Search Results (15,250)

Surface water extent (SWE) is a key indicator of the regional water balance in dryland environments. However, the hydrological processes regulating SWE responses remain poorly constrained. Focusing on the Mu Us Sandy Land (MUSL), this study integrates multi-source remote sensing and hydrological datasets to investigate the long-term evolution of SWE and, critically, to distinguish the hydrological linkages between SWE dynamics and water storage variability in endorheic and exorheic regions during 1987–2024. An improved water extraction method was implemented on the Google Earth Engine platform, and SWE dynamics were interpreted within a water-balance framework supported by attribution analysis using machine learning. The results show that total SWE exhibited a significant increasing trend (7.95 km² yr⁻¹, p < 0.05) during 1987–2024, primarily driven by permanent SWE, while fundamentally different hydrological regimes governed SWE evolution. In the endorheic basin, SWE exhibited strong co-variation with subsurface water storage, with soil moisture and groundwater storage changes occurring concurrently with SWE changes. In contrast, no synchronous increase in SWE with groundwater storage was observed in the exorheic region. Instead, SWE expansion was mainly associated with accelerated groundwater storage depletion and reservoir construction. These contrasting patterns indicated that SWE dynamics in the endorheic basin were primarily controlled by subsurface water storage, whereas in exorheic regions they were largely driven by human-induced water redistribution rather than increases in total water storage. These findings highlight the importance of integrated surface–subsurface water management for sustaining long-term water security under climate change and increasing human water regulation. Full article

The preventive maintenance (PM) of asphalt pavements reduces life-cycle costs and minimizes resource consumption compared with reactive rehabilitation, yet its cost-effectiveness is highly sensitive to application timing. This study develops a data-driven framework for determining optimal PM timing on Korean expressways by integrating network-level pavement management system (PMS) deterioration modeling with life-cycle cost analysis (LCCA). Using 10-year PMS time-series data from approximately 2200 asphalt pavement sections (2012–2021), a nonlinear regression of the Highway Pavement Condition Index (HPCI) yielded an exponential deterioration model with exponent β = 1.87 (R² = 0.996), confirming accelerating deterioration beyond a critical service age. The HPCI inflection coincides with the Grade-2 boundary (3.5–4.0), where surface distress growth—dominated by linear cracking (91.3% of total SD)—also peaks. A LCCA across 44 scenarios demonstrated that PM applied immediately before this acceleration onset minimizes the 40-year net present value (NPV; discount rate 4.5%). The optimal first PM application time was estimated at 10.8 years (≈56% of the 19.3-year average service life), reducing the 40-year NPV by up to 7 million KRW per section relative to the milling and overlay baseline (up to 16 million KRW in absolute NPV terms for concrete overlay sections). These findings provide a quantitative, reproducible basis for PM timing decisions applicable to the approximately 4000 km of expressway pavement managed by Korea Expressway Corporation. Full article

Tiny Machine Learning (TinyML) enables Machine Learning (ML) models to run on resource-constrained devices, which is critical for Industrial Internet of Things (IIoT) systems requiring low latency, energy efficiency, and local decision-making. Nevertheless, deploying TinyML in IIoT remains challenging due to diverse applications, hardware, frameworks, and deployment methodologies, highlighting the need for a structured and focused review. Existing review articles mainly address general IoT or edge AI, leaving a critical gap in a unified and systematic understanding of TinyML applications, system components, and methodologies within IIoT contexts. Consequently, this systematic literature review (SLR) addresses this gap by analyzing 35 peer-reviewed studies published between 2018 and 2026, offering a comprehensive and structured synthesis of TinyML-enabled IIoT systems. The selected works are synthesized across three major dimensions: applications, system components, and methodologies. In terms of applications, TinyML is primarily used for predictive maintenance, equipment monitoring, anomaly detection, energy management, and general-purpose applications. The general category captures cross-domain solutions that do not fit into a single industrial application. A comparative analysis of all application categories is conducted in terms of accuracy, latency, memory, and energy. For system components, a structured comparison shows how hardware, software, and sensing choices shape performance and applicability. Hardware platforms are grouped by microcontroller families, highlighting dominant types. Software frameworks are summarized, showing the widespread use of lightweight toolchains for on-device inference. Sensor types are categorized, with vibration sensing most common. They are supported by other sensing methods such as vision, sound (acoustic), and environmental sensors. Finally, the methodologies examined in this SLR provide a comprehensive view of the data foundations, model selection, and optimization strategies. In short, this SLR converges diverse TinyML–IIoT applications, microcontroller-based hardware, lightweight software frameworks, sensing modalities, varied datasets, and optimization strategies, while also identifying challenges and future research directions. Full article

Background: Critically ill cardiac patients who require invasive mechanical ventilation represent a high-risk population with persistently elevated in-hospital mortality, despite advances in cardiovascular and critical care management. Real-world data describing clinical profiles and prognostic patterns in this population remain limited. Objectives: The aim of this study was to characterize clinical profiles and prognostic patterns among critically ill cardiac patients requiring invasive mechanical ventilation and to identify variables associated with in-hospital mortality. Methods: We conducted a five-year retrospective observational cohort study, including 492 adult patients admitted to a tertiary cardiovascular intensive care unit who required invasive mechanical ventilation. The demographic characteristics, cardiovascular risk factors, primary cardiac diagnoses, major in-hospital complications, duration of mechanical ventilation, length of hospital stay, and in-hospital mortality were analyzed. Results: The overall in-hospital mortality was 53.9%. Acute myocardial infarction was the most frequent primary diagnosis. Advanced age, diabetes mellitus, cardiogenic shock, acute renal dysfunction, hepatic dysfunction and prolonged hospitalization were significantly associated with increased mortality (p < 0.05 for all comparisons). Cardiogenic shock showed the strongest association (p < 0.001). Ventilator-associated respiratory infections occurred in 16.9% of patients, and were associated with a prolonged hospital stay (p < 0.05), without a statistically significant association with mortality. Conclusions: Critically ill cardiac patients requiring invasive mechanical ventilation exhibit distinct high-risk clinical profiles characterized by advanced age, cardiogenic shock, metabolic comorbidities, and the development of multi-organ dysfunction. These findings highlight prognostic patterns that may support risk stratification and generate hypotheses for future prospective studies in cardiac intensive care. Full article

Microplastics (MPs) are emerging pollutants of global concern, posing significant ecological and human health risks. They are frequently detected in stormwater systems, with urban runoff serving as a major transport pathway into the environment. Green stormwater infrastructure, particularly bioretention systems (BRSs), offers a promising approach to mitigate these risks by filtering and retaining various contaminants. However, the occurrence of MPs in BRSs and their capacity to retain these pollutants remain largely unexplored in the literature, despite being critical for stormwater management and water quality protection. Therefore, this study attempted to examine the occurrence, vertical distribution, and trapping of MPs within a field-installed BRS, potentially emphasizing their role in reducing microplastic (MP) transport. Therefore, field samples were collected at depths of 2, 12, and 24 inches below the surface and processed in the laboratory for MP detection and quantification. The results revealed an average concentration of 1095 particles per kg of dried sediment, with fragments (microplastics shape) accounting for 78.54% of the total MPs. Although no clear vertical distribution pattern was observed, the initial findings showed that MPs were mostly retained at 24 inches, potentially indicating their transport through the media and the retention capacity of a BRS (surface and middle layer) in capturing microplastics from stormwater environments. However, there is no direct evidence to explain the mechanisms driving the observed concentrations at greater depths. The preliminary findings of this study highlight that the concentrations of different sizes of MPs can vary with soil depth in bioretention media. Integrating a BRS into urban stormwater infrastructure likely provides the dual benefits of improved stormwater management and reduced plastic pollution. This study underscores the importance of optimizing bioretention design and media composition to enhance MP trapping from stormwater. Full article

The Sierra Madre Occidental (SMO) is a vital biological corridor in Mexico, yet its floristic knowledge remains fragmented. This study inventories and analyzes the vascular flora of Cerro Mohinora, the highest peak in Chihuahua and a protected area critical for mountain biodiversity. Through the collection of 1200 specimens, we identified 350 taxa across 205 genera and 76 families. Asteraceae (57 taxa) and Poaceae (32) are the most species-rich, with hemicryptophytes dominating the life forms (55.7%). The native flora exhibits a predominantly Nearctic affinity (56.6%), followed by Neotropical (37.2%). Notably, 33.7% of species are endemic to Mexico, including 11.4% to the SMO and 2.9% related to microendemics. Cerro Mohinora serves as the type locality for 18 species, including Salvia reginae, which was discovered during the fieldwork of this study and formally described in 2019. It should be noted that not all of these taxa were recorded in the present survey. Regarding conservation, eight species are listed nationally and 54 internationally. Low exotic species representation (2.6%) contrasts with the vulnerability of the endemic flora. Our findings characterize Cerro Mohinora as a critical boreal refuge and an active evolutionary center, underscoring the need to strengthen conservation frameworks and management strategies to mitigate climate change impacts. Full article

Background: High-grade vaginal intraepithelial neoplasia (VaIN 2+) is a rare condition with limited evidence to guide optimal management. This study aimed to evaluate the efficacy of various treatment strategies and identify clinical risk factors associated with treatment failure. Methods: A systematic literature search in PubMed, Scopus, Web of Science, and Cochrane databases was performed following PRISMA guidelines. The meta-analysis included 15 retrospective studies including patients treated for VaIN 2+. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated for treatment modalities (laser ablation, surgical excision, topical therapy) and clinical risk factors (prior hysterectomy, multifocality, immunosuppression, HPV16 infection and history of cervical intraepithelial neoplasia (CIN)). Results: Immunosuppression was significantly associated with a higher risk of treatment failure (RR = 2.01; 95% CI 1.12–3.60; p = 0.030). Topical therapies were found to have a significantly higher risk of treatment failure compared to laser ablation (RR = 1.92; 95% CI 1.34–2.92; p = 0.009). No statistically significant difference in recurrence risk was found between laser ablation and surgical excision, and between surgical excision and topical therapy. Factors such as prior hysterectomy, multifocality, and history of CIN did not show a statistically significant association with recurrence in the pooled models. Conclusions: Immunosuppression is a critical risk factor for VaIN 2+ recurrence, highlighting the need for individualized management and closer surveillance in this population. Surgical and ablative methods appear superior to topical agents in controlling high-grade disease. Given the retrospective nature of current data, standardized prospective studies are required to refine treatment algorithms. Full article

Rapid global urbanization has exacerbated the conflict between land expansion and ecosystem carrying capacity, making the enhancement of urban land use efficiency (ULUE), a critical pathway for sustainable development. While the digital economy offers a new engine for green transition, its spatiotemporal mechanisms remain underexplored. Taking China, a representative emerging economy, as a case study, this paper investigates the impact of digital transformation on ULUE from 2013 to 2020. By integrating the Super-EBM model with GTWR, we reveal a dynamic evolution where national efficiency improves while regional polarization intensifies. A key finding challenges traditional agglomeration theory, that population density increasingly exerts a negative impact on ULUE, suggesting that congestion costs and ecological pressures are outweighing agglomeration benefits in the digital era. Furthermore, digital infrastructure demonstrates a consistent positive effect by overcoming geographical barriers, whereas environmental regulation exhibits a J-curve effect that is initially constraining but eventually boosts efficiency. These insights provide a roadmap for developing nations to leverage digital tools for balancing economic growth with ecological sustainability, emphasizing the need for spatially differentiated strategies to manage the digital divide and urban congestion. Full article

This paper explores the behavioural change process initiated within the Gdańsk Coastal City Living Lab (CCLL)—a site-based effort, initiated under the H2020 SCORE project and significantly deepened through the Horizon Europe PRO-CLIMATE project—through the lens of transforming human–nature relationships for sustainable urban biodiversity conservation. While SCORE established the technical baseline for Nature-based Solutions (NbSs), PRO-CLIMATE provides the critical behavioural framework to ensure these solutions are socially adopted and sustained. Located in a flood-prone coastal city, the Gdańsk CCLL addresses the critical need for nature-based solutions (NbSs) in minimizing the negative impacts of climate change, particularly pluvial flooding. At the heart of this initiative is a participatory change process facilitated by local Change Agents in collaboration with key stakeholders across water management, local government, academia, and civil society. Drawing on interdisciplinary insights from social science, the paper uses the Nature Futures Framework to analyse how conservation actions are influenced by the relational, intrinsic, and instrumental values that stakeholders and residents attach to nature. The paper situates these values in the Gdańsk context and examines how they shape motivations and willingness to engage in urban NbS, such as green roofs, retention parks, and rainwater gardens. The study presents qualitative findings from stakeholder engagement workshops, Change Agents’ reflections, and support mechanisms from behavioural change experts. It evaluates how behavioural change was facilitated through shared vision building, feedback loops, and trust-based relationships, and how barriers were negotiated. A key contribution of the paper is the exploration of how bottom-up and top-down processes intersect in urban adaptation strategies and how behavioural change frameworks can be designed to institutionalise sustainable human–nature interactions in urban governance. The Gdańsk case offers transferable insights for other cities facing climate vulnerabilities while striving to embed biodiversity conservation into everyday practice. Full article

This study proposes a novel transformation method for analyzing block minima using the generalized extreme value distribution (GEVD). The negative power transformation (NPT), which includes a tunable hyperparameter and reduces to the reciprocal transformation (RT) when set to 1, improves the accuracy and robustness in estimating long-term return levels (RL). Compared to traditional methods, the NPT-GEVD demonstrates lower bias, standard errors, and root mean square errors in Monte Carlo simulations. Furthermore, the NPT-GEVD provides consistent RL estimates with improved robustness across varying parameterizations and sample sizes, mainly when using L-moments for small datasets. The application of the NPT-GEVD to rainfall data from South Korea revealed that the RLs for detecting hourly cumulative rainfall threshold levels varied from 30 min to over 4 h, depending on the location and threshold. This research underscores the value of advanced transformation techniques in environmental risk management, offering critical insights for flood prediction and mitigation strategies in climate change. Full article

The release of heavy metals into the environment due to human activities is increasing, and this has led to concern about heavy-metal contamination on farmland. Prior studies have primarily focused on short-term investigations or specific pollution sources, lacking systematic monitoring of cadmium’s long-term input-output fluxes and their mass balance at the scale of a complete farmland ecosystem. This study clarified the cadmium (Cd) pollution trends for a typical paddy system in southern China. A six-year long-term monitoring study (2019–2024 inclusive) of a Cd-contaminated paddy system in Ningxiang City, Hunan Province, China, was conducted. The Cd flux dynamics for three input pathways (atmospheric deposition, irrigation water, and fertilizer) and three output pathways (crop harvesting, surface runoff, and subsurface infiltration) were investigated. The results showed that atmospheric deposition is the primary source of Cd input, accounting for 76% of total inputs, and leads to persistent net accumulation of soil Cd. Straw removal serves as the dominant output mechanism, facilitating substantial Cd removal, representing 77% of total Cd exports, while straw retention significantly reduces export fluxes. The study found that the net Cd fluxes from 2019 to 2024 were 1.994, 2.624, 8.984, 11.299, 9.944, and 20.162 g·(hm²·a)⁻¹, straw removal was primarily adopted during the period. A net flux analysis showed that progressive soil Cd accumulation had occurred over the study period. The results suggest that science-based straw management is critical when attempting to mitigate soil Cd pollution and enhance safe land utilization. These findings can be used to improve region-specific pollutant source control strategies and soil management policies. Full article

Background: Thoracentesis is pivotal in managing pleural effusion (PE), particularly in invasive mechanical ventilation (IMV), with documented improvements in respiratory mechanics, oxygenation, and hemodynamic parameters. However, its efficacy may vary based on effusion type and drained volume. Methods: A retrospective longitudinal study was conducted at a high-complexity care center in Cali, Colombia (2019–2024), including 93 (IMV) patients who underwent therapeutic thoracentesis (TT). Respiratory and hemodynamic parameters were assessed before and up to 24 h post-procedure. Stratified analysis was performed by drained volume, fluid type, and left ventricular ejection fraction (LVEF). Results: TT yielded significant improvements in fraction of inspired oxygen (FiO₂) (−4%), positive end expiratory pressure (PEEP) (−0.5 cmH₂O), and Oxygen arterial Pressure Index/Inspired Oxygen Fraction (PaO₂/FiO₂-ratio) (+27.1), with greater impact for volumes ≥500 mL and transudative PE. Patients with LVEF ≤ 40% showed increased mean arterial pressure (MAP) and PaO₂. Complication rates were low (<4%). Conclusions: TT is safe and effective in critically ill IMV patients, particularly for transudative PE and drained volumes ≥500 mL, as well as in subjects with LVEF ≤ 40%. Its positive impact on oxygenation and ventilation supports its therapeutic utility in critical care. Full article

Information security compliance has become critical for organizations worldwide, with the ISO/IEC 27000 family serving as the most widely adopted framework for establishing information security management systems. Despite their global acceptance, these standards present significant interpretation challenges due to their formal language, abstract structure, and extensive cross-referencing across 97 documents. Traditional retrieval-augmented generation (RAG) systems, which rely on independent text chunking and dense vector retrieval, prove inadequate for such highly interconnected regulatory materials, often fragmenting contextual relationships and reducing accuracy. This study introduces a privacy-preserving RAG framework that integrates LightRAG, a knowledge graph-based retrieval system, with locally hosted open-source language models. Unlike chunk-based RAG systems that treat document segments independently, the system in this study constructs a semantic knowledge graph that explicitly models relationships between clauses through typed edges representing cross-references, semantic similarity, and hierarchical dependencies. To enable rigorous evaluation, we developed a curated benchmark dataset of 222 multiple-choice questions with authoritative ground-truth answers, systematically constructed from official ISO standards, certification preparation materials, and academic sources. Through systematic evaluation on this benchmark, we show that knowledge graph-based retrieval achieves higher accuracy than chunk-based RAG and non-retrieval LLM baselines within the evaluated setup. The analysis indicates that embedding model quality is strongly associated with system performance, that hybrid retrieval modes combining local and global graph traversal tend to yield better accuracy, and that mid-sized open-source models paired with strong retrievers can approach the performance of larger proprietary systems. The best configuration achieves 90.54% accuracy, demonstrating the promising effectiveness of graph-structured retrieval for multiple-choice regulatory questions. Full article

Customer loyalty is a critical asset for the restaurant industry, yet the mechanisms linking the physical environment, price perception, and satisfaction remain underexplored in emerging Latin American gastronomy markets. This study examines the relationships among three servicescape dimensions—décor and artifacts, spatial layout, and ambient conditions—price perception, customer satisfaction, and loyalty in full-service restaurants in northern Peru (Chiclayo, Trujillo, and Piura). A cross-sectional survey was administered to 310 diners, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) with 10,000 bootstrap resamples. Results supported seven of nine direct hypotheses and three of four mediation hypotheses. Décor and artifacts and ambient conditions significantly predicted both price perception and satisfaction, while spatial layout showed no significant effect on any path. Price perception partially mediated the effect of décor and ambient conditions on satisfaction, and satisfaction partially mediated the relationship between price perception and loyalty. The satisfaction–loyalty path yielded the largest effect size (β = 0.708, f² = 0.798). Serial chain analyses revealed that the physical environment shapes diner loyalty through sequential cognitive and evaluative mechanisms. These findings offer actionable insights for hospitality managers seeking to enhance gastronomy destination competitiveness through strategic servicescape investment. Full article

Ground-level ozone (GLO₃) poses a critical threat to public health and the success of the Saudi Green Initiative, yet its long-term spatiotemporal evolution across the Arabian Peninsula remains poorly constrained. Utilizing CAMS-derived mixing ratios (1000–850 hPa) from 2003 to 2024, this study identifies a major systemic regime shift occurring in 2016–2017, marking a transition toward a more O₃-enriched atmospheric state across Saudi Arabia. While the early study period was characterized by pronounced spatial heterogeneity, post-2017 diagnostics reveal a synchronized intensification of GLO₃, particularly within the urban industrial belts of the Eastern and Western Provinces. Statistical trend metrics, including Mann–Kendall and regime-shift detection, show a persistent upward trend in GLO₃ concentrations, most significantly during winter and over the southwestern highlands. These trends are robustly coupled with increasing boundary-layer height, temperature, and UV-B radiation, alongside shifting precursor stoichiometry (CO, VOCs, NO_x) that separates titration-dominated from production-dominated regimes. Our results suggest that this mid-decade intensification reflects a convergence of anthropogenic forcing under Saudi Vision 2030 and shifting regional climatic drivers. By uncovering the transition from localized variability to kingdom-wide synchronization, this research provides a process-based foundation for targeted air quality management and the safeguarding of regional sustainability frameworks. Full article