An Empirical Study on the Effects of Regional Financial Structure’s Transformation on Economic Growth: Based on the Data of Henan Province, China

Based on the data of Henan province during the year of 1994 to 2013, this paper empirically tests the effects of regional financial structure on economic growth by employing some econometric methods, such as Co-integration, Granger causality test, impulse response and variance decomposition based on VAR etc.. The results are as follows: to some extent, the transformation of Henan province’s financial structure has a negative effect on its economic growth, but variance decomposition shows that the negative effect is very limited

An Empirical Study on the Volatility of Public Opinion on Coal Mine Safety Accidents

This paper empirically studies the volatility of public opinion evolution on coal mine safety accidents based on weekly average data of coal mine accidents from January 2011 to May 2014 in Baidu search index. The findings are as follows: The volatility of public opinion evolution of coal mine safety accidents shows some characteristics such as aggregation, ARCH effect. And, the estimation of a GARCH model shows that public opinion evolution of coal mine safety accidents has conditional heteroscedasticity character, and this GARCH model successfully portrays the volatility of the public opinion on coal mine safety accidents

Incorporating internal gradient and restricted diffusion effects in Nuclear Magnetic Resonance log interpretation

It is shown that internal gradient combined with the restricted diffusion effect can significantly influence the D-T2 cross plots, which are widely used for fluid typing in Nuclear Magnetic Resonance (NMR) well-logging applications. By using models that capture the most important features of the internal gradient in the sedimentary rocks, such effects can be accounted for in the D-T2 inversion process, making fluid typing more accurate

AI-Based Collaborative Teaching: Strategies and Analysis in Visual Communication Design

With the rapid development of technology, AI has been widely applied in multiple fields, especially the field of education. As a discipline involving art, technology and creativity, visual communication design is facing the challenge of keeping up with the times and combining new technologies for innovation. Collaborative teaching model emphasizes multi-party participation and collaborative learning, and its proposal has injected new vitality into traditional educational patterns. However, existing studies, which combine collaborative teaching model with artificial intelligence, still have limitations in application and practice, and most of them remain in the theoretical discussion stage and lack empirical support. This study aimed to make up for this deficiency. After in-depth analysis of educational data, a forecasting model of collaborative teaching demand based on AI was proposed. Course content suitable for the collaborative teaching model was further planned for the education in visual communication design

BIOMECHANICAL CHARACTERISTICS OF THE WRIST JOINT MUSCLE IN CHINESE ADULTS

The purpose of this study was to (1) establish the biomechanical characteristics of the wrist muscle in normal Chinese adults, (2) provide scientific information for the evaluation of sports techniques, strength training, sports injuries, and rehabilitation, (3) provide basic data for muscle building, injury and rehabilitation in the general population. A total of 69 adults cross-country participated in this study. The following conclusions were drawn: (1) With increasing angular velocity, peak torque and total work declined, but average power increased, (2) Peak torque, total work and average power of wrist flexion were greater than wrist extension

Quantile autoregressive conditional heteroscedasticity

This paper proposes a novel conditional heteroscedastic time series model by applying the framework of quantile regression processes to the ARCH(\infty) form of the GARCH model. This model can provide varying structures for conditional quantiles of the time series across different quantile levels, while including the commonly used GARCH model as a special case. The strict stationarity of the model is discussed. For robustness against heavy-tailed distributions, a self-weighted quantile regression (QR) estimator is proposed. While QR performs satisfactorily at intermediate quantile levels, its accuracy deteriorates at high quantile levels due to data scarcity. As a remedy, a self-weighted composite quantile regression (CQR) estimator is further introduced and, based on an approximate GARCH model with a flexible Tukey-lambda distribution for the innovations, we can extrapolate the high quantile levels by borrowing information from intermediate ones. Asymptotic properties for the proposed estimators are established. Simulation experiments are carried out to access the finite sample performance of the proposed methods, and an empirical example is presented to illustrate the usefulness of the new model

Castration modulates singing patterns and electrophysiological properties of RA projection neurons in adult male zebra finches

Castration can change levels of plasma testosterone. Androgens such as testosterone play an important role in stabilizing birdsong. The robust nucleus of the arcopallium (RA) is an important premotor nucleus critical for singing. In this study, we investigated the effect of castration on singing patterns and electrophysiological properties of projection neurons (PNs) in the RA of adult male zebra finches. Adult male zebra finches were castrated and the changes in bird song assessed. We also recorded the electrophysiological changes from RA PNs using patch clamp recording. We found that the plasma levels of testosterone were significantly decreased, song syllable’s entropy was increased and the similarity of motif was decreased after castration. Spontaneous and evoked firing rates, membrane time constants, and membrane capacitance of RA PNs in the castration group were lower than those of the control and the sham groups. Afterhyperpolarization AHP time to peak of spontaneous action potential (AP) was prolonged after castration.These findings suggest that castration decreases song stereotypy and excitability of RA PNs in male zebra finches

Identification of aromatic amino acid residues in conserved region VI of the large polymerase of vesicular stomatitis virus is essential for both guanine-N-7 and ribose 2'-O methyltransferases

AbstractNon-segmented negative-sense RNA viruses possess a unique mechanism for mRNA cap methylation. For vesicular stomatitis virus, conserved region VI in the large (L) polymerase protein catalyzes both guanine-N-7 (G-N-7) and ribose 2'-O (2'-O) methyltransferases, and the two methylases share a binding site for the methyl donor S-adenosyl-l-methionine. Unlike conventional mRNA cap methylation, the 2'-O methylation of VSV precedes subsequent G-N-7 methylation. In this study, we found that individual alanine substitutions in two conserved aromatic residues (Y1650 and F1691) in region VI of L protein abolished both G-N-7 and 2'-O methylation. However, replacement of one aromatic residue with another aromatic residue did not significantly affect the methyltransferase activities. Our studies provide genetic and biochemical evidence that conserved aromatic residues in region VI of L protein essential for both G-N-7 and 2'-O methylations. In combination with the structural prediction, our results suggest that these aromatic residues may participate in RNA recognition

Modeling Link-level Road Traffic Resilience to Extreme Weather Events Using Crowdsourced Data

Climate changes lead to more frequent and intense weather events, posing escalating risks to road traffic. Crowdsourced data offer new opportunities to monitor and investigate changes in road traffic flow during extreme weather. This study utilizes diverse crowdsourced data from mobile devices and the community-driven navigation app, Waze, to examine the impact of three weather events (i.e., floods, winter storms, and fog) on road traffic. Three metrics, speed change, event duration, and area under the curve (AUC), are employed to assess link-level traffic change and recovery. In addition, a user's perceived severity is computed to evaluate link-level weather impact based on crowdsourced reports. This study evaluates a range of new data sources, and provides insights into the resilience of road traffic to extreme weather, which are crucial for disaster preparedness, response, and recovery in road transportation systems

A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models

This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties: (1) the new search direction possesses not only a sufficient descent property but also a trust region feature; (2) the presented algorithm has global convergence for nonconvex functions; (3) the numerical experiment showed that the new algorithm is more effective than similar algorithms