scholarly journals Research on the Structural Characteristics of Entertainment Industrial Correlation in China: Based on Dual Perspective of Input-Output and Network Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yang Xun ◽  
Wensheng Shi ◽  
Tianyu Liu
Keyword(s):  
Network Analysis ◽  
Industrial Development ◽  
Structural Characteristics ◽  
Rapid Development ◽  
Correlation Network ◽  
Entertainment Industry ◽  
Input Output ◽  
Positive Role ◽  
Industrial Sectors ◽  
Dual Perspective

Based on the dual perspective of input-output and network analysis, this study takes typical industrial sectors of China’s entertainment industry as representatives. Through the input-output analysis of industrial correlation characteristic indicators and construction of an industrial correlation network, we conduct a systematic and quantitative study on the entertainment industrial correlation characteristics and structural characteristics of the industrial correlation network in China. Furthermore, we clarify the role of the entertainment industry in China’s industrial development and its positioning in China’s whole industrial correlation network. We have the following key findings: China’s entertainment industry as a whole shows the characteristics of final demand-oriented industries, whose rapid development plays a certain positive role in boosting consumption and driving economic growth. Within the whole industrial correlation network in China, there is frequent interaction between the entertainment industry and other industry sectors within the directly related network; it will especially exert obvious radiation and driving effect on the upstream industry. However, limited by the scale of the direct industrial correlation network, such influence is still difficult to achieve the common development of most industries in China.

scholarly journals Lipidomic Network of Mild Cognitive Impairment from the Mayo Clinic Study of Aging

2021 ◽  
pp. 1-11
Author(s):  
Xuewei Wang ◽  
Hai Bui ◽  
Prashanthi Vemuri ◽  
Jonathan Graff-Radford ◽  
Clifford R. Jack Jr ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Network Analysis ◽  
Mayo Clinic ◽  
Plasma Lipids ◽  
Amyloid Β ◽  
Cognitive Status ◽  
Correlation Network ◽  
Lipid Species ◽  
Clinic Study

Background: Lipid alterations contribute to Alzheimer’s disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers. Objective: To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groups Methods: Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without. Results: Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses. Conclusion: Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.

scholarly journals The Changes of Carbon Emission in China’s Industrial Sectors from 2002 to 2010: A Structural Decomposition Analysis and Input-Output Subsystem

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoxing Zhang ◽  
Mingxing Liu
Keyword(s):  
Carbon Emissions ◽  
Emission Intensity ◽  
Carbon Emission ◽  
Decomposition Analysis ◽  
Final Demand ◽  
Good Effect ◽  
Input Output ◽  
Carbon Emission Intensity ◽  
Industrial Sectors ◽  
Three Components

Based on 2002–2010 comparable price input-output tables, this paper first calculates the carbon emissions of China’s industrial sectors with three components by input-output subsystems; next, we decompose the three components into effect of carbon emission intensity, effect of social technology, and effect of final demand separately by structure decomposition analysis; at last, we analyze the contribution of every effect to the total emissions by sectors, thus finding the key sectors and key factors which induce the changes of carbon emissions in China’s industrial sectors. Our results show that in the latest 8 years five departments have gotten the greatest increase in the changes of carbon emissions compare with other departments and the effect of final demand is the key factor leading to the increase of industrial total carbon emissions. The decomposed effects show a decrease in carbon emission due to the changes of carbon emission intensity between 2002 and 2010 compensated by an increase in carbon emissions caused by the rise in final demand of industrial sectors. And social technological changes on the reduction of carbon emissions did not play a very good effect and need further improvement.

Effects of open innovation breadth on industrial innovation input–output relationships

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alejandro Germán Frank ◽  
Guilherme Brittes Benitez ◽  
Mateus Ferreira Lima ◽  
João Augusto Bonzanini Bernardi
Keyword(s):  
Open Innovation ◽  
Transaction Cost Economics ◽  
Secondary Data ◽  
Moderating Effects ◽  
Input Output ◽  
Industrial Innovation ◽  
Content Type ◽  
Innovation Activities ◽  
Industrial Sectors ◽  
The Relationship

PurposeOpen innovation breadth (OIB) considers the diversity of external collaboration partners for innovation. The authors investigate the moderating effect of OIB on the relationship between industrial innovation activities (innovation inputs) and industrial innovation results (innovation outputs).Design/methodology/approachThis study is based on secondary data from the Brazilian innovation survey, representing more than 30,000 innovative companies across 55 industrial sectors.FindingsThis study’s results show that OIB has different moderating effects regarding the several innovation input–output relationships. While OIB benefits some relationships, others are hampered by the diversity of collaboration partners.Originality/valueFew studies have addressed OIB at the macro level. Using the perspective of transaction cost economics (TCE), the authors discuss the contributions and limitations of OIB at the industry level.

scholarly journals Using Network Analysis to Study the History of Archival Collections Formation: A Case-Study of the Collection of N.P. Likhachev from the Scientific Historical Archive of the St. Petersburg Institute of History

2020 ◽  
pp. 277-292
Author(s):  
Ekaterina I. Nosova ◽  
Keyword(s):  
Network Analysis ◽  
Rapid Development ◽  
Petersburg Institute ◽  
Russian Academy Of Sciences ◽  
Historical Archive ◽  
European Section ◽  
History Of ◽  
Western European ◽  
Academy Of Sciences

Interest in the history of book collections is not a recent phenomenon. However, rapid development of computers and the Internet over the past twenty years has provided researchers with new tools for network analysis, such as UCI6 и NetDraw 2.160. Continuing to identify the provenance of the documents kept in the Western European Section of the Scientific Historical Archive of the St. Petersburg Institute of History of the Russian Academy of Sciences, the author had to face the fact that abundance of information and complexity of the links between various sources make it difficult to make out the complete picture. The Western European section of the Scientific Historical Archive of the St. Petersburg Institute of History of the Russian Academy of Sciences is mostly based on the collection of the academician N P. Likhachev (1862—1936). N.P. Likhachev contacted hundreds of antiquarian firms around the world, and thus his collection fits into the complex and interwoven system of the European antiquarian market of the late 19th–early 20th century. To overcome the problem of branching data, the author decided to call on the experience of sociologists and to use computer programs for network analysis that enable to reflect and comprehend the links between objects. The article is to present the process and results of this work, as well as to underscore problems and specificity of the programs in relation to the archival material. The main source is data from the personal provenance archive of the academician N. P. Likhachev, collection of documents on the history of the Western European Section, and artifacts from the Likhachev collection. The second layer of sources is antiquarian catalogs. The program can visualize these two layers of information in different ways by using different colors and lines. Overlaying of the schemes allows completing of missing elements in the chain of provenance. It should be noted that due to the richness of the sources, the network, originally compiled for the collection of N.P. Likhachev, grows into a pan-European system of “collector-antiquarian” relationships. It opens wide perspectives for research.

scholarly journals Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Tao Yan ◽  
Shijie Zhu ◽  
Miao Zhu ◽  
Chunsheng Wang ◽  
Changfa Guo
Keyword(s):  
Atrial Fibrillation ◽  
Network Analysis ◽  
Molecular Mechanism ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Correlation Network ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

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