Abstract:Black-box risk scores erode counselor trust when interventions must be explained to students and families. Gradient-boosted trees trained on anonymized LMS clickstreams, assignment lateness, and forum participation are paired with SHAP explanations that surface actionable drivers per learner. A semester-long pilot flags at-risk students two weeks earlier than GPA-only rules, and advisors report higher willingness to act when feature attributions match observed engagement patterns.
Abstract:Satellite land-surface temperature layers understate midday heat exposure where metal roofs and asphalt dominate open-air markets. Community mappers equipped with low-cost sensors and phone GPS co-produce fine-scale heat maps over eight weeks, while interviews document shade structures, misting, and staggered hours used by vendors. Overlay analysis identifies pockets where municipal tree planting and temporary canopy permits would yield the largest reductions in physiological heat stress.
Abstract:Manual inspection at 400 bottles per minute misses intermittent seal and label faults that trigger costly recalls. Compact YOLO variants quantized for ARM-based edge GPUs are trained on a multi-plant defect corpus covering crooked closures, missing labels, and fill-level outliers. Online trials maintain precision above 0.94 at line speed with under 25 ms latency, enabling reject actuators to fire within existing conveyor spacing without slowing production.
Abstract:Hard-surfaced classrooms elevate reverberation times that impair listening for students with mild hearing loss. Low-cost panels fabricated from post-consumer textile waste are installed on rear and side walls of twelve secondary classrooms. Measured RT60 drops into recommended bands, and word recognition scores improve significantly in bilingual instruction settings, demonstrating a circular-economy retrofit path for districts without capital for full acoustic ceilings.
Abstract:Evaporation ponds leave lithium-rich liquors still mixed with magnesium and calcium that complicate precipitation. Cross-linked graphene oxide laminates with tuned interlayer spacing are tested as selective nanofiltration layers on synthetic and field brines. Rejection of divalent cations exceeds 90% while lithium permeance remains industrially relevant over 200-hour continuous runs, cutting chemical consumption in subsequent carbonate precipitation relative to solvent-extraction baselines.
Abstract:Tariff design for shared solar-battery microgrids often ignores how reliability and payment flexibility trade off for cash-constrained users. A discrete choice experiment with 640 households estimates part-worth utilities for outage hours, prepaid versus postpaid billing, and cooperative ownership. Preference heterogeneity clusters by employment type; evening-shift workers value reliability more than ownership stakes, informing tariff menus that raise uptake without subsidies that crowd out cost recovery.
Abstract:Deficit irrigation saves water but often cuts marketable yield when stomatal closure persists through fruit set. Foliar sprays of compost tea enriched with finely ground rice-husk biochar are evaluated in a two-season split-plot trial under 70% and 50% of full evapotranspiration. Treated plants maintain higher leaf relative water content and total soluble solids, recovering 12–18% of yield lost under severe deficit without increasing total seasonal water use.
Abstract:Hospitals hesitate to pool perioperative records for AKI models because of privacy rules and heterogeneous EHR schemas. We train a federated gradient-boosted ensemble across seven cardiac centers that never exchange raw features, synchronizing only encrypted parameter updates. External validation on a held-out site yields AUROC comparable to a centrally trained baseline while reducing false-positive alerts that drive unnecessary nephrology consults during the first 48 postoperative hours.
Abstract:In the face of environmental, economic and social pressures to organizations, the areas of interest related to green procurement, green human resource management, and cost performance are linked to must-study topics. This paper will make a thorough review of the literature, focusing on the two variables GP and GHRM, and their effect on cost performance outcomes both separately and together, from articles published within the 2016-2025 timeframe. Based on 78 peer-reviewed articles that were retrieved from Scopus and Web of Science databases, co-occurrence and co-citation networks and the country collaboration map, accounting for 77% of citations, were used to perform the analysis of the field's intellectual structure using VOSviewer. Three themes arose—(i) the relationship between practice and performance in green procurement, (ii) GHRM as a mediator between operational and financial outcomes and (iii) the workings of an integrated GHRM–GSCM–cost-performance framework. The results indicate a significant increase in the number of publications since 2020, and China, India, the United Kingdom and Germany are the most productive countries in the field. The top venues include Journal of Cleaner Production and Sustainability, Journal of business and office interior design, and Business Strategy and the Environment. Although this expansion has occurred, empirical studies on integration of GHRM with GP into a single cost-performance model are still under-developed, and available research does not distinguish between cost-specific outcomes that the two practices can produce, treating GHRM and GP as two separate practices or as parts of more extensive GSCM designs. In order to further the research, the study suggests four research channels: (i) integrative models that connect GP, GHRM and cost performance, (ii) longitudinal cost-impact studies, (iii) sector-specific contextualisation, and (iv) digital-technological catalysation in bibliometric methodology. The results have added to theory building for the Resource-Based View or the Ability–Motivation–Opportunity framework and managerial insights of implementing green practices into cost control strategies.
Abstract:The convergence of Artificial Intelligence, employee engagement, and logistics performance has attracted significant scholarly attention over the past decade, yet the integrative dynamics among these three constructs in the logistics sector remain insufficiently consolidated. This bibliometric study maps the intellectual structure of research linking AI adoption, employee engagement, and logistics performance between 2017 and 2025, drawing on 86 peer-reviewed sources indexed in Scopus and Web of Science. Using PRISMA-aligned screening, VOSviewer co-authorship and keyword co-occurrence analysis, and Biblioshiny performance mapping, the study identifies influential authors, leading journals, thematic clusters, and emerging research trajectories. Four research objectives guide the synthesis: (i) to examine bibliometric trends of AI adoption research in logistics, (ii) to assess the influence of AI adoption on employee engagement, (iii) to examine the relationship between employee engagement and logistics performance, and (iv) to explore the integrative relationship among AI adoption, employee engagement, and logistics performance. Findings reveal that research output has grown exponentially since 2018, with China, India, the United Kingdom, and the United States dominating contributions. Five thematic clusters emerge: AI-driven operational excellence, human-machine collaboration, organizational commitment, last-mile delivery technology, and workforce analytics. The study identifies a critical gap in triangulating the AI–engagement–performance triad within the logistics sector and proposes a conceptual framework and research agenda. The findings hold implications for practitioners, policymakers, and academicians seeking to align algorithmic adoption with the human and operational dimensions of logistics competitiveness.