THE CORRELATION BETWEEN PSYCHIATRIC DISORDERS AND COVID-19: A NARRATIVE REVIEW

Since December 2019, the havoc caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has increased exponentially in a short period of time. As the COVID-19 pandemic is raging around the world, scientists are trying to reveal its mysteriousness. Although COVID-19 is predominantly a respiratory disease, the most common symptoms are fever, dry cough, and fatigue, but extrapulmonary manifestations are increasingly recognized. Recent studies have shown that there is a strong genetic correlation between one or more psychiatric disorders and the occurrence of SARS-CoV-2 infection. Historical epidemiological perspectives and recent neurobiological evidence link infection and psychosis. What is the relationship between COVID-19 and psychiatric disorders? In this article, we will review the correlation between COVID-19 and psychoses, the possible reasons, and the possible pathophysiological mechanisms. The purpose of this review is to provide a reference for clinicians to make correct judgment and treatment when facing patients with COVID-19 and/or psychiatric disorders

Reform of Elastic-Plastic Mechanics and Strength Design of Pipelines Based on Ideological and Political Education

Oil and gas storage and transportation safety courses are very important in oil and gas storage and transportation engineering. With the ideological and political construction of the course in the new period, the mode of professional knowledge teaching cannot meet the teaching requirements. The teaching team has been practicing in the course for many years. By inserting typical characters, typical projects, national policies and industry trends into the course, students' patriotism, academic confidence and environmental protection awareness have been cultivated, and remarkable results have been achieved. At the same time, it can provide some reference for the ideological and political education of engineering majors

Learning One-Class Hyperspectral Classifier from Positive and Unlabeled Data for Low Proportion Target

Hyperspectral imagery (HSI) one-class classification is aimed at identifying a single target class from the HSI by using only positive labels, which can significantly reduce the requirements for annotation. However, HSI one-class classification is far more challenging than HSI multi-class classification, due the lack of negative labels and the low target proportion, which are issues that have rarely been considered in the previous HSI classification studies. In this paper, a weakly supervised HSI one-class classifier, namely HOneCls is proposed to solve the problem of under-fitting of the positive class occurs in the HSI data with low target proportion, where a risk estimator -- the One-Class Risk Estimator -- is particularly introduced to make the full convolutional neural network (FCN) with the ability of one class classification. The experimental results obtained on challenging hyperspectral classification datasets, which includes 20 kinds of ground objects with very similar spectra, demonstrate the efficiency and feasibility of the proposed One-Class Risk Estimator. Compared with the state-of-the-art one-class classifiers, the F1-score is improved significantly in the HSI data with low target proportion

The Reform of Elastic-plastic Mechanics Teaching for Petroleum Engineering Related Majors

“Elastic-plastic Mechanics” is an important course for undergraduates and postgraduates of general engineering majors. However, the theoretical derivation of equations is complex, and the connection with engineering practice is inadequate. Therefore, teaching becomes difficult and boring for a number of students. Firstly, this paper introduces the importance of Elastic-plastic Mechanics for petroleum engineering related majors. Based on the recent teaching experience, the teaching reform of Elastic-plastic Mechanics course is carried out focusing on teaching method and learning content, and a discussion teaching mode based on students’ independent discussion and engineering cases is formed. Remarkable results have been achieved in improving students’ learning efficiency and classroom teaching effect. Furthermore, students’ comprehensive ability of independent innovation and practice is enhanced

Crossover between Weak Antilocalization and Weak Localization of Bulk States in Ultrathin Bi2Se3 Films

We report transport studies on the 5 nm thick Bi2Se3 topological insulator films which are grown via molecular beam epitaxy technique. The angle-resolved photoemission spectroscopy data show that the Fermi level of the system lies in the bulk conduction band above the Dirac point, suggesting important contribution of bulk states to the transport results. In particular, the crossover from weak antilocalization to weak localization in the bulk states is observed in the parallel magnetic field measurements up to 50 Tesla. The measured magneto-resistance exhibits interesting anisotropy with respect to the orientation of B// and I, signifying intrinsic spin-orbit coupling in the Bi2Se3 films. Our work directly shows the crossover of quantum interference effect in the bulk states from weak antilocalization to weak localization. It presents an important step toward a better understanding of the existing three-dimensional topological insulators and the potential applications of nano-scale topological insulator devices

Sphere-shaped Mn3O4 catalyst with remarkable low-temperature activity for Methyl-Ethyl-Ketone combustion

Mn3O4, FeMnOx, and FeOx catalysts synthesized via a solvothermal method were employed for catalytic oxidation of methyl−ethyl−ketone (MEK) at low temperature. Mn3O4 with sphere-like morphology exhibited the highest activity for MEK oxidation, over which MEK was completely oxidized to CO2 at 200 °C, and this result can be comparable to typical noble metal loaded catalysts. The activation energy of MEK over Mn3O4 (30.8 kJ/mol) was much lower than that of FeMnOx (41.5 kJ/mol) and FeOx (47.8 kJ/mol). The dominant planes, surface manganese species ratio, surface-absorbed oxygen, and redox capability played important roles in the catalytic activities of catalysts, while no significant correlation was found between specific surface area and MEK removal efficiency. Mn3O4 showed the highest activity, accounting for abundant oxygen vacancies, low content of surface Mn4+ and strong reducibility. The oxidation of MEK to CO2 via an intermediate of diacetyl is a reaction pathway on Mn3O4 catalyst. Due to high efficiency and low cost, sphere-shaped Mn3O4 is a promising catalyst for VOCs abatement