Search Results (175)

Early detection of clinical deterioration in emergency department (ED) patients is critical for timely interventions. This study evaluated the predictive performance of the National Early Warning Score (NEWS) parameters using machine learning. We conducted a single-center retrospective observational study including 27,238 adult ED patients admitted to Merano Hospital (Italy) between June 2022 and June 2023. NEWS vital signs were collected at triage, and mortality at 48 h, 7 days, and 30 days was obtained from ED database. Decision tree analysis (CHAID algorithm) was used to identify predictors of mortality; 10-fold cross-validation was applied to avoid overfitting. Mortality was 0.4% at 48 h, 1% at 7 days, and 2.45% at 30 days. For 48-h mortality, oxygen supplementation (FiO₂ >21%) and AVPU = “U” were the strongest predictors, with a maximum risk of 31.6%. For 7-day mortality, SpO₂ was the key predictor, with mortality up to 48.1%. At 30 days, patients with AVPU ≠ A, FiO₂ > 21%, and SpO₂ ≤ 94% had a mortality risk of 66.7%. Decision trees revealed different cut-offs compared to the standard NEWS. This study demonstrated that for ED patients, the NEWS may require some adjustments in both the cut-offs for vital parameters and the methods of collecting these parameters. Full article

Background/Objectives: Hospitalized peripartum patients who later decompensate and require an upgrade to the intensive care unit (ICU) may have an increased risk for poor outcomes. Most of the literature regarding the need for ICU involves Modified Early Warning Scores in already hospitalized patients or the evaluation of specific comorbid conditions or diagnoses. This systematic review and meta-analysis aimed to assess the differences in clinical scores at admission among adult peripartum patients to identify the later need for ICU. Methods: We systematically searched Ovid-Medline, PubMed, EMBASE, Web of Science and Google Scholar for randomized and observational studies of adult patients ≥18 years of age who were ≥20 weeks pregnant or up to 40 days post-partum, were admitted to the wards from the emergency department and later required critical care services. The primary outcome was the Sequential Organ Failure Assessment (SOFA) score. Secondary outcomes included other clinical scores, the hospital length of stay (HLOS) and mortality. The Newcastle–Ottawa Scale was utilized to grade quality. Descriptive analyses were performed to report demographic data, with means (±standard deviation [SD]) for continuous data and percentages for categorical data. Random-effects meta-analyses were performed for all outcomes when at least two studies reported a common outcome. Results: Seven studies met the criteria, with a total of 1813 peripartum patients. The mean age was 27.2 (±2.36). Patients with ICU upgrades were associated with larger differences in mean SOFA scores. The pooled difference in means was 2.76 (95% CI 1.07–4.46, p < 0.001). There were statistically significant increases in Sepsis in Obstetrics Scores, APACHE II scores, and HLOS in ICU upgrade patients. There was a non-significantly increased risk of mortality in ICU upgrade patients. There was high overall heterogeneity between patient characteristics and management in our included studies. Conclusions: This systematic review and meta-analysis demonstrated higher SOFA or other physiologic scores in ICU upgrade patients compared to those who remained on the wards. ICU upgrade patients were also associated with a longer HLOS and higher mortality compared with control patients. Full article

Forest fires in the Hindu Kush Himalaya (HKH) region are increasing in frequency and severity, driven by climate variability, prolonged dry periods, and human activity. Nepal, a critical part of the HKH, recorded over 22,700 forest fire events in the past decade, with fire incidence nearly doubling in 2023. Despite this growing threat, operational early warning systems remain limited. This study presents Nepal’s first high-resolution early fire risk outlook system, developed by adopting the Canadian Fire Weather Index (FWI) using meteorological forecasts from the High-Impact Weather Assessment Toolkit (HIWAT). The system generates daily and two-day forecasts using a fully automated Python-based workflow and publishes results as Web Map Services (WMS). Model validation against MODIS, VIIRS, and ground fire records for 2023 showed that over 80% of fires occurred in zones classified as Moderate to Very High risk. Spatiotemporal analysis confirmed fire seasonality, with peaks in mid-April and over 65% of fires occurring in forested areas. The system’s integration of satellite data and high-resolution forecasts improves the spatial and temporal accuracy of fire danger predictions. This research presents a novel, scalable, and operational framework tailored for data-scarce and topographically complex regions. Its transferability holds substantial potential for strengthening anticipatory fire management and climate adaptation strategies across the HKH and beyond. Full article

This paper investigates the spillover effects and transmission networks of systemic risk within China’s national economic sectors under extreme conditions from both time and frequency domain perspectives, building upon the spillover index methodology and calculating the ∆CoVaR index for Chinese industries. The findings indicate the following: (1) Extreme-risk spillovers synchronize across industries but exhibit pronounced time-varying peaks during the 2008 Global Financial Crisis, the 2015 crash, and the COVID-19 pandemic. (2) Long-term spillovers dominate overall connectedness, highlighting the lasting impact of fundamentals and structural linkages. (3) In terms of risk volatility, Energy, Materials, Consumer Discretionary, and Financials are most sensitive to systemic market shocks. (4) On the risk spillover effect, Consumer Discretionary, Industrials, Healthcare, and Information Technology consistently act as net transmitters of extreme risk, while Energy, Materials, Consumer Staples, Financials, Telecom Services, Utilities, and Real Estate primarily serve as net receivers. Based on these findings, the paper suggests deepening the regulatory mechanisms for systemic risk, strengthening the synergistic effect of systemic risk measurement and early warning indicators, and coordinating risk monitoring, early warning, and risk prevention and mitigation. It further emphasizes the importance of avoiding fragmented regulation by establishing a joint risk prevention mechanism across sectors and departments, strengthening the supervision of inter-industry capital flows. Finally, it highlights the need to closely monitor the formation mechanisms and transmission paths of new financial risks under the influence of the pandemic to prevent the accumulation and eruption of risks in the post-pandemic era. Authorities must conduct annual “Industry Transmission Reviews” to map emerging risk nodes and supply-chain vulnerabilities, refine policy tools, and stabilize market expectations so as to forestall the build-up and sudden release of new systemic shocks. Full article

Background: Respiratory infections (RIs) are a common cause of care by Prehospital Emergency Medical Services (PEMS). Early Warning Scores (EWS) are tools used by PEMS to assess patients with acute pathology. However, there is little evidence of their application in RIs. The primary aim of this study was to assess the ability of five EWS to predict one-year mortality (M1Y) and two-year (M2Y) mortality in patients with suspected RI assisted by PEMS. The secondary objective was to perform a survival analysis. Methods: An observational and prospective study was conducted in adult patients with RIs transferred by EMS to their referral hospital. The variables necessary for the calculation of EWS [National Early Warning Score 2 (NEWS2), Quick Sequential Organ Failure Assessment (qSOFA) score, Quick COVID-19 Severity Index (qCSI), CURB-65 Score for Pneumonia Severity (CURB-65) and BAP-65 Score for Acute Exacerbation of COPD (BAP-65) score] were collected. The prognostic ability of the EWS was assessed by the area under the receiver operating characteristic curve (AUC). Patients were followed up and a survival study was performed. Results: A total of 819 patients met the inclusion criteria. M1Y was 55.9% and M2Y was 63.5%. BAP-65 showed the best predictive ability at both 1 and 2 years, with AUC of 0.716 and 0.711, respectively. 48.8% of deaths took place during the first month. Conclusions: BAP-65 was the score with the best ability to predict both M1Y and M2Y after the index event in patients with RIs. All other EWS analyzed showed poor performance except in patients with low comorbidity. Full article

Improved medical treatments have extended survival and life expectancy in adults with congenital heart defects (ACHD), placing greater emphasis on psychosocial health. Up to one-third of ACHD experience anxiety or depression, and half develop a mental illness during their lifetime. While there is solid evidence on the prevalence of mental health, many do not receive psychological, psychotherapeutic, or psychiatric treatment (PST) and the psychological care situation remains understudied. In a nationwide, online cross-sectional survey conducted in Q1 2024, 1486 ACHD aged 18 to 85 (M_age = 36.84 years; 60.8% female) registered in the German National Register for Congenital Heart Defects (NRCHD) completed self-report questionnaires on sociodemographics, illness identity (Illness Identity Questionnaire), mental well-being, and utilisation of PST. CHD diagnoses were determined in conformity with the International Pediatric and Congenital Cardiac Code (IPCCC) and CHD was classified according to Warnes et al. (simple/moderate/complex). Analyses included chi-square tests, t-tests, and binary logistic regression. Overall, 32.8% of participants reported current and/or previous PST (women 37.5%, men 25.3%). PST utilisation was significantly higher in those with complex (40.2%) compared to moderate (29.6%) and simple CHD (25.3%) (ps < 0.01). Primary treatment reasons were mental illness (41.7%) and CHD-related concerns (37.2%). Nearly half of treatments were self-initiated (45.8%) and about one-third were physician-recommended (30.8%). Logistic regression revealed CHD severity as a significant predictor of PST use (ps < 0.05), with lower odds for simple (OR = 0.48) and moderate (OR = 0.66) compared to complex CHD when controlling for sex (p < 0.001, OR = 1.87), age (p = 0.022, OR = 1.011), education level (ps between 0.060 and 0.780), and net income (ps < 0.05). Those receiving PST showed significantly higher maladaptive illness-identity scores (engulfment, rejection) and lower acceptance. Approximately one in three ACHD requires mental health support, particularly those with complex CHD. The CHD itself acts as a key stressor and treatment motivator. Findings underscore the need for integrated care linking cardiological and psychosocial services. Routine screening for psychological distress and low-threshold access to PST—also for patients with simple and moderate CHD—are essential to identify and address mental health needs early. Full article

Low Earth orbit (LEO) satellite networks have shown extensive application in the fields of navigation, communication services in remote areas, and disaster early warning. Inspired by multi-access edge computing (MEC) technology, satellite edge computing (SEC) technology emerges, which deploys mobile edge computing on satellites to achieve lower service latency by leveraging the advantage of satellites being closer to users. However, due to the limitations in the size and power of LEO satellites, processing computationally intensive tasks with a single satellite may overload it, reducing its lifespan and resulting in high service latency. In this paper, we consider a scenario of multi-satellite collaborative offloading. We mainly focus on computation offloading in the satellite edge computing network (SECN) by jointly considering the transmission power and task assignment ratios. A maximum delay minimization problem under the power and energy constraints is formulated, and a distributed balance increasing penalty dual decomposition (DB-IPDD) algorithm is proposed, utilizing the triple-layer computing structure that can leverage the computing resources of multiple LEO satellites. Simulation results demonstrate the advantage of the proposed solution over several baseline schemes. Full article

The developments in building information modeling (BIM) technology provide a new approach for remote real-time visualized bridge health monitoring and structural damage detection, but so far, there are scarcely any application cases of a BIM-based SHM system for butterfly arch bridges around the world. This paper reviewed the recent progress on the butterfly arch bridge and its requirements for the integration between SHM and BIM. Based on an actual project in southwest China, work on the spatial mechanical properties, the analysis of monitoring requirements, and the design of functional modules of SHM are elaborately conducted. Subsequently, the lightweight BIM is established and integrated into the web client-side of the SHM system with the skeleton-template method, CATIA platform, and sensor data. With the implementation of user-defined virtual sensor parameter linkage, the design of the specific databases is accomplished in the SQL server environment. Based on one actual incident that saw an overweight/oversize vehicle (with the weight of 80 t, 2015) pass over the arch bridge, the fuzzy relation synthesis and data cleaning method were improved to compare the standard deviation with the threshold value of the correlation degree, and a method is adopted to evaluate the structural operation behavior of the bridge and the service condition of the BIM-based SHM system after the ultra-limit accident. The study results evince the validity and efficiency of the BIM-based SHM system, which could lay a foundation for the visualized assessment and early warning system of long-span bridges. Full article

The desert locust is documented as one of the most destructive polyphagous plant pests that require preventive or proactive management practices due to its phase polyphenism, rapid breeding, transnational migration, and heavy feeding behaviour. Desert locust situation analysis, forecasting and early warning are complex due to the systemic interaction of biological, meteorological, and geographical factors that play different roles in facilitating the survival, breeding and migration of the pest. This article seeks to elucidate the factors that affect desert locust distribution and review the application of earth observation (EO) data in explaining the pest’s infestations and impact. The review presents details concerning the application of EO data to understand factors that affect desert locust breeding and migration, elaborates on impact assessment through vegetation change detection and discusses modelling techniques that can support the effective management of the pest. The review reveals that the application of EO technology is inclined in favour of desert locust habitat suitability assessment with a limited financial quantification of losses. The review also finds a progressive advancement in the use of multi-modelling approaches to address identified gaps and reduce computational errors. Moreover, the review recognises great potential in applications of EO tools, products and services for anticipatory action against desert locusts to ensure resource use efficiency and environmental conservation. Full article

The energy-saving retrofit (ESR) of existing buildings under the energy performance contracting (EPC) mode depends on the effective risk early warnings of energy service companies (ESCOs); therefore, this paper constructs an ESCO risk early warning model for energy-saving retrofit projects of existing buildings based on cloud matter element theory (CMET). The ESCO risk early warning indicator system is established according to the essential characteristics of ESR projects of existing buildings. The subjective weighting method (G1 method) and the objective weighting method (entropy weight method) are introduced to determine the comprehensive weights of ESCO risk early warning indicators. The ESCO risk warning level of ESR projects of existing buildings is evaluated based on the cloud matter element model concerning the randomness and ambiguity of the ESCO risk early warning indicators. Finally, the risk early warning model is applied to the ESCO risk management practice of an existing building ESR project in Tianjin. By comparing the actual project and the risk early warning model constructed in this paper, it is concluded that the model has high levels of feasibility, reasonableness, and efficiency. This model has scientific guidance value for ESCO enterprise risk control. Full article

Sorghum (Sorghum bicolor L.) is a globally important energy and food crop that is becoming increasingly integral to food security and the environment. However, its production is significantly hampered by various fungal phytopathogens that affect its yield and quality. This review aimed to provide a comprehensive overview of the major fungal phytopathogens affecting sorghum, their impact, current management strategies, and potential future directions. The major diseases covered include anthracnose, grain mold complex, charcoal rot, downy mildew, and rust, with an emphasis on their pathogenesis, symptomatology, and overall economic, social, and environmental impacts. From the initial use of fungicides to the shift to biocontrol, crop rotation, intercropping, and modern tactics of breeding resistant cultivars against mentioned diseases are discussed. In addition, this review explores the future of disease management, with a particular focus on the role of technology, including digital agriculture, predictive modeling, remote sensing, and IoT devices, in early warning, detection, and disease management. It also provide key policy recommendations to support farmers and advance research on disease management, thus emphasizing the need for increased investment in research, strengthening extension services, facilitating access to necessary inputs, and implementing effective regulatory policies. The review concluded that although fungal phytopathogens pose significant challenges, a combined effort of technology, research, innovative disease management, and effective policies can significantly mitigate these issues, enhance the resilience of sorghum production to facilitate global food security issues. Full article

A farm-specific early warning system has been developed to mitigate agricultural damage caused by climate change. This system utilizes weather data at the farm level to predict crop growth, forecast weather disaster risks, and provide risk alerts to farmers and local governments. For effective implementation, local governments must lead operating early warning services that reflect regional agricultural characteristics and farmers’ needs, while the central government provides foundational data. The system connects data from each region to the cloud, enabling the establishment of a nationwide integrated service operation framework that includes the central government, metropolitan cities, municipalities, and farmers. Full article

The Australian Bureau of Meteorology provides flood forecasting and warning services across Australia for most major rivers in Australia, in cooperation with other government, local agencies and emergency services. As part of this service, the Bureau issues a flood watch product to provide early advice on a developing situation that may lead to flooding up to 4 days prior to an event. This service is based on (a) an ensemble of available Numerical Weather Prediction (NWP) rainfall forecasts, (b) antecedent soil moisture, stream and dam conditions, (c) hydrological forecasts using event-based models and (d) expert meteorological and hydrological input by Bureau of Meteorology staff, to estimate the risk of reaching pre-specified river height thresholds at locations across the continent. A flood watch provides information about a developing weather situation including forecasting rainfall totals, catchments at risk of flooding, and indicative severity where required. Although there is uncertainty attached to a flood watch, its early dissemination can help individuals and communities to be better prepared should flooding eventuate. This paper investigates the utility of forecasts of daily gridded national runoff to inform the risk of riverine flooding up to 7 days in advance. The gridded national water balance model (AWRA-L) runoff outputs generated using post-processed 9-day Numerical Weather Prediction hindcasts were evaluated as to whether they could accurately predict exceedance probabilities of runoff at gauged locations. The approach was trialed over 75 forecast locations across North East Australia (Queensland). Forecast 3-, 5- and 7-day accumulations of runoff over the catchment corresponding to each location were produced, identifying whether accumulated runoff reached either 95% or 99% historical levels (analogous to minor, moderate and major threshold levels). The performance of AWRA-L runoff-based flood likelihood was benchmarked against that based on precipitation only (i.e., not rainfall–runoff transformation). Both products were evaluated against the observed runoff data measured at the site. Our analysis confirmed that this runoff-based flood likelihood guidance could be used to support the generation of flood watch products. Full article

Quantifying the dynamic changes and relationships between ecosystem services (ESs) and land use change is critical for sustainable ecosystem management and land use optimization. However, comprehensive discussions on the spatiotemporal variations of ESs and their relationships with land use intensity (LUI) are lacking, particularly in the context of significant climate warming. Systematic analyses of the forestry management unit scale are limited, leading to considerable uncertainty in sustainable ecosystem management, especially in alpine ecosystems of the Northern Hemisphere, where ESs have significantly degraded. The study focuses on the Daxing’anling forest area, Inner Mongolia (DFIAM), a representative sensitive alpine ecosystem and crucial ecological security barrier in Northern China. Utilizing the InVEST model, we analyzed the spatiotemporal variations in land use and four essential ESs, water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ), from 2013 to 2018. We also assessed the dynamic relationships between LUI and these ESs using a four-quadrant model. Our findings indicate the following: (1) Land use types in DFIAM remained relatively stable between 2013 and 2018, with forest being the dominant type (approximately 93%). During this period, areas of forest, cropland, impervious surfaces, and bare land increased, while areas of grassland, water, and wetland decreased. Although the overall change of LUI was gentle, a spatial pattern of “high in the southeast and low in the northwest” emerged, with low LUI areas showing slight expansion. (2) WY, SC, and HQ decreased, while CS increased from 2013 to 2018. The spatial distributions of these ESs showed higher values in the center and lower values at the edges, with forests demonstrating a strong capacity to provide multiple ESs. (3) The relationship between LUI and the four ESs from 2013 to 2018 was predominantly negative, primarily situated in Quadrant II, indicating that increased LUI inhibited ES supply capacity. Within Quadrant II, the distribution range of LUI, WY, and HQ decreased, while CS remained stable and SC increased. Furthermore, Quadrant III (positive correlation) accounted for a large proportion (19.23%~42.31%), highlighting the important role of non-anthropogenic factors in ES changes. Overall, most ESs in the DFAIM showed a decline while LUI remained relatively stable, with predominantly negative correlations between LUI and ESs. The increased LUI driven by human activities, and other non-human factors, may have contributed significantly to ES degradation. To improve ESs, we proposed implementing differentiated land use planning and management, systematic ecological protection and restoration strategies, a multi-level ecological early-warning monitoring and evaluation network, ecological corridors and buffer zones, and a collaborative management system with multiple participation. These results provide scientific guidance for the sustainable management of alpine ecosystems, enhancement of ESs, and formulation of land resource protection policies. Full article

Ethiopia is highly vulnerable to the effects of climate change, with the increasing geographic extent, intensity, and frequency of drought. This study aimed to examine how pastoralist communities understand climate change and its impacts. We conducted a qualitative study among pastoral communities in Ethiopia using focus group discussions with community representatives and key informant interviews with human and animal health and agriculture experts. The collected data were analyzed using qualitative content analysis. Participants viewed deforestation and population growth as the main causes of climate change. They found that climate change caused high temperatures, a shortage of rainfall, and drought. These changes affected the environment, food security, and animal health, impacting their livelihoods, health, and social systems. Coping strategies included engaging in new economic activities, environmental recovery attempts, migration, and seeking food aid for survival. They suggested providing food aid, improving access to human and animal health care, and implementing early warning systems at the community level. The pastoralists perceived that climate change destroyed the natural environment, increased food insecurity, and negatively affected social systems and health. Collaborative actions are needed to mitigate these effects, initiate local environmental adaptation mechanisms, enhance water and food security, and improve animal and human health services. Full article