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Abstract Traffic information is crucial for managing transportation and city planning, but obtaining national-scale data is difficult due to privacy concerns. Consequently, most current traffic datasets have limitations in terms of time and location coverage, leading to a lack of comprehensive public access to national traffic data. To address this issue, a multi-source highway traffic dataset has been created, featuring 2042 sensors in New Zealand over a 9-year period with 15-minute intervals and accompanying metadata. The dataset includes data of both light-duty and heavy-duty vehicles, as well as weather information like temperature and precipitation. This dataset has diverse potential research applications such as traffic flow prediction and congestion management.

Abstract Background Transcervical resection of adhesions (TCRA) is the standard treatment for intrauterine adhesion (IUA). Previous studies have shown that postoperative oral estrogen or an intrauterine physical barrier could reduce the recurrence of IUA by promoting the proliferation of the endometrium or inhibiting the reformation of adhesions. Our team designed an intrauterine stent that can release estrogen within the uterine cavity slowly. In this study, we aimed to investigate the efficacy and safety of the estrogen-releasing intrauterine system in preventing the recurrence of moderate to severe IUA. Methods This was a multicenter prospective randomized controlled 2-arm parallel trial that included patients who were diagnosed with moderate to severe IUA and who received TCRA. A total of 250 patients were randomly assigned, at a 1:1 ratio, to receive the intrauterine estrogen-releasing system or a Foley catheter balloon combined with oral estrogen therapy after surgery. The primary outcome was the rate of adhesion reduction in the two groups. The secondary outcomes included endometrial thickness at the ovulation period, menstrual improvement rates, and other reported adverse events during follow-up. Results The average daily drug release amount for all the tested stents was 0.21 mg/day. At 60 days postoperatively, the rate of adhesion reduction was significantly greater in the experimental group than in the control group (93.33% vs. 58.56%, p

Infections with vancomycin-resistant Enterococcus (VRE) have been increasingly reported, especially in immunocompromised patients. Bacteriophages (phages) are often considered as potential therapeutic candidates in treating infectious diseases. To search for therapeutic phages as antimicrobial agents for the treatment of Enterococcus faecium infections, eight E. faecium phages were isolated from the environments. One of these, phage φEc-ZZ2, which was capable of eliciting efficient lysis of E. faecium, was selected for analysis. Transmission electron microscopy revealed its resemblance to members of the family Siphoviridae, with a tail 200 nm long and an icosahedral head 45 nm in diameter. Phage φEc-ZZ2 exhibited rapid adsorption (> 99% adsorbed in 10 min), a short latency period of 20 min and a large burst size of 180 PFU/cell. Host range determination shows that φEc-ZZ2 has a relatively broader host range (specificity for 54.5% of tested E. faecium strains). Furthermore, when φEc-ZZ2 alone was incubated at different pH, the phage was stable over a wide pH range (5 to 9). These characteristics of φEc-ZZ2 will provide useful information for further research on the interaction between Enterococcus phages and their hosts. Moreover, in consideration of its pH stability and broader host range, φEc-ZZ2 may be a good candidate as a therapeutic/disinfectant agent to control nosocomial infections caused by E. faecium.

IntroductionAmid sudden public health crises, preserving the well-being and optimal working states of frontline healthcare professionals is imperative for efficaciously managing the emergences. However, there is a paucity of research investigating the health status of frontline healthcare professionals through the perspective of work–family conflict. This study sought to elucidate the complex interrelations between work–family conflict, work engagement, job burnout, and self-rated health among public health emergency responders within the context of the COVID-19 pandemic.MethodsA convenience sampling method was employed to survey 1,309 public health emergency responders at the Jilin Provincial Center for Disease Control and Prevention. An online survey was administered utilizing a self-constructed questionnaire. The hypothesized relationships between the variables were tested using structural equation modeling.ResultsThe direct impact of work–family conflict on self-rated health is not significant. The association between work–family conflicts and self-rated health was significantly mediated by work engagement and job burnout, respectively. Meanwhile, work engagement and job burnout had a chain mediating effect on work–family conflict and self-rated health.ConclusionWork–family conflict plays a critical role in shaping the health and work status of public health emergency responders during public health crises. Organizations and managers should, in their workplace management practices, focus not only on work-related factors but also give due consideration to family-related factors. Supportive policies, including family-friendly initiatives, should be developed to safeguard the health and work engagement of public health emergency responders.

This research utilized a typical solvothermal approach, by employing Na2PdCl4 as the synthetic precursor, L-ascorbic acid (AA) as the reductant agent, and polyvinylpyrrolidone (PVP) as the practical surfactant, palladium (Pd) octahedra was finally effectively synthesized by the hydrothermal and solvothermal methods. Subsequently, characterizations of Pd octahedra were conducted by using TEM, XPS, XRD, and other analytical methods. Whereafter, Pd octahedra displayed a consistent shape and size, featuring a distinctive tip-shaped structure, which conferred upon them outstanding optical absorption properties within the near-infrared (NIR) region. Consequently, under NIR laser exposure, Pd octahedra could elevate local reaction temperature via in-situ photothermal conversion, thereby stimulating the formation of active sites of Fenton catalysts. The Photo-Fenton catalytic activity of Pd octahedra was investigated by using methylene blue (MB) as a model pollutant. The degradation efficiency of MB reached 94.8 % within 35 min under 808 nm laser irradiation, and the removal rate of MB by Pd octahedra could still reach more than 90 % after five cycles of use. All the results manifest that Pd octahedra exhibit excellent purification performance for MB dyestuff wastewater.

Abstract Background Type 2 diabetes mellitus (T2DM) increases the risk of liver cancer among people living with hepatitis B virus (HBV). Our study aimed to estimate the global burden and trends of liver cancer attributable to comorbid T2DM among people living with HBV from 1990 to 2019. Methods We calculated the population attributable fractions (PAFs) of liver cancer attributable to comorbid T2DM among the burden of HBV-related liver cancer. We applied the PAFs to the burden of HBV-related liver cancer derived from the Global Burden of Disease (GBD) 2019 database to obtain the burden of liver cancer attributable to HBV–T2DM comorbidity. The prevalence, disability-adjusted life year (DALY), and deaths of liver cancer attributable to the comorbidity were assessed at the global, regional, and country levels and then stratified by the sociodemographic index (SDI), sex, and age group. Estimated annual percentage changes (EAPCs) were calculated to quantify the temporal trends. Results In 2019, the global age-standardized prevalence and DALY rates of liver cancer attributable to HBV–T2DM comorbidity were 9.9 (8.4–11.5) and 182.4 (154.9–212.7) per 10,000,000 individuals, respectively. High-income Asia Pacific and East Asia had the highest age-standardized prevalence and DALY rates of liver cancer attributable to HBV–T2DM comorbidity, respectively. From 1990 to 2019, age-standardized prevalence and DALY rates increased in 16 out of 21 GBD regions. High-income North America had the largest annual increases in both age-standardized prevalence rates (EAPC = 6.07; 95% UI, 5.59 to 6.56) and DALY rates (EAPC = 4.77; 95% UI, 4.35 to 5.20), followed by Australasia and Central Asia. Across all SDI regions, the high SDI region exhibited the most rapid increase in age-standardized prevalence and DALY rates from 1990 to 2019. Additionally, men had consistently higher disease burdens than women across all age groups. The patterns of mortality burden and trends are similar to those of DALYs. Conclusions The burden of liver cancer attributable to comorbid T2DM among people living with HBV has exhibited an increasing trend across most regions over the last three decades. Tailored prevention strategies targeting T2DM should be implemented among individuals living with HBV.

IntroductionWith the rapid development of China's pharmaceutical industry, issues of corruption and regulatory effectiveness have become increasingly prominent, posing critical challenges to public health safety and the industry's sustainable development.MethodsThis paper adopts a bounded rationality perspective and employs a game-theoretic evolutionary approach to establish a tripartite evolutionary game model involving pharmaceutical companies, third-party auditing organizations, and health insurance regulatory agencies. It analyzes the stable strategies of the parties involved and the sensitivity of key parameters within this tripartite game system.ResultsThe study reveals that adherence to health insurance regulations by pharmaceutical companies, refusal of bribes by third-party auditing organizations, and the implementation of lenient regulations by health insurance agencies can form an effective governance equilibrium. This equilibrium state contributes to reducing corruption in the pharmaceutical industry, balancing the interests of all parties, and promoting healthy industry development.DiscussionPharmaceutical companies must balance compliance costs against the risks of non-compliance benefits while maximizing profits; third-party auditing organizations need to choose between fulfilling their duties and accepting bribes, considering their economic benefits and professional reputation; health insurance regulatory agencies adjust their strategies between strict and lenient regulation to maximize social welfare. The paper suggests enhancing policy support, strengthening compliance supervision, improving audit independence, and adjusting regulatory strategies to optimize governance in the pharmaceutical industry. Additionally, the research highlights the role of collaborative efforts among the three parties in achieving sustainable governance. Furthermore, the study conducts a numerical simulation analysis to demonstrate the impact of various parameters on the evolutionary stability of the system, providing practical insights into the implementation of regulatory policies. This research offers new insights for policy formulation and governance in China's pharmaceutical sector, providing significant reference value for guiding the industry's sustainable development.

Electrochemical technology is frequently used to treat industrial dye wastewater. However, its degradation efficiency is restricted by pH, and the low current efficiency and high energy consumption limit its broader application. Based on this, we constructed an innovative electro-driven catalytic system by integrating nanotechnology with electric current. This system operates without pH constraints, has low energy consumption, and allows for the recycle and reuse of both electrodes and catalysts. Firstly, we synthesized palladium (Pd) cubes via a solvothermal method, and characterized their morphology, structural composition, and crystalline properties using transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and other methods. The prepared Pd cubes possessed dual catalytic properties of electro-driven catalysis and Fenton catalysis, achieving a synergistic degradation effect under an electric field. Subsequently, the study explored how catalysts dosage, H2O2 concentration, pH and Cl− concentration affect the catalytic rate. The optimized system was able to degrade 99.17 % of MB within 1 h and was effective against various organic pollutants. After five cycles of reuse, the recovered catalysts maintained over 90 % degradation efficiency in decomposing MB. This process realizes efficient degradation with a low concentration of catalysts, offering a novel approach for nanotechnology in wastewater treatment under electro-driven conditions.

BackgroundDiabetic retinopathy (DR) is considered one of the most severe complications of diabetes mellitus, but its pathogenesis is still unclear. We hypothesize that certain genes exert a pivotal influence on the progression of DR. This study explored biomarkers for the diagnosis and treatment of DR through bioinformatics analysis.MethodsWithin the GSE221521 and GSE189005 datasets, candidate genes were acquired from intersections of genes obtained using WGCNA and DESeq2 packages. Mendelian randomization (MR) analysis selected candidate biomarkers exhibiting causal relationships with DR. Receiver Operating Characteristic (ROC) analysis determined the diagnostic efficacy of biomarkers, the expression levels of biomarkers were verified in the GSE221521 and GSE189005 datasets, and a nomogram for diagnosing DR was constructed. Enrichment analysis delineated the roles and pathways associated with the biomarkers. Immune infiltration analysis analyzed the differences in immune cells between DR and control groups. The miRNet and networkanalyst databases were then used to predict the transcription factors (TFs) and miRNAs, respectively, of biomarkers. Finally, RT-qPCR was used to verify the expression of the biomarkers in vitro.ResultsMR analysis identified 13 candidate biomarkers that had causal relationships with DR. The ROC curve demonstrated favorable diagnostic performance of three biomarkers (OSER1, HIPK2, and DDRGK1) for DR, and their expression trends were consistent across GSE221521 and GSE189005 datasets. The calibration curves and ROC curves indicated good predictive performance of the nomogram. The biomarkers were enriched in pathways of immune, cancer, amino acid metabolism, and oxidative phosphorylation. Ten immune cell lines showed notable disparities between the DR and control groups. Among them, effector memory CD8+ T cells, plasmacytoid dendritic cells, and activated CD4+ T cells exhibited good correlation with biomarker expression. The TF-mRNA-miRNA network suggested that hsa-mir-92a-3p, GATA2, and RELA play important roles in biomarker targeting for DR. RT-qPCR results also demonstrated a notably high expression of HIPK2 in patients with DR, whereas notably low expression of OSER1.ConclusionOSER1, HIPK2, and DDRGK1 were identified as biomarkers for DR. The study findings provide novel insights into the pathogenesis of DR.

Electricity consumption behavior (ECB) clustering analysis has received much attention in recent years due to its importance in electricity market pricing, demand side management, and load forecasting. However, the existing ECB analysis methods are not only inefficient but also fail to deeply explore the behavioral logic behind ECB, resulting in clustering results are difficult to satisfy application requirements. In this paper, a multi-feature fusion ECB analysis method is proposed, which can improve efficiency and deeply dig into the behavior logic behind ECB. To improve efficiency, the maximal relevance and minimal redundancy (mRMR) feature selection algorithm is improved by the ReliefF algorithm and the maximal information coefficient (MIC) to further reduce the redundancy between electricity consumption features (ECFs). To analyze in depth the characteristics of users' electricity consumption, different external influencing factors (EIFs) such as weather, electricity price, and income are quantified and fused with ECFs for clustering analysis. A case study using a standard dataset of ECFs shows that the number of ECFs extracted by the improved mRMR feature selection algorithm proposed in this paper is only two-thirds of those extracted by the traditional mRMR algorithm with the same accuracy. Meanwhile, the data from the London area is used to evaluate the multi-feature fusion ECB analysis method proposed in this paper, the results indicate that the proposed method can effectively distinguish users with similar ECB but different reasons for electricity consumption. Furthermore, the obtained clustering results can offer more valuable references for precise power marketing and the exploration of demand response potential.

Underwater hyperspectral imaging is crucial for various marine applications, with underwater hyperspectral target detection (HTD) holding significant importance. However, existing research on underwater HTD is limited, as most methods fail to adequately consider the impact of underwater target spectral variability and image quality degradation. To address these critical issues, we propose a novel joint framework for underwater hyperspectral image restoration and target detection, which is based on a conditional diffusion model. Our proposed framework consists of two main modules: the variable spectral group extraction module, and the joint underwater hyperspectral image restoration and target detection (JURTD) module. The variable spectral group extraction module leverages the conditional diffusion model to extract variable spectral image groups, thereby simulating the diverse range of underwater target spectra. Subsequently, the JURTD module extracts deep features from intrinsic images and the group of variable spectral images. Operating under the dual constraints of image restoration and target detection, this module achieves high-quality restored images and superior detection performance concurrently. Experimental evaluations conducted on both real-world and synthetic datasets demonstrate the effectiveness of our proposed framework in enhancing image quality and improving target detection performance. Moreover, the results indicate that our framework outperforms state-of-the-art methods, underscoring its practical utility and superiority in underwater hyperspectral imaging applications.

Abstract Background Discharged psychiatric patients are at higher risk of suicide due to various risk factors in their lives compared to the general population. However, specific problems and needs of these patients after discharge remain unclear. This research constitutes a segment of a broader implementation study designed to formulate an interventional strategy targeting post-discharge suicide among Chinese psychiatric patients. The present study seeks to qualitatively investigate the problems and needs from the perspectives of patients, their lay healthcare supporters (LHSs), and mental health professionals (MPs), aiming to enhance the efficacy of the interventional strategy. Methods This study is part of a larger implementation study based on Shenzhen Kangning Hospital (SKH) in Shenzhen, Guangdong, China. Under the community-based participatory research framework, we recruited discharged psychiatric patients, their LHSs, and MPs as a collaborative community team, and we conducted individual in-depth interviews for patients and LSHs and focus group interviews with MPs. We utilized a thematic analysis approach to identify sub-themes and themes from interviews through systematically coding and analyzing the data. Results A total of 45 participants were recruited for interviews, comprising 17 patients, 8 LHSs, and 20 MPs. We conducted 25 individual in-depth interviews and 3 focus group interviews. Through the interviews, we identified three themes of post-discharge problems: problems related to self, family-related problems, societal and community-related problems. We also identified four themes related to reducing post-discharge suicide: proactive self-management, multifunctional relatives, multifunctional MP group, and a warm society. The tangible support from LHSs and emotional support from MPs are strongly emphasized. Follow-up interventions were identified as the most significant way to addressing these unmet needs. Instrumental support from the community and a caring and non-discriminatory environment for individuals with mental disorders are essential for reducing suicide risk. Conclusions Establishing an integrated mental health care service network that connects psychiatric patients, LHSs, and MPs cross community and societal sectors, with patient-centered follow-up care at its core, is a practical approach to better address patients’ needs and reduce post-discharge suicide. Trial registration Registration number: NCT04907669. Date of registration: May 26th,2021.

Abstract Background China bears a high burden of both hepatitis B virus (HBV) infection and type 2 diabetes mellitus (T2DM). T2DM accelerates the progression of liver disease among individuals infected with HBV. This study aims to assess the excess disease burden caused by comorbid T2DM among HBV-infected individuals in China. Methods We estimated the disease burden of HBV and its complications in China from 2006 to 2030 using individual-based Markov models. The baseline population consisted of 93 million HBV-infected individuals derived from the 2006 National Serological Epidemiological Survey. We developed two models: one incorporated the impact of T2DM on the disease progression of HBV infection, while the other did not consider the impact of T2DM. By comparing the outcomes between these two models, we estimated the excess disease burden attributable to comorbid T2DM among HBV-infected individuals. Results The incidence of severe HBV complications, including cirrhosis, hepatocellular carcinoma (HCC), and liver-related deaths, exhibited an increasing trend from 2006 to 2030 among the Chinese HBV-infected population. Comorbid T2DM increased the annual incidence and cumulative cases of severe HBV complications. From 2006 to 2022, comorbid T2DM caused 791,000 (11.41%), 244,000 (9.27%), 377,000 (8.78%), and 796,000 (12.19%) excess cases of compensated cirrhosis, decompensated cirrhosis, HCC, and liver-related deaths, respectively. From 2023 to 2030, comorbid T2DM is projected to result in an 8.69% excess in severe HBV complications and an 8.95% increase in liver-related deaths. Among individuals aged 60 and older at baseline, comorbid T2DM led to a 21.68% excess in severe HBV complications and a 28.70% increase in liver-related deaths from 2006 to 2022, with projections indicating a further 20.76% increase in severe HBV complications and an 18.31% rise in liver-related deaths over the next seven years. Conclusions Comorbid T2DM imposes a substantial disease burden on individuals with HBV infection in China. Healthcare providers and health policymakers should develop and implement tailored strategies for the effective management and control of T2DM in individuals with HBV infection.

Abstract Objective Resilience has been reported as an important predictor of better mental health and prognoses in cancer patients, while its mechanisms were not clearly elucidated. In this study, we surveyed a large sample of nasopharyngeal carcinoma patients to investigate the mediating role of illness‐related cognition (illness perception, stigma and meaning in life) on the associations between resilience and symptoms of anxiety and depression. Methods This cross‐sectional study involved 773 participants diagnosed with nasopharyngeal carcinoma. Participants completed a self‐reported structured questionnaire to assess their illness perception, stigma and meaning in life, resilience and symptoms of anxiety and depression. Structural equation models (SEM) were employed to explore the relationship between resilience and symptoms of anxiety and depression in the entire sample, as well as in two subgroups: Subgroup I (0–1 year since diagnosis), and Subgroup II (over 1 year since diagnosis). Results In the entire sample, after adjusting for potential confounders, illness perception, stigma and meaning in life were found to mediate the protective effect of resilience on symptoms of depression (mediating effect proportion: 65.25%) and anxiety (mediating effect proportion: 67.63%). In Subgroup I, direct effects were dominant in the associations between resilience and symptoms of anxiety (mediating effect proportion: 37.95%) and depression (mediating effect proportion: 29.13%). However, in Subgroup II, the associations between resilience and symptoms of anxiety (mediating effect proportion: 98.92%) and depression (mediating effect proportion: 81.04%) were completely mediated. Conclusions Our study suggests that direct and indirect effects of resilience on depression and anxiety dominate in early periods (0–1 year) and long‐term periods (over 1 year) following the cancer diagnosis, respectively. The findings indicate that comprehensive intervention considering both the direct effect of resilience in early stages (e.g., health education prescription and social support groups) and the indirect effects of illness cognition in long‐term periods (e.g., cognitive behavioral therapies) are likely to yield the most favorable outcomes for cancer patients.

Exopolysaccharides (EPSs) produced by microorganisms play an important role in biotolerance and reducing heavy metal (HM) contamination by limiting the migration of HMs into plants. However, research on the application of EPS-producing marine bacteria for soil heavy metal remediation remains limited, particularly regarding their mechanisms of HM immobilization in soil and impact on plant growth. In this study, the EPS-producing marine bacterium Micrococcus antarcticus HZ was investigated for its ability to immobilize Pb and produce EPSs in soil filtrate. The effects on the growth quality and biomass of pakchoi (Brassica chinensis L.), as well as bacterial communities in inter-root soil contaminated with Pb, were also investigated. The results indicated that HZ could reduce the Pb concentration in the soil filtrate, achieving a removal rate of 43.25–63.5%. The EPS content and pH levels increased in the presence of Pb. Pot experiments showed that adding HZ significantly increased the biomass of pakchoi (9.45–14.69%), vitamin C (Vc) (9.69–12.92%), and soluble protein content (22.58–49.7%). HZ reduced the Pb content in the roots (17.52–47.48%) and leaves (edible tissues) (43.82–52.83%) of pakchoi. HZ increased soil enzyme activities (alkaline phosphatase, dehydrogenase, and urease), and the contents of ammonium nitrogen and nitrate nitrogen. Additionally, HZ also increased the relative abundance of beneficial bacteria (e.g., Proteobacteria, Cyanobacteria, and Chlorobacteria) in the inter-root soil, which have prophylactic and heavy-metal fixation functions. In summary, HZ reduces effective Pb content in edible tissues, roots, and inter-root soil by regulating inter-root soil microbial community structure, increasing soil pH, nitrogen content, and soil enzyme activity, and altering dominant phylum abundance.

In response to the challenges of bearing fault diagnosis under small sample sizes and variable operating conditions, this paper proposes a novel method based on the two-dimensional analysis of vibration acceleration signals and a Multi-Task Conditional Generative Adversarial Network (MTC-GAN). This method first constructs two-dimensional images of vibration signals by leveraging the physical properties of the bearing acceleration signals and employs Local Binary Patterns (LBP) to extract subtle texture features from these images, thereby generating fault feature signatures with high discriminative power across different operating conditions. Subsequently, MTC-GAN is utilized for data augmentation, and the trained discriminator is used to perform fault classification tasks, improving classification accuracy under conditions with small sample sizes. Experimental results demonstrate that the proposed method achieves excellent fault diagnosis accuracy and robustness under both small sample sizes and varying operating conditions. Compared to traditional methods, this approach exhibits higher efficiency and reliability in handling complex operating conditions and data scarcity.

An equatorial plasma bubble (EPB) is characterized by ionospheric irregularities which disturb radio waves by causing phase and amplitude scintillations or even signal loss. It is becoming increasingly important in space weather to assure the reliability of radio systems in both space and on the ground. This paper presents a newly established GNSS ionospheric observation network (GION) around the north equatorial ionization anomaly (EIA) crest in south China, which has a longitudinal coverage of ∼30° from 94°E to 124°E. The measurement with signals from geostationary earth orbit (GEO) satellites of the BeiDou navigation satellite system (BDS) is capable of separating the temporal and spatial variations of the ionosphere. A temporal fluctuation of TEC (TFT) parameter is proposed to characterize EPBs. The longitude of the EPBs’ generation can be located with TFT variations in the time–longitude dimension. It is found that the post-sunset EPBs have a high degree of longitudinal variability. They generally show a quasiperiodic feature, indicating their association with atmospheric gravity wave activities. Wave-like structures with different scale sizes can co-exist in the same night.

Abstract Background As a global pandemic, The Corona Virus Disease 2019 (COVID-19) has brought significant challenges to the primary health care (PHC) system. Health professionals are constantly affected by the pandemic’s harmful impact on their mental health and are at significant risk of job burnout. Therefore, it is essential to gain a comprehensive understanding of how their burnout was affected. The study aimed to examine the relationship between COVID-19 event strength and job burnout among PHC providers and to explore the single mediating effect of job stress and work engagement and the chain mediating effect of these two variables on this relationship. Methods Multilevel stratified convenience sampling method was used to recruit 1148 primary medical staff from 48 PHC institutions in Jilin Province, China. All participants completed questionnaires regarding sociodemographic characteristics, COVID-19 event strength, job stress, work engagement, and job burnout. The chain mediation model was analyzed using SPSS PROCESS 3.5 Macro Model 6. Results COVID-19 event strength not only positively predicted job burnout, but also indirectly influenced job burnout through the mediation of job stress and work engagement, thereby influencing job burnout through the “job stress → work engagement” chain. Conclusions This study extends the application of event systems theory and enriches the literature about how the COVID-19 pandemic impacted PHC medical staff job burnout. The findings derived from our study have critical implications for current and future emergency response and public policy in the long-term COVID-19 disease management period.

Abstract Acute appendicitis is one of the common acute abdominal diseases in pediatrics. However, the implementation of radiological examination guided endoscopic retrograde appendicitis therapy (ERAT) in adults is limited in children. Our previous research explored the non-invasive guidance of high-frequency ultrasound (HFUS) for ERAT and achieved good therapeutic effects. This study mainly focuses on exploring the application value of HFUS in the feasibility assessment of ERAT in children with appendicitis. 163 children with appendicitis received ERAT guided by HFUS were analyzed retrospectively. According to the parameters evaluated by HFUS before and during ERAT, the results indicated that the distance between the appendix orifice and the ileocecal valve significantly affected the time required for the guidewire to enter the appendix cavity (P

Hyper-heuristic algorithms are known for their flexibility and efficiency, making them suitable for solving engineering optimization problems with complex constraints. This paper introduces a self-learning hyper-heuristic algorithm based on a genetic algorithm (GA-SLHH) designed to tackle the logistics scheduling problem of prefabricated modular cabin units (PMCUs) in cruise ships. This problem can be regarded as a multi-objective fuzzy logistics collaborative scheduling problem. Hyper-heuristic algorithms effectively avoid the extensive evaluation and repair of infeasible solutions during the iterative process, which is a common issue in meta-heuristic algorithms. The GA-SLHH employs a genetic algorithm combined with a self-learning strategy as its high-level strategy (HLS), optimizing low-level heuristics (LLHs) while uncovering potential relationships between adjacent decision-making stages. LLHs utilize classic scheduling rules as solution support. Multiple sets of numerical experiments demonstrate that the GA-SLHH exhibits a stronger comprehensive optimization ability and stability when solving this problem. Finally, the validity of the GA-SLHH in addressing real-world decision-making issues in cruise ship manufacturing companies is validated through practical enterprise cases. The results of a practical enterprise case show that the scheme solved using the proposed GA-SLHH can reduce the transportation time by up to 37%.

Neural network models, such as BP, LSTM, etc., support only numerical inputs, so data preprocessing needs to be carried out on the categorical variables to convert them into numerical data. For unordered multi-categorical variables, existing encoding methods may produce dimensional catastrophes and may also introduce additional order misrepresentation and distance bias in neural network computation. To solve the above problems, this paper proposes an unordered multi-categorical variable encoding method O-AE using orthogonal matrix for encoding and encoding representation learning and dimensionality reduction via an autoencoder. Bayesian optimization is used for hyperparameter optimization of the autoencoder. Finally, seven experiments were designed with the basic O-AE, Bayesian optimization of the hyperparameters of the autoencoder for O-AE, and other encoding methods to encode unordered multi-categorical variables in five datasets, and they were input into a BP neural network to carry out target prediction experiments. The results show that the experiments using O-AE and O-AE-b have better prediction results, proving that the method proposed in this paper is highly feasible and applicable and can be an optional method for the data processing of unordered multi-categorical variables.

This study examines the challenges related to the storage and distribution of cabin materials on board during the construction of cruise ships. The construction process of cruise ships involves the assembly of various cabin materials, which are temporarily stored and transported in a complex deck environment with multiple obstacles. These processes can be viewed as location-routing problems (LRPs). However, existing solutions for LRPs do not account for the obstacles commonly encountered in deck environments. Therefore, this paper introduces a new variant of LRPs, termed as the BE-LRP (blocking environment location-routing problem). Initially, by considering the optimization objectives of minimizing the distribution distance and the number of vehicles required, the paper develops an optimization model for the location-routing of on-board materials while taking obstacles into consideration. Subsequently, a method for estimating blocked distances is proposed. This method utilizes Gaussian process regression to predict blocked distances and enables the rapid estimation of distances obstructed by obstacles between different destinations. Lastly, a hybrid obstacle blocking distance processing HO-NSGAII algorithm is formulated to address the BE-LRP. Experimental comparisons demonstrate that the distribution scheme derived from this research method does not necessitate modifications to the delivery distance when compared to the traditional NSGAII algorithm, and better aligns with the actual deck conditions. With an equivalent number of delivery vehicles, the scheme results in shorter delivery distances. The delivery distance can be reduced by 3–17% under varying circumstances. These findings are advantageous for enhancing the efficiency of cruise ship construction and mitigating the impact of warehousing and distribution on construction progress.

Prefabricated cabin modular units (PMCUs) are a widespread type of intermediate products used during ship or offshore platform construction. This paper focuses on the scheduling problem of PMCU assembly flow shops, which is summarized as a multi-objective, fuzzy-blocking hybrid flow-shop-scheduling problem based on learning and fatigue effects (FB-HFSP-LF) to minimize the maximum fuzzy makespan and maximize the average fuzzy due-date agreement index. This paper proposes a multi-objective non-dominated sorting gravitational search algorithm (MONSGSA) to solve it. In the proposed MONSGSA, the ranked-order value is used to convert continuous solutions to discrete solutions. Multi-dimensional Latin hypercube sampling is used to enhance initial population diversity. Setting up an external archive to maintain non-dominated solutions while introducing an adaptive inertia factor and a trap avoidance operator to guide individual positional updates. The results of multiple sets of experiments show that Pareto solutions of MONSGSA have better distribution and convergence compared to other competitors. Finally, the instance of PMCU manufacturer is used for validation, and the results show that MONSGSA has better applicability to practical problems.

Abstract Background China has one of the highest hepatitis B virus (HBV) disease burdens worldwide and tracking progress toward the 2030 HBV elimination targets is essential. This study aimed to assess the impact of biomedical interventions (i.e., adult vaccination, screening and treatment) on the adult HBV epidemic, estimate the time for HBV elimination, and evaluate the cost-effectiveness of the interventions in China. Methods A deterministic compartmental model was developed to project the HBV epidemic from 2022 to 2050 and estimate the time to meet elimination targets under four intervention scenarios. Cost-effectiveness was calculated using incremental cost per quality-adjusted life year (QALY) gained, i.e., average cost-effectiveness ratio (CER). Results Under the status quo, there will be 42.09–45.42 million adults living with HBV in 2050 and 11.04–14.36 million HBV-related deaths cumulatively from 2022 to 2050. Universal vaccination would cumulatively avert 3.44–3.95 million new cases at a cost of US$1027–1261/QALY gained. The comprehensive strategy would cumulatively avert 4.67–5.24 million new chronic cases and 1.39–1.85 million deaths, expediting the realization of the elimination targets forward to 2049. This strategy was also cost-effective with an average CER of US$20,796–26,685/QALY and a saved healthcare cost of US$16.10–26.84 per person. Conclusion China is not on track to meet the elimination targets but comprehensive biomedical interventions can accelerate the realization of the targets. A comprehensive strategy is cost-effective and cost-saving, which should be promoted in primary care infrastructures. Universal adult vaccination may be appropriate in the near future considering practical feasibility.

BackgroundLung cancer (LC) is the second-highest incidence and the first-highest mortality cancer worldwide. Early screening and precise treatment of LC have been the research hotspots in this field. Artificial intelligence (AI) technology has advantages in many aspects of LC and widely used such as LC early diagnosis, LC differential classification, treatment and prognosis prediction.ObjectiveThis study aims to analyze and visualize the research history, current status, current hotspots, and development trends of artificial intelligence in the field of lung cancer using bibliometric methods, and predict future research directions and cutting-edge hotspots.ResultsA total of 2931 articles published between 2003 and 2023 were included, contributed by 15,848 authors from 92 countries/regions. Among them, China (40%) with 1173 papers,USA (24.80%) with 727 papers and the India(10.2%) with 299 papers have made outstanding contributions in this field, accounting for 75% of the total publications. The primary research institutions were Shanghai Jiaotong University(n=66),Chinese Academy of Sciences (n=63) and Harvard Medical School (n=52).Professor Qian Wei(n=20) from Northeastern University in China were ranked first in the top 10 authors while Armato SG(n=458 citations) was the most co-cited authors. Frontiers in Oncology(121 publications; IF 2022,4.7; Q2) was the most published journal. while Radiology (3003 citations; IF 2022, 19.7; Q1) was the most co-cited journal. different countries and institutions should further strengthen cooperation between each other. The most common keywords were lung cancer, classification, cancer, machine learning and deep learning. Meanwhile, The most cited papers was Nicolas Coudray et al.2018.NAT MED(1196 Total Citations).ConclusionsResearch related to AI in lung cancer has significant application prospects, and the number of scholars dedicated to AI-related research on lung cancer is continually growing. It is foreseeable that non-invasive diagnosis and precise minimally invasive treatment through deep learning and machine learning will remain a central focus in the future. Simultaneously, there is a need to enhance collaboration not only among various countries and institutions but also between high-quality medical and industrial entities.

Sarmentosin (SA) and Quercetin (QC) are two active components of Sedum Sarmentosum Bunge, which is a traditional Chinese herbal medicine. This study aimed to investigate the role and regulatory mechanism of SA and QC in fatty liver of Genetic Improvement of Farmed Tilapia (GIFT) tilapia. GIFT tilapia were randomly divided into two groups with three replicates per treatment (30 fish in each replicate): normal diet group (average weight 3.51±0.31 g) and high-fat diet group (average weight 3.44±0.09 g). After 8 weeks feeding trial, growth index, lipid deposition, and biochemical indexes were measured. Lipid deposition, and lipid and inflammation-related gene expression were detected in a primary hepatocyte model of fatty liver of GIFT tilapia treated with SA or QC. Our results showed that high-fat diet caused lipid deposition and peroxidative damage in the liver of GIFT tilapia. The cell counting kit-8 assay results indicated that 10 μM SA and 10 μM of QC both had the least effect on hepatocyte proliferation. Moreover, both 10 μM of SA and 10 μM of QC showed lipolytic effects and inhibited the expression of lipid-related genes (FAS, Leptin, SREBP-1c, and SREBP2) in fatty liver cells. Interestingly, QC induced autophagosome-like subcellular structure and increased the expression of IL-8 in fatty liver cells. In conclusion, this study confirmed that SA and QC improved fatty liver caused by high-fat diet, providing a novel therapeutic approach for fatty liver of GIFT tilapia.

Dysgerminoma is a rare occurrence in Turner syndrome patients without Y chromosome mosaicism or hormone therapy during puberty. We present a unique case of a 33-year-old nulliparous Chinese woman with intermittent epilepsy and Mullerian anomalies carrying a double uterus, cervix, and vagina. The patient is also characterized as having Turner syndrome accompanied by 46,X, del(Xp22.33-11.23) and del(2)(q11.1-11.2). MRI exhibited a 17.0 cm × 20.0 cm × 10.5 cm solid ovarian lesion. Radical surgery and pathology revealed dysgerminoma at stage IIIc with lymphatic metastases and a KIT gene mutation identified in exon 13. Furthermore, the tumor microenvironment (TME) displayed robust expression of CD4+ T lymphocytes and PD-1, whereas the distribution of CD8+ T lymphocytes and PDL-1 was sporadic. Despite the administration of enoxaparin to prevent thromboembolism, the patient experienced multiple cerebral infarctions during chemotherapy. Subsequently, the patient chose to decline further treatment and was discharged. This exceptional case imparts several noteworthy lessons. First, the coexistence of Mullerian anomalies, although rare, is not incompatible with Turner syndrome. Second, screening for KIT mutations is imperative to reduce the risk of dysgerminoma in Turner syndrome, especially for patients with Y mosaicism who are recommended for hormone replacement therapy. Lastly, comprehensive anticoagulation therapy is crucial for Turner syndrome patients undergoing cisplatin-based chemotherapy.

Abstract Aims To examine the effectiveness of Self-Help Plus (SH+) as an intervention for alleviating stress levels and mental health problems among healthcare workers. Methods This was a prospective, two-arm, unblinded, parallel-designed randomised controlled trial. Participants were recruited at all levels of medical facilities within all municipal districts of Guangzhou. Eligible participants were adult healthcare workers experiencing psychological stress (10-item Perceived Stress Scale scores of ≥15) but without serious mental health problems or active suicidal ideation. A self-help psychological intervention developed by the World Health Organization in alleviating psychological stress and preventing the development of mental health problems. The primary outcome was psychological stress, assessed at the 3-month follow-up. Secondary outcomes were depression symptoms, anxiety symptoms, insomnia, positive affect (PA) and self-kindness assessed at the 3-month follow-up. Results Between November 2021 and April 2022, 270 participants were enrolled and randomly assigned to either SH+ (n = 135) or the control group (n = 135). The SH+ group had significantly lower stress at the 3-month follow-up (b = −1.23, 95% CI = −2.36, −0.10, p = 0.033) compared to the control group. The interaction effect indicated that the intervention effect in reducing stress differed over time (b = −0.89, 95% CI = −1.50, −0.27, p = 0.005). Analysis of the secondary outcomes suggested that SH+ led to statistically significant improvements in most of the secondary outcomes, including depression, insomnia, PA and self-kindness. Conclusions This is the first known randomised controlled trial ever conducted to improve stress and mental health problems among healthcare workers experiencing psychological stress in a low-resource setting. SH+ was found to be an effective strategy for alleviating psychological stress and reducing symptoms of common mental problems. SH+ has the potential to be scaled-up as a public health strategy to reduce the burden of mental health problems in healthcare workers exposed to high levels of stress.

PurposeTo explore the clinical value of contrast-enhanced ultrasound (CEUS) quantitative analysis in the evaluation and prognosis of neoadjuvant chemoradiotherapy for locally advanced rectal cancer (LARC).MethodsEighty-three consecutive patients undergoing neoadjuvant chemoradiotherapy and total mesorectal excision for LARC were retrospectively included. According to pathological results, patients were categorized into complete or incomplete response groups. Differences in ultrasonic parameters, pathological results, and clinical data between groups were evaluated. The cutoff point for a complete response as determined by quantitative analysis of CEUS was assessed using a receiver operating characteristic curve; additionally, overall survival (OS) and progression-free survival (PFS) were analyzed.ResultsOf the 83 patients, 12 (14.5%) achieved a complete response and 71 (85.5%) did not. There were significant between-group differences in carcinoembryonic antigen (CEA) levels, differentiation degree, proportion of tumor occupying the lumen, anterior-posterior and superior-inferior diameters of the lesion, and intensity of enhancement (P

Introduction and Objectives: Cavin1 is a cell membrane caveolin, with controversial function in different tumors. Meanwhile, the role of Cavin1 in hepatocellular carcinoma (HCC) progression remains unclear. In this study, we attempted to elucidate the significance of Cavin1 in HCC occurrence and progression. Materials and Methods: Cavin1 content was examined in HCC tissues and paired adjacent normal liver tissues by qRT-PCR and IHC among 81 HCC patients. The Cavin1-mediated regulation of HCC proliferation and metastasis was assessed through in vitro and in vivo experiments. Finally, using GSEA, we found out Cavin1 could be a potential regulator of the Wnt pathway. The alterations of the Wnt pathway-related proteins were identified by Western Blot analysis. Results: Cavin1 was lower expressed in HCC, which implied poor survival outcomes in HCC patients. Phenotypic experiments revealed that Cavin1 strongly suppressed HCC proliferation and migration in vitro and in vivo. Besides, altered epithelial-mesenchymal transition (EMT)-related protein expressions were detected. Based on our GSEA analysis, Cavin1 activated the Wnt pathway, and Western Blot analysis revealed diminished β-catenin, c-Myc, and MMP9 contents upon Cavin1 overexpression. Conclusions: Cavin1 suppresses HCC progression by modulating HCC proliferation and migration via inhibiting the Wnt/β-catenin axis activation.

Abstract Background The COVID-19 pandemic continues to impact global health and China requires a 14-day quarantine for individuals on flights with positive COVID-19 cases. This quarantine can impact mental well-being, including sleep. This study aims to examine the impact of psychosocial and behavioral factors on insomnia among individuals undergoing quarantine in hotels. Methods This study was a cross-sectional survey carried out in Guangzhou, China. The data was gathered through online questionnaires distributed to international passengers who arrived in Guangzhou on flights and were required to undergo a 14-day quarantine in hotels arranged by the local government. The questionnaires were sent to the participants through the government health hotline "12,320." Results Of the 1003 passengers who were quarantined, 6.7% reported significant anxiety and 25.0% had varying degrees of insomnia. Anxiety was positively associated with insomnia (β = 0.92, P

Abstract Background Epilepsy is a neurological disorder that is usually detected by electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a laborious and time-consuming process, lots of automatic epilepsy detection algorithms have been proposed. However, most of the available classification algorithms for epilepsy EEG signals adopted a single feature extraction, in turn to result in low classification accuracy. Although a small account of studies have carried out feature fusion, the computational efficiency is reduced due to too many features, because there are also some poor features that interfere with the classification results. Methods In order to solve the above problems, an automatic recognition method of epilepsy EEG signals based on feature fusion and selection is proposed in this paper. Firstly, the Approximate Entropy (ApEn), Fuzzy Entropy (FuzzyEn), Sample Entropy (SampEn), and Standard Deviation (STD) mixed features of the subband obtained by the Discrete Wavelet Transform (DWT) decomposition of EEG signals are extracted. Secondly, the random forest algorithm is used for feature selection. Finally, the Convolutional Neural Network (CNN) is used to classify epilepsy EEG signals. Results The empirical evaluation of the presented algorithm is performed on the benchmark Bonn EEG datasets and New Delhi datasets. In the interictal and ictal classification tasks of Bonn datasets, the proposed model achieves an accuracy of 99.9%, a sensitivity of 100%, a precision of 99.81%, and a specificity of 99.8%. For the interictal-ictal case of New Delhi datasets, the proposed model achieves a classification accuracy of 100%, a sensitivity of 100%, a specificity of 100%, and a precision of 100%. Conclusion The proposed model can effectively realize the high-precision automatic detection and classification of epilepsy EEG signals. This model can provide high-precision automatic detection capability for clinical epilepsy EEG detection. We hope to provide positive implications for the prediction of seizure EEG.

Background: The escalating complexity of the COVID-19 epidemic underscores the need for heightened attention to booster vaccinations. This study aims to examine the changing trend in the public’s intention to receive the second COVID-19 booster vaccination over time and the associated factors following the COVID-19 policy optimization in China. Method: Eight cross-sectional surveys utilizing SMS questionnaire links were conducted in Guangzhou, China, from December 2022 to April 2023. The Mann–Kendall test was employed to analyze the trend in intentions to receive the second booster vaccination across the survey time. Adjusted and multivariate logistic analyses were used to analyze the factors associated with vaccination intention. Parallel analyses were performed for two subgroups with different COVID-19 infection statuses. Results: A total of 9860 respondents were surveyed in the eight rounds, of which 8048 completed the first booster vaccination and were included in the analysis. The overall COVID-19 infection rate was 60.0% (4832/8048), while the overall vaccination intention was 72.2% (5810/8048) among respondents. The vaccination intention exhibited a significant declining trend over time, decreasing from 81.5% in December 2022 to 52.2% in April 2023. An adjusted logistic regression analysis revealed that anxiety and depression were negatively associated with an intention to receive the second booster vaccination, while COVID-19-related preventive behaviors and a high engagement in COVID-19-related information were positively associated with an intention to receive the second booster vaccination. A subgroup analysis revealed that the association between psychological and behavioral characteristics and vaccination intention remained relatively stable among individuals with different histories of COVID-19 infections. Conclusion: There was a significant decline in the intention to receive the second booster vaccination following the optimization of the COVID policy in China. Our findings emphasize the urgency of the second booster vaccination and provide a foundation for the development of tailored interventions to enhance and sustain vaccination intention among the public.

BackgroundWeak handgrip strength (HGS) has been linked to adverse health outcomes including stroke. However, the joint associations of HGS weakness and asymmetry between limbs with stroke incidence remain underexplored.MethodsThis cohort study analyzed data of participants aged ≥45 years from three waves (2011, 2013, and 2015) of the China Health and Retirement Longitudinal Study. Weak HGS was defined according to the recommendation of European Working Group on Sarcopenia in Older People. Asymmetric HGS was defined if the HGS ratio of both hands was over 1.1 or below 0.9. New-onset stroke was confirmed through self-report of physician’s diagnosis.ResultsA total of 10,966 participants without stroke at baseline were included in the analysis. During the 4 years follow-up, there were 262 (2.39%) new-onset stroke cases. Compared to individuals with non-weak and symmetric HGS, those with HGS asymmetry alone and weakness alone were associated with hazards of 1.09 (95% confidence interval [CI]: 0.80–1.48) and 1.27 (95%CI: 0.86–1.88) for new-onset stroke, respectively, while co-occurrence of both HGS asymmetry and weakness was associated with 1.80 (95%CI: 1.24–2.60) greater hazard for new-onset stroke after controlling for confounders. Such associations were consistent in older adults aged ≥60 years, but not in those aged

ObjectivesThis study aimed to investigate the relationship between the functional limitation and happiness among Chinese older people and examined the multiple mediating effects of intergenerational support (instrumental support and financial support) and intergenerational relationship.MethodData was drawn from the Chinese Family Panel Survey (CFPS) 2018 and 2020. Structural equation modeling was adopted to analyze the association among functional limitations, intergenerational support, intergenerational relationship, and the older adults happiness.ResultsThere was a significant association between the functional limitations and the lower happiness levels among the older adults. The instrumental support from adult children positively mediated the relationship between the functional limitation and the happiness. However, intergenerational relationships were reduced due to the dysfunction of the older adults, and played a negatively mediated role between the functional limitation and the happiness. In addition, instrumental and financial support play chain-mediating roles between functional limitation and happiness in older adults through intergenerational relationships.ConclusionIntergenerational relationships and instrumental support enhance the happiness of older adults with functional impairments, but their role is limited by the changing structure of modern families. Long-term care programs combined with the intergenerational support from families for people with functional impairments in old age would be more effective to reduce the burden on adult children and maintain the quality of life of the older adults.

Background In this study, our aim was to quantify eHealth literacy and determine a cut-off value for eHEALS scores that signifies adequate eHealth literacy among rural residents in Gansu, China. Methods This cross-sectional investigation encompassed 18 rural areas across three cities—Lanzhou, Wuwei, and Dingxi—in Gansu. A total of 451 residents were recruited and underwent evaluations for both eHealth literacy and eHealth skills, utilizing the eHEALS and self-constructed tasks, respectively. A receiving operator characteristic curve was plotted with eHealth skills as the dependent variable and eHealth literacy levels as the independent variable, aiming to determine a cut-off value for eHEALS indicating adequate eHealth literacy and evaluate its predictive capacity. Results Among the 451 respondents, 10.9% did not possess a personal electronic device with Internet access, while 6.4% owned but had never used them. Within the remaining 373 residents, the mean eHealth literacy score was 25.85 (SD:10.93), item scores ranged from 3.12 (SD:1.45) to 3.42 (SD:1.60). Completion rates for three eHealth skills varied from 39.1% to 59.8%. The cut-off value was 29.5 determined by the Youden index. The area under the receiver operating curve was 0.829, with a sensitivity of 86.7%, and a specificity of 66.8%. Conclusions Our findings emphasized that eHealth literacy among rural residents remains at a low level. Moreover, we identified a cut-off value of 29.5 for eHEALS scores that signifies adequate eHealth literacy within this demographic.

Abstract The anticoagulation and hemostatic properties of blood-contacting materials are opposite lines of research, but their realization mechanisms are inspired by each other. Contact between blood and implantable biomaterials is a classic problem in tribological research, as both antithrombotic and hemostatic materials are closely associated with this problem. Thrombus formation on the surfaces of blood-contacting biomedical devices can detrimentally affect their performance and patient life, so specific surface functionalization is required. Currently, intensive research has focused on the development of super-lubricated or super-hydrophobic coatings, as well as coatings that deliver antithrombotic drugs. In addition, hemostatic biomaterials with porous structures, biochemical substances, and strongly adhesive hydrogels can be used to achieve rapid and effective hemostasis via physical or biochemical mechanisms. This article reviews methods of preparing anticoagulant coatings on material surfaces and the current status of rapid hemostatic materials. It also summarizes fundamental concepts for the design and synthesis of anticoagulant and hemostatic materials by discussing thrombosis and hemostasis mechanisms in biomedical devices and normal organisms. Because there are relatively few reports reviewing the progress in surface-functionalized design for anticoagulation and hemostasis, it is anticipated that this review can provide a useful summary of the applications of both bio-adhesion and bio-lubrication techniques in the field of biomedical engineering.

Highlights 1. The epidemiology of A. baumannii in Jilin Province showed distinctive local characteristic. 2. Newly discovered sequence types (STs), the results of genetic relatedness and geographical distribution of all STs showed epidemiological research by multi-locus sequence typing (MLST) in single hospital is helpful to monitor and control nosocomial infection of A. baumannii. 3. The rate of carbapenems resistance among A. baumannii is about 94% in Jilin province (northeast China). Carbapenems resistance is a helpful factor for predominant STs spreading.

Abstract Background Both excessive screen time and early screen exposure have been linked to children’s health outcomes, but few studies considered these two exposures simultaneously. The aim of this study was to explore the independent and interactive associations of excessive screen time and early screen exposure with health-related quality of life (HRQOL) and behavioral problems among Chinese children attending preschools. Methods A cross-sectional study of 4985 children aged between 3 and 6 years was conducted in Chengdu, China. Each parent has finished an online questionnaire regarding their children’s screen use, HRQOL, and behavioral problems. Children with screen time over 1 h/day were considered as having excessive screen time. Early screen exposure was defined if the children had started using screen-based media before the age of 2 years. HRQOL was assessed by the Pediatric Quality of Life Inventory version 4.0 (PedsQL 4.0), while behavioral problems were confirmed with the 48-item Conners’ Parent Rating Scale (CPRS-48). Results Of the 4985 children (2593 boys and 2392 girls) included, the mean age was 4.6 (SD: 1.0) years. After adjustment for confounders and early screen exposure, excessive screen time was significantly associated with worse HRQOL scores in all dimensions and summary scales, as well as each type of behavioral problems (all p values

Abstract Background Current global health course is most set as elective course taught in traditional teacher-taught model with low credit and short term. Innovate teaching models are required. Crowdsourcing characterized by high flexibility and strong application-orientation holds its potential to enhance global health education. We applied crowdsourcing to global health teaching for undergraduates, aiming to develop and evaluate a new teaching model for global health education. Methods Crowdsourcing was implemented into traditional course-based teaching via introducing five COVID-19 related global health debates. Undergraduate students majoring in preventative medicine and nursing grouped in teams of 5–8, were asked to resolve these debates in reference to main content of the course and with manner they thought most effective to deliver the messages. Students' experience and teaching effect, were evaluated by questionnaires and teachers’ ratings, respectively. McNemar's test was used to compare the difference in students' experience before and after the course, and regression models were used to explore the influencing factors of the teaching effect. Results A total of 172 undergraduates were included, of which 122 (71%) were females. Students' evaluation of the new teaching model improved after the course, but were polarized. Students’ self-reported teaching effect averaged 67.53 ± 16.8 and the teachers’ rating score averaged 90.84 ± 4.9. Students majoring in preventive medicine, participated in student union, spent more time on revision, and had positive feedback on the new teaching model tended to perform better. Conclusion We innovatively implemented crowdsourcing into global health teaching, and found this new teaching model was positively received by undergraduate students with improved teaching effects. More studies are needed to optimize the implementation of crowdsourcing alike new methods into global health education, to enrich global health teaching models.

Abstract Ionospheric irregularities have been studied since ~ 70 years ago. With the development of Global Navigation Satellite system (GNSS), networks of GNSS receivers have been used to obtain the characteristics of the irregularities, including the drift velocity, the structure, and the evolution. In this paper, keograms based on the Crustal Movement Observation Network of China (CMONOC) were used to characterize the irregularities over the area from longitude 85 to 125 °E and latitude 11 to 35 °N in 2014. Keograms were obtained for the rate of TEC index (ROTI) for every 0.5 degree longitude and 30 min universal time pixel. The results showed that the occurrence rate of irregularities in 2014 was high in the equinox months and December, and lowest in June. In equinox months the irregularities often appeared after sunset. In March the irregularities usually had long lifetime of ~ 5–7 h and ~ 5 degrees apparent longitudinal width. The long lifetime usually was accompanied by obvious eastward drift of ~ 100 m/s and large vertical ROTI (vROTI). In September the irregularities had weaker ROTI and shorter lifetime than those in March. The irregularities in the 2 equinox months should be related to the equatorial plasma bubbles (EPBs). In June, they appeared ~ 2–3 h later than those in equinoxes and drifted westward. The summer irregularities had weakest ROTI and their latitude was ~ 30 °N, much higher than those in equinoxes. In December, the irregularities were discrete patches with a longitudinal width of ~ 2 degrees and short lifetime of ~ 2 h. Unlike the equatorial irregularities in equinox months which are part of equatorial plasma bubbles, the solstice irregularities mainly appear to be a local phenomenon. Graphical Abstract

ABSTRACT Linker histone H1 plays a crucial role in various biological processes, including nucleosome stabilization, high-order chromatin structure organization, gene expression, and epigenetic regulation in eukaryotic cells. Unlike higher eukaryotes, little about the linker histone in Saccharomyces cerevisiae is known. Hho1 and Hmo1 are two long-standing controversial histone H1 candidates in budding yeast. In this study, we directly observed at the single-molecule level that Hmo1, but not Hho1, is involved in chromatin assembly in the yeast nucleoplasmic extracts (YNPE), which can replicate the physiological condition of the yeast nucleus. The presence of Hmo1 facilitates the assembly of nucleosomes on DNA in YNPE, as revealed by single-molecule force spectroscopy. Further single-molecule analysis showed that the lysine-rich C-terminal domain (CTD) of Hmo1 is essential for the function of chromatin compaction, while the second globular domain at the C-terminus of Hho1 impairs its ability. In addition, Hmo1, but not Hho1, forms condensates with double-stranded DNA via reversible phase separation. The phosphorylation fluctuation of Hmo1 coincides with metazoan H1 during the cell cycle. Our data suggest that Hmo1, but not Hho1, possesses some functionality similar to that of linker histone in Saccharomyces cerevisiae, even though some properties of Hmo1 differ from those of a canonical linker histone H1. Our study provides clues for the linker histone H1 in budding yeast and provides insights into the evolution and diversity of histone H1 across eukaryotes. IMPORTANCE There has been a long-standing debate regarding the identity of linker histone H1 in budding yeast. To address this issue, we utilized YNPE, which accurately replicate the physiological conditions in yeast nuclei, in combination with total internal reflection fluorescence microscopy and magnetic tweezers. Our findings demonstrated that Hmo1, rather than Hho1, is responsible for chromatin assembly in budding yeast. Additionally, we found that Hmo1 shares certain characteristics with histone H1, including phase separation and phosphorylation fluctuations throughout the cell cycle. Furthermore, we discovered that the lysine-rich domain of Hho1 is buried by its second globular domain at the C-terminus, resulting in the loss of function that is similar to histone H1. Our study provides compelling evidence to suggest that Hmo1 shares linker histone H1 function in budding yeast and contributes to our understanding of the evolution of linker histone H1 across eukaryotes.

Summary: Background: Drug overdose deaths in the USA have increased rapidly in the past 20 years, and understanding patterns and trends in mortality is essential to develop policy responses. This study aimed to determine whether cohort patterns in mortality due to drug overdose have changed in the past two decades and assess these patterns by race and sex. Methods: The national records of accidental drug overdose death were extracted from Centers for Disease Control and Prevention, National Center for Health Statistics Mortality Data for 2000–2020. Age-period-cohort analysis was performed to examine independent effects of age, period and birth cohort on accidental drug overdose mortality. Findings: The number of accidental drug overdose deaths increased by 622% between 2000 and 2020, and age-standardized mortality rates increased nearly four-fold in both men and women. Age-period-cohort decomposition found rapid increases in mortality since 2012 in men and women, with higher mortality risk in cohorts born after 1990. The fastest increase occurred in Black Americans since 2012, and Americans of all races born after 1975 had significantly higher mortality risk, with mortality risk increasing rapidly in more recent cohorts. The peak of mortality has shifted from the 40–59 age group to the 30–40 year age group in the past decade. Interpretation: The burden of drug overdose mortality has shifted to younger Americans, and a new generation of Americans are at significantly higher and rapidly increasing risk of overdose death. Urgent action is needed to prevent an entire generation of young people being consigned to decades of preventable mortality. Funding: None.

In the context of increasingly competitive shipbuilding, the flexible multi-level picking system, composed of high-rise shelves, Automated Guided Vehicles (AGVs), and picking stations, has been of gradual interest because of its advantages in operation efficiency, system flexibility, and system robustness. Compared with other simple-level systems, the flexible multi-level picking system has a more complex coupling temporal relationship, which makes the scheduling optimization of shipbuilding automated collaborative order picking (SACOP) extremely difficult. In order to avoid the dilemma of finding a feasible and optimal collaborative scheduling scheme under the constraints of a complex temporal relationship, this paper proposed a multi-AGV-driven pallet-picking scheduling optimization (MADPSO) method, which takes the AGV scheduling scheme as the direct solution and modifies it to a feasible solution under the reasonably designed interaction strategy of stacker, AGV, and the interaction strategy of picking station, AGV. Furthermore, taking the minimum energy consumption and operation time as the optimization objectives, a multi-objective optimization mathematical model was established to describe MADPSO, and an improved NSGA-III algorithm was designed to solve the problem. Finally, several experiments were conducted in various scenarios and verified that using MADPSO can achieve a comprehensive optimization index improvement of 52.02–75.66% compared with traditional picking methods, which has a certain reference significance for shipyards.

In cruise ship manufacturing, it is common practice for prefabricated modular cabin units (PMCU) to be assembled in the workshop and transported to a designated installation location on board the ship. This paper proposed a Radau pseudospectral method based on a probabilistic roadmap (PRM) for PMCU path planning in complex deck environments. Firstly, a kinematic model is constructed, and the continuous-time optimal control path planning problem is established. Among them, an area-based obstacle avoidance constraint is applied to the approach. Then, the continuous-time optimal control problem is discretized into a nonlinear programming (NLP) problem using the orthogonal collocation method. For the initial value-sensitive NLP problem solving, a strategy using PRM combined with a heuristic rule is used to obtain a high-quality initial guess. Finally, experiments under two operating scenarios of PMCU pushing demonstrate that the method is capable of generating a better path while ensuring that the whole process is collision-free. The results show that the algorithm proposed in this paper can effectively solve the PMCU pushing path planning problem in the complex deck environment, and the path considering kinematic characteristics can be used for cabin installation, which has strong operability and applicability.

The regression model based on the support vector machine (SVM) is a standard mid-term and long-term load forecasting method. However, the hyperparameters of traditional SVM are challenging to determine, leading to its poor forecasting effect. This paper proposes an improved sparrow search algorithm (ISSA) to solve the problem of hyperparameter selection of the SVM model and construct the mid-long term load prediction model by ISSA-SVM. This ISSA is enhanced by a new dynamic adaptive t-distribution mutation. Compared to the SSA, the ISSA has better convergence precision, stability and speed, which was verified by the comparative test based on six benchmark functions. The simulation results also show that the ISSA-SVM can effectively improve the prediction accuracy compared with the original SVM, BP neural network, multiple linear regression, etc.

To fight against climate change and environmental pollution, the share of renewable energy capacity immensely grows worldwide, especially photovoltaic power. Meanwhile, road transportation develops quickly for the convenience of traveling. Due to abundant solar resources in road transportation and flexible installation of photovoltaic power, solar road generation with huge generation potentials will be a promising solution to alleviate environmental burden in the future. To analyze the influence of solar road integration on power flow, this paper proposes a power flow (PF) analysis method with solar road integration. Based on the photovoltaic model, the solar road generation model coupled with traffic flow is formulated. Two representative scenarios are developed to represent the uncertainties of solar road (i.e., solar irradiation, traffic flow). Finally, the simulation results performed on IEEE 33-bus system under three test cases verify the feasibility and effectiveness of the proposed solar road generation model.

Abstract Mural is an important component of culture and art of Dunhuang in China. Unfortunately, these murals had been ruined or are being ruined by some diseases such as cracking, hollowing, falling off, mildew, dirt, and so on. Existing image restoration algorithms have problems such as incomplete repair and disharmonious texture during large-area repair, so the effect of mural image disease area repair is poor. Due to lack of a standard mural datasets, Dunhuang mural datasets are created in the paper. Meanwhile, our network architecture SeparaFill is proposed which connects two generators based on U-Net. Based on the characteristics of the painting, the contour line pixel area of the mural image is innovatively separated from the content pixel area. Firstly, the contour restoration generator network with skip connect and hierarchical residual blocks is employed to repair contour lines. Then, the color mural image is repaired by the content completion network with guide of the repaired contour. Full resolution branches and generator branches of the U type are exploited in content completion generators. Convolution layers of different kernel sizes are fused to improve the reusability of the underlying features. Finally, global and local discriminant networks are applied to determine whether the repaired mural image is authentic in terms of both the modified and unmodified areas. The proposed SeparaFill shows good performance in restoring the line structure of the damaged mural images and retaining the contour information of the mural images. Compared with existing restoration algorithms in mural real damage repair experiment, our algorithm increases the peak signal-to-noise ratio (PSNR) by an average of 1.1–4.3 dB and the structural similarity (SSIM) values were slightly improved. Experimental results reveal the good performance of the proposed model, which can contribute to digital restorations of ancient murals.

Abstract Background Despite the understanding of the COP9 signalosome subunit 5 (CSN5) in tumor genesis, there is no conclusive evidence on its value to predict the survival and prognosis of digestive system tumor patients. Hence this study aimed to evaluate the impact of CSN5 levels on the survival and clinicopathological parameters of digestive system neoplasm patients. Methods First, a comprehensive search was conducted in four databases. We utilized the Hazard Ratio (HR) with a 95% confidence interval (CI) to evaluate the prognostic value of CSN5 for the overall survival (OS) and recurrence-free survival (RFS) of patients. Then, we estimated the connection between CSN5 and the clinicopathological parameters based on the Odds Ratio (OR) with the corresponding 95% CI. Results This meta-analysis included 22 studies and 2193 patients diagnosed with digestive system tumors. High expression of CSN5 was correlated to poorer OS (HR = 2.28, 95% CI: 1.71–3.03; p

A thick plate of Ti–6Al–2Zr–2Sn–3Mo–1.5Cr–2Nb (TC21) damage-tolerant alloy was electron-beam welded and the joint was treated via solution aging. The microstructural characterizations and mechanical properties of the welding and solution-aging states were also investigated. The results indicated that in the welding state, the fusion zone (FZ) is composed of grain boundary α, martensite α′, and residual β phases. The heat-affected zone (HAZ) consists mainly of primary α, martensite α′, and residual β phases. The microhardness value of the FZ is higher than that of HAZ and base metal (BM), and the hardness value of the welded joint from the FZ to BM fluctuates greatly. The ultimate tensile strength (UTS) and elongation (EL) of the welded joint are 1183 MPa and 7.5%, respectively. The weak spot of impact toughness on the welded joint is the FZ, about 11 J. After solution aging, the martensite α′ in the FZ and HAZ transforms completely into lamellar α. Compared with the welding state, the fluctuation in the hardness value markedly decreases. The UTS and EL of the welded joint are 1145 MPa (a 3% decrease) and 12.5% (a 66.7% increase), respectively. The impact toughness of the FZ is 27 J, an increase of approximately 145%. The strength of the welded joint is well matched with their plasticity and toughness.