Search Results (1,208)

Soil erosion (SE) is a constant, complex land degradation process, a common natural disaster that occurs all over the world and severely impacts soil fertility, food security, and environmental balance. Soil erosion depends on many factors, including soil properties, slope, vegetation, rainfall amount and intensity, and anthropogenic activities. There are two main natural erosive forces by which soil is eroded and transported—water and wind. Water erosion refers to the detachment, transportation, and deposition of soil particles (solid runoff) into river networks. These particles, varying in size and composition, are the main products of soil erosion and most strongly affect river ecosystems. Solid runoff, or sediment-laden runoff, affects water quality, destroying habitats, carrying pollutants, reducing reservoir storage, and causing flooding. Erosion control activities also influence river ecosystems in different ways. Hydrotechnical facilities, a major erosion control practice, can alter the composition of aquatic biota by disrupting longitudinal connectivity and isolating populations. Reforestation and afforestation are other erosion control practices that have a strong impact on ecosystems. Stormwater retention systems in urban and forest areas are also important measures addressed in this review. This review examines complex environmental interactions and the roles of erosion and erosion control activities in river ecosystems. During the research, several key points were established: erosion and erosion control activities significantly affect river ecosystems. There is a lack of quantitative analysis of erosion intensity and its influence on ecosystems. This is probably due to the exceptional complexity and diversity of river ecosystems, but such a study would provide important information about complex relationships in nature. Full article

In the current higher education landscape, students frequently resort to “cramming” or massed study practices, which often lead to superficial learning and rapid information decay rather than long-term memory (LTM) consolidation. This systematic review aims to analyze the evidence on the effectiveness of neurodidactic strategies based on spaced learning for LTM consolidation in university contexts. Following the PRISMA statement and the PICOS model, a comprehensive search was conducted in Scopus and Web of Science, identifying 19 empirical studies that met the eligibility criteria. The corpus was then subjected to a risk of bias assessment using RoB-2, ROBINS-I, and MMAT. The results indicate that neurodidactic strategies—categorized into operative, methodological, and socio-emotional types—are associated with improved knowledge retention in several contexts when learning episodes are distributed over time. Some studies report positive trends in retention compared to massed practice, particularly in health sciences and language learning, but the heterogeneity of methodologies and outcome measures limits definitive conclusions. Therefore, while the integration of spaced learning within a neurodidactic framework appears promising, the evidence should be interpreted as suggestive rather than conclusive, and further research is needed to confirm these observations across diverse settings. This systematic review has been registered in the Open Science Framework (OSF). Full article

Large-diameter rescue shafts serve as critical infrastructure for emergency response in mining disaster scenarios, and their structural deformation directly affects the safe passage of rescue capsules. In this paper, we investigate three-dimensional (3D) reconstruction techniques for large-diameter rescue shaft environments and develop a Neural Radiance Fields (NeRF)-based reconstruction and deformation assessment scheme. The proposed workflow integrates no reference signal-to-noise-ratio (NR-SNR), image-quality filtering, SfM-based camera-pose estimation, Nerfacto reconstruction, point-cloud export, and circular-section fitting. The NR-SNR retention-ratio experiment shows that retaining approximately 35% high-quality images provides a practical efficiency–quality trade-off for the present dataset, reducing the computational burden of SfM pose estimation while preserving sufficient geometric information for subsequent reconstruction. The reconstructed radiance field is further exported as a dense point cloud and evaluated using relative radius error, circle-fitting residuals, and image-level rendering metrics. Experiments on a simulated large-diameter rescue shaft platform show that the proposed NeRF-based scheme provides favorable geometric measurement applicability and visual reconstruction quality under weak-texture and low-illumination conditions. Compared with conventional MVS and the tested 3DGS baseline, the proposed scheme produces a point-cloud output that is more suitable for subsequent circular-section fitting and deformation-related assessment. In addition, comparison with a representative SDF-based baseline indicates that direct implicit surface recovery remains challenging for the tested hollow cylindrical shaft-wall scene. The results demonstrate the potential of the proposed NeRF-based workflow for rescue-shaft inner-wall reconstruction and engineering-oriented deformation evaluation. Full article

Background: Exercise prehabilitation may improve physiological resilience before colorectal cancer (CRC) surgery. However, patient acceptance, reflected by recruitment, retention and adherence, is variably reported. Understanding how acceptance is captured and described is essential for designing effective, equitable interventions. Objectives: Map how CRC prehabilitation programmes report recruitment, retention and adherence, and identify characteristics associated with high acceptance. Methods: A scoping review was conducted following published guidance. MEDLINE, Embase, CINAHL, PsycINFO and Cochrane databases were searched. Studies of unimodal or multimodal prehabilitation interventions including an exercise component were included. Data relating to recruitment processes, retention, adherence and engagement-enhancing strategies were extracted and summarised using descriptive and content analysis. Reporting quality and variation were mapped. Results: Thirty-four studies were included: 15 randomised controlled trials, 12 prospective cohorts, four retrospective comparative cohorts, two non-randomised trials, and one quality-improvement project. Recruitment rates varied widely (3.8% to >90%), with four studies not reporting the proportion of eligible patients who declined and no study providing demographic characterisation of patients not recruited. Retention was reported in 31 of 34 studies and was generally high, including seven studies reporting 100% retention, although no consistent definition was used. Adherence was not reported in nine studies; among those reporting it, supervised programmes achieved attendance rates of 68–100% and unsupervised programmes 78–98%. Only four studies quantified adherence to prescribed exercise intensity or volume. No consistent association emerged between programme format (location, supervision, and digital support) and patient acceptance. Conclusions: Substantial variability exists in how CRC prehabilitation studies report recruitment, retention and adherence, constraining understanding of acceptance. Future research should prioritise standardised, detailed acceptance reporting and consider behaviour change theory informed, patient-centred intervention design to ensure effective and equitable CRC prehabilitation. Full article

Background: The integration of internationally educated nurses (IENs) into healthcare workforces is expanding globally, yet organization-led support models remain understudied. Successful IEN integration requires ethical recruitment, structured onboarding, workforce support, and stakeholder engagement in policy discussions related to transition and retention. Objective: To examine the conceptualization, implementation, and policy implications of the Philippine Nurses Association of America Cy Pres Task Force’s national initiative to support IEN onboarding and transition into U.S. healthcare. Methods: This descriptive program evaluation utilized governance documents, program planning records, policy summit materials, aggregated survey findings, PNAA Human Rights Committee resources, and the Handbook for Filipino Nurses Immigrating to the United States to examine initiative development, implementation processes, and program outputs. A descriptive narrative synthesis was used to characterize program structure, stakeholder engagement, and policy priorities. Findings: The PNAA Cy Pres governance model was built around ethical recruiting, workforce integration, and advocacy. The work began with policy summits with nurse leaders, health care organizations, recruitment agencies, and policy experts, focusing on hiring, onboarding, legal issues, and staff retention. Stakeholder engagement, interdisciplinary collaboration, and appreciative inquiry were used to identify best practices and goals. Key outputs included the establishment of a national governance structure, implementation of national and regional policy summits, and identification of policy priorities related to ethical recruitment, onboarding, workforce integration, and governance. Conclusions: The PNAA Cy Pres initiative provides an implementation-informed approach that may help guide future workforce integration efforts. The study illustrates how ethical recruitment, workforce integration, and stakeholder engagement can help translate workforce policy principles into practice. Policy & Practice Implications: Healthcare institutions, policymakers, and professional organizations need to work together to standardize onboarding, ethical recruitment, and support mechanisms to facilitate the integration and sustainability of the IEN workforce. Full article

LY104 (previously designated as B7) is a selective phosphodiesterase 4 inhibitor with promising activity against chronic obstructive pulmonary disease. We previously reported its single-dose pharmacokinetics and tissue distribution in rats. In the present study, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the simultaneous quantification of LY104 and its major metabolite M1 in rat plasma following ICH M10 guidelines. The method showed excellent linearity over 20–1200 ng/mL for both analytes, with retention times of 2.85 min (LY104) and 3.22 min (M1). Using this method, we extended our previous work in several directions. Re-analysis of previously published single-dose pharmacokinetic and tissue distribution data revealed no significant sex differences for LY104. Newly generated multiple-dose studies (1 mg/kg daily for 7 days) demonstrated no accumulation of LY104 or M1. The pharmacokinetic profile of M1 was quantified for the first time. Comprehensive in vitro investigations included plasma and liver microsomal stability, plasma protein binding, and excretion studies. This systematic preclinical pharmacokinetic characterization of LY104 and M1, incorporating re-analysis of existing data with sex stratification, newly generated multiple-dose and metabolite data, excretion studies, and comprehensive in vitro investigations, provides useful information to support further drug development and clinical trial design. Full article

Node-level cargo-volume forecasting in logistics sorting networks requires modeling temporal dynamics together with directed inter-node dependencies and planned topology perturbations. This study addresses 1-h-ahead forecasting under a partial-information boundary, where historical node volumes, the pre-change network structure, and planned route-topology changes are available before prediction, whereas continuous post-change dynamic edge weights and realized post-change graph states are unavailable. We propose a perturbation-aware framework that represents the sorting system as a directed network and integrates temporal features, pre-change structural descriptors, topology-change encodings, perturbation-response proxies, and similarity-assisted support for data-scarce nodes within a unified forecasting protocol. A shared random forest backbone is used only to assess the incremental value of these representations. Experiments on 57 sorting centers show that temporal dynamics dominate under stable-network conditions. Under topology perturbation, topology-change signals reduce test weighted absolute percentage error (WAPE) from 18.10% to 17.11%, and perturbation-response proxies further reduce it to 16.91%. For data-scarce nodes, similarity support reduces test WAPE from 29.43% to 26.68%, with consistent gains under 10%, 20%, and 30% sample-retention settings. These results suggest that the framework provides an interpretable and information-admissible representation strategy for node-level forecasting in directed networked systems. Full article

Background: Community-based mental health and social interventions focusing on housing stability, integrated care and psychosocial support are being increasingly recognised as essential for improving the mental health and wellbeing of people experiencing homelessness. However, evidence regarding the effectiveness of these interventions remains fragmented across different models of care and study designs. This review synthesises how these interventions address mental health and social determinants of health. Methods: Following PRISMA 2020 guidelines, a systematic search of six electronic databases (2019–2025) was conducted (PROSPERO: CRD420250653260). The review included 29 quantitative, qualitative, and mixed-methods studies examining community-based interventions for people experiencing homelessness and mental health conditions according to predefined eligibility criteria. Methodological quality was assessed using the Mixed Methods Appraisal Tool. Results: Community-based interventions, particularly Housing First models, were frequently associated with improved housing stability, mental health outcomes, and programme retention. Integrated multidisciplinary services and outreach promote psychosocial wellbeing, continuity of care and reducing emergency service use. Peer-led programmes support social integration, although evidence regarding technology-based interventions was inconsistent, with some studies reporting improved engagement and access to support, while others found limited effects on mental health outcomes. Conclusions: Addressing social determinants of health through structured community-based interventions is essential to tackle mental health inequalities. The findings support the implementation of integrated community-based services combining housing, mental health, and social support. These results may inform policymakers, healthcare providers, and community organisations seeking to reduce mental health inequalities among people experiencing homelessness. Full article

Background/Objectives: Popcorn (Zea mays L. var. everta) is an important specialty maize type; however, the genetic variation underlying popping-related quality traits remains insufficiently characterized in breeding. Methods: In this study, 18 popcorn inbred lines were analyzed using 25 simple sequence repeat (SSR) markers distributed across all 10 maize chromosomes, and 16 lines were further evaluated for popping performance and image-based flake morphology. Results: Substantial phenotypic variation was observed among the tested lines, with expansion volume ranging from 173.33 to 343.33 mL and expandability ranging from 16.79- to 32.46-fold. Image-based analysis of 957 popped kernels revealed continuous variation in flake circularity, indicating that flake morphology represents a quantitative trait rather than a strictly discrete classification. SSR analysis detected 2 to 11 alleles per locus, with polymorphism information content values ranging from 0.05 to 0.85, indicating moderate-to-high genetic diversity among the tested lines. Principal component analysis (PCA), unweighted pair group method with arithmetic mean (UPGMA) clustering, and population structure analysis revealed clear genetic differentiation and heterogeneous genetic backgrounds within the germplasm collection. Marker–trait association analysis identified several putative SSR loci associated with expansion efficiency, flake morphology, pericarp retention, and popping dynamics. Notably, marker M18 was putatively associated with both expansion volume and expandability. Conclusions: Based on these results, a conceptual framework was proposed in which popping-related traits were organized into partially independent but interconnected functional modules. Overall, this study provides SSR-based genetic information for popcorn germplasm characterization and offers preliminary marker resources for quality-oriented popcorn breeding. Full article

Interest in Natural Water Retention Measures (NWRMs) for large river basins is growing rapidly as a result of a wide range of benefits, including improved water retention capacity and regulation of ecosystem services. However, suitable site-specific NWRMs in small ungauged basins prone to flash floods and erosion, such as the Vrutci Reservoir Basin in Serbia, have yet to be evaluated and applied, primarily because of a lack of necessary data. The aim of this study was to design an easy-to-implement approach to evaluating the effects of NWRMs on peak discharge, tailored specifically to small basins with significant data gaps. The approach involves developing and analyzing a synthetic unit hydrograph (SUH) based on the available landscape geospatial data and evaluating the effects of NWRMs on the SUH before and after implementation of site-specific NWRMs. This methodological framework allows for quantification of the NWRMs’ effects on the basin and evaluates the proposed measures’ impact to secure better acceptance among stakeholders and informed decision-makers regarding their location in the basin. The results underscore a peak discharge rate reduction from 5% to 33% and hence indicate a positive impact on basin water retention potential. These results highlight the need for support for improved regulating ecosystem services in integrated water management. Full article

Background/Objectives: To compare the incidence of postoperative acute urinary retention (AUR) between traditional open laminectomy and percutaneous endoscopic lumbar surgery (PELS) using a large-scale real-world database, with specific stratification by urologic status, age, and sex. Methods: A retrospective, propensity score-matched analysis was conducted using the TriNetX Global Health Research Network (2015–2024). Adult patients undergoing PELS were compared to those undergoing open laminectomy. To rule out the confounding effect of routine intraoperative catheterization, the primary outcome was defined as de novo AUR occurring between 24 h and 3 months postoperatively. Subgroup analyses were performed for patients with benign prostatic hyperplasia (BPH), females, and age-stratified cohorts (<70 vs. ≥70 years). This study was approved by the Institutional Review Board (IRB/REC: CE25727C) and conducted under a waiver of informed consent. Results: In the matched cohorts of non-BPH males, females, and patients aged < 70 years, PELS was associated with a statistically significant reduction in AUR risk (Hazard Ratios: 0.445, 0.649, and 0.403, respectively) compared to open surgery. However, in males with BPH, the protective benefit of the endoscopic technique was attenuated and did not reach statistical significance (p = 0.0744), suggesting the study was underpowered for this subgroup or that baseline obstruction remains a dominant risk factor. Conclusions: Percutaneous endoscopic lumbar surgery was associated with a significantly lower risk of postoperative AUR compared to open laminectomy, particularly in patients without preexisting urologic obstruction. This benefit is likely attributable to minimized tissue trauma and the anti-inflammatory effects of continuous saline irrigation. However, in patients with BPH, baseline pathology outweighs surgical factors, necessitating medical prophylaxis regardless of the surgical approach. Full article

The molecular management of elite-relevant lines in clonally exploited crops requires more than broad genetic structure alone. In Stevia rebaudiana, breeding materials derived from cv. ‘Morita II’ may retain useful variation while also concentrating molecularly similar lines, increasing redundancy within selection pipelines. This study assessed whether a reduced five-locus SSR dataset could provide an operational molecular-affinity framework for redundancy screening and breeding-context interpretation of previously identified elite-relevant lines in a ‘Morita II’-derived breeding collection. A curated five-locus SSR dataset comprising 85 genotypes from a tropical breeding programme was analysed using the Wang relatedness estimator, operational molecular-affinity classes, UPGMA clustering based on Wang-derived dissimilarity and permutation-based assessment of mean Wang relatedness. The collection combined a broad fraction of comparisons showing no detectable positive molecular affinity with a relevant high-affinity component, and this pattern differed between the two reference molecular strata. One subset showed a compact high-affinity profile and higher mean Wang relatedness than expected under random reassignment, whereas the other was dominated by comparisons with no detectable positive molecular affinity. Importantly, the five-locus SSR framework is interpreted here as an operational, locally validated decision-support tool rather than as genome-wide or pedigree-level relatedness inference. These findings suggest that reduced SSR-derived molecular-affinity information can complement phenotypic, physiological and clonal evaluations by providing redundancy context for line retention, clonal advancement, and parental-diversification decisions in tropical stevia breeding. Full article

Multi-agent perimeter defense plays a critical role in cooperative defense scenarios in unmanned swarms. However, existing deep reinforcement learning approaches struggle to effectively exploit both coordination and temporal information under constrained local communication, and they lack generalization capability under dynamic variations in swarm size. To address these challenges, this paper proposes a multi-agent reinforcement learning strategy that integrates coordination under local communication constraints with spatiotemporal feature modeling. Specifically, a GraphSAGE-based spatial aggregation module is employed to enhance information exchange among defenders, while a GRU-based temporal encoding module processes historical observation sequences to improve coordination and anticipatory capability. Furthermore, to overcome scalability limitations, the inductive node-level aggregation mechanism enables agents to adapt to varying numbers of local neighbors, eliminating dependence on a fixed swarm size. Experimental results demonstrate that the proposed GR-MAPPO consistently improves capture performance under limited communication and exhibits better performance retention under cross-scale transfer across different swarm scales. Full article

Organizational commitment is crucial for employee retention and performance; however, little is known about how social and leadership resources translate into organizational commitment through routine learning behaviors. Based on the Conservation of Resources (COR) theory, this study explores how trust and leader’s vision of talent influence organizational commitment through three informal training formats: peer/supervisor coaching, knowledge sharing, and job rotation. Using data from the 2023 Korea Human Capital Enterprise Survey (N = 10,371), this study employs a generalized structural equation model that combines Bernoulli logit mediation equations with Gaussian identity outcome equations, along with the bootstrap method, to test the proposed mediation model. The results show that trust and leader’s vision of talent are positively correlated with organizational commitment, whereas knowledge sharing and job rotation significantly mediate these relationships. Peer/supervisor coaching shows no mediating effect. This study conceptualizes informal training as a mechanism through which workplace resources are implemented and translated into employee attitudes, thereby extending COR theory from resource acquisition and protection to resource utilization processes in everyday organizational contexts. The findings suggest that organizations should strengthen trust-based and development-oriented human resource practices to foster employee commitment. These implications extend beyond Korean firms to global HR practitioners seeking to build learning-supportive workplaces. Full article

This study examines customer retention intention in neobanking environments using a theory-informed explainable machine learning framework. Existing digital banking research typically relies on linear modelling approaches to explain retention behaviour, potentially overlooking nonlinear, value-range-dependent, and interaction-based predictive patterns. Using a publicly available survey of 305 neobank users, this study compares regularized linear models, a partial least squares structural equation modelling (PLS-SEM)-inspired benchmark, and XGBoost (version 3.2.0) under repeated nested cross-validation. SHapley Additive exPlanations (SHAP)-based explainability, SHAP interaction analysis, generalized additive model (GAM) diagnostics, construct-level aggregation, and construct-sensitivity checks are used to interpret model behaviour and assess robustness. The results show that XGBoost substantially outperforms the linear benchmarks, achieving the lowest average RMSE and highest average R² across 100 out-of-sample test-fold estimates. Trust-related indicators provide the largest share of model-based predictive importance, followed by perceived security and switching costs. SHAP and GAM diagnostics suggest that trust and switching costs may contribute to retention intention in heterogeneous and nonlinear ways, while perceived security displays a more stable positive predictive pattern. Age-related nonlinearities appear weak and should be interpreted cautiously given the young sample profile. The analysis also suggests possible non-additive relationships between trust and perceived security. The study contributes to digital banking and FinTech research by showing how explainable machine learning can complement theory-driven retention models, identify potentially nonlinear predictive patterns, and preserve interpretability. The findings offer practical insight for trust-building, visible security assurance, and retention diagnostics in neobanking contexts. Full article