Search Results (22,865)

This study examines the impact of energy security risk on the economic growth rate of the world’s 74 largest energy-consuming countries. The Energy Security Risk Index is employed to assess national vulnerability to fluctuations in energy security risk over a specified period. To investigate the empirical relationship between energy security risk and economic growth, the analysis utilizes a balanced panel dataset spanning from 1980 to 2025 and applies a series of econometric techniques, including cross-section dependence tests, unit root tests, Pedroni’s residual cointegration test, pooled mean group estimation, and a heterogeneous panel causality test. The empirical findings confirm the presence of a statistically significant causal relationship running from energy security risk to economic growth (LESR → GDPG) at the aggregate panel level. In advanced economies, energy security risk is found to constrain economic growth. Conversely, in developed economies, the results indicate that energy security risk exerts a positive and statistically significant effect on economic growth, which may be attributable to energy-related investments that drive structural transformation. These findings carry important implications for the global community, given that energy continues to serve as the lifeblood of modern production systems. Full article

Improving emergency vehicle mobility in congested urban environments is a critical challenge for transportation systems. Although roadway capacity expansions, such as widening roads, are often deployed to reduce congestion, their impact on emergency response performance is not always guaranteed, especially when delays concentrate at critical intersections. This study investigates how roadway capacity expansion affects emergency vehicle performance by using a microscopic traffic simulation framework. The study was applied to a real urban corridor in Mohammedia, Morocco, to provide a solid base for simulations with real-world conditions. A SUMO model was calibrated to represent two roadway configurations: a baseline two-lane layout and a three-lane post-widening scenario. Traffic volumes from 1056 to 3520 vehicles per hour were simulated, and performance was assessed using three emergency-specific indicators: Emergency Response Time (ERT), Delay Ratio (DR), and Priority Mobility Index (PMI). An initial single-run comparison suggested a substantial ERT reduction under moderate demand (343.40 s to 270.90 s, 21.11%); however, a 30-seed replication with paired Wilcoxon signed-rank tests shows that this and nearly all other widening effects are not statistically distinguishable from stochastic simulation noise. Only one of 12 emergency vehicle comparisons (Priority Mobility Index at 18:00) reached significance, and it favored the baseline configuration; none of 12 general traffic comparisons improved significantly, and general traffic was significantly slower under the widened configuration at 22:00 (p < 0.01). A supplementary sensitivity analysis (±20% emergency vehicle demand share) further shows that Delay Ratio conclusions are considerably more sensitive to this assumption (up to 34% relative change) than ERT or PMI (under 8%). These findings indicate that, in this network, roadway capacity expansion alone does not deliver a statistically robust improvement in either emergency vehicle or general mobility, and that a persistent signalized-intersection bottleneck remains the dominant constraint irrespective of lane geometry. The study provides a replicable, statistically validated simulation framework for assessing roadway capacity expansion effectiveness and cautions against single-run comparisons, which can substantially overstate the causal effect of infrastructure interventions in microscopic traffic simulation studies. Full article

What happens to emotional life when running water fails not for a day but for a decade? Drawing on 20 semi-structured interviews in a rural Romanian commune that went more than ten years without a functioning public water supply, and where a new network now reaches only part of the settlement, we examine how the emotional demands of chronic water scarcity are socially organised. We identify four recurrent patterns, which we analyse as feeling rules: shame before visiting outsiders, worry tied to falling household reserves, hope maintained in public, and resignation expressed in contained, formulaic terms. The four carry unequal normative warrant, which we assess explicitly. We propose the concept of infrastructural emotion work, the unpaid emotion work generated by the sustained failure of systems socially expected to function, and identify formulaic emotional display as one of its mechanisms, in which a conventional phrase provides an interactionally acceptable response while foreclosing elaboration. We argue that these expectations are socio-materially generated rather than culturally prescribed alone, and that the resulting burdens are unevenly distributed by gender. Where infrastructure is unreliable, households assemble an emotional infrastructure of their own. Full article

Unmanned surface vehicle (USV) clusters operating in contested maritime environments face communication degradation from jamming, satellite denial, and partial node loss. Existing countermeasures either react after link failure or rely on a single signal quality indicator. A framework is presented that integrates two complementary mechanisms for resilient USV cluster communication: (1) a multi-indicator communication quality metric $Q_{\mathrm{comm}}$ that fuses signal-to-noise ratio, packet loss rate, latency, and temporal stability into a single scalar; and (2) a multi-modal backup communication chain spanning acoustic modem, optical link, and multi-hop RF(Radio Frequency) relay that provides physical-layer redundancy when primary radio frequency links are degraded. Across five representative failure scenarios simulated on a seven-vehicle cluster with 50 independent runs per configuration, the multi-indicator $Q_{\mathrm{comm}}$ metric achieves a mean of 0.521, outperforming single-indicator baselines on the composite $Q_{\mathrm{comm}}$ metric (Cohen’s d = 8.020, p < 0.0001, n = 250 per method); $Q_{\mathrm{comm}}$ is the framework’s own optimization target; this comparison is, therefore, presented as an internal consistency demonstration rather than an independent validation. The framework reduces recovery time from 113.8 s (single-indicator) to 15.3 s—an 86.6% improvement. With the backup communication chain enabled, delivery rates exceed 94% across all methods and scenarios. A direct Monte Carlo ablation (50 seeds × 5 scenarios) reveals that multi-indicator fusion is the primary driver of assessment accuracy and recovery speed, while the multi-modal backup chain is the dominant delivery driver: without it, delivery falls from 94.6% to 24.2%. A sigmoid-blended topology utility function is included as an architectural design component; its independent validation requires extended-duration threat experiments identified as future work. The contributions of this work are the validated multi-indicator fusion metric and the multi-modal backup chain architecture, which together provide a practical foundation for resilient USV communication. Full article

Claims of AI sovereignty are increasingly invoked but operational control remains uneven. Claims to control are made through national models, sovereign clouds, data localization mandates, and procurement rules; however, whether such claims translate into demonstrable control over how AI systems are run, inspected, and contested remains poorly understood. This paper introduces credible sovereignty, the gap between declared and demonstrable control in deployment, as a conceptual lens for analyzing AI governance to examine how this gap is opened and closed across infrastructure, data, and model supply chains. Using a PRISMA-guided social-science corpus and machine learning-based BERTopic modeling, validated through topic diversity and topic separation diagnostics and triangulated through close reading, the analysis identifies four governance logics through which sovereignty is contested: data infrastructure and legitimacy frameworks; techno-bloc diplomacy and infrastructure politics; European regulatory sovereignty; and community-driven sovereignty in the Global South. Across these logics, sovereignty is enacted less through national capabilities than through proxy mechanisms—certification regimes, procurement clauses, cloud governance, and deployment architectures—each carrying trade-offs between autonomy, dependence, and accountability. Rereading the corpus through an Antecedents–Decisions–Outcomes lens yields a testable research agenda: antecedents that push actors toward sovereignty seeking; design and governance choices that translate ambition into implementation; and outcomes—resilience, inclusion, accountability—against which sovereign AI programs should be assessed. This paper reframes sovereignty as a layered operational capability rather than a discursive claim and links computational synthesis to a normative construct that applies across jurisdictions and scales. Full article

Few-shot compound fault diagnosis of induction motors can be overestimated when correlated windows from the same continuous run are split across support and query sets. This study develops a run-disjoint few-shot framework in which each complete experimental run is treated as one shot and support and query sets are separated by run ID. Forty-eight multidomain features are extracted from synchronized triaxial vibration windows, classified using task-specific XGBoost, and aggregated to obtain run-level predictions; TreeSHAP provides post hoc feature attribution. In a matched comparison with identical query runs and windows, window-mixed partitioning increased the task-level mean run-level Macro-F1 from 0.9212 to 0.9934. After repeated predictions were aggregated over 108 unique query runs, the corresponding difference was 0.0093 with a 95% paired-bootstrap confidence interval of [0.0000, 0.0282], showing that the estimated magnitude depends on the statistical unit. Under the predefined strict 3-shot protocol, XGBoost achieved a Macro-F1 of 0.9263 and run-level accuracy of 0.9292. Additional sensitivity and controlled comparisons showed that performance depends on within-run sampling, representation, and classifier design, while strict cross-speed tests revealed the limitation of fixed-frequency features under rotational-speed shifts. The framework provides a leakage-aware evaluation procedure for few-shot compound-fault diagnosis using independently labeled runs. Full article

Water scarcity in semi-arid regions makes efficient irrigation scheduling a priority, yet farm-level adoption of soil-moisture monitoring remains limited by the cost, low portability and installation complexity of commercial sensing systems. This study presents the development and field validation of WaziSense, a low-cost, solar-powered Internet-of-Things (IoT) smart tensiometer, developed within the OSIRRIS platform for soil-water monitoring and irrigation scheduling. The device couples a Watermark granular-matrix sensor and a DS18B20 temperature probe to an ATmega328P microcontroller (Arduino Pro-Mini, 3.3 V, 8 MHz) with long-range LoRa communication and a maximum-power-point-tracking (MPPT) solar-charging stage, logging soil matric potential and soil temperature every 15 min. An open-source edge/cloud stack (WaziGate, WaziApp) retrieves weather forecasts from an open API and runs an automated machine learning (AutoML) regression pipeline that forecasts soil-water dynamics and the time to a user-defined threshold, from which irrigation is scheduled and its applied volume verified by a flow meter. The system was deployed at three bioclimatic sites in Tunisia (durum wheat at Cherfech, citrus at Nabeul, apple at Sbeitla), with tensiometers installed at 20 and 40 cm depths, and validated against commercial 10HS capacitive probes coupled to a ZL6 data logger, with which the co-located readings were significantly correlated (r = 0.81). Calibrated readings showed a strong relationship between soil–water content and soil–water potential (R² = 0.99), and the edge forecasting model reproduced soil–water dynamics on unseen data (Sbeitla apple site, 5-day horizon) with R² = 0.73, RMSE = 0.35, MAE = 0.23 and MPE = 12.52%. With a material cost under about 90 EUR per node and fully open-source hardware and software, WaziSense is one to two orders of magnitude cheaper than commercial monitoring stations, offering an affordable, reproducible and scalable tool for data-driven irrigation in water-limited agriculture. Full article

Accurate identification of multiphase flow patterns in vertical pipelines is critical for operational safety and efficiency in the oil and gas industry. Yet, conventional methods struggle with subjectivity and transitional regimes. This study develops and integrates three neural network architectures: a convolutional neural network (CNN) for spatial features, a transformer neural network (TNN) for long-range dependencies, and a physics-encoding network (PEN) for embedding physical constraints. These are combined into a hybrid framework trained on an experimental dataset of 2131 images from a wire mesh sensor, annotated using a semi-automated pipeline. Results show the hybrid model achieved 95.91% test accuracy with a macro F1-score of 0.96, the highest of the four models evaluated, with its main advantage in transitional regimes. A multi-seed ablation shows that the convolutional branch provides the dominant discriminative signal, while the transformer and physics-inspired branches added complementary improvements that are consistent across runs. This hybridisation mitigates individual model weaknesses, with the physics-inspired branch acting as a spatial regulariser that improves interpretability, providing a robust and objective tool for reliable pipeline monitoring. Full article

Medium-resolution building-footprint mapping is limited by two coupled problems: 10 m optical pixels mix roofs with roads and bare surfaces, and SAR observations are degraded by speckle and viewing geometry. We present ACBDT, a Sentinel-1/2 framework that encodes each modality separately, learns a diffusion-inspired time-step-conditioned fused teacher representation, transforms it through a Cross-Modal Distillation Bridge (CMDB), and refines the output with a Student Refinement Decoder. The time-step variable is used only as a stochastic conditioning index; ACBDT does not implement a forward noising schedule, reverse diffusion, or iterative diffusion sampling. Training and evaluation used 2680 paired 256 × 256 patches over eight Yangtze River Delta cities with a spatially disjoint block partition. In three independent runs on the held-out test partition, ACBDT achieved 85.61 ± 0.32% building IoU, 92.24 ± 0.19% F1, and 83.74 ± 0.34% dataset-level boundary F1, compared with 83.21 ± 0.24% IoU for the strongest baseline, FTransUNet. Repeated-seed ablation showed 79.01 ± 0.42% IoU without CMDB and 84.53 ± 0.20% IoU without time-step conditioning. The separate density diagnostic retained a positive full-minus-optical IoU difference across all five building-density strata. Conclusions are limited to this Yangtze River Delta evaluation; city-held-out and cross-season transfer were not tested. Full article

This study addresses a large-scale location–allocation problem in a three-echelon automotive supply chain comprising 382 suppliers, candidate distribution centers, and six assembly plants. The planning task is to redesign the inbound consolidation network while minimizing transportation and distribution center operating costs, enforcing a 480 km supplier-to-center service radius, and achieving at least 90% demand-weighted coverage. We formulate a mixed discrete-continuous model with supplier-to-center assignment, center location, throughput, and flow decisions. A feasibility-oriented hybrid algorithm uses a genetic algorithm as the main search engine, ant colony construction to seed solutions near the feasible region, adaptive mutation and simulated annealing to preserve exploration and refine elite solutions, and an online neural surrogate to avoid a subset of costly exact fitness evaluations. The design differs from a simple collection of metaheuristics: all components share one variable-length encoding, the same feasibility metrics, and periodic exact reevaluation of candidate solutions. Using the competition case data, the redesigned network reduces total cost by 27.0% relative to the six-center baseline, decreases the demand-weighted average supplier-to-center distance from 461.3 km to 53.0 km, lowers the maximum distance from 2807.22 km to 441.78 km, and raises coverage from 45.0% to 100%. Across ten independent runs, the hybrid method obtains a mean cost 10.3% below that of a standard genetic algorithm, with lower run-to-run dispersion. The results show that feasibility-aware initialization, adaptive search, and selective surrogate evaluation can support practical redesign of a strongly constrained, national-scale inbound logistics network. The directly attached reproducibility package provides the MATLAB implementation and the seven supplied input workbooks used by the reported model. The evidence is limited to one deterministic competition instance, a fixed cost schedule, and fixed-topology sensitivity calculations; generalization under demand uncertainty, facility disruption, and alternative road conditions remains to be tested. Full article

Global biodiversity policy increasingly depends on community-led conservation, yet the comparative evidence base contains little from South Asia’s frontier regions. This article asks how a long-running grassroots organisation in a politically and ecologically marginal region combined community mobilisation, vernacular knowledge, scientific evidence, and engagement with public institutions in pursuing conservation outcomes, and which features of that process may be relevant beyond Northeast India. Four campaigns of Nature’s Beckon, founded in Dhubri, Assam, in 1982, are compared as distinct types of intervention: species-led protected-area mobilisation at Chakrashila; landscape-scale conservation against extractive pressure at Dihing Patkai; species research with public ecological education; and community-managed institution-building. The available evidence indicates a documented and substantial, though not exclusive, role in campaigns associated with the notification of two protected areas whose current notified areas total approximately 279.83 km². Advocacy alone does not adequately explain these outcomes: where a formal government decision was required, sustained organisational capacity became consequential only when it coincided with a favourable political and administrative opening. Measured against four design features associated with successful community-based conservation, the model corresponds strongly to capacity-building investment and external linkage, in qualified form to equitable benefit-sharing, and only partly to tenure security. The article develops an ecology of the margins framework and specifies which elements appear transferable and which do not. Full article

Magnesium oxychloride (MOA) adhesive plywood represents a novel inorganic matrix panel technology that eliminates organic volatile compounds from the adhesive system and avoids high-temperature hot pressing, potentially offering significant carbon footprint advantages. This study presents a comparative life cycle carbon footprint assessment of conventional urea–formaldehyde (UF) plywood and MOA plywood manufactured in China, using 1 m³ of a finished panel as the functional unit under a cradle-to-grave system boundary, comprising the production stage (Modules A1–A3)—explicitly including forestry operations (silviculture, felling, extraction/forwarding, loading and log haulage) and veneer manufacture within Module A1, now reported as a disaggregated inventory and delimited in a system boundary diagram—and the end-of-life stage (Modules C2–C4), evaluated across three end-of-life (EOL) scenarios: incineration, landfill, and mechanical recycling. Foreground data (process energy, adhesive formulation, transport distances) are metered/primary data collected over a full production year at a single large-scale plywood plant in Suqian, Jiangsu; background data are from ecoinvent v3.9.1 (cut-off), characterised with IPCC AR6 GWP100. Results indicate that MOA plywood generates approximately 253 kg CO₂-e/m³ at the production stage (A1–A3), compared with 301 kg CO₂-e/m³ for UF plywood, a reduction of 15.8% (47.5 kg CO₂-e/m³). Contribution analysis attributes virtually the entire gap to process energy (steam 65.7%, electricity 34.3%), while adhesive raw materials and inbound transport cancel to within rounding, demonstrating that the advantage is a process energy rather than a green chemistry phenomenon. A parameter-specific one-at-a-time analysis and a 200,000-run Monte Carlo simulation with triangular distributions show no reversal of the UF–MOA ranking in any of the 200,000 realisations within the adopted uncertainty ranges, with an approximately 56 kg CO₂-e/m³ median advantage (5th–95th percentile of about 31–85). Under EOL incineration, MOA plywood retains a substantial advantage even after the newly quantified burden of flue gas HCl neutralisation (13.3 kg CO₂-e/m³) and inorganic residue management (0.9 kg CO₂-e/m³) arising from the chloride content of the Sorel cement binder are charged to the MOA system. Under landfill, both products behave similarly, as wood carbon dynamics dominate. A break-even analysis shows that the service life of MOA plywood would have to fall below 25.3 years (against a 30-year reference) for its cradle-to-gate advantage to be erased. These findings clarify the lifecycle trade-offs of inorganic adhesive plywood and provide actionable data for environmental product declarations and procurement frameworks. Full article

Satellite precipitation products like GPM IMERG are crucial for hydrological modeling and disaster prevention; yet, their reliability in complex mountainous monsoon regions remains challenging. While the latest IMERG V07 introduces key upgrades, including a Climatological Calibration Algorithm (CCA), its cross-scale error propagation mechanisms and performance heterogeneity in complex underlying surfaces are poorly understood. This study evaluates the daily and monthly performance of IMERG V07 and V06 (Early, Late, and Final Runs) from 2014 to 2020 against 91 rain gauges in Guangxi, China—a typical mountainous monsoon region. The evaluation employs multiple statistical metrics and a multi-dimensional stratification approach based on elevation, precipitation intensity, and seasonality to quantify error propagation and climate-topography coupling effects. The results reveal that V07, particularly the Late Run, enhances daily precipitation detection capabilities, it significantly increases the proportion of systematic positive bias from 62.3 to 64.8% (V06) to 67.2–68.9% (V07). Consequently, upon temporal aggregation to the monthly scale, this systematic overestimation is severely amplified, leading to degraded performance, with the Final Run suffering the most substantial accuracy loss. Furthermore, retrieval accuracy is heavily constrained by surface heterogeneity, with systematic overestimation surging in areas where relatively dry (mean annual precipitation < 1300 mm) and complex terrain (elevation 100–500 m) coincide. The introduced CCA effectively improved dry season estimations but failed during wet season by introducing substantial positive biases. Ultimately, while V07 better captures short-term precipitation dynamics, its structural systematic biases compromise long-term cumulative reliability, highlighting the necessity for physics-based bias correction in hydrological applications and dynamic calibration in future algorithm upgrades. Full article

Funeral-service facility relocation redistributes spatial burdens and public benefits among origin-site residents, destination communities, service users, and the wider public. Using the Xihuayuan–Haping Road relocation in Harbin, China, this study applies an LLM-assisted multi-actor scenario reasoning framework, operationalized as a structured comparative scenario analysis, to examine relocation governance from a spatial justice perspective. Six governance variables were organized into a 3⁶ full-factorial design, producing 729 scenarios. Each scenario was generated through a six-actor, six-stage LLM interaction and assessed by a separate standardized post-simulation LLM evaluation for NIMBY conflict intensity, relocation progress, resident acceptance, and spatial justice. The results show that new-site burden fairness produced the largest reduction in conflict intensity and the strongest improvement in resident acceptance, whereas siting-process transparency showed the largest improvement in relocation progress and spatial justice. Repeated runs of nine typical configurations and one case-approximate configuration showed point-score variation but retained the broad contrast between weaker and stronger governance conditions. The case-based findings indicate that relocation planning should combine burden fairness, procedural transparency, psychological buffering, service continuity, and public return rather than rely on technical compliance or site-selection standards alone. Full article

Background: Handgrip strength has been proposed as an objective marker of post-COVID functional impairment, but its contribution relative to fatigue and sleep quality has not been formally evaluated in Latin American populations. Methods: We conducted an exploratory cross-sectional analysis of 130 adults with post-COVID condition in Palmira, Colombia. The outcome was any functional limitation on the Post-COVID Functional Status (PCFS) scale (grades 1–4 versus grade 0). Eight predictors were pre-specified on clinical grounds before examining outcome associations, and ridge-penalized logistic regression was pre-specified as the primary model. Sample size adequacy followed the criteria of Riley et al. Internal validation used bootstrap optimism correction (B = 1000), re-running the complete pipeline within each replicate. We assessed calibration, decision curves, prediction stability, SHapley Additive exPlanations (SHAP) with bootstrap rank intervals, and subgroup performance. Reporting followed TRIPOD + AI; risk of bias was self-assessed with PROBAST + AI. Results: Functional limitation affected 91/130 participants (70.0%). The minimum sample required for eight parameters was 566; the cohort met 23.0% of this requirement, so the analysis is exploratory. The optimism-corrected area under the curve was 0.748 (95% confidence interval (CI) 0.669–0.830), with calibration slope 1.15 (0.71–1.69). Fatigue ranked first in SHAP importance (54.0% of resamples), whereas grip strength ranked fifth (median rank 6). Net benefit exceeded both default strategies between thresholds 0.38 and 0.88. Thirty percent of participants changed classification in over 20% of resamples. Conclusions: Fatigue, sleep quality and acute-phase severity, rather than grip strength, emerged as the most influential correlates. These hypothesis-generating findings require confirmation in adequately powered cohorts. Full article