Search Results (4,005)

Multiple uncertainties in traffic demand fluctuations and infrastructure vulnerability during seismic events pose significant challenges for the resilience assessment of highway transportation networks (HTNs). While Monte Carlo simulation remains the dominant approach for uncertainty propagation, its high computational cost limits its scalability, particularly in metropolitan-scale networks. This study proposes an EQResNet framework for accelerated post-earthquake resilience assessment of HTNs. The model integrates network topology, interregional traffic demand, and roadway characteristics into a streamlined deep neural network architecture. A comprehensive surrogate modeling strategy is developed to replace conventional traffic simulation modules, including highway status realization, shortest path computation, and traffic flow assignment. Combined with seismic fragility models and recovery functions for regional bridges, the framework captures the dynamic evolution of HTN functionality following seismic events. A multi-dimensional resilience evaluation system is also established to quantify network performance from emergency response and recovery perspectives. A case study on the Sioux Falls network under probabilistic earthquake scenarios demonstrates the effectiveness of the proposed method, achieving 95% prediction accuracy while reducing computational time by 90% compared to traditional numerical simulations. The results highlight the framework’s potential as a scalable, efficient, and reliable tool for large-scale post-disaster transportation system analysis. Full article

Background/Objectives: Mumps remains a relevant vaccine-preventable disease globally, especially in settings where immunization coverage fluctuates or vaccine-induced immunity wanes. This study aimed to assess long-term trends in mumps incidence, vaccination coverage, clinical outcomes, and demographic characteristics in the Autonomous Province of Vojvodina (AP Vojvodina), Serbia, over a 47-year period. Methods: We conducted a retrospective observational study using surveillance data from the Institute of Public Health of Vojvodina. Analyses included annual mumps incidence rates (1978–2024), coverage with mumps-containing vaccines (MuCVs; 1986–2024), monthly case counts, and individual-level case data for the 1997–2024 period. Variables analyzed included age, month of notification, gender, vaccination status, presence of clinical complications, and the method used for case confirmation. Results: Following the introduction of MuCV in 1986, the mumps incidence markedly declined, with limited resurgences in 2000, 2009, and 2012. Between 1997 and 2024, a total of 1358 cases were reported, with 62.7% occurring in males. Over time, the age distribution shifted, with adolescents and young adults being increasingly affected during the later (2011–2024) observed period. In 2012, the highest age-specific incidence was observed among individuals aged 10–19 and 20–39 years (49.1 and 45.5 per 100,000, respectively). Vaccination coverage for both MuCV doses was suboptimal in several years. The proportion of unvaccinated cases decreased over time, while the proportion with unknown vaccination status increased. Mumps-related complications—such as orchitis, pancreatitis, and meningitis—were rare and predominantly affected unvaccinated individuals: 84.2% of orchitis, 40.0% of pancreatitis, and all meningitis cases. Only two pancreatitis cases (40.0%) were reported after one MMR dose, while fully vaccinated individuals (two doses) had one orchitis case (5.3%) and no other complications. Laboratory confirmation was applied more consistently from 2009 onward, with 49.6% of cases confirmed that year (58 out of 117), and, in several years after 2020, only laboratory-confirmed cases were reported, indicating improved diagnostic capacity. Conclusions: Despite substantial progress in controlling mumps, gaps in vaccine coverage, waning immunity, and incomplete vaccination records continue to pose a risk for mumps transmission. Strengthening routine immunization, ensuring high two-dose MuCV coverage, improving vaccination record keeping, and enhancing laboratory-based case confirmation are critical. Consideration should be given to booster doses in high-risk populations and to conducting a seroepidemiological study to estimate the susceptible population for mumps in AP Vojvodina. Full article

The growing demand for power and the rising awareness of the need to reduce carbon footprints have led to wider acceptance of photovoltaic (PV)-integrated microgrids. PV-based microgrids have numerous significant advantages over other distributed energy resources; however, creating a dependable protection scheme for the DC microgrid is difficult due to the closely resembling current and voltage profiles of PV array faults and line faults in the DC network. The conventional methods fail to clearly discriminate between them. In this regard, a fault-resilient scheme exploiting the inherent characteristics of Fourier–Bessel Series Expansion and Empirical Wavelet Transform (FBSE-EWT) has been utilized in the present work. In order to enhance the efficacy of the bagging tree-based ensemble classifier, Artificial Gorilla Troop Optimization (AGTO) has been used to tune the hyperparameters. The hybrid protection approach is proposed for accurate fault detection, discrimination between scenarios (source-side fault and line-side fault), and classification of various fault types (pole–pole and pole–ground). The discriminatory attributes derived from voltage and current signals recorded at the DC bus using the hybrid FBSE-EWT have been utilized as an input feature set for the AGTO tuned bagging tree-based ensemble classifier to perform the intended tasks of fault detection and discrimination between source faults (PV array faults) and line faults (DC network). The proposed approach has been found to outperform the decision tree and SVM techniques, demonstrating reliability in terms of discriminating between the PV array faults and the DC line faults and resilience against fluctuations in PV irradiance levels. Full article

Investigating the coevolution between ecosystem services (ES) and human well-being (HWB) holds significant implications for achieving the sustainable operation of human–environment systems. However, limited research has focused on ES-HWB interactions in ecotourism-dominated counties. To address this gap, this study takes Chun’an County in Zhejiang Province, China, as a case study, with the research objective of exploring the processes, patterns, and mechanisms of the coevolution between ecosystem services (ES) and human well-being (HWB) in ecotourism-dominated counties. By integrating multi-source heterogeneous data, including land use data, the normalized difference vegetation index (NDVI), and statistical records, and employing methods such as the dynamic equivalent factor method, the PLUS model, the coupling coordination degree model, and comprehensive evaluation, we analyzed the synergistic evolution of ES-HWB in Chun’an County from 2000 to 2020. The results indicate that (1) the ecosystem service value (ESV) fluctuated between 30.15 and 36.85 billion CNY, exhibiting a spatial aggregation pattern centered on the Qiandao Lake waterbody, with distance–decay characteristics. The PLUS model confirms ecological conservation policies optimize ES patterns. (2) The HWB index surged from 0.16 to 0.8, driven by tourism-led economic growth, infrastructure investment, and institutional innovation, facilitating a paradigm shift from low to high well-being at the county level. (3) The ES-HWB interaction evolved through three phases—disordered, antagonism, and coordination—revealing tourism as a key mediator driving coupled human–environment system sustainability via a pressure–adaptation–synergy transmission mechanism. This study not only advances the understanding of ES-HWB coevolution in ecotourism-dominated counties, but also provides a transferable methodological framework for sustainable development in similar regions. Full article

Background: Meniere’s disease is characterized by a triad of vertigo episodes, fluctuating hearing loss, and tinnitus. The disease is followed by a loss of quality of life in patients, with the severity depending on the individual and the stage of the disease. Since there are no quantitatively validated tests that connect all elements of the disease, the only source of subjective data that can be analyzed is the disease diary and questionnaires, among which the MDPOSI (Meniere’s Disease Patient-Oriented Symptom-Severity Index) stands out as a designated quality-of-life assessment tool. This study aims to evaluate the differences in the questionnaire depending on the clinical characteristics of the disease. Methods: The study recruited 60 patients, with clinical variables including age, gender, disease laterality, caloric testing results, and PTA results, the presence of spontaneous nystagmus, pathological values of calorimetric testing, or rotatory chair testing abnormalities. Results: The appearance of spontaneous nystagmus showed a significant association with worse hearing threshold values at 500 Hz (p = 0.036, OR 4.416) and higher. Worse SRT scores correlated with Q1 (p = 0.011), Q2 (p = 0.028), Q4 (p = 0.045), Q5 (p = 0.013), and the total MDPOSI score (p = 0.008, 0.339). Multivariate analysis showed that a higher total value of the MDPOSI questionnaire was statistically significantly associated with older age (p = 0.042) and spontaneous nystagmus (p = 0.037). Conclusions: There is a correlation between the clinical characteristics of Meniere’s disease and the MDPOSI questionnaire, making it useful for assessing quality of life and disease progression. Full article

The secondary metabolites of the fungus Penicillium thymicola, fumiquinazolines F and G, have antibacterial and antifungal characteristics; however, their potential anti-tumor action against human cancer cells remains unknown. The goal of our study was to determine the biological efficacy of fumiquinazolines F and G on breast and prostate cancer cells. Cancer cell proliferation and migration were monitored in real time using xCELLigence technology and flow cytometry. Alterations in mRNA and protein expression were assessed by RT-qPCR, ELISA, and Western blotting. Our data indicate that fumiquinazolines F and G are more effective in inhibiting breast cancer cell proliferation than prostate cancer cells. Fumiquinazoline F is active against both hormone-dependent epithelial MCF-7 (IC₅₀ 48 μM) and hormone-resistant triple-negative mesenchymal MDA-MB-231 breast cancer cells (IC₅₀ 54.1 μM). The metabolite has low cytotoxicity but slows cell cycle progression. In fumiquinazoline F-treated MDA-MB-231 cells, the levels of proteins implicated in epithelial–mesenchymal transition (EMT) (such as E-cadherin, vimentin, and CD44) fluctuate, resulting in a decrease in cell migratory rate and adhesion to a hyaluronic acid-coated substrate. Thus, fumiquinazolines F and G exhibit anticancer activity by inhibiting EMT, cell proliferation, and migration, hence reverting malignant cells to a less pathogenic phenotype. The compound’s multi-target anticancer profile underscores its potential for further exploration of novel EMT-regulating pathways. Full article

The safe and reliable operation of autonomous vehicles is contingent on comprehensive testing. However, the operational scenarios are inexhaustible. Corner cases, which critically influence autonomous vehicle safety, occur at an extremely low probability and follow a long-tail distribution. Corner cases can be defined as combinations of driving task and scenario elements. These scenarios are characterized by low probability, high risk, and a tendency to reveal functional limitations inherent to autonomous driving systems, triggering anomalous behavior. This study constructs a novel corner case dataset using naturalistic driving data, specifically tailored for autonomous vehicle testing. A scenario marginality quantification method is designed to analyze multi-source naturalistic driving data, enabling efficient extraction of corner cases. Heterogeneous scenarios are systematically transformed, resulting in a dataset characterized by diverse interaction behaviors and standardized formatting. The results indicate that the scenario marginality of the dataset constructed in this study is 2.78 times that of mainstream naturalistic driving datasets, and the scenarios exhibit considerable diversity. The trajectory and velocity fluctuations, quantified at 0.013 m and 0.021 m/s, respectively, are consistent with the kinematic characteristics of real-world driving scenarios. These results collectively demonstrate the dataset’s high marginality, diversity, and applicability. Full article

The uncertainties arising from high renewable energy penetration on both the generation and demand sides pose significant challenges to distribution network security. Smart microgrids are considered an effective way to solve this problem. Existing studies exhibit limitations in prediction accuracy, Alternating Current (AC) power flow modeling, and integration with optimization frameworks. This paper proposes a closed-loop technical framework combining high-confidence interval prediction, second-order cone convex relaxation, and robust optimization to facilitate renewable energy integration in distribution networks via smart microgrid technology. First, a hybrid prediction model integrating Variational Mode Decomposition (VMD), Long Short-Term Memory (LSTM), and Quantile Regression (QR) is designed to extract multi-frequency characteristics of time-series data, generating adaptive prediction intervals that accommodate individualized decision-making preferences. Second, a second-order cone relaxation method transforms the AC power flow optimization problem into a mixed-integer second-order cone programming (MISOCP) model. Finally, a robust optimization method considering source–load uncertainties is developed. Case studies demonstrate that the proposed approach reduces prediction errors by 21.15%, decreases node voltage fluctuations by 16.71%, and reduces voltage deviation at maximum offset nodes by 17.36%. This framework significantly mitigates voltage violation risks in distribution networks with large-scale grid-connected photovoltaic systems. Full article

A multilayer linear response model (MLRM) is proposed to generate time-series data based on linear response theory. The proposed MLRM is designed to generate data for anomalous dynamics by extending the conventional single-layer linear response model (SLRM) into multiple layers. While the SLRM is a linear equation with respect to external forces, the MLRM introduces nonlinear interactions, enabling the generation of a wider range of dynamics. The MLRM is applicable to various fields, such as finance, as it does not rely on machine learning techniques and maintains interpretability. We investigated whether the MLRM could generate anomalous dynamics, such as those observed during the coronavirus disease 2019 (COVID-19) pandemic, using pre-pandemic data. Furthermore, an analysis of the log returns and realized volatility derived from the MLRM-generated data demonstrated that both exhibited heavy-tailed characteristics, consistent with empirical observations. These results indicate that the MLRM can effectively reproduce the extreme fluctuations and tail behavior seen during high-volatility periods. Full article

Discovering, analyzing, and finding a key to understanding the physiological and biochemical responses that Vitis vinifera L. undertakes against drought stress is of fundamental importance for this profitable crop. Today’s considerable climatic fluctuations force researchers and farmers to focus on this issue with solutions inclined to respect the ecosystem. In this academic work, we focused on describing the drought stress consequences on several parameters of secondary metabolites on Vitis vinifera leaves (quercetins, kaempferol, resveratrol, proline, and xanthophylls) and on some ecophysiological characteristics (e.g., water potential, stomatal conductance, and leaf temperature) to compare the answers that diverse agronomic management techniques (i.e., irrigation with and without zeolite, pure zeolite and no application) could instaurate in the metabolic pathway of this important crop with the aim to find convincing and thought-provoking responses to use this captivating and versatile mineral, the zeolite known as the “magic rock”. Stressed grapevines reached 56.80 mmol/m²s gs at veraison and a more negative stem Ψ (+10.63%) compared to plants with zeolite. Resveratrol, in the hottest season, fluctuated from 0.18–0.19 mg/g in zeolite treatments to 0.37 mg/g in stressed vines. Quercetins were inclined to accumulate in response to drought stress too. In fact, we recorded a peak of quercetin (3-O-glucoside + 3-O-glucuronide) of 11.20 mg/g at veraison in stressed plants. It is interesting to note how the pool of metabolites was often unchanged for plants treated with zeolite and for plants treated with water only, thus elevating this mineral to a “stress reliever”. Full article

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

Blade tip leakage vortex (TLV) is a critical phenomenon in hydraulic machinery, which can significantly affect the internal flow characteristics and deteriorate the hydraulic performance. In this paper, the blade tip leakage flow and TLV characteristics in a novel dishwasher pump were investigated. The correlation between the vorticity distribution in various directions and the leakage vortices was established within a rotating coordinate system. The results show that the TLV in a composite impeller can be categorized into initial and secondary leakage vortices. The initial leakage vortex originates from the evolution of two corner vortices that initially form at different locations within the blade tip clearance. This vortex induces pressure fluctuations at the impeller inlet; its shedding is identified as the primary contributor to localized energy loss within the flow passage. These findings provide insights into TLVs in complex pump geometries and provide solutions for future pump optimization strategies. Full article

Mitochondria play a crucial role in adapting to fluctuating energy demands, particularly in various heart diseases. In addition to functional analyses such as the measurement of ROS or ATP, analysis of mitochondrial ultrastructure can be used to draw further conclusions about their functions and effects in tissue. In this protocol, we introduce a set of measurements to compare the ultrastructural and functional characteristics of human left ventricular mitochondria, using transmission electron microscopy (TEM). Measured parameters included mean size in µm², elongation, count, percental mitochondrial area in the measuring frame, and a conglomeration score. We also introduce a novel method of defining hydropic mitochondria as a comparable evaluation standard. With this cluster of measurement parameters, we aim to contribute a protocol for studying human mitochondrial morphology, distribution, and functionality. Full article

This work aims to solve the problem of product quality fluctuations caused by batch-to-batch variations in the adsorption capacity of activated carbon during the production of traditional Chinese medicine (TCM) injections. In this work, Shenqi Fuzheng injection was selected as an example. Diluted Shenqi Extract (DSE), an intermediate in the production process of Shenqi Fuzheng injection, was adsorbed with different batches of activated carbon. The adsorption capacities of adenine, adenosine, calycosin-7-glucoside, and astragaloside IV in DSE were selected as evaluation indices for activated carbon absorption. Characterization methods such as nitrogen adsorption, X-ray photoelectron spectrum (XPS), and Fourier transform infrared (FTIR) were chosen to explore the quantitative relationships between the properties of activated carbon (i.e., specific surface area, pore volume, surface elements, and spectrum) and the adsorption capacities of these four components. It was found that the characteristic wavelengths from FTIR characterization, i.e., 1560 cm⁻¹, 2325 cm⁻¹, 3050 cm⁻¹, and 3442 cm⁻¹, etc., showed the strongest correlation with the adsorption capacities of these four components. Prediction models based on the transmittance at characteristic wavelengths were successfully established via multiple linear regression. In validation experiments of models, the relative errors of predicted adsorption capacities of activated carbon were mostly within 5%, indicating good predictive ability of the models. The results of this work suggest that the prediction method of adsorption capacity based on the mid-infrared spectrum can provide a new way for the quality control of activated carbon. Full article

To further enhance the economic performance of fuel cell vehicles (FCVs), this study develops a model-adaptive model predictive control (MPC) strategy. This strategy leverages the dynamic relationship between proton exchange membrane fuel cell (PEMFC) output characteristics and temperature to track its optimal operating temperature (OOT), addressing challenges of temperature control accuracy and high energy consumption in the PEMFC thermal management system (TMS). First, PEMFC and TMS models were developed and experimentally validated. Subsequently, the PEMFC power–temperature coupling curve was experimentally determined under multiple operating conditions to serve as the reference trajectory for TMS multi-objective optimization. For MPC controller design, the TMS model was linearized and discretized, yielding a predictive model adaptable to different load demands for stack temperature across the full operating range. A multi-constrained quadratic cost function was formulated, aiming to minimize the deviation of the PEMFC operating temperature from the OOT while accounting for TMS parasitic power consumption. Finally, simulations under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions evaluated the OOT tracking performance of both PID and MPC control strategies, as well as their impact on stack efficiency and TMS energy consumption at different ambient temperatures. The results indicate that, compared to PID control, MPC reduces temperature tracking error by 33%, decreases fan and pump speed fluctuations by over 24%, and lowers TMS energy consumption by 10%. These improvements enhance PEMFC operational stability and improve FCV energy efficiency. Full article