The association between victimization experiences and suicidality:The mediating roles of sleep and depression

Background Prior work suggests that multiple forms of victimization were associated with higher suicide risk among adolescents. However, the mechanisms underlying this association remain unclear. The present study aimed to understand the relationships between the multiple forms of victimization and suicidality by examining the potential mediators of sleep duration and depression. Methods Data for this study came from the 2019 Youth Risk Behavior Survey (YRBS). The hypothesized mediation model included 13,677 American adolescents in 9th through 12th-grade students (48.6 % female) were analyzed using Mplus 7.4, and suicidality (including suicidal ideation, plan, and attempts) as the outcome variables and the multiple forms of victimization (including bullying at school, being threatened at school, electronic bullying, sexual victimization, sexual dating victimization, and physical dating victimization) as the main explanatory variable. Results The relationships between the multiple forms of victimization and suicide risk were mediated by sleep duration, depression, and also serially mediated by sleep duration and depression. Limitations This is a cross-sectional study, and the results cannot inform the causality between these variables. This investigation only included adolescent sleep duration, and other specific sleep problem indicators should be included. Conclusions Longer sleep duration is an important protective factor, pointing the way forward for developing suicide prevention strategies and targeted interventions for adolescents

The impact of board demographic diversity on firm performance: evidence from China

The board plays a critical role in strategy formulation, oversight and resource provision to improve corporate performance and is influenced by the demographics of directors. The empirical evidence on the relationship between board demographic diversity and firm performance presents inconsistent results. The purpose of this study is to advance research by examining the impact of board demographic diversity on firm performance in the Chinese market. Based on panel data of listed A-share companies in Shanghai and Shenzhen in China from 2010-2019, the study employed a two-factor fixed effects model to conduct separate regression tests on the constructed composite board demographic diversity indicator and the individual demographic attributes comprising it including gender, age, education and tenure. Further testing of the diversity-performance relationship was carried out by dividing the sample into state-owned and private companies according to ownership. The study found that board demographic diversity had an overall positive impact on firm performance. Specifically for the individual variables a linear positive relationship was found between tenure diversity and firm performance, a positive U-shaped curve relation was identified for age diversity, while gender and education were not significantly related. A positive association was found for private firms and a non-significant association for state-owned enterprises under different ownership. The findings complement the evidence from the Chinese context and help to expand the boundaries of the literature in the field of corporate governance and the business case for board demographic diversity research. In addition, this study would contribute to better design of boards and selection of appropriate members by companies, as well as help policy makers to actively develop proposals and laws to guide the composition of boards of directors of Chinese companies in a scientific manner

Efficient semi-supervised inference for logistic regression under case-control studies

Semi-supervised learning has received increasingly attention in statistics and machine learning. In semi-supervised learning settings, a labeled data set with both outcomes and covariates and an unlabeled data set with covariates only are collected. We consider an inference problem in semi-supervised settings where the outcome in the labeled data is binary and the labeled data is collected by case-control sampling. Case-control sampling is an effective sampling scheme for alleviating imbalance structure in binary data. Under the logistic model assumption, case-control data can still provide consistent estimator for the slope parameter of the regression model. However, the intercept parameter is not identifiable. Consequently, the marginal case proportion cannot be estimated from case-control data. We find out that with the availability of the unlabeled data, the intercept parameter can be identified in semi-supervised learning setting. We construct the likelihood function of the observed labeled and unlabeled data and obtain the maximum likelihood estimator via an iterative algorithm. The proposed estimator is shown to be consistent, asymptotically normal, and semiparametrically efficient. Extensive simulation studies are conducted to show the finite sample performance of the proposed method. The results imply that the unlabeled data not only helps to identify the intercept but also improves the estimation efficiency of the slope parameter. Meanwhile, the marginal case proportion can be estimated accurately by the proposed method

The impact of honors education on students’ academic and innovative achievements: a longitudinal study in China (2011–2021)

Honors education has ascended as an integral element within the sphere of global higher education, concentrating on fostering individuals who exhibit creativity and a history of innovative achievements. Despite its widespread adoption, there remains a scarcity of exhaustive longitudinal studies investigating its effects and associated variables. To address this shortcoming, this study deploys rigorous structural equation modeling (SEM) and linear regression analyses to meticulously examine a dataset comprising 319 students, who enrolled over a decade (2011–2021) in a prestigious honors college at a preeminent university in China. The primary objective is to discern the predictive efficacy of Chinese honors education selection criteria on students’ creative and academic accomplishments. This endeavor strives to clarify the complex interplay among students’ creative personalities, academic performance, creative achievements, and standardized college entrance exam scores. The findings emphasize that individuals who exhibit enhanced creative personality traits are predisposed to elevated levels of both innovation and academic attainment (β = 0.170, p  = 0.017). Additionally, a significant inverse relationship is observed between general learning aptitude and subsequent academic performance (β = −0.008, p = 0.023), while students pursuing science disciplines demonstrate superior innovation outcomes compared to their liberal arts counterparts (β = 0.125, p  = 0.048). Interestingly, neither gender nor general academic prowess exerts significant predictive power over collegiate innovation (β  = −0.002, p = 0.134). These empirical insights equip policymakers and scholars with nuanced perspectives on the determinants shaping students’ refined educational experiences, thereby inciting critical discourse concerning the refinement of selection criteria and the imperative of nurturing students’ creative proclivities

Research progress on postharvest quality deterioration and preservation technology of blueberry

Because of high moisture content, blueberries are susceptible to disease and insect infestation leading to corruption and deterioration, which has serious influence on the shelf life of blueberry fruits. This article summarizes the cause mechanism of postharvest quality deterioration of blueberry fruits and the research progress of blueberry preservation technology at home and abroad, mainly including physical, chemical and biological preservation methods; and emphasizes the application of biological methods in the postharvest preservation of blueberries

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

The impact of board demographic diversity on firm performance: evidence from China

The board plays a critical role in strategy formulation, oversight and resource provision to improve corporate performance and is influenced by the demographics of directors. The empirical evidence on the relationship between board demographic diversity and firm performance presents inconsistent results. The purpose of this study is to advance research by examining the impact of board demographic diversity on firm performance in the Chinese market. Based on panel data of listed A-share companies in Shanghai and Shenzhen in China from 2010-2019, the study employed a two-factor fixed effects model to conduct separate regression tests on the constructed composite board demographic diversity indicator and the individual demographic attributes comprising it including gender, age, education and tenure. Further testing of the diversity-performance relationship was carried out by dividing the sample into state-owned and private companies according to ownership. The study found that board demographic diversity had an overall positive impact on firm performance. Specifically for the individual variables a linear positive relationship was found between tenure diversity and firm performance, a positive U-shaped curve relation was identified for age diversity, while gender and education were not significantly related. A positive association was found for private firms and a non-significant association for state-owned enterprises under different ownership. The findings complement the evidence from the Chinese context and help to expand the boundaries of the literature in the field of corporate governance and the business case for board demographic diversity research. In addition, this study would contribute to better design of boards and selection of appropriate members by companies, as well as help policy makers to actively develop proposals and laws to guide the composition of boards of directors of Chinese companies in a scientific manner