Relationship Between Physical Activity and Mental Health in Chinese Engineering College Students During COVID-19

The issue of mental health among college students is concerning during COVID-19 outbreak. Since engineering college students are vulnerable to mental health issues, the objectives of this study were: (1) to analyze the relationship between physical activity, parental psychological control, basic psychological needs, anxiety, and mental health in Chinese engineering college students during COVID-19 pandemic; and (2) to examine the mediation effect of anxiety between the relationship of basic psychological needs and mental health. A cross-sectional study was conducted among several universities in Shandong Province, China. We randomly selected 254 Chinese engineering college students. Participants completed the Physical Activity Rating Scale (PARS-3), Basic Needs Satisfaction in General Scale (BNSG-S), Parental Psychological Control Questionnaire, the Beck Anxiety Inventory (BAI), and the Kessler 10 (K10) scale. The mediation model was conducted to assess the mediation effect of anxiety between the relationship of basic psychological needs and mental health. Among 254 Chinese college students majoring in engineering, their mental health was in the mid-level range. Besides, physical activity and basic psychological needs is positively correlated with mental health, respectively, while parental psychological control is not correlated with mental health. Anxiety is negatively associated with mental health. Mediation analysis revealed that anxiety played a mediation role in the relationship between basic psychological needs and mental health. To our knowledge, this is the first study to examine the relationships between physical activity, parental psychological control, basic psychological needs, anxiety, and mental health in Chinese engineering college students during COVID-19 pandemic. Mental health of Chinese engineering college students deserves extensive attention during COVID-19 pandemic. In the current study, we found that physical activity, basic psychological need was positively associated with mental health, while anxiety was negatively correlated to mental health. Besides, anxiety played a mediation effect in the relationship between basic psychological needs and mental health. Government or educators can guide and help meet students’ basic psychological needs and promote physical activity participation, thus reducing their anxiety level and improving their mental health

A LID APPROACH FOR PREDICTING WAVE INDUCED MOTIONS OF TRIMARAN IN REGULAR WAVES

The wave induced motions of a trimaran sailing in regular head waves were predicted by using the three dimensional boundary integral method. Large wave elevation on the free surface in between the trimaran’s main-hull and the outriggers occurred at some specific frequencies in the numerical model. The large wave elevation also induced large heave and pitch motions of trimaran. However, the large wave elevation and corresponding large motions were not observed during towing tank tests. A lid approach was introduced in this paper by placing lid on the free surface in between hulls to suppress the unrealistically large wave elevation and to correctly predict the induced motions of trimaran. The feasibility and practicability of lid approach were validated against experimental results

Nonlinear robust control of tail-sitter aircrafts in flight mode transitions

© 2018 Elsevier Masson SAS In this paper, a nonlinear robust controller is proposed to deal with the flight mode transition control problem of tail-sitter aircrafts. During the mode transitions, the control problem is challenging due to the high nonlinearities and strong couplings. The tail-sitter aircraft model can be considered as a nominal part with uncertainties including nonlinear terms, parametric uncertainties, and external disturbances. The proposed controller consists of a nominal H∞controller and a nonlinear disturbance observer. The nominal H∞controller based on the nominal model is designed to achieve the desired trajectory tracking performance. The uncertainties are regarded as equivalent disturbances to restrain their influences by the nonlinear disturbance observer. Theoretical analysis and simulation results are given to show advantages of the proposed control method, compared with the standard H∞control approach

Chronology of the Basalt Units Surrounding Chang’e-4 Landing Area

The Chang’e-4 (CE-4) lunar probe, the first soft landing spacecraft on the far side of the Moon, successfully landed in the Von Kármán crater on 3 January 2019. Geological studies of the landing area have been conducted and more intensive studies will be carried out with the in situ measured data. The chronological study of the maria basalt surrounding the CE-4 landing area is significant to the related studies. Currently, the crater size-frequency distribution (CSFD) technique is the most popular method to derive absolute model ages (AMAs) of geological units where no returned sample is available, and it has been widely used in dating maria basalt on the lunar surface. In this research, we first make a mosaic with multi-orbital Chang’e-2 (CE-2) images as a base map. Coupled with the elevation data and FeO content, nine representative areas of basalt units surrounding the CE-4 landing area are outlined and their AMAs are derived. The dating results of the nine basalt units indicate that the basalts erupted from 3.42 to 2.28 Ga ago in this area, a period much longer than derived by previous studies. The derived chronology of the above basalt units establishes a foundation for geological analysis of the returned CE-4 data

Learning to Detect Noisy Labels Using Model-Based Features

Label noise is ubiquitous in various machine learning scenarios such as self-labeling with model predictions and erroneous data annotation. Many existing approaches are based on heuristics such as sample losses, which might not be flexible enough to achieve optimal solutions. Meta learning based methods address this issue by learning a data selection function, but can be hard to optimize. In light of these pros and cons, we propose Selection-Enhanced Noisy label Training (SENT) that does not rely on meta learning while having the flexibility of being data-driven. SENT transfers the noise distribution to a clean set and trains a model to distinguish noisy labels from clean ones using model-based features. Empirically, on a wide range of tasks including text classification and speech recognition, SENT improves performance over strong baselines under the settings of self-training and label corruption

Exploring the relationship between distress rumination, resilience, depression, and self-injurious behaviors among Chinese college athletes infected with COVID-19: a cross-sectional study

ObjectivesDistress rumination is a cause of suicidality and self-injurious behavior (SSIB) among individuals. Although previous studies have shown that distress rumination, SSIB, resilience, and depression are significantly related, the interaction mechanism remains unclear. This study aimed to evaluate resilience and depression as mediators of the relationship between distress rumination and SSIB among Chinese college athletes infected with COVID-19.MethodsConvenience sampling was used to recruit participants from the National College Football Championship in Guangxi City, China from January to February 2023. Participants completed the Ruminative Responses Scale (RRS), a subscale of the Health-Risk Behavior Inventory (HBI), the Mental Toughness Index (MTI) and the Patient Health Questionnaire (PHQ-9). We used the PROCESS macro for SPSS to determine the mediating effect of resilience and depression between distress rumination and SSIB.ResultsA total of 350 Chinese college athletes participated in this study and completed the questionnaire survey. 289 (81.7% boys; Mage = 20.31 years, SD = 1.60) of them have been infected with COVID-19. 59.9% (n = 173) participants were from urban areas and 15.6% (n = 45) of participants have engaged in self-injurious behaviors or suicidal ideation. College athletes’ distress rumination was significantly negatively correlated with resilience (r = − 0.28, p < 0.01), and was significantly positively correlated with depression (r = 0.49, p < 0.01) and SSIB (r = − 0.18, p < 0.01). Resilience was significantly negatively correlated with depression (r = − 0.35, p < 0.01) and SSIB (r = − 0.30, p < 0.01). Finally, depression was significantly positively correlated with SSIB (r = − 0.38, p < 0.01). Resilience and depression played a mediating role of the total effects of distress rumination and SSIB, respectively. Meanwhile, the chain mediating effect of resilience and depression was also significant.ConclusionThis study found that distress rumination can directly predict SSIB, and indirectly predict SSIB through the mediating effect of resilience and depression, and the chain mediating effect of resilience-depression. Therefore, reducing the degree of distress rumination of college athletes infected by COVID-19 and improving their resilience, as well as reducing their depression may help prevent SSIB

Real-time equilibrium reconstruction by neural network based on HL-3 tokamak

A neural network model, EFITNN, has been developed capable of real-time magnetic equilibrium reconstruction based on HL-3 tokamak magnetic measurement signals. The model processes inputs from 68 channels of magnetic measurement data gathered from 1159 HL-3 experimental discharges, including plasma current, loop voltage, and the poloidal magnetic fields measured by equilibrium probes. The outputs of the model feature eight key plasma parameters, alongside high-resolution ($129\times129$) reconstructions of the toroidal current density $J_{\text P}$ and poloidal magnetic flux profiles $\Psi_{rz}$. Moreover, the network's architecture employs a multi-task learning structure, which enables the sharing of weights and mutual correction among different outputs, and lead to increase the model's accuracy by up to 32%. The performance of EFITNN demonstrates remarkable consistency with the offline EFIT, achieving average $R^2 = 0.941, 0.997$ and $0.959$ for eight plasma parameters, $\Psi_{rz}$ and $J_{\text P}$, respectively. The model's robust generalization capabilities are particularly evident in its successful predictions of quasi-snowflake (QSF) divertor configurations and its adept handling of data from shot numbers or plasma current intervals not previously encountered during training. Compared to numerical methods, EFITNN significantly enhances computational efficiency with average computation time ranging from 0.08ms to 0.45ms, indicating its potential utility in real-time isoflux control and plasma profile management

Proteins of the food-borne pathogen <i>Listeria monocytogenes</i> strain F2365 relevant to lethal acidic stress and during rapid inactivation

Listeria monocytogenes, which causes human listeriosis after consumption of contaminated food, can adapt and survive under a wide range of physiological and chemical stresses. In this study, the overall proteomic response of the L. monocytogenes strain F2365—a strain with mutations limiting its ability to tolerate acidic conditions—to progressive non-thermal acidic inactivation was investigated. The challenge process was investigated in the early stationary growth phase where F2365 cultures were acidified (pH 3.0, HCl) at 5 min, 1 h, and 2 h, generating pH 4.8, pH 4.1, and pH 3.5, respectively, with protein abundance measured using iTRAQ. Approximately 73 proteins increased in abundance and 8 declined when acidic stress became non-growth-permissive (pH &lt; 4.1) and inactivation accelerated to approximately 2 log units/h. The functional categories of responding proteins were broad but the proteins involved were specific in nature and did not include whole pathways. Many responses likely accentuate energy conservation and compensate vital metabolic processes. For example, further repression of FlaA, normally repressed under acidic stress, occurs accompanied by an increase in quinol oxidase subunit QoxA and glycerol kinase GlpK. Proteins maintaining cell wall integrity, such as Iap and CwlO, manifested the overall largest abundance increase trend. Virulence proteins were also induced, including InlA, InlC, Hyl, Mpl, PlcA, and PlcB, suggesting that acidification may have mimicked conditions inducing some host survival traits. The overall suite of proteins affected appears to be the "last ditch" responses to non-thermal inactivation above and beyond the standard protections afforded in the stationary-growth phase. The array of proteins found here may provide a deeper understanding of the physiological responses of this pathogen during non-thermal inactivation