores the need for continuous monitoring, updated risk assessments, and the adoption of advanced treatment technologies specific to beauty salon effluents. The information presented in this work may support further studies and guide public management agencies in developing policies for mitigating the impacts of hair dye pollutants within the One Health perspective. Full article