Study on AADDS Plunger Pump Driving Bearing Properties

The Auto Anti-Deviation Drilling System (AADDS) is a high-performance, highly automated vertical drilling hydraulic guide control system. This article takes its power extraction device - driving bearing for the study object, analyzed the single-plunger pump's principle, established the mathematical model of hydraulic guide system, applied Matlab/Simulink to simulate the pump outlet flow under different contour curve of the driving bearing. The results show the oval-shaped bearing is of high efficiency under lower drilling speed, and its performance is better than that of original eccentric-shaped and clover-shaped

Detecting Blurred Boundary Advertisement in Social Media Marketing Platform

Consumers seek organic reviews of products and services (organic eWOM) to verify whether they made the right choice (Erkan and Evans, 2016). However, the authenticity of brand promotion (e.g., blurred boundary advertisement) hinders consumers’ decision making. Consumers are calling for transparency of information between social platforms and users. This study is to develop efficient models to distinguish blurred boundary advertisements from organic eWOM. Drawing upon dual-process theory, we developed logistic models which can distinguish blurred boundary advertisements from organic eWOM in social media marketing platforms with decent explanations. Blurred boundary advertisement can be detected by features about posts, comments, bloggers and followers. Moreover, number of followers, number of posts and number of comments showed U- shape relationships with detecting blurred boundary advertisement. With more accurate statistical and machine learning-based models, this study helps consumers and platforms solve possible fairness issues in digital marketing

Energy Dissipation in Magnetic Islands Formed during Magnetic Reconnection

Magnetic reconnection converts magnetic energy into particle kinetic energy, and satellite observations have shown that 20%–50% of magnetic energy is channeled into electron kinetic energy. How such a large amount of magnetic energy is dissipated into electron kinetic energy is in debate. In this paper, by performing a large-scale 2D particle-in-cell simulation of magnetic reconnection with a guide field, we find that there exist both ion and electron shear flows in magnetic islands formed during magnetic reconnection, which are unstable to the ion and electron Kelvin–Helmholtz (K-H) instabilities. With the development of the K-H instabilities, the magnetic field lines are twisted in these magnetic islands, and intensified electron-scale current sheets are consequently generated. We quantitatively analyze the energy dissipation during such a process in magnetic islands and find that electrons obtain kinetic energy from the magnetic field while ion kinetic energy is transferred into magnetic energy. At last, it results that about 42% of magnetic energy is dissipated into electron kinetic energy in the whole process of magnetic reconnection. Our results help us better understand why a large amount of magnetic energy can be dissipated into electron kinetic energy

Reconnection Rate and Transition from Ion-coupled to Electron-only Reconnection

Standard collisionless magnetic reconnection couples with both electron and ion dynamics. Recently, a new type of magnetic reconnection, electron-only magnetic reconnection without ion outflow, has been observed, and its reconnection rate has been found to be much higher than that in ion-coupled reconnection. In this paper, using 2D particle-in-cell simulations, we find that when the ion gyroradius is much smaller than the size of the simulation domain, magnetic reconnection is standard with ion outflows. As the ion gyroradius increases, the ion response gradually weakens, and the reconnection rate becomes higher. Electron-only reconnection occurs when the ion gyroradius is comparable to the size of the simulation domain. This trend applies to both strong and weak guide field situations. Therefore, the key factor that controls the transition from ion-coupled reconnection to electron-only reconnection is the ratio between the ion gyroradius and the size of the simulation domain. We further show that, in electron-only reconnection, when the initial electron current sheet is thinner, the reconnection rate and the electron outflow speed are higher

Controlled Sharing Mechanism of Data Based on the Consortium Blockchain

In the process of sharing data, the costless replication of electric energy data leads to the problem of uncontrolled data and the difficulty of third-party access verification. This paper proposes a controlled sharing mechanism of data based on the consortium blockchain. The data flow range is controlled by the data isolation mechanism between channels provided by the consortium blockchain by constructing a data storage consortium chain to achieve trusted data storage, combining attribute-based encryption to complete data access control and meet the demands for granular data accessibility control and secure sharing; the data flow transfer ledger is built to record the original data life cycle management and effectively record the data transfer process of each data controller. Taking the application scenario of electric energy data sharing as an example, the scheme is designed and simulated on the Linux system and Hyperledger Fabric. Experimental results have verified that the mechanism can effectively control the scope of access to electrical energy data and realize the control of the data by the data owner

Oxidative Stress and Psychiatric Disorders: Evidence from the Bidirectional Mendelian Randomization Study

Observational studies have shown that oxidative stress is highly related to psychiatric disorders, while its cause–effect remains unclear. To this end, a Mendelian randomization study was performed to investigate the causal relationship between oxidative stress and psychiatric disorders. On the one hand, all causal effects of oxidative stress injury biomarkers (OSIB) on psychiatric disorders were not significant (p > 0.0006), while the findings suggested that part of OSIB was nominally associated with the risk of psychiatric disorders (causal OR of uric acid (UA), 0.999 for bipolar disorder (BD), and 1.002 for attention-deficit/hyperactivity disorder (ADHD); OR of catalase was 0.903 for anorexia nervosa (AN); OR of albumin was 1.162 for autism; p < 0.05). On the other hand, major depressive disorder (MDD) was significantly associated with decreased bilirubin (p = 2.67 × 10−4); ADHD was significantly associated with decreased ascorbate (p = 4.37 × 10−5). Furthermore, there were also some suggestively causal effects of psychiatric disorders on OSIB (BD on decreased UA and increased retinol; MDD on increased UA and decreased ascorbate; schizophrenia on decreased UA, increased retinol and albumin; ADHD on increased UA, and decreased catalase, albumin, and bilirubin; AN on decreased UA). This work presented evidence of potential causal relationships between oxidative stress and psychiatric disorders

Direct Vapor Deposition Growth of 1T′ MoTe2 on Carbon Cloth for Electrocatalytic Hydrogen Evolution

© 2019 American Chemical Society. Phase engineering has a profound effect on the chemical bonding and electric configuration, which play significant roles in regulating the activities of catalysts. The metallic phases of transition-metal dichalcogenides (TMDs) have been proposed to show more excellent performance in electrocatalysis over their semiconductor phase; however, the controllable phase engineering for these compounds remains a challenge. In this work, filmlike 1T′ MoTe2 (F-1T′ MoTe2), filmlike 1T′/2H MoTe2, porous 1T′ MoTe2, small granular 1T′ MoTe2, and large granular 1T′ MoTe2 were successfully synthesized on a flexible carbon cloth (CC) substrate with 3D network structure by chemical vapor deposition (CVD). The high activity of the as-synthesized F-1T′ MoTe2/CC electrode for HER in 1 M H2SO4 solution was demonstrated by the small onset overpotential of -230.7 mV, a low Tafel slope of 127.1 mV dec-1, and robust electrochemical durability. The enhanced electrocatalytic activity and stability of F-1T′ MoTe2/CC benefit from excellent catalytically active sites and remarkable conductivity of the F-1T′ MoTe2. The results demonstrate an efficient route to designing and constructing metallic-phase TMD catalysts for high-performance electrocatalytic devices

Eating disorders symptoms and depressive symptoms in Chinese Tibetan University students: a network analysis

Abstract Background Depression is being increasingly acknowledged as a global public health concern, and following this trend, attention towards eating disorders (EDs) has surged within China’s national consciousness. EDs symptoms frequently coexist with various mental health conditions, including depression. However, research focusing on EDs symptoms and depressive symptoms among Tibetan students in China remains scant. This study employs network analysis to estimate the relational network between EDs and depressive symptoms. Methods Tibetan (n = 2,582) and Han (n = 1,743) students from two universities in the Xizang Autonomous Region, China, completed the Eating Attitude Test-26 (EAT-26) and the Patient Health Questionnaire-9 (PHQ-9). We estimated the network structure of EDs symptoms and depressive symptoms, identified central and bridge symptoms, and examined whether network characteristics differed by gender and ethnic. Results The core symptoms identified within this study were Calorie_awareness, Desire_to_thin and Fatigue. Conversely, bridge symptoms included Appetite, Suicide, Anhedonia, Guilty, Body_fat_awareness, and Food_preoccupation. The study also revealed no significant gender differences within the network model. However, disparities among ethnic groups were observed within the network structure. Conclusions Our study examined the correlation between EDs symptoms and depressive symptoms in Tibetan college students. Focusing on the individual's quest for the perfect body shape and some Tibetan students' appetite problems – potentially stemming from transitioning to a new university environment, adapting to the school canteen's diet, or being away from their hometown – could aid in the prevention and management of EDs and depression symptoms. It could reduce the incidence of complications by helping students maintain good physical and mental health. Concurrently, our research provides insights into the relatively higher levels of depression triggered by the unique plateau environment

Table_1_A deep learning-based model for detecting depression in senior population.XLSX

ObjectivesWith the attention paid to the early diagnosis of depression, this study tries to use the biological information of speech, combined with deep learning to build a rapid binary-classification model of depression in the elderly who use Mandarin and test its effectiveness.MethodsDemographic information and acoustic data of 56 Mandarin-speaking older adults with major depressive disorder (MDD), diagnosed with the Mini-International Neuropsychiatric Interview (MINI) and the fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5), and 47 controls was collected. Acoustic data were recorded using different smart phones and analyzed by deep learning model which is developed and tested on independent validation set. The accuracy of the model is shown by the ROC curve.ResultsThe quality of the collected speech affected the accuracy of the model. The initial sensitivity and specificity of the model were respectively 82.14% [95%CI, (70.16–90.00)] and 80.85% [95%CI, (67.64–89.58)].ConclusionThis study provides a new method for rapid identification and diagnosis of depression utilizing deep learning technology. Vocal biomarkers extracted from raw speech signals have high potential for the early diagnosis of depression in older adults.</p