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"Zhang, Xinfeng"
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Association between internet addiction and insomnia among college freshmen: the chain mediation effect of emotion regulation and anxiety and the moderating role of gender
Background
The advancement of the information age has led to the widespread use of the internet, accompanied by numerous internet-related issues that often correlate with various physical and mental health conditions, particularly among college freshmen. We examined the relationship between internet addiction (IA) and insomnia among these students, using emotion regulation (ER) and anxiety as mediators and gender as a moderating variable.
Methods
This cross-sectional study included 7,353 freshmen from a university in Jingzhou City, Hubei Province, China. Data were collected through an online self-administered questionnaire, including the Internet Addiction Test (IAT), the Emotion Regulation subscale (ER), the Generalized Anxiety Disorder 7-item scale (GAD-7), and the Insomnia Severity Index (ISI). Data analysis was conducted using SPSS 21.0 and PROCESS version 4.1 to test the hypothesized relationships among variables.
Results
In our survey, correlation analysis showed that ER was significantly negatively correlated with IA, anxiety, and insomnia; IA was significantly positively correlated with anxiety and insomnia (all
p
< 0.01). The mediating effect analysis indicated that IA was a significant positive predictor of insomnia. ER and anxiety played a chain - mediating role in the development of insomnia (β = 0.039, 95% confidence interval = 0.035–0.043). The moderating effect analysis showed that the interaction term of IA and gender had a significant negative predictive effect on ER (β = -0.014, 95% confidence interval [-0.027, -0.001]) and insomnia (β = -0.022, 95% confidence interval [-0.036, -0.007]). Males (direct effect: β = 0.048, 95% confidence interval = [0.037, 0.059]) had a stronger predictive ability for the level of insomnia than females (direct effect: β = 0.026, 95% confidence interval = [0.014, 0.037]). Females (indirect effect 1: β = 0.015, 95% confidence interval = [0.010, 0.020]; indirect effect 2: β = 0.041, 95% confidence interval = [0.037, 0.045]) had a stronger predictive ability for the level of insomnia through the level of IA than males (indirect effect 1: β = 0.014, 95% confidence interval = [0.009, 0.018]; indirect effect 2: β = 0.037, 95% confidence interval = [0.033, 0.041]).
Conclusion
IA can exacerbate insomnia in college freshmen by compromising their ER, subsequently triggering anxiety symptoms. The process differs by gender, suggesting tailored strategies for each. These findings may play crucial roles in promoting the physical and mental well-being of college freshmen.
Journal Article
Lithium-Ion Battery Modeling and State of Charge Prediction Based on Fractional-Order Calculus
Predicting lithium-ion batteries’ state of charge (SOC) is essential to electric vehicle battery management systems. Traditional lithium-ion battery models mainly include equivalent circuit models (ECMs) and electrochemical models (EMs). ECMs are based on integer-order component modeling, which cannot characterize the internal electrochemical reaction mechanism of the battery, resulting in lower SOC prediction accuracy. In contrast, due to their complex structure, EMs are limited in their application. This study takes lithium batteries as the research object and proposes a fractional-order impedance model (FOIM) that characterizes the dynamic properties of the internal behavior of lithium-ion batteries using fractional-order elements. Considering the highly nonlinear characteristics of lithium-ion batteries, this study introduces the theory of fractional-order calculus into the extended Kalman filter (EKF) algorithm, and proposes the fractional-order extended Kalman filter (FEKF) algorithm applied to the prediction of battery charge state. Comparative analysis of simulation and experimental results shows that the accuracy of the FOIM, compared to ECMs, is significantly improved. The FEKF algorithm has good robustness in estimating the SOC, and the SOC prediction accuracy achieved with the algorithm is also improved compared with that obtained using the EKF algorithm of the integer-order model.
Journal Article
Damage and Crack Propagation Mechanism of Q345 Specimen Based on Peridynamics with Temperature and Bolt Holes
With the increasing demand for the performance and design refinement of steel structures (including houses, bridges, and infrastructure), many structures have adopted ultimate bearing capacity in service. The design service lives of steel building structures are generally more than 50 years, and most of them contain bolted connections, which suffer from extreme conditions such as fire (high temperature) during service. When the structure contains defects or cracks and bolt holes, it is easy to produce stress concentration at the defect location, which leads to crack nucleation and crack propagation, reduces the bearing capacity of the structure, and causes the collapse of the structure and causes disasters. In the process of structural damage and crack propagation, the traditional method has some disadvantages, such as stress singularity, the mesh needing to be redivided, and the crack being restricted to mesh; however, the integral method of peridynamics (PD) can completely avoid these problems. Therefore, in this paper, the constitutive equation of PD in high temperature is derived according to the variation law of steel material properties when changed by temperature increase and peridynamics parameters; the damage and crack expansion characteristics of Q345 steel specimens with bolt holes and a central double-crack at 20 °C, 200 °C, 400 °C, and 600 °C were analyzed to clarify the structural damage and failure mechanism. This study is helpful for providing theoretical support for the design of high-temperature steel structures, improving the stability of the structure, and ensuring the bearing capacity of the structure and the safety of people’s lives and property.
Journal Article
BOS1 is a basic helix–loop–helix transcription factor involved in regulating panicle development in rice
Panicle development is crucial to increase the grain yield of rice ( Oryza sativa ). The molecular mechanisms of the control of panicle development in rice remain unclear. In this study, we identified a mutant with abnormal panicles, termed branch one seed 1-1 ( bos1-1 ). The bos1-1 mutant showed pleiotropic defects in panicle development, such as the abortion of lateral spikelets and the decreased number of primary panicle branches and secondary panicle branches. A combined map-based cloning and MutMap approach was used to clone BOS1 gene. The bos1-1 mutation was located in chromosome 1. A T-to-A mutation in BOS1 was identified, which changed the codon from TAC to AAC, resulting in the amino acid change from tyrosine to asparagine. BOS1 gene encoded a grass-specific basic helix–loop–helix transcription factor, which is a novel allele of the previously cloned LAX PANICLE 1 ( LAX1 ) gene. Spatial and temporal expression profile analyses showed that BOS1 was expressed in young panicles and was induced by phytohormones. BOS1 protein was mainly localized in the nucleus. The expression of panicle development-related genes, such as OsPIN2 , OsPIN3 , APO1 , and FZP , was changed by bos1-1 mutation, suggesting that the genes may be the direct or indirect targets of BOS1 to regulate panicle development. The analysis of BOS1 genomic variation, haplotype, and haplotype network showed that BOS1 gene had several genomic variations and haplotypes. These results laid the foundation for us to further dissect the functions of BOS1.
Journal Article
Nanotheranostics in Breast Cancer Bone Metastasis: Advanced Research Progress and Future Perspectives
Breast cancer is the leading cause of cancer-related morbidity and mortality among women worldwide, with bone being the most common site of all metastatic breast cancer. Bone metastases are often associated with pain and skeletal-related events (SREs), indicating poor prognosis and poor quality of life. Most current therapies for breast cancer bone metastasis primarily serve palliative purposes, focusing on pain management, mitigating the risk of bone-related complications, and inhibiting tumor progression. The emergence of nanodelivery systems offers novel insights and potential solutions for the diagnosis and treatment of breast cancer-related bone metastasis. This article reviews the recent advancements and innovative applications of nanodrug delivery systems in the context of breast cancer bone metastasis and explores future directions in nanotheranostics.
Journal Article
Guideline for extraction, qualitative, quantitative, and stability analysis of anthocyanins
Anthocyanins, as a kind of natural pigment, have a broad development prospect in the field of human production and life due to its safety, nontoxic, rich resources, and rich pharmacological effects. However, due to the structure instability of anthocyanins, anthocyanins are susceptible to physical and chemical factors during food processing, such as light, temperature, pH, metal ions, food additives, oxidation reductants, and cochromatic factors. This review summarized the experimental methods for these factors affecting anthocyanin content, structural transformation, and degradation dynamics, which lays the foundation for further studies of anthocyanins in plants. Meanwhile, we expounded the methods for obtaining accurate quantitative and qualitative data of anthocyanin by UV‐vis, HPLC, LC‐MS, and NMR, which can provide a basis for further development and utilization of anthocyanin resources.
Journal Article
Deep encoder/decoder dual-path neural network for speech separation in noisy reverberation environments
In recent years, the speaker-independent, single-channel speech separation problem has made significant progress with the development of deep neural networks (DNNs). However, separating the speech of each interested speaker from an environment that includes the speech of other speakers, background noise, and room reverberation remains challenging. In order to solve this problem, a speech separation method for a noisy reverberation environment is proposed. Firstly, the time-domain end-to-end network structure of a deep encoder/decoder dual-path neural network is introduced in this paper for speech separation. Secondly, to make the model not fall into local optimum during training, a loss function stretched optimal scale-invariant signal-to-noise ratio (SOSISNR) was proposed, inspired by the scale-invariant signal-to-noise ratio (SISNR). At the same time, in order to make the training more appropriate to the human auditory system, the joint loss function is extended based on short-time objective intelligibility (STOI). Thirdly, an alignment operation is proposed to reduce the influence of time delay caused by reverberation on separation performance. Combining the above methods, the subjective and objective evaluation metrics show that this study has better separation performance in complex sound field environments compared to the baseline methods.
Journal Article
Aerodynamic Interaction Characteristics Study of the Ducted Coaxial Propeller for a Novel eVTOL in Hovering
The ducted coaxial propeller (DCP) is highly advantageous in the design of eVTOL aircraft due to its safety, compactness, and low noise levels. To study the aerodynamic characteristics of DCP in hovering, a novel eVTOL was used, and a slip grid model was established to solve the three-dimensional unsteady N-S equation. The aerodynamic characteristics of DCP were compared to those of the free coaxial propeller (FCP) and ducted single propeller (DSP) to reveal the interaction mechanism of unsteady flow between the duct and propellers. The results indicate that the duct significantly mitigates the intensity of tip vortexes by changing the characteristics of propeller tip winding, which reduces the corresponding energy loss. Additionally, the static pressure loss is decreased by the reduced radical-induced velocity in the slipstream area. Finally, the induced power loss is reduced by the decreased axial-induced velocity and suppressed wake contraction, resulting in DCP having 39% higher aerodynamic efficiency than FCP and the duct accounting for 41.7% of the total lift. Although DCP generates 1.77 times more lift than DSP, its aerodynamic efficiency is only 91.08% of DSP.
Journal Article
Control of Semiactive Suspension Systems Using Preview Information and Convolutional Neural Networks
Due to the complexity and variability of road conditions during vehicle operation, the ability of suspension systems to effectively suppress vehicle vibrations is often limited. To enhance ride comfort of the vehicle across varying road surfaces, a preview control strategy is designed based on the convolutional neural network (CNN) and skyhook control for semiactive suspension. First, the advantages and limitations of conventional skyhook control are analyzed, and a mixed adaptive damping system (M‐ADS) incorporating preview functionality is developed. Meanwhile, a target classification model based on the CNN is constructed. This model adopts the road surface type recognition model of residual neural network (ResNet152) and can automatically recognize 15 types of road surfaces such as Belgian roads accurately and quickly. Finally, the control process for the M‐ADS is designed, and the effectiveness of the designed controller is demonstrated by the comparative vehicle road tests. The test results show that compared with the skyhook wheelbase preview controller (SWPC), skyhook controller (SC), and passive suspension (PS), the proposed controller can effectively improve the ride comfort of the vehicle.
Journal Article