Dividend policy and stock price volatility: Chinese evidence

This dissertation explored the impacts of dividend policy on stock price volatility in Chinese market. A sample of 322 Chinese companies is used during the period from 2000 to 2019. Dividend yield and dividend payout are used as measures for dividend policy and the results provided by the two measures are compared. The empirical results obtained by this dissertation suggest that the dividend payment policy is inversely correlated with stock price volatility and the dividend yield rather than the dividend payout is the dominant variable. This finding suggests that it is possible for the management to control the stock price volatility through changing dividend policy. This dissertation also observes a positive relationship between firm size and stock price volatility, which is contrast to the hypothesis. Allen and Rachim (1996) has provided an explanation for this positive correlation by relating firm size to leverage level. However, the results obtained by this dissertation demonstrate that leverage level is inversely correlated with stock price volatility, violating the assumption made by Allen and Rachim (1996)

Dividend policy and stock price volatility: Chinese evidence

This dissertation explored the impacts of dividend policy on stock price volatility in Chinese market. A sample of 322 Chinese companies is used during the period from 2000 to 2019. Dividend yield and dividend payout are used as measures for dividend policy and the results provided by the two measures are compared. The empirical results obtained by this dissertation suggest that the dividend payment policy is inversely correlated with stock price volatility and the dividend yield rather than the dividend payout is the dominant variable. This finding suggests that it is possible for the management to control the stock price volatility through changing dividend policy. This dissertation also observes a positive relationship between firm size and stock price volatility, which is contrast to the hypothesis. Allen and Rachim (1996) has provided an explanation for this positive correlation by relating firm size to leverage level. However, the results obtained by this dissertation demonstrate that leverage level is inversely correlated with stock price volatility, violating the assumption made by Allen and Rachim (1996)

Study on the Strategy of Playing Doudizhu Game Based on Multirole Modeling

Doudizhu poker is a very popular and interesting national poker game in China, and now it has become a national competition in China. As this game is a typical example of incomplete information game problem, it has received more and more attention from artificial intelligence experts. This paper proposes a multirole modeling-based card-playing framework. This framework includes three parts: role modeling, cards carrying, and decision-making strategies. Role modeling learns different roles and behaviors by using a convolutional neural network. Cards carrying can calculate reasonable rules especially for “triplet” by using an evaluation algorithm. Decision making is for implementing different card strategies for different player roles. Experimental results showed that this card-playing framework makes playing decisions like human beings, and it can to some extent learn, collaborate, and reason when facing an incomplete information game problem. This framework won the runner-up in the 2018 China Computer Game Competition

Unsafe Mining Behavior Identification Method Based on an Improved ST-GCN

Aiming to solve the problems of large environmental interference and complex types of personnel behavior that are difficult to identify in the current identification of unsafe behavior in mining areas, an improved spatial temporal graph convolutional network (ST-GCN) for miners’ unsafe behavior identification network in a transportation roadway (NP-AGCN) was proposed. First, the skeleton spatial-temporal map constructed using multi-frame human key points was used for behavior recognition to reduce the interference caused by the complex environment of the coal mine. Second, aiming to solve the problem that the original graph structure cannot learn the association relationship between the non-naturally connected nodes, which leads to the low recognition rate of climbing belts, fighting and other behaviors, the graph structure was reconstructed and the original partitioning strategy was changed to improve the recognition ability of the model for multi-joint interaction behaviors. Finally, in order to alleviate the problem that the graph convolution network has difficulty learning global information due to the small receptive field, multiple self-attention mechanisms were introduced into the graph convolution to improve the recognition ability of the model for unsafe behaviors. In order to verify the detection ability of the model regarding identifying unsafe behaviors of personnel in a coal mine belt area, our model was tested on the public datasets NTU-RGB + D and the self-built datasets of unsafe behaviors in a coal mine belt area. The recognition accuracies of the proposed model in the above datasets were 94.7% and 94.1%, respectively, which were 6.4% and 7.4% higher than the original model, which verified that the proposed model had excellent recognition accuracies

The Influence of Organic and Conventional Cultivation Patterns on Physicochemical Property, Enzyme Activity and Microbial Community Characteristics of Paddy Soil

Cultivation patterns can cause soil structure alteration. However, few studies have clarified the influence of cultivation pattern and soil depth on soil. The purpose of this experiment was to study the community characteristics of soil microorganisms in the 0–10 cm and 10–20 cm layers beneath paddy fields under organic and conventional cultivation patterns, and reveal the response mechanism of microbial community to cultivation patterns through the correlation analysis of soil nutrient content, enzyme activity and microbial dominant phyla, so as to provide a theoretical basis for high-yield rice cultivation from the perspective of microorganisms. In this study, four types of soil organic cultivation topsoil (OF_S), organic cultivation undersoil (OF_X), conventional cultivation topsoil (CF_S) and conventional cultivation undersoil (CF_X) in paddy fields were collected for nutrient and enzyme activity determination, and composition spectrum analysis of soil microbial community diversity was performed using a high-throughput sequencing platform. The results revealed that organic cultivation increased the contents of alkali-hydrolyzable nitrogen, available phosphorus, available potassium and organic substances in both topsoil and undersoil as well as sucrase and urease activity in the undersoil. α diversity indicated that bacterial abundance in both topsoil and undersoil was organic > conventional cultivation; the microbial diversity index in the undersoil under organic cultivation technique was greater than that of conventional cultivation. A Venn diagram revealed that there was considerable difference in species between topsoil and undersoil under organic and conventional cultivation patterns. The composition of the community structure indicated that Proteobacteria, Acidobacteria, Chloroflexi and Bacteroidetes were the dominant phyla of bacterial communities in paddy fields. Ascomycota and Basidiomycota were the dominant phyla of the fungal community. Cluster analysis results indicated that soil depth of both patterns produced apparent clustering effects on microorganisms. Correlation analysis revealed that contents of various soil nutrients and enzyme activities affected the relative abundance of the dominant bacteria and fungi in varying degrees. Alkali-hydrolyzable nitrogen, available potassium and organic matters were significant factors affecting the dominant phyla of soil. The present study demonstrated that compared with conventional cultivation, organic cultivation improved soil physicochemical property, enhanced soil enzyme activity, and altered soil microbial diversity and bacterial abundance. Soil nutrients, enzyme activity and the microbial community of paddy fields interacted with each other and affected the soil structure together

Oxidative dehydrogenation of ethane to ethene over a superbase supported LiCl system

LiCl-promoted superbase catalysts were found to be stable and highly selective to ethene for oxidative dehydrogenation of ethane, giving 84% ethane conversion and 74% ethene yield at 923 K. Results indicated that the stronger the basicity of LiCl-based catalysts, the better the catalytic performance. (C) 2010 Yu Bao Zhao. Published by Elsevier B.V. on behalf of Chinese Chemical Society. All rights reserved.Ministry of Science and Technology of China [2005CB221408]; Science and Technology Projects of Hunan Province [2007FJ4151

Qualitative Recognition of Primary Taste Sensation Based on Surface Electromyography

Based on surface electromyography (sEMG), a novel recognition method to distinguish six types of human primary taste sensations was developed, and the recognition accuracy was 74.46%. The sEMG signals were acquired under the stimuli of no taste substance, distilled vinegar, white granulated sugar, instant coffee powder, refined salt, and Ajinomoto. Then, signals were preprocessed with the following steps: sample augments, removal of trend items, high-pass filter, and adaptive power frequency notch. Signals were classified with random forest and the classifier gave a five-fold cross-validation accuracy of 74.46%, which manifested the feasibility of the recognition task. To further improve the model performance, we explored the impact of feature dimension, electrode distribution, and subject diversity. Accordingly, we provided an optimized feature combination that reduced the number of feature types from 21 to 4, a preferable selection of electrode positions that reduced the number of channels from 6 to 4, and an analysis of the relation between subject diversity and model performance. This study provides guidance for further research on taste sensation recognition with sEMG

Intrinsic dielectric properties and vibration characteristics of La(Mg1/2Sn1/2)O3 ceramic

La(Mg1/2Sn1/2)O3 (LMS) ceramic was synthesized via the conventional solid-state reaction method. The main phase of the sample is LMS with a double perovskite structure (monoclinic P121/n1 symmetry), which is confirmed by X-ray diffraction. Scanning electron microscopy shows the sample is well-crystallized with dense and uniform grains as well as clear grain boundaries. The Raman scattering and Fourier transform far-infrared reflection spectroscopies were employed to analyze the lattice vibrational modes of the sample. The Raman active modes were fitted by the Lorentz function, and the lattice vibrational modes were assigned and illustrated accurately. The four-parameter semiquantum model was applied to simulate the intrinsic dielectric properties, which agree well with the data calculated from the microscopic polarizability & damping angles. The A1g(La) Raman mode in A-site has a great impact on the dielectric loss, and F3u(2) mode makes the largest contribution to the dielectric constant and the dielectric loss. Keywords: Microwave dielectric ceramic, Double perovskite, Crystal structures, Intrinsic dielectric properties, Vibration characteristic