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Fengting Wang,1,* Limin Rong,1,* Linlin Luo,2 Fuqin Mu,1 Liju Qian,3 Yandan Qian,4 Xinyao Zhang,1 Yuying Lang,1 Weijia Wang,1 Yan Liu,5,6 Ying Zhang,7 Jianli Wang1,8 1School of Mental Health, Jining Medical University, Jining, Shandong, People’s Republic of China; 2Department of Hematology, Tai’an Central Hospital, Tai’an, Shandong, People’s Republic of China; 3Shandong Daizhuang Hospital, Jining, Shandong, People’s Republic of China; 4The Third People’s Hospital of Jiashan County, Jiashan, Zhejiang, People’s Republic of China; 5School of Public Health, Jining Medical University, Jining, Shandong, People’s Republic of China; 6Center of Evidence-Based Medicine, Jining Medical University, Jining, Shandong, People’s Republic of China; 7School of Public Health, University of Sydney, Sydney, NSW, Australia; 8Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada*These authors contributed equally to this workCorrespondence: Fengting Wang, School of Mental Health, Jining Medical University, Jining, Shandong, 272013, People’s Republic of China, Email wft.0810@163.com Yan Liu, School of Public Health, Jining Medical University, Jining, Shandong, 272013, People’s Republic of China, Email hakunaly@163.comBackground: Youth and young adults have a high prevalence of major depressive disorder (MDD). Limited longitudinal research has explored the relationship between different dimensions of psychological stress and MDD. This study aimed to estimate the effect of psychological stress on the risk of first onset MDD in a sample of Chinese freshmen.Methods: Using a longitudinal design, 8079 Chinese first-year students were recruited at baseline, and 6985 were followed up one year later. The Psychological Stress Scale for College Students was utilized to evaluate the levels of psychological stress. MDD was evaluated using the Chinese version of the Composite International Diagnostic Interview (CIDI-3.0). Logistic regression modeling was utilized to estimate the associations between dimensions of psychological stress and the risk of MDD.Results: Two dimensions of psychological stress, namely learning stress (OR=1.05, 95% CI:1.01– 1.09, P=0.017) and economic stress (OR=1.11, 95% CI:1.04– 1.19, P=0.001), were significantly associated with the risk of MDD. Other dimensions of psychological stress (specify family stress, interpersonal stress, intimate relationship stress, employment stress and appearance stress) were not associated with MDD.Conclusion: Psychological stress, especially learning and economic stresses, could increase the risk of MDD in university students. These factors should be incorporated into mental health prevention and intervention programs at universities to reduce the risks of MDD.Keywords: major depressive disorder, psychological stress, longitudinal study, freshmen

Donna D Carstens,1 Diego J Maselli,2 Erin E Cook,3 Fan Mu,3 Jingyi Chen,3 Danni Yang,3 Jessica Karacz DeMartino,1 Yen Chung1 1Respiratory & Immunology, AstraZeneca, Wilmington, DE, USA; 2Division of Pulmonary Diseases & Critical Care, University of Texas Health, San Antonio, TX, USA; 3Health Economic and Outcomes Research, Analysis Group, Boston, MA, USACorrespondence: Jessica Karacz DeMartino, AstraZeneca Pharmaceuticals, 1800 Concord Pike, Wilmington, DE, 19897, USA, Tel +1 302-897-0843, Email jessica.demartino@astrazeneca.com

Fengchun Mu,1,2,&ast; Bingjie Fan,1,&ast; Butuo Li,1 Wenru Qin,1 Haoqian Li,1,2 Chunni Wang,1 Bing Zou,1 Shijiang Wang,1 Linlin Wang1 1Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People’s Republic of China; 2Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 271016, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Linlin Wang, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People’s Republic of China, Tel +86-531-67626142, Fax +86-531-67626141, Email wanglinlinatjn@163.comPurpose: The present study aimed to evaluate the incidence rate of radiation pneumonitis (RP) in patients with advanced lung adenocarcinoma treated with first-generation (1G), second-generation (2G), or third-generation (3G) epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) combined with thoracic radiotherapy (TRT).Patients and Methods: Patients with advanced lung adenocarcinoma simultaneously treated with 1G/2G/3G EGFR-TKIs and TRT between 2015– 2021 at Shandong Cancer Hospital and Institute were screened. The incidence rate of clinical and imaging RP was compared between the three groups.Results: A total of 200 patients treated with EGFR-TKIs were enrolled in this study, including 100 patients who were treated with 1G EGFR-TKIs, 50 patients who were treated with 2G EGFR-TKIs, and 50 patients who were treated with 3G EGFR-TKIs (patients matched in a 2:1:1 ratio for tumor characteristics). The overall incidence of clinical RP in the 1G, 2G, and 3G EGFR-TKI groups were 29%, 48%, and 28% (p=0.043), respectively, and that of imaging RP were 33%, 58%, and 36% (p=0.010), respectively. The incidence of RP with a clinical grade ≥ 3 in the three groups were 14%, 28%, and 12% (p=0.055), respectively, and that with an imaging grade ≥ 3 in the three groups were 11%, 32%, and 10% (p=0.002), respectively. The incidence of clinical RP was higher in the CFRT group than in the SBRT group, with an overall clinical grade of 38% vs 10% (p< 0.001) and imaging grade of 46% vs 10% (p< 0.001), respectively. In the multivariate analysis, only GTV volume was an independent predictive factor for all risks of clinical and imaging RP. V20 and grouping of 1G/2G/3G EGFR-TKIs were other independent predictive factors for the risk factors of RP for imaging grades.Conclusion: Compared with 2G EGFR-TKIs combined with TRT, 1G or 3G EGFR-TKIs combined with TRT achieved a lower incidence of RP.Keywords: EGFR-TKI, molecular targeted therapy, radiation pneumonitis, thoracic radiotherapy, lung adenocarcinoma

Background Immunosuppressed recipients of liver transplantation (LT) are more likely to develop coronavirus disease 2019 (COVID-19) and may have an increased risk of developing worse outcomes. Aim To assess the effect of ursodeoxycholic acid (UDCA) on preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in LT recipients. Design Adult patients (aged ≥ 18 years) who underwent LT between 1 January 2015 and 31 December 2022 were included and categorized into two groups according to their use of UDCA. Methods The prevalence and severity of COVID-19 among transplantation patients between the UDCA and non-UDCA groups were estimated and compared. Results Among the 897 LT patients who met the inclusion criteria, infection rate of SARS-CoV-2 was 78.4%, and the rate of severe illness was 5.1% from January 2022 to January 2023 in China. In the multivariate analysis, only UDCA treatment (P  = 0.006) was found to be a protective factor against SARS-CoV-2 infection. After propensity score matching, the SARS-CoV-2 infection rate in the UDCA group was lower than that in the non-UDCA group (74.1% vs. 84.6%, P  = 0.002). This rate was further reduced to 62.1% (P  = 0.002) when the oral administration dose was >15 mg/kg/day. There was no difference in the rates of severe COVID-19 illness, ICU admission, or ventilation rate or length of hospital stay with or without UDCA treatment (all P  > 0.05). Conclusions The use of UDCA in LT patients significantly reduced the SARS-CoV-2 infection rate and showed a dose-dependent protective effect. [ABSTRACT FROM AUTHOR]

Based on the CICE sea ice model and the PDAF parallel data assimilation framework, this paper uses the local error subspace transform Kalman filter method (LESTKF) to assimilate the sea ice concentration, sea ice thickness and sea ice freeboard data into the model, and designs experiments to study the improvement of multi-parameter assimilation on the simulation of Arctic sea ice concentration and range. The results show that data assimilation has a good improvement effect on the simulation of Arctic sea ice concentration and range. The average deviation, root mean square error and mean absolute error of the assimilation experiment are significantly reduced compared with the control experiment. The assimilation experiment improves the simulation of sea ice concentration and range most obviously in summer. Multi-parameter assimilation can improve the prediction accuracy and reliability of Arctic sea ice change.

The pressure and density dependence of the shear strength of sand poses a tricky problem in pile foundation design. In this study, a correlation is suggested to link the effective friction angle of sand with its initial confining pressure and relative density, and a simple approach incorporating this correlation is presented for predicting pile end bearing capacity. Assessment of the approach against pile load tests shows reasonably good agreement between predictions and measurements. It is also shown that the effect of the state-dependent strength is particularly important in cases where long piles are installed in dense sand deposits and the use of critical state friction angle will produce a conservative prediction in such cases. CE Database subject headings: Bearing capacity; Piles; Pile foundations; Sand; Shear strength.

Buried pipelines are widely used, so it is necessary to analyze and study their fracture characteristics. The locations of corrosion defects on the pipe are more susceptible to fracture under the influence of internal pressure generated during material transportation. In the open literature, a large number of studies have been conducted on the failure pressure or residual strength of corroded pipelines. On this basis, this study conducts a fracture analysis on buried pipelines with corrosion areas under seismic loads. The extended finite element method was used to model and analyze the buried pipeline under seismic load, and it was found that the stress value at the crack tip was maximum when the circumferential angle of the crack was near 5° in the corrosion area. The changes in the stress field at the crack tip in the corrosion zone of the pipeline under different loads were compared. Based on the BP algorithm, a neural network model that can predict the stress field at the pipe crack tip is established. The neural network is trained using numerical model data, and a prediction model with a prediction error of less than 10% is constructed. The crack tip characteristics were further studied using the BP neural network model, and it was determined that the tip stress fluctuation range is between 450 MPa and 500 MPa. The neural network model is optimized based on the GA algorithm, which solves the problem of convergence difficulties and improves the prediction accuracy. According to the prediction results, it is found that when the internal pressure increases, the corrosion depth will significantly affect the crack tip stress field. The maximum error of the optimized neural network is 5.32%. The calculation data of the optimized neural network model were compared with the calculation data of other models, and it was determined that GA-BPNN has better adaptability in this research problem.

With the large-scale integration of distributed renewable energy into low-voltage distribution station areas, rapidly growing services put forward new requirements on transparent monitoring. In order to accurately and objectively quantify the transparency of various distribution station areas and measure the impact of different dimensional indexes on the transparency evaluation of distribution station areas, this paper proposes a confidence relative off-target distance-based multi-dimensional transparency evaluation method. First, a multi-dimensional transparency evaluation index system with electrical and communication integration is constructed. Second, an improved gray target model combining both positive and negative target vectors is established to realize bi-directional quantitative analysis. Then, the relative off-target distance is calculated based on the endowment coefficient by leveraging both subjective and objective weights. Finally, the confidence of the relative off-target distance is calculated based on fuzzy entropy to improve the reliability of transparency evaluation. The simulation results show that this method can effectively distinguish the transparency gap between different distribution station areas, identify the single dimensional index with the greatest contribution or potential, and verify the effectiveness of the proposed method applied to the transparency evaluation of distribution station areas.

The global football market has grown in the past three decades, and football clubs' sustainable financial operations have gradually gained attention. This study aims to construct a financial risk assessment model applicable to the football industry, explore globally listed football clubs' overall financial operating characteristics, and analyse the leading causes of the club's financial crisis. We selected a sample of 24 currently listed football clubs worldwide and an exploratory factor analysis (EFA) model to construct the model of financial risk assessment for football clubs. The model identified and classified the financial risk components for listed football clubs, thus facilitating risk warning and prevention for modern professional clubs. This study found that football clubs are at higher financial risk overall, with the following general characteristics: (1) small amount of listed capital; (2) high asset-liability ratio; (3) low net profits and a large proportion of clubs make losses; and (4) weak asset liquidity. Finally, the study discussed the leading causes of the financial crises of football clubs in both external and internal dimensions, providing a reference for the self-sustainability of clubs and football authorities.

In the past 30 years, the global influence of the FIFA World Cup has continued to grow. According to statistics, the final match of the 2022 World Cup in Qatar attracted an audience of over 3 billion. Nowadays, nations (and regions) emphasize the correlation between overall social progress, football tradition, and national sporting prowess. This study aims to comprehend the dynamics of international football development and secure a competitive edge in the global arena. The study collected panel data from 68 countries (regions) participating in the final stage of the World Cup from 1994 to 2022. It modelled them using a generalized linear mixed model (GLMM) to reveal the macro determinants of success and winning patterns in international football performance. The findings show that (1) football tradition's “characteristic values” (e.g. World Cup host, the experience of hosting the World Cup and the number of all-time World Cup winners) and national comprehensive sporting strength (as represented by the Olympic Games results) have significantly contributed to the national team's World Cup performance; (2) the country's Human Development Index (HDI) has a significant negative impact on World Cup performance; (3) the history of football participation (e.g. the number of years of membership in the Intercontinental Football Association (IFA), history of professional leagues) will have little impact on World Cup performance; (4) two interactive variables: population scale × national comprehensive sporting strength (GPOP × CSOGMedals) and economic level × football tradition (lnGDP × PLHistory), have a negative and positive combined effect on World Cup performance, respectively.