A Study on the Training Mode of Electronic Application- Oriented Undergraduate with Industry Needs

Electronic industry is an economic pillar in China. Due to the Moore’s Law, the industry requires continuous development and innovation. In order to achieve these goals, the cultivation of electronic application-oriented undergraduate is essential. However, at current, the innovative educational concepts and teaching methods are lagging behind so that the graduates cannot meet the requirements of electronic industry. In this paper, we adopt a variety of measures, which include the construction of parallel course system, the establishment of cooperative education mechanics and the creation of training evaluation mode, to improve the training quality of electronic application-oriented undergraduate. The research findings show that the undergraduates improve their engineering practices and innovation abilities

High-dimensional quantile mediation analysis with application to a birth cohort study of mother-newborn pairs

MOTIVATION: There has been substantial recent interest in developing methodology for high-dimensional mediation analysis. Yet, the majority of mediation statistical methods lean heavily on mean regression, which limits their ability to fully capture the complex mediating effects across the outcome distribution. To bridge this gap, we propose a novel approach for selecting and testing mediators throughout the full range of the outcome distribution spectrum. RESULTS: The proposed high-dimensional quantile mediation model provides a comprehensive insight into how potential mediators impact outcomes via their mediation pathways. This method\u27s efficacy is demonstrated through extensive simulations. The study presents a real-world data application examining the mediating effects of DNA methylation on the relationship between maternal smoking and offspring birthweight. AVAILABILITY AND IMPLEMENTATION: Our method offers a publicly available and user-friendly function qHIMA(), which can be accessed through the R package HIMA at https://CRAN.R-project.org/package=HIMA

HIMA2: High-dimensional mediation analysis and its application in epigenome-wide DNA methylation data

Mediation analysis plays a major role in identifying significant mediators in the pathway between environmental exposures and health outcomes. With advanced data collection technology for large-scale studies, there has been growing research interest in developing methodology for high-dimensional mediation analysis. In this paper we present HIMA2, an extension of the HIMA method (Zhang in Bioinformatics 32:3150-3154, 2016). First, the proposed HIMA2 reduces the dimension of mediators to a manageable level based on the sure independence screening (SIS) method (Fan in J R Stat Soc Ser B 70:849-911, 2008). Second, a de-biased Lasso procedure is implemented for estimating regression parameters. Third, we use a multiple-testing procedure to accurately control the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. We demonstrate its practical performance using Monte Carlo simulation studies and apply our method to identify DNA methylation markers which mediate the pathway from smoking to reduced lung function in the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Coal based carbon dots: recent advances in synthesis, properties, and applications

Carbon dots are zero-dimensional carbon nanomaterials with quantum confinement effects and edge effects, which have aroused great interests in many disciplines such as energy, chemistry, materials, and environmental applications. They can be prepared by chemical oxidation, electrochemical synthesis, hydrothermal preparation, arc discharge, microwave synthesis, template method, and many other methods. However, the raw materials' high cost, the complexity and environmental-unfriendly fabrication process limit their large-scale production and commercialization. Herein, we review the latest developments of coal-based carbon dots about selecting coal-derived energy resources (bituminous coal, anthracite, lignite, coal tar, coke, etc.) the developments of synthesis processes, surface modification, and doping of carbon dots. The coal-based carbon dots exhibit the advantages of unique fluorescence, efficient catalysis, excellent water solubility, low toxicity, inexpensive, good biocompatibility, and other advantages, which hold the potentiality for a wide range of applications such as environmental pollutants sensing, catalyst preparation, chemical analysis, energy storage, and medical imaging technology. This review aims to provide a guidance of finding abundant and cost-effective precursors, green, simple and sustainable production processes to prepare coal-based carbon dots, and make further efforts to exploit the application of carbon dots in broader fields

Regulation of microglia polarization after cerebral ischemia

Stroke ranks second as a leading cause of death and permanent disability globally. Microglia, innate immune cells in the brain, respond rapidly to ischemic injury, triggering a robust and persistent neuroinflammatory reaction throughout the disease’s progression. Neuroinflammation plays a critical role in the mechanism of secondary injury in ischemic stroke and is a significant controllable factor. Microglia activation takes on two general phenotypes: the pro-inflammatory M1 type and the anti-inflammatory M2 type, although the reality is more complex. The regulation of microglia phenotype is crucial to controlling the neuroinflammatory response. This review summarized the key molecules and mechanisms of microglia polarization, function, and phenotypic transformation following cerebral ischemia, with a focus on the influence of autophagy on microglia polarization. The goal is to provide a reference for the development of new targets for the treatment for ischemic stroke treatment based on the regulation of microglia polarization

Exosomal Vimentin from Adipocyte Progenitors Protects Fibroblasts against Osmotic Stress and Inhibits Apoptosis to Enhance Wound Healing

Mechanical stress following injury regulates the quality and speed of wound healing. Improper mechanotransduction can lead to impaired wound healing and scar formation. Vimentin intermediate filaments control fibroblasts' response to mechanical stress and lack of vimentin makes cells significantly vulnerable to environmental stress. We previously reported the involvement of exosomal vimentin in mediating wound healing. Here we performed in vitro and in vivo experiments to explore the effect of wide-type and vimentin knockout exosomes in accelerating wound healing under osmotic stress condition. Our results showed that osmotic stress increases the size and enhances the release of exosomes. Furthermore, our findings revealed that exosomal vimentin enhances wound healing by protecting fibroblasts against osmotic stress and inhibiting stress-induced apoptosis. These data suggest that exosomes could be considered either as a stress modifier to restore the osmotic balance or as a conveyer of stress to induce osmotic stress-driven conditions

A cascade learning approach for automated detection of locomotive speed sensor using imbalanced data in ITS

Automatic and intelligent railway locomotive inspection and maintenance are fundamental issues in high-speed rail applications and intelligent transportation system (ITS). Traditional locomotive equipment inspection is carried out manually on-site by workers, and the task is exhausting, cumbersome, and unsafe. Based on computer vision and machine learning, this paper presents an approach to the automatic detection of the locomotive speed sensor equipment, an important device in locomotives. Challenges to the detection of speed sensor mainly concerns complex background, motion blur, muddy noise, and variable shapes. In this paper, a cascade learning framework is proposed, which includes two learning stages: target localization and speed sensor detection, to reduce the complexity of the research object and solve the imbalance of samples. In the first stage, histogram of oriented gradient feature and support vector machine (HOG-SVM) model is used for multi-scale detection. Then, an improved LeNet-5 model is adopted in the second stage. To solve the problem of the imbalance of positive and negative samples of speed sensor, a combination strategy which draws on four individual classifiers is designed to construct an ensemble of classifier for recognition, and the results of three different algorithms are compared. The experimental results demonstrate that our approach is effective and robust with respect to changes in speed sensor patterns for robust equipment identification.N/

Single Fasting Plasma Glucose Versus 75-g Oral Glucose-Tolerance Test in Prediction of Adverse Perinatal Outcomes::A Cohort Study

Background: There remains uncertainty regarding whether a single fasting glucose measurement is sufficient to predict risk of adverse perinatal outcomes. Methods: We included 12,594 pregnant women who underwent a 75-g oral glucose-tolerance test (OGTT) at 22–28 weeks' gestation in the Born in Guangzhou Cohort Study, China. Outcomes were large for gestational age (LGA) baby, cesarean section, and spontaneous preterm birth. We calculated the area under the receiver operator characteristic curves (AUCs) to assess the capacity of OGTT glucose values to predict adverse outcomes, and compared the AUCs of different components of OGTT. Results: 1325 women had a LGA baby (10.5%). Glucose measurements were linearly associated with LGA, with strongest associations for fasting glucose (odds ratio 1.37, 95% confidence interval 1.30–1.45). Weaker associations were observed for cesarean section and spontaneous preterm birth. Fasting glucose have a comparable discriminative power for prediction of LGA to the combination of fasting, 1 h, and 2 h glucose values during OGTT (AUCs, 0.611 vs. 0.614, P = 0.166). The LGA risk was consistently increased in women with abnormal fasting glucose (≥5.1 mmol/l), irrespective of 1 h or 2 h glucose levels. Conclusions: A single fasting glucose measurement performs comparably to 75-g OGTT in predicting risk of having a LGA baby