Search Results (1,286)

As extreme weather events increasingly threaten global food systems, accurately assessing climate risks and predicting regional crop yields remains a critical challenge. Conventional prediction models often rely on direct weather-to-yield relationships, bypassing continuous crop physiological responses and limiting their capacity to capture fine-grained temporal impacts of meteorological anomalies. To address this, we propose a novel two-stage spatiotemporal functional framework that integrates high-resolution daily weather trajectories with satellite-derived indicators, utilizing the Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) to represent canopy structural vigor and hydraulic status, respectively. In the first stage, a Historical Functional Linear Model (HFLM) dynamically maps daily meteorological trajectories (temperature, precipitation, and solar radiation) onto continuous physiological curves under strict temporal causality constraints. This generates bivariate coefficient surfaces that reveal dynamic windows of vulnerability and capture divergent, lagged physiological responses to climate stress. In the second stage, a spatially heterogeneous functional additive model integrates these weather-shaped physiological trajectories alongside raw meteorological dynamics as joint predictors for county-level yields. By extracting functional principal components and modeling flexible non-linear biological responses while accounting for continuous spatial heterogeneity, this dual-channel frameworkcaptures key aspects of both chronic physiological stress and acute meteorological shocks. Validated across a 25-year (2000–2024) U.S. Corn Belt panel, the proposed DC-FAM achieves a mean weighted mean squared prediction error (WMSPE) of 242.33 (bu/acre)² and a median out-of-sample $R_{\mathrm{cv}}^2$ of 0.422, outperforming all benchmarks including a random forest. Attribution of the 2012 flash drought further demonstrates the framework’s capacity to mechanistically trace the complete disaster propagation chain from anomalous spring warming to mid-summer hydraulic failure. The proposed framework provides a transparent, biophysically grounded tool for decoding dynamic climate stress trajectories and disaster propagation chains, offering potential implications for adaptive farm management and precision agricultural insurance. Full article

Photovoltaic (PV) generation and electric vehicle (EV) charging infrastructure are changing the dynamic behavior of current power systems, especially in terms of voltage stability and LVRT capabilities. In this work, 50% PV penetration on a modified Kundur two-area power system was tested to mitigate transient instability under severe fault circumstances. With PV units running at unity power factors under steady-state conditions, 50% PV penetration was defined relative to the system’s total active load demand. A steady-state power-flow study ensured generation–load balance before MATLAB/Simulink dynamic simulations. Controllable reactive power compensation was used as an EV aggregator on Bus 7. We constructed and evaluated a genetic algorithm (GA)-optimized fractional-order proportional–integral–derivative (FOPID) controller with a traditional PID controller utilizing identical optimization conditions. An inter-area tie-line critical three-phase fault was applied and removed after 100 ms to evaluate system performance. While the GA-PID controller increased transient performance, it did not restore system stability. Instead, the GA-FOPID controller provided superior dynamic support by restoring Bus 7 voltage to 0.9–1.1 pu within 250 ms after fault clearance and maintaining about 95% LVRT compliance. The suggested controller also reduced rotor angle oscillations and enhanced inter-area damping. Fractional-order control increased EV aggregators’ reactive power response during transient shocks. Thus, in renewable-energy-dominated power systems, the GA-FOPID-controlled EV support technique may improve voltage stability and LVRT compliance. Full article

Background: Infectious diseases remain a leading cause of mortality in South Africa, compounded by a high HIV prevalence. This study aimed to delineate the spectrum and clinicopathological characteristics of fatal infectious diseases through a postmortem audit to inform clinical practice and public health strategy. Methods: A retrospective, cross-sectional descriptive study was conducted on all autopsies with a final cause of death attributed to infectious disease at a National Health Laboratory Service, in Northern Pretoria, Gauteng, South Africa, from 2012 to 2021. Using the Systematised Nomenclature of Medicine Clinical Terms (SNOMED) code and word search engines codes, 55 cases were identified. Data on demographics, clinical presentation, HIV status, antiretroviral therapy (ART), comorbidities, and final autopsy diagnosis were extracted from the laboratory information system. Histological confirmation was performed using standard stains. Descriptive statistical analysis was conducted using STATA-18. Results: The cohort (n = 55) had a median age of 31 years (IQR 19–45) and was predominantly female (67%). HIV prevalence was 35%, with 68% of those on ART. The leading cause of death was multilobar pneumonia (36%), followed by bronchopneumonia (22%). AIDS-defining illnesses were present in 27% of cases, with disseminated tuberculosis being the most common (46%). Septic shock was identified in 18% of decedents. A significant proportion (60%) of the cohort was HIV-negative. Conclusions: This autopsy series reveals a high burden of fatal community-acquired pneumonias and HIV-associated opportunistic infections, with a notable proportion of deaths occurring in HIV-negative individuals. The findings underscore diagnostic gaps and highlight the critical role of autopsy in accurate mortality surveillance, advocating for enhanced antemortem diagnostic protocols and targeted public health interventions. Full article

This study provides strong evidence of structural asymmetries between religious and non-religious tourism demand in Saudi Arabia over the period 2015Q1–2024Q4. The unit root results indicate that all variables are integrated of order one, supporting the application of the ARDL framework. The bounds test confirms the existence of a long-run equilibrium relationship for both religious and non-religious tourism. However, the strength and determinants of these relationships differ across tourism segments, providing evidence of structural heterogeneity in tourism demand. The empirical findings show that global oil prices do not have a statistically significant direct effect on either tourism segment in both the short run and the long run, suggesting that their influence is indirect and transmitted through broader macroeconomic channels. In contrast, non-oil GDP exerts a positive effect on non-religious tourism and remains weakly significant in the long run, highlighting the critical role of economic diversification and sustained income growth under Vision 2030. Religious tourism, however, remains largely unaffected by economic growth, reflecting its institutional and policy-driven nature. The COVID-19 pandemic had a severe and persistent negative impact on tourism demand, with a more immediate and pronounced effect on religious tourism due to the suspension of Hajj and Umrah activities. Adjustment dynamics indicate that both tourism segments converge toward their long-run equilibrium following short-run shocks, although religious tourism exhibits a somewhat faster speed of adjustment. Diagnostic tests confirm that all econometric assumptions are satisfied, supporting the robustness and reliability of the results. Full article

Accurate forecasting of hourly electricity consumption is critical for smart grid management, energy market operations, national policy planning, and—particularly for import-dependent economies such as Türkiye—energy security. This study presents, to the best of the authors’ knowledge, the first systematic benchmark of four state-of-the-art time series architectures—TimesNet, PatchTST, iTransformer, and Temporal Fusion Transformer (TFT)—conducted specifically on a national-scale Turkish multivariate energy dataset from the Energy Exchange Istanbul (EPİAŞ), covering 72,322 hourly observations across 15 generation, consumption, and market-clearing price variables from January 2018 to April 2026. While benchmark studies of Transformer-based architectures exist on general time-series datasets, no prior work has applied this specific combination of architectures to the EPİAŞ dataset under unified experimental conditions with an explicit energy-security interpretation. All models were trained under standardized preprocessing (StandardScaler), a 24 h lookback window, and systematic hyperparameter optimization. Experimental results demonstrate that iTransformer achieves the best predictive performance (MAE = 521.34 MWh, RMSE = 748.12 MWh, R² = 0.9881, MAPE = 1.34%), followed by TFT (R² = 0.9863) and PatchTST (R² = 0.9844). TimesNet, while the most computationally efficient, achieves an R² of 0.9791. Beyond predictive benchmarking, this study situates the findings within Türkiye’s energy security agenda: the dataset captures fossil fuel dependency, the growing share of domestic renewables, and market-clearing price dynamics shaped by geopolitical shocks, including the Russo–Ukrainian war and evolving EU–Türkiye energy relations. Comprehensive analysis of model architectures, attention mechanisms, temporal feature importance, and computational efficiency is provided. These findings establish a rigorous baseline for deploying modern sequence models in large-scale, real-time national energy forecasting systems that serve both market-efficiency and strategic-energy-autonomy objectives. The results specifically highlight how high-fidelity forecasting can serve as a risk-mitigation tool against geopolitical supply disruptions by quantifying the impact of domestic renewable integration. Full article

Cold-chain supply systems depend on a sequence of linked production and logistics decisions. In prepared-food cold chains, quality may deteriorate not because one visible failure occurs, but because testing, traceability records, temperature monitoring, and abnormal-condition reporting are gradually weakened under cost pressure. Once such hidden effort reduction accumulates, external disturbances may push the system from strict assurance to weakened governance. To explain this nonlinear process, an asymmetric evolutionary game is built between prepared-food producers and cold-chain logistics providers, each choosing between strict and weakened quality assurance. White Gaussian noise is introduced to represent random operating shocks, and the two-population strategy system is projected onto a system-level quality-governance coordinate, $q$. This projection is used as a transparent baseline coordinate rather than as an assumption of linear system evolution. The reduced system is then transformed into a stochastic cusp catastrophe model, with a resilience indicator used to measure the distance from critical transition conditions. Numerical simulations show that quality assurance costs and short-term cost-saving benefits move the system toward a weakened-governance basin, whereas external incentives, coordination degree, and credible accountability mechanisms support recovery toward strict collaboration. The framework offers a scenario-based resilience diagnosis approach for identifying threshold effects in cold-chain quality governance. Digital traceability, temperature-data sharing, incentive alignment, and accountability rules are further interpreted as operational innovations that improve resilience and reduce avoidable quality losses in sustainable cold-chain operations. Full article

This paper investigates the interplay between oil, critical minerals, and military expenditure in the U.S. and China. The research goal is to evaluate how sensitive the military expenditure of these countries is to shocks in energy markets. It develops a stylized dynamic model of the arms race and conflict, with a particular focus on U.S.–China tensions surrounding access to these vital resources. Empirical analysis using VAR estimations reveals that: (1) shocks to China’s military spending prompt increases in U.S. military expenditure, whereas the reverse effect is not observed; (2) critical mineral production significantly influences China’s military spending; and (3) U.S. military expenditure is affected by both Chinese military spending and fluctuations in oil prices. Full article

Ultra-high-speed rarefied gas wind tunnels (RGWTs) are critical for estimating the aerodynamic forces acting on spacecraft in very low Earth orbit (VLEO). These tunnels utilize nozzles with large expansion ratios to generate extreme freestream conditions ($Ma>20$, $Kn>1$). However, the large expansion ratio induces a multiscale flow within the nozzle that simultaneously spans the continuum and transitional regimes, making the investigation of such flows extremely challenging. The present work applies a multiscale particle method to investigate the RGWT nozzle flow in a unified manner. Simulations reveal that the nozzle flow is underexpanded and characterized by rarefaction effects, and can be categorized into a central core and a surrounding region comprising the shock wave and boundary layer. This surrounding region occupies a significant portion of the nozzle exit, notably degrading flow quality. The wall suction technique increases the uniform flow radius by 11% at a total pressure of 500 kPa, while its effectiveness is limited at 50 kPa due to heightened rarefaction. Finally, a wall smoothing technique is proposed to improve the quality of nozzle flow by recognizing that strongly rarefied flows are governed by gas-surface interactions. Full article

Against the backdrop of intensifying global climate change, climate policy uncertainty (CPU) and investor sentiment have become critical factors influencing the stability of financial markets. In this study, a quantitative index of investor sentiment is constructed using stock trading volume, turnover rate, price-to-earnings ratio, circulating market value, and the consumer confidence index. The QVAR-DY model is employed to analyze the risk contagion mechanisms among CPU, investor sentiment, and China’s financial sub-markets across different quantiles. Furthermore, five machine learning models—LSTM, BiLSTM, CNN, XGBoost, and LightGBM—are used to forecast risk spillover indices, and their performance is compared with three benchmark models (ARIMA, Persistence, and HistMean) to systematically evaluate the advantages of machine learning models in capturing tail risk spillover effects. The findings reveal significant cross-market risk contagion in financial markets, characterized by asymmetry. The level of risk spillover under extreme conditions is substantially higher than under normal conditions, indicating high sensitivity to extreme events and major policies. CPU exhibits the most pronounced spillover effect on the money market, while investor sentiment has the greatest impact on the stock market. The stock, real estate, and commodity markets act simultaneously as sources of risk and receivers of shocks. In terms of forecasting performance, LightGBM performs best under normal conditions, whereas LSTM achieves the highest prediction accuracy under extreme conditions. Full article

Against the backdrop of global energy transition and the widespread adoption of Hydrogen-Blended Natural Gas (HBNG), the safety of urban gas pipeline networks faces severe challenges. This paper systematically reviews the research progress of numerical simulation in the field of natural gas pipeline safety, focusing on its core supporting roles throughout the “Leakage–Dispersion–Evolution–Consequence” disaster chain. First, it analyzes the kinetic modeling of high-pressure leakage holes and property corrections based on real gas equations of state, elaborating on the numerical characterization of HBNG multi-component transport. Second, it compares the dispersion mechanisms and environmental coupling modeling methods in typical scenarios such as buried porous media, confined spaces in utility tunnels, underwater environments, and urban building clusters. Third, it reviews leakage monitoring technologies based on physical field simulation and data-driven approaches (e.g., Convolutional Neural Network, Long Short-Term Memory), emphasizing the value of numerical simulation in constructing digital twin training sets. Furthermore, it explores the dynamic evolution of explosion flame–shock wave interactions and the evaluation models for secondary disaster consequences. Finally, the current research status of grid-based risk pre-warning and emergency response strategies is summarized. In conclusion, numerical simulation is not only a robust method for precisely quantifying and characterizing complex physical mechanisms but also a critical technological foundation for building smart and resilient energy cities. Future research should focus on the deep coupling of multi-physics fields, physics-informed learning, and the development of system-level integrated defense systems. Full article

Mitochondrial dysfunction in colonic smooth muscle cells (SMCs) is closely associated with impaired gut motility in functional constipation (FC), but the underlying molecular mechanisms remain incompletely understood. The mitochondrial unfolded protein response (UPR^mt) is a critical pathway for maintaining mitochondrial proteostasis, and heat shock factor 1 (HSF1) acts as an important upstream regulator of this response. In the present study, we employed a loperamide-induced FC mouse model, combined with single-cell transcriptomic, molecular, and functional analyses to characterize the HSF1-UPR^mt pathway in colonic SMCs and to investigate its role in FC. Single-cell transcriptomic analysis of colon tissue from FC mice revealed marked downregulation of UPR^mt-associated genes in colonic SMCs. Immunofluorescence, Western blotting, and RT-qPCR analyses of colonic tissue confirmed that HSF1 expression was reduced in colonic SMCs, along with the downregulation of the UPR^mt components, including HSP60, mtHSP70, and LONP1. These molecular changes were accompanied by mitochondrial structural damage, seen by transmission electron microscopy, and by functional impairments, including reduced mitochondrial membrane potential, elevated mtROS production, decreased ATP levels, and diminished activities of respiratory chain complexes I–V. AAV9-mediated overexpression of HSF1 reactivated the UPR^mt pathway, improved mitochondrial function, and ameliorated constipation, whereas shRNA-mediated knockdown of HSF1 further suppressed UPR^mt activity and aggravated mitochondrial damage, indicating that HSF1 bidirectionally regulates this pathway. Complementary experiments in primary colonic SMCs confirmed that this regulatory mechanism operates in a cell-autonomous manner, as modulation of HSF1 expression produced corresponding changes in the UPR^mt pathway, in the expression of mitochondrial respiratory chain complex subunits (ATP5A, NDUFA9, COX1, SDHA, UQCRC1), and in ATP production, mirroring the in vivo findings. Collectively, these results demonstrate that HSF1 plays a pivotal role in maintaining mitochondrial homeostasis in colonic SMCs through regulation of the UPR^mt pathway and that HSF1 dysfunction is closely associated with slowed gut motility in FC. These findings offer a new mechanistic perspective on FC and point to the HSF1–UPR^mt axis as a potential therapeutic target. Full article

This study investigates the cross-border consequences of large-scale military attacks on Ukraine’s critical energy infrastructure and their implications for European energy resilience. Unlike prior research focused primarily on national-level disruption, this paper conceptualizes wartime infrastructure destruction as a source of systemic spillover risk within interconnected electricity systems. We develop an analytical framework integrating three dimensions: shock probability, structural vulnerability, and recovery capacity. Using evidence from 2022–2026 and comparative assessment of selected European Network of Transmission System Operators for Electricity (ENTSO-E) countries, we identify substantial asymmetries in exposure and resilience. Moldova appears highly vulnerable due to structural dependence and limited flexibility, whereas Poland demonstrates stronger resilience supported by diversification and institutional capacity. The findings show that shocks originating in Ukraine propagate through electricity trade flows, balancing constraints, and price volatility. The results highlight that large-scale attacks on the energy system threaten not only immediate regional security but also the long-term energy sustainability of the interconnected European network. The paper contributes to the literature by linking war-induced infrastructure damage with sustainable energy governance and by proposing resilience tools such as digital twins and blockchain coordination. The results are relevant for policymakers, transmission operators, and crisis management institutions across Europe. Full article

Background and Clinical Significance: We report an exceptionally rare case of mechanical aortic valve replacement necessitated by self-inflicted needle penetration with aortic valve and left ventricular involvement in a patient with recurrent self-harm behavior. Case Presentation: A 24-year-old female with post-traumatic stress disorder and emotionally unstable personality disorder, borderline type, presented with dyspnea two weeks after self-inserting multiple needles into her thorax. Computed tomography revealed a needle lodged in the aortic root and an intramyocardial needle with hemorrhagic pericardial effusion. Emergency sternotomy revealed inflammatory destruction of the right coronary aortic cusp with complete perforation. Following failed reconstruction attempts, mechanical aortic valve replacement was performed. The patient survived the immediate postoperative period but demonstrated recurrent non-adherence to oral anticoagulation, including multiple episodes of over- and under-anticoagulation. More than six years after surgery, she presented with cardiogenic shock due to prosthetic valve thrombosis after discontinuing warfarin for two weeks. Despite venoarterial ECMO and fibrinolytic therapy, she died from refractory left ventricular failure. Conclusions: This case highlights critical challenges in managing patients with severe psychiatric disorders requiring mechanical valve prostheses and suggests that bioprosthetic valves may warrant careful consideration in patients with major concerns regarding long-term anticoagulation adherence. Full article

This study investigates the relationship between renewable energy (RE) expansion and economic diversification in Egypt over 1990–2023 using a nonlinear autoregressive distributed lag (NARDL) framework. Egypt’s fossil fuel share stands at approximately 93% of primary energy supply, yet the country has committed to a 42% renewable electricity target by 2035. Despite quadrupling utility-scale RE capacity from 2.8 GW to 11.2 GW between 2015 and 2023, the Economic Diversification Index (EDI) has remained broadly stagnant. The bounds test confirms long-run cointegration (F = 6.760), exceeding small-sample critical values at the 1% level. Long-run estimates reveal that positive RE shocks are associated with lower diversification (θ⁺ = −0.571, p = 0.035) and negative shocks exhibit a statistically similar adverse effect (θ⁻ = −0.271, p = 0.024). Oil rents exhibit a positive long-run association (β = 0.145, p = 0.003). The error-correction term (−0.569) indicates approximately 57% annual adjustment. The Wald test provides marginal evidence against long-run symmetry (F = 2.999, p = 0.097). To complement the Granger causality analysis and address small-sample concerns, we additionally implement the Toda and Yamamoto augmented VAR procedure, which confirms robust unidirectional temporal precedence from LRE to LEDI (χ² = 23.48, p < 0.001) without reverse feedback (χ² = 2.25, p = 0.133). These patterns are interpreted through the lens of the Green Dependency Paradox—a conceptually distinct framework characterized by three mechanisms absent from classical resource curse theory: technology-mediated capital flight, procurement-induced deindustrialization, and policy-reversible lock-in operating under conditions of high import content, absent local content mandates, and fragmented industrial policy coordination. A tri-phase, evidence-grounded policy framework is proposed. All findings are explicitly conditional on Egypt’s current institutional context. Full article

Global warming-triggered heat stress severely restricts plant growth and crop productivity. Peanut (Arachis hypogaea L.), a vital oilseed and cash crop that is susceptible to high temperatures throughout its growth cycle, exhibits inhibited peg and pod development, growth retardation, and premature leaf senescence under heat stress, which ultimately causes substantial yield losses. Heat shock factors (Hsfs) serve as core regulatory modulators of plant abiotic stress tolerance, among which the HsfB subfamily exerts a critical function in thermotolerance modulation. Nevertheless, the biological functions of peanut HsfB genes remain largely uncharacterized. In the present study, a total of 16 HsfB subfamily members were identified from the peanut genome, possessing highly conserved gene structures and protein motifs. Phylogenetic analysis revealed that the peanut AhHsfB genes are classified into four distinct subfamilies. Chromosomal localization analysis indicated that these 16 AhHsfB genes are unevenly distributed across nine peanut chromosomes. Transcriptomic profiling demonstrated that the transcript levels of AhHsfB genes were significantly upregulated by 6- to 120-fold upon heat stress exposure. Subcellular localization and transcriptional activity assays further validated that AhHsfB1-5A is a nucleus-localized protein with intrinsic transcriptional activation activity. Ectopic overexpression of AhHsfB1-5A in Arabidopsis thaliana remarkably enhanced seed germination ability and antioxidant capacity under heat stress conditions, with a maximum 18.84% increase in green seedling rate. This study systematically characterizes the HsfB subfamily in peanut and elucidates the positive regulatory role of AhHsfB1-5A in plant thermotolerance. These findings deepen our understanding of the role of HsfB and provide valuable genetic resources for molecular breeding of heat-resistant peanut varieties. Full article