Search Results (1,032)

Global climate change has intensified urban heat exposure risks due to extreme heat events, posing significant health threats, particularly to socially vulnerable groups such as the elderly and children. However, the spatial allocation of urban public cooling resources exhibits heterogeneity, leading to insufficient or mismatched provision of cooling facilities in high heat exposure areas. Taking the central urban area of Guangzhou, China as an example, we employ the hazard–exposure–vulnerability (HEV) framework to evaluate a composite heat risk index (HRI). Using a coupling coordination degree and development coordination coefficient, we identify the matching status and temporal dynamic between heat risk and facility supply across 2010 and 2020. The results indicate that (1) HRI generally exhibits high-value clustering in the core areas of the old city, while peripheral areas show relatively lower levels; (2) the coupling coordination degree (CCD) exhibits clear spatial clustering characteristics, and highly coordinated streets are mostly concentrated in old city areas, whereas newly developed and peripheral districts generally show low coordination; and (3) from 2010 to 2020, cooling facility development in old city districts was generally proactive, while newly developed and peripheral areas exhibited slower progress relative to increasing heat risk. This study highlights the issue of adaptive imbalance in the allocation of cooling resources concerning vulnerable populations, providing guidance for future urban planning. Full article

Objectives: Hepatitis E virus (HEV) infection is associated with severe hepatitis and high mortality rates, yet vaccination coverage remains suboptimal. Investigating public preferences for HEV vaccination is critical for developing targeted prevention strategies. This study employed a discrete choice experiment (DCE) to quantify attribute preferences and willingness-to-pay (WTP) for HEV vaccination among Chinese residents (in Shaanxi Province, for example), aiming to inform evidence-based immunization policy optimization. Methods: A cross-sectional survey recruited 3300 participants using stratified random sampling. The vaccine attributes—protective efficacy, duration of protection, and out-of-pocket cost—were identified using a systematic literature review and expert consultation. A comparative analysis of preference characteristics was conducted using conditional logit (Model 1) and mixed logit (Model 2) regression models. Population heterogeneity in vaccination preferences was further analyzed using the conditional logit framework, with marginal WTP estimated using parameter coefficients. Results: Among 3199 valid responses, duration of protection (Model 2: 10-years; β = 0.456, p < 0.001) and out-of-pocket cost (Model 2: 2000–3000 CNY; β = −0.179, p < 0.001) significantly influenced vaccination decisions. Preference heterogeneity was observed: women of childbearing age prioritized longer protection (10 years; β = 0.677, p < 0.001) and were sensitive to the cost of 1000–2000 CNY (β = 0.169, p = 0.011), while urban residents valued extended protection more than rural counterparts. Conclusions: Protection duration emerged as the primary determinant of HEV vaccination preference. Policy recommendations include implementing tiered pricing strategies and targeted health education campaigns emphasizing long-term protection benefits to enhance vaccine uptake and affordability. Full article

The energy management strategy of Hybrid Electric Vehicles (HEVs) plays a key role in improving fuel economy and reducing battery energy consumption. This paper proposes a Deep Reinforcement Learning-based energy management strategy optimized by the experience pool (P-HER-DDPG), aimed at improving the fuel efficiency of HEVs while accelerating the training speed. The method integrates the mechanisms of Prioritized Experience Replay (PER) and Hindsight Experience Replay (HER) to address the reward sparsity and slow convergence issues faced by the traditional Deep Deterministic Policy Gradient (DDPG) algorithm when handling continuous action spaces. Under various standard driving cycles, the P-HER-DDPG strategy outperforms the traditional DDPG strategy, achieving an average fuel economy improvement of 5.85%, with a maximum increase of 8.69%. Compared to the DQN strategy, it achieves an average improvement of 12.84%. In terms of training convergence, the P-HER-DDPG strategy converges in 140 episodes, 17.65% faster than DDPG and 24.32% faster than DQN. Additionally, the strategy demonstrates more stable State of Charge (SOC) control, effectively mitigating the risks of battery overcharging and deep discharging. Simulation results show that P-HER-DDPG can enhance fuel economy and training efficiency, offering an extended solution in the field of energy management strategies. Full article

The energy management strategy (EMS) is a core technology for improving the fuel economy of hybrid electric vehicles (HEVs). However, the coexistence of both discrete and continuous control variables, along with complex physical constraints in HEV powertrains, presents significant challenges for the design of efficient EMSs based on deep reinforcement learning (DRL). To further enhance fuel efficiency and coordinated powertrain control under complex driving conditions, this study proposes a hierarchical DRL-based EMS. The proposed strategy adopts a layered control architecture: the upper layer utilizes the soft actor–critic (SAC) algorithm for continuous control of engine torque, while the lower layer employs a deep Q-network (DQN) for discrete gear selection optimization. Through offline training and online simulation, experimental results demonstrate that the proposed strategy achieves fuel economy performance comparable to dynamic programming (DP), with only a 3.06% difference in fuel consumption. Moreover, it significantly improves computational efficiency, thereby enhancing the feasibility of real-time deployment. This study validates the optimization potential and real-time applicability of hierarchical reinforcement learning for hybrid control in HEV energy management. Furthermore, its adaptability is demonstrated through sustained and stable performance under long-duration, complex urban bus driving conditions. Full article

Background: Hepatitis presents a major health and economic challenge in Saudi Arabia, necessitating insight into its epidemiology, risk factors, and control measures. This review aims to synthesize current evidence on the epidemiology, risk factors, and prevention strategies for viral hepatitis in Saudi Arabia. It evaluates the effectiveness of existing interventions and proposes data-driven approaches to advance national hepatitis elimination goals. Methods: This study reviewed data from 2016 to 2024, sourced from PubMed, Google Scholar, ResearchGate, and ScienceDirect, focusing on hepatitis epidemiology and prevention in Saudi Arabia. Studies relevant to Saudi-specific trends and prevention strategies were included. Results: Saudi Arabia has achieved significant reductions in viral hepatitis prevalence, notably HBV (1.3%) due to universal infant vaccination (98% coverage), and HCV (0.124%) through the Saudi National Hepatitis Program (SNHP), which provides free DAAs (95% cure rate) and has screened 5 million people. However, challenges persist: HAV susceptibility is rising in adults (seroprevalence 33.1%), HDV affects 7.7% of HBV patients, and key risk factors include socioeconomic disparities (higher HAV/HEV in rural/low-income areas), intravenous drug use (30–50% of HCV cases), unsafe medical/cultural practices (e.g., Hijama), and limited healthcare access for migrants/rural populations. While interventions like water sanitation initiatives (58% HAV decline) and prenatal screening are effective, advancing elimination goals requires addressing gaps in HDV/HEV surveillance, outdated seroprevalence data, equitable treatment access (35% lower in rural areas), stigma reduction, and targeted strategies for high-risk groups to meet WHO 2030 targets. Conclusions: Saudi Arabia has made significant progress in hepatitis control through vaccination and public health efforts, but challenges persist. Strengthening healthcare systems, improving community engagement, and ensuring equitable access are key to sustaining elimination efforts. Full article

Hybrid electric vehicles (HEVs) have gained significant attention for their superior energy efficiency and are becoming a predominant mode of urban transportation. The DC/DC converter plays a critical role in HEV energy management systems, especially in matching the voltage levels between the battery and DC bus. This paper proposes a novel high-gain DC/DC converter with a wide input voltage range based on coupled inductors. The innovation lies in the integration of a resonant cavity and the simultaneous realization of zero-voltage switching (ZVS) and zero-current switching (ZCS), effectively reducing both voltage/current stresses on the power switches and switching losses. Compared with conventional topologies, the proposed design achieves higher voltage gain without extreme duty cycles, improved conversion efficiency, and enhanced reliability. Detailed operating principles are analyzed, and design conditions for voltage stress reduction, gain extension, and soft switching are derived. The simulation model has been conducted in a PSIM environment, and a 300 W experimental prototype, implemented using a dsPIC33FJ64GS606 digital controller, has been established and demonstrates 93% peak efficiency at a 10 times voltage gain. The performance and practical feasibility of the proposed topology have been evaluated by both simulation and experiments. Full article

This study proposes a current control strategy to enhance the control stability of an interior permanent magnet synchronous motor (IPMSM) under transient conditions, such as rapid acceleration or deceleration in electric vehicle (EV) applications. Conventional current control methods provide optimal steady-state current references corresponding to torque commands using a lookup table (LUT)-based approach. However, during transitions between these reference points, particularly in the field-weakening region at high speeds, the voltage limit may be exceeded. When the voltage limit is exceeded, unstable overmodulation states may occur, degrading stability and resulting in overshoot of the inverter input current. Although ramp generators are commonly employed to interpolate between current references, a fixed ramp slope may fail to ensure a sufficient voltage margin during rapid transients. In this study, a method is proposed to dynamically adjust the rate of change of the d-axis current reference in real time based on the difference between the inverter output voltage and its voltage limit. By enabling timely field-weakening before rapid changes in speed or q-axis current, the proposed strategy maintains control stability within the voltage limit. The effectiveness of the proposed method was verified through simulations based on real vehicle driving profiles and dynamometer experiments using a 38 kW class IPMSM for a hybrid electric vehicle (HEV), demonstrating reduced input DC current overshoot, improved voltage stability, and enhanced torque tracking performance under high-speed transient conditions. Full article

In this paper, we address the problem of jerk and disturbance suppression during mode transitions in power-split hybrid electric vehicles. First, a transient switching model of the PS-HEV is developed. Next, the mechanisms underlying shock generation and the influence of disturbances on transition smoothness are analyzed. Based on this, a fixed-time dynamic coordinated control strategy is proposed, comprising a novel sliding mode control law and a fixed-time extended state observer. The proposed fixed-time sliding mode control law is independent of initial state values and ensures superior convergence performance. Meanwhile, the fixed-time extended state observer enables real-time estimation of external disturbances, thereby reducing the conservatism of the control law. Finally, simulation and hardware-in-the-loop results demonstrate that the proposed strategy markedly improves mode transition performance under various disturbance scenarios. This work provides a new perspective on hybrid mode transition control and effectively enhances transition smoothness. Full article

Compound dry and hot events or extremes (CDHEs) have emerged as major climatic threats to agricultural production and food security in the middle reaches of the Yangtze River Basin (MRYRB), a critical grain-producing region in China. However, agricultural risks associated with CDHEs, incorporating both natural and socio-economic factors, remain poorly understood in this area. Using a Hazard-Exposure-Vulnerability (HEV) framework integrated with a weighting quantification method and supported by remote sensing technology and integrated geographic data, we systematically assessed the spatiotemporal dynamics of agricultural CDHE risks and corresponding crop responses in the MRYRB from 2000 to 2019. Results indicated an increasing trend in agricultural risks across the region, particularly in the Poyang Lake Plain (by 21.9%) and Jianghan Plain (by 9.9%), whereas a decreasing trend was observed in the Dongting Lake Plain (by 15.2%). Spatial autocorrelation analysis further demonstrated a significant negative relationship between gross primary production (GPP) and high agricultural risks of CDHEs, with a spatial concordance rate of 52.6%. These findings underscore the importance of incorporating CDHE risk assessments into agricultural management. To mitigate future risks, we suggest targeted adaptation strategies, including strengthening water resource management and developing multi-source irrigation systems in the Poyang Lake Plain, Dongting Lake, and the Jianghan Plain, improving hydraulic infrastructure and water source conservation capacity in northern and southwestern Hunan Province, and prioritizing regional risk-based adaptive planning to reduce agricultural losses. Our findings rectify the longstanding assumption that hydrological abundance inherently confers robust resistance to compound drought and heatwave stresses in lacustrine plains. Full article

The mitigation of climate change impacts from the automotive sector is important for sustainable development, and for that purpose, synthetic liquid fuel vehicles (SLF-Vs) are being considered as a potential clean option alongside electric vehicles (EVs). However, the energy-intensive production of synthetic liquid fuels (SLFs) requires a thorough life-cycle analysis, as CO₂ emissions vary significantly depending on the power sources and feedstock production technologies. This study evaluates the life-cycle CO₂ emissions of SLF-Vs in Japan through long-term multiple scenarios up to 2050 and compares them with those of gasoline vehicles (GVs), hybrid electric vehicles (HEVs), and battery electric vehicles (BEVs). The results reveal that, in 2020, SLF-Vs’ life-cycle CO₂ emissions were more than 2.9 times higher than those of GVs. By 2050, SLF-Vs’ emissions could only decrease to BEV-like levels if Japan achieves significant decarbonization of its power grid. Even if hydrogen is produced via water electrolysis in Australia, where renewable energy is abundant, and then imported, emissions remain high if Japan’s power grid remains insufficiently decarbonized. This highlights the critical importance of expanding domestic decarbonized power sources, particularly renewable energy, to reduce the life-cycle CO₂ emissions of SLF-Vs in Japan. Full article

Hepatitis E virus (HEV) is an emerging zoonotic pathogen capable of both human-to-human and animal-to-human transmission. However, limited data are available regarding HEV infections in pigs in Heilongjiang Province, China. To investigate the prevalence of HEV in pigs in this region, liver samples from diseased or deceased pigs and fecal samples from healthy pigs were collected and analyzed. A total of 82 liver samples and 86 fecal samples were obtained from 13 farms and tested for HEV genotypes 3 and 4 using nested RT-PCR assays targeting the ORF2 gene. Samples with high viral loads were further subjected to direct sequencing and phylogenetic analysis. Overall, 32 samples tested positive for HEV RNA and were classified as genotype 3 or 4, with genotype 4 being the most prevalent. The identified subtypes included 3a, 4a, and 4d, among which subtype 4d was the most common. Phylogenetic analysis revealed that swine HEV genotype 3 (subtype 3a) and genotype 4 (subtypes 4a and 4d) clustered closely with reference sequences 3a/AB089824/JA10, 4a/JX9974449/NJ6, and 4d/JX997439/NJ5. These strains exhibited close genetic similarity to human HEV isolates previously reported in Tokyo, Japan, and eastern China. These findings indicate that HEV genotypes 3 and 4 are distributed in pig farms across Heilongjiang Province and suggest that zoonotic transmission between pigs and humans is frequent in China. Full article

With the significant growth in the number of PHEVs, conducting in-depth research on their CO₂ emission characteristics is essential. This study used the Horiba OBS-ONE Portable Emission Measurement System (PEMS) to measure the CO₂ emissions of three Plug-in Hybrid Electric Vehicle (PHEV) types: one Series Hybrid Electric Vehicle (S-HEV), one Parallel Hybrid Electric Vehicle (P-HEV), and one Series-Parallel Hybrid Electric Vehicle (SP-HEV), during real driving conditions. The findings show a correlation between acceleration and increased CO₂ emissions for P-HEV, while acceleration has a relatively minor impact on S-HEV and SP-HEV emissions. Under urban driving conditions, the SP-HEV displays the lowest average CO₂ emission rate. However, under suburban and highway conditions, the average CO₂ emission rates follow the order S-HEV > SP-HEV > P-HEV. An analysis of CO₂ emission factors across different road types and vehicle-specific power (VSP) ranges indicates that within low VSP intervals (VSP ≤ 0 for urban, VSP ≤ 5 for suburban, and VSP ≤ 15 for highway roads), the P-HEV exhibits the best CO₂ emission control. As VSP increases, the P-HEV’s emission factors rise under all three road conditions, with its emission control capability weakening when VSP exceeds 5 in urban, 15 in suburban, and 20 on highway roads. For the SP-HEV, CO₂ emission factors increase with VSP in urban and suburban areas but remain stable on highways. The S-HEV shows minimal changes in emission factors with varying VSP. This research provides valuable insights into the CO₂ emission patterns of PHEVs, aiding vehicle optimization and policy development. Full article

Hepatitis E virus (HEV) is a leading cause of acute viral hepatitis and is primarily transmitted via contaminated water and food. Groundwater may also serve as a potential vector for HEV transmission. This study aimed to optimize real-time polymerase chain reaction (rtPCR) for the detection of HEV, employing both TaqMan probe- and SYBR Green-based methods. A total of 12 primer sets for the TaqMan probe-based method and 41 primer sets for the SYBR Green-based method were evaluated in order to identify the optimal combinations. Primer sets #4 (TaqMan probe-based) and #21 (SYBR Green-based) demonstrated the highest sensitivity and specificity, successfully detecting HEV in artificially spiked samples at 1 fg/μL. The TaqMan probe-based method facilitated rapid detection with minimized non-specific amplification, whereas the SYBR Green-based method allowed for broader primer exploration by leveraging melting curve analysis. Despite the absence of HEV detection in 123 groundwater samples, this study underscores the value of real-time PCR for environmental monitoring and paves the way for enhanced diagnostic tools for public health applications. Full article

Currently, most studies evaluating storm surges are conducted at the provincial level, and there is a lack of detailed research focusing on cities. This paper focuses on the urban scale, using some fine-scale data of coastal areas obtained through remote sensing images. This research is based on the Hazard–Exposure–Vulnerability (H-E-V) framework and PPRR (Prevention, Preparedness, Response, and Recovery) crisis management theory. It focuses on 52 Chinese coastal cities as the research subject. The evaluation system for the disaster response capabilities of Chinese coastal cities was constructed based on three aspects: the stability of the disaster-incubating environment (S), the risk of disaster-causing factors (R), and the vulnerability of disaster-bearing bodies (V). The significance of this study is that the storm surge capability of China’s coastal cities can be analyzed based on the results of the evaluation, and the evaluation model can be used to identify its deficiencies. In this paper, these storm surge disaster response capabilities of coastal cities were scored using the entropy weighted TOPSIS method and the weight rank sum ratio (WRSR), and the results were also analyzed. The results indicate that Wenzhou has the best comprehensive disaster response capability, while Yancheng has the worst. Moreover, Tianjin, Ningde, and Shenzhen performed well in the three aspects of vulnerability of disaster-bearing bodies, risk of disaster-causing factors, and stability of disaster-incubating environment separately. On the contrary, Dandong (tied with Qinzhou), Jiaxing, and Chaozhou performed poorly in the above three areas. Full article

Helium (He) accumulation in tungsten—widely used as a plasma-facing material in fusion reactors—can lead to clustering, trap mutation, and eventual formation of helium bubbles, critically impacting material performance. To clarify the atomic-scale mechanisms governing this process, we conducted systematic molecular statics and molecular dynamics simulations across a wide range of vacancy cluster sizes (n = 1–27) and temperatures (500–2000 K). We identified the onset of trap mutation through abrupt increases in tungsten atomic displacement. At 0 K, the critical helium-to-vacancy (He/V) ratio required to trigger mutation was found to scale inversely with cluster size, converging to ~5.6 for large clusters. At elevated temperatures, thermal activation lowered the mutation threshold and introduced a distinct He/V stability window. Below this window, clusters tend to dissociate; above it, trap mutation occurs with near certainty. This critical He/V ratio exhibits a linear dependence on temperature and can be described by a size- and temperature-dependent empirical relation. Our results provide a quantitative framework for predicting trap mutation behavior in tungsten, offering key input for multiscale models and informing the design of radiation-resistant materials for fusion applications. Full article