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This book argues that groundwater pollution risk assessment is the essential foundation of groundwater pollution prevention and control. It is on this basis that economic leverage is used to make new breakthroughs in groundwater protection and governance. Presenting a case study on the Jilin Section of the Songhua River, the book applies the overlay index method to assess the shallow groundwater pollution risk and identify high-risk areas and major pollution sources in an effort to identify the mechanism of interaction between industrial structures and groundwater pollution. Further, it proposes concrete measures for preventing and controlling groundwater pollution from an industrial economics perspective. As such, the book offers a valuable resource for all graduate students, lecturers and researchers who are interested in learning about resources and environmental economics.

As educational environments become increasingly heterogeneous, conventional teaching strategies often fall short in accommodating the diverse and evolving learning behaviors of students, particularly when individual learning preferences are ambiguous or not explicitly expressed. To address this growing complexity, we introduce SRE-TransformerNet, a robust AI-driven framework designed to foster personalized and inclusive educational experiences. This framework synergistically integrates the capabilities of Swin Transformer, ResNet, and EfficientNet, enabling it to dynamically identify and respond to variations in learning styles. To further optimize data processing, three novel preprocessing techniques are embedded into the pipeline. The Adaptive Range Scaling (ARS) method ensures consistency in feature distribution. Feature Fusion and Weight Adjustment (FFWA) enhances the relevance of selected features, while Uncertainty-Driven Transformation (UDT) is specifically designed to improve model resilience in scenarios involving incomplete or ambiguous data. To comprehensively assess the effectiveness of the model, we introduce three new performance metrics. The Categorical Similarity Score (CSS) evaluates inter-class pattern recognition, the Temporal Consistency Index (TCI) captures the model’s stability over time, and the Multi-Class Imbalance Metric (MCIM) quantifies the system’s robustness in imbalanced learning scenarios. Empirical evaluations demonstrate that SRE-TransformerNet achieves high predictive performance, with an F1-score of 0.987, AUC of 0.995, and accuracy of 0.988, alongside a recall rate of 0.986. These results underscore the model’s efficacy in minimizing misclassifications across diverse student profiles. Ultimately, the framework has strong potential to support adaptive learning systems−whether deployed in intelligent tutoring environments or large-scale e-learning platforms−offering a scalable solution for enhancing educational equity and effectiveness in real time.

Lithium-oxygen batteries with ultrahigh energy density have received considerable attention as of the future energy storage technologies. The development of effective electrocatalysts and a corresponding working mechanism during cycling are critically important for lithium-oxygen batteries. Here, a single cobalt atom electrocatalyst is synthesized for lithium-oxygen batteries by a polymer encapsulation strategy. The isolated moieties of single atom catalysts can effectively regulate the distribution of active sites to form micrometre-sized flower-like lithium peroxide and promote the decomposition of lithium peroxide by a one-electron pathway. The battery with single cobalt atoms can operate with high round-trip efficiency (86.2%) and long-term stability (218 days), which is superior to a commercial 5 wt% platinum/carbon catalyst. We reveal that the synergy between a single atom and the support endows the catalyst with excellent stability and durability. The promising results provide insights into the design of highly efficient catalysts for lithium-oxygen batteries and greatly expand the scope of future investigation. Li–O 2 batteries represent one of the promising paths toward high energy density battery systems. Here the authors synthesize single atom Co electrocatalysts to regulate the formation and decomposition of the major discharge product Li 2 O 2 , realizing high round-trip efficiency and stability in a Li–O 2 cell.

To determine the therapeutic efficacy and safety of risk‐adapted stereotactic body radiation therapy (SBRT) schedules for patients with early‐stage central and ultra‐central inoperable non‐small cell lung cancer. From 2006 to 2015, 80 inoperable T1‐2N0M0 NSCLC patients were treated with two median dose levels: 60 Gy in six fractions (range, 48‐60 Gy in 4‐8 fractions) prescribed to the 74% isodose line (range, 58%‐79%) for central lesions (ie within 2 cm of, but not abutting, the proximal bronchial tree; n = 43), and 56 Gy in seven fractions (range, 48‐60 Gy in 5‐10 fractions) prescribed to the 74% isodose line (range, 60%‐80%) for ultra‐central lesions (ie abutting the proximal bronchial tree; n = 37) on consecutive days. Primary endpoint was overall survival (OS); secondary endpoints included progression‐free survival (PFS), tumor local control rate (LC), and toxicity. Median OS and PFS were 64.47 and 32.10 months (respectively) for ultra‐central patients, and not reached for central patients. Median time to local failure, regional failure, and any distant failures for central versus ultra‐central lesions were: 27.37 versus 26.07 months, 20.90 versus 12.53 months, and 20.85 versus 15.53 months, respectively, all P < .05. Multivariate analyses showed that tumor categorization (ultra‐central) and planning target volume ≥52.76 mL were poor prognostic factors of OS, PFS, and LC, respectively (all P < .05). There was one grade 5 toxicity; all other toxicities were grade 1‐2. Our results showed that ultra‐central tumors have a poor OS, PFS, and LC compared with central patients because of the use of risk‐adapted SBRT schedules that allow for equal and favorable toxicity profiles. There is great interest in defining risk‐adapted dose‐fractionation schedules for “ultra‐central” and “central” early‐stage NSCLC. Our results showed that compared with central lesions, ultra‐central tumors have worse OS, PFS, and LC following risk‐adapted SBRT dose‐fractionation regimens. Toxicity profiles of the two groups are similar, with almost no patients having grade 3 or higher toxicity.

In situ formation of a stable interphase layer on zinc surface is an effective solution to suppress dendrite growth. However, the fast transport of bivalent Zn-ions within the solid interlayer remains very challenging. Herein, we engineer the SEI components and enable superior kinetics of Zn metal batteries under harsh conditions through regulating the sequence of interfacial chemical reaction. With the differences in chemical reactivity of trimethyl phosphate co-solvent and trifluoromethanesulfonate anions in the Zn 2+ -solvation shell, Zn 3 (PO 4 ) 2 and ZnF 2 are successively generated on Zn metal surface to form a gradient ZnF 2 –Zn 3 (PO 4 ) 2 interphase. Mechanistic studies reveal the outer ZnF 2 facilitates Zn 2+ desolvation and inner Zn 3 (PO 4 ) 2 serves as channels for fast Zn 2+ transport, contributing to long-term cycling at subzero temperatures. Impressively, the gradient SEI enables a high lifespan over 7000 hours in Zn symmetric cell and a capacity retention of 86.1% after 12000 cycles in Zn–KVOH full cell at –50 °C. Zinc batteries have received intense attentions but suffer from inferior low-temperature performance. Here, the authors constructed a gradient phosphatized interphase in situ on zinc surface to accelerate zinc-ion desolvation and transport, greatly enhancing the cycling performance at subzero temperatures.

This is the first randomised controlled trial for assessment of the immunogenicity and safety of a candidate non-replicating adenovirus type-5 (Ad5)-vectored COVID-19 vaccine, aiming to determine an appropriate dose of the candidate vaccine for an efficacy study. This randomised, double-blind, placebo-controlled, phase 2 trial of the Ad5-vectored COVID-19 vaccine was done in a single centre in Wuhan, China. Healthy adults aged 18 years or older, who were HIV-negative and previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-free, were eligible to participate and were randomly assigned to receive the vaccine at a dose of 1 × 1011 viral particles per mL or 5 × 1010 viral particles per mL, or placebo. Investigators allocated participants at a ratio of 2:1:1 to receive a single injection intramuscularly in the arm. The randomisation list (block size 4) was generated by an independent statistician. Participants, investigators, and staff undertaking laboratory analyses were masked to group allocation. The primary endpoints for immunogenicity were the geometric mean titres (GMTs) of specific ELISA antibody responses to the receptor binding domain (RBD) and neutralising antibody responses at day 28. The primary endpoint for safety evaluation was the incidence of adverse reactions within 14 days. All recruited participants who received at least one dose were included in the primary and safety analyses. This study is registered with ClinicalTrials.gov, NCT04341389. 603 volunteers were recruited and screened for eligibility between April 11 and 16, 2020. 508 eligible participants (50% male; mean age 39·7 years, SD 12·5) consented to participate in the trial and were randomly assigned to receive the vaccine (1 × 1011 viral particles n=253; 5 × 1010 viral particles n=129) or placebo (n=126). In the 1 × 1011 and 5 × 1010 viral particles dose groups, the RBD-specific ELISA antibodies peaked at 656·5 (95% CI 575·2–749·2) and 571·0 (467·6–697·3), with seroconversion rates at 96% (95% CI 93–98) and 97% (92–99), respectively, at day 28. Both doses of the vaccine induced significant neutralising antibody responses to live SARS-CoV-2, with GMTs of 19·5 (95% CI 16·8–22·7) and 18·3 (14·4–23·3) in participants receiving 1 × 1011 and 5 × 1010 viral particles, respectively. Specific interferon γ enzyme-linked immunospot assay responses post vaccination were observed in 227 (90%, 95% CI 85–93) of 253 and 113 (88%, 81–92) of 129 participants in the 1 × 1011 and 5 × 1010 viral particles dose groups, respectively. Solicited adverse reactions were reported by 183 (72%) of 253 and 96 (74%) of 129 participants in the 1 × 1011 and 5 × 1010 viral particles dose groups, respectively. Severe adverse reactions were reported by 24 (9%) participants in the 1 × 1011 viral particles dose group and one (1%) participant in the 5 × 1010 viral particles dose group. No serious adverse reactions were documented. The Ad5-vectored COVID-19 vaccine at 5 × 1010 viral particles is safe, and induced significant immune responses in the majority of recipients after a single immunisation. National Key R&D Programme of China, National Science and Technology Major Project, and CanSino Biologics.

In the realm of air combat, autonomous decision-making in regard to Unmanned Aerial Vehicle (UAV) has emerged as a critical force. However, prevailing autonomous decision-making algorithms in this domain predominantly rely on rule-based methods, proving challenging to design and implement optimal solutions in complex multi-UAV combat environments. This paper proposes a novel approach to multi-UAV air combat decision-making utilizing hierarchical reinforcement learning. First, a hierarchical decision-making network is designed based on tactical action types to streamline the complexity of the maneuver decision-making space. Second, the high-quality combat experience gained from training is decomposed, with the aim of augmenting the quantity of valuable experiences and alleviating the intricacies of strategy learning. Finally, the performance of the algorithm is validated using the advanced UAV simulation platform JSBSim. Through comparisons with various baseline algorithms, our experiments demonstrate the superior performance of the proposed method in both even and disadvantaged air combat environments.

Owing to the complex anatomical structure and biomechanics, the current standard palliative treatments for cervical spinal metastases are associated with a high risk of recurrence and complications. Stereotactic body radiotherapy (SBRT) can provide radical dose to tumors while protecting normal organs to the maximum extent. However, the efficacy and safety of SBRT for cervical spinal metastases is not well characterized. Data from 71 patients with cervical spine metastases who were treated with SBRT using CyberKnife between 2006 and 2021 were obtained from our prospectively maintained database. Primary endpoint was pain response at 12 weeks following SBRT completion; secondary endpoints included local control (LC), overall survival (OS), and adverse events. Standard‐risk patients were planned to receive 30 Gy (range 21–36) with median fractions of 3 (range 1–3) and high‐risk patients 35 Gy (range 24–50) with median fractions of 5 (range 4–5) according to the spinal cord and esophagus dose constraints. The median follow‐up time was 17.07 months (range 3.1–118.9). After 12 weeks of SBRT completion, 54 (98.2%) of 55 patients with baseline pain achieved pain response and 46 (83.6%) achieved complete pain response. LC rates were 93.1% and 90% at 1 year and 2 year, respectively. The 1‐year and 2‐year OS rates were 66.2% and 37.4%, respectively. Eight patients experienced grades 1–4 adverse events (six vertebral compression fracture [VCF], five of them had VCF before SBRT; and two hemiparesis). No grade 5 adverse events were observed. Therefore, risk‐adapted SBRT for cervical spine metastases achieved high pain control and LC rates with acceptable adverse events. Risk‐adapted SBRT for cervical spine metastases achieved high pain control and LC rates with acceptable adverse events. No grade 5 adverse events were observed. Importantly, these results were comparable regardless of spinal cord involvement.

Understanding the changing profiles of cardiovascular disease (CVD) and modifiable risk factors is essential for CVD prevention and control. We aimed to report the comprehensive trends in CVD and risk factors in China from 1990 to 2019. Data on the incidence, death, and disability-adjusted life years (DALYs) of total CVD and its 11 subtypes for China were obtained from the Global Burden of Disease Study 2019. The CVD burden attributable to 12 risk factors was also retrieved. A secondary analysis was conducted to summarize the leading causes of CVD burden and attributable risk factors. From 1990 to 2019, the number of CVD incidence, death, and DALYs considerably increased by 132.8%, 89.1%, and 52.6%, respectively. Stroke, ischemic heart disease, and hypertensive heart disease accounted for over 95.0% of CVD deaths in 2019 and remained the top three causes during the past 30 years. Between 1990 and 2019, the age-standardized rate of stroke decreased significantly (percentage of decreased incidence: -9.3%; death: -39.8%; DALYs: -41.6%), while the rate of ischemic heart disease increased (percentage of increased incidence: 11.5%; death: 17.6%; DALYs: 2.2%). High systolic blood pressure, unhealthy diet, tobacco, and air pollution continued to be the major contributors to CVD deaths and DALYs (attributing to over 70% of the CVD burden), and the high body mass index (BMI)-associated CVD burden had the largest increase between 1990 and 2019. The significant increases in the number of CVD incident cases, deaths, and DALYs suggest that the CVD burden is still a concern. Intensified strategies and policies are needed to maintain promising progress in stroke and to reduce the escalating burden of ischemic heart disease. The CVD burden attributable to risk factors has not yet made adequate achievements; even worse, high BMI has contributed to the increasing CVD burden.

The outbreak of novel infectious diseases presents major public health challenges, highlighting the urgency of accelerating vaccination efforts to reduce morbidity and mortality. Vaccine allocation has become a crucial societal concern. This paper introduces a dynamic vaccine allocation model that considers demand uncertainty and vaccination willingness, focusing on the trade-off between fairness and efficiency. We develop a multi-period dynamic vaccine allocation model, evaluating optimal strategies over different periods. The model addresses structural differences among vaccination groups, strategy selection, dynamic demand, and vaccination willingness. Our findings suggest that prioritizing efficiency in the initial outbreak stages may lead to inequitable distribution, causing adverse social impacts, while overemphasizing fairness can undermine overall utility. Therefore, we propose a dynamic optimization-based strategy balancing fairness and efficiency at different pandemic stages. Our results indicate that allocation strategies should shift from efficiency to fairness as the pandemic evolves to enhance vaccine utility. Additionally, macro-level interventions like reducing free-rider behavior and increasing vaccination convenience can improve total vaccine utility. This study offers new perspectives and methodologies for dynamic vaccine allocation, highlighting the trade-off between fairness and efficiency, providing crucial insights for policy formulation and pandemic response.