Topological characteristics of international business cycle synchronization: A network analysis of the BRI economies.
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ABSTRACT:
SUBMITTER: Qiu Z
PROVIDER: S-EPMC9239471 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundOccupational accidents occur for a variety of reasons, such as unsafe behaviors of workers and insufficient safety equipment at the workplace, but there are also various economic and social factors that can impact working conditions and working environment. This study analyzed the relationship between changes in economic factors and the occurrence of occupational accidents in Korea.MethodsMultilinear regression analysis was used as the analysis model. The general to specific method was also used, which consecutively removes statistically insignificant variables from a general model that includes dependent variables and lagged variables of dependent variables.ResultsThe frequency of occupational accidents was found to have a statistically significant relationship to economic indicators. The monthly number of cases of occupational injury and disease and fatal occupational injuries were found to be closely related to manufacturing capacity utilization, differences in the production index in the services sector, and commencements of building construction. The increase in equipment investment indicators was found to reduce fatal occupational injuries.ConclusionThe results of this study may be used to develop occupational accident trends or leading indicators, which in turn can be used by organizations that manage and monitor occupational accidents toward taking administrative action designed to reduce occupational accidents. The results also imply that short-term and mid- to long-term economic and social changes that can impact workers, workplaces and working conditions, and workplace organizations must be taken into account if more effective government policies are to be established and implemented toward further prevention of occupational accidents.
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Project description:Background: Awake craniotomy with intraoperative stimulation has been utilized in glioma surgical resection to preserve the quality of life. Epilepsy may occur in 5-20% of cases, leading to severe consequences. This study aimed to discuss the mechanism of intraoperative stimulation-related epilepsy (ISE) using DTI-based graph theoretical analysis. Methods: Twenty patients with motor-area glioma were enrolled and divided into two groups (Ep and nEp) according to the presence of ISE. Additionally, a group of 10 healthy participants matched by age, sex, and years of education was also included. All participants underwent T1, T2, and DTI examinations. Graph theoretical analysis was applied to reveal the topological characteristics of white matter networks. Results: Three connections were found to be significantly lower in at least one weighting in the Ep group. These connections were between A1/2/3truL and A4ulL, A1/2/3truR and A4tR, and A6mL and A6mR. Global efficiency was significantly decreased, while the shortest path length increased in the Ep group in at least one weighting. Ten nodes exhibited significant differences in nodal efficiency and degree centrality analyses. The nodes A6mL and A6mR showed a marked decrease in total four weightings in the Ep group. Conclusions: The hub nodes A6mL and A6mR are disconnected in patients with ISE, causing subsequent lower efficiency of global and regional networks. These findings provide a basis for presurgical assessment of ISE, for which caution should be taken when it involves hub nodes during intraoperative electrical stimulation.
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Project description:Protein-protein interaction (PPI) networks are viable tools to understand cell functions, disease machinery, and drug design/repositioning. Interpreting a PPI, however, it is a particularly challenging task because of network complexity. Several algorithms have been proposed for an automatic PPI interpretation, at first by solely considering the network topology, and later by integrating Gene Ontology (GO) terms as node similarity attributes. Here we present MTGO - Module detection via Topological information and GO knowledge, a novel functional module identification approach. MTGO let emerge the bimolecular machinery underpinning PPI networks by leveraging on both biological knowledge and topological properties. In particular, it directly exploits GO terms during the module assembling process, and labels each module with its best fit GO term, easing its functional interpretation. MTGO shows largely better results than other state of the art algorithms (including recent GO-based ones) when searching for small or sparse functional modules, while providing comparable or better results all other cases. MTGO correctly identifies molecular complexes and literature-consistent processes in an experimentally derived PPI network of Myocardial infarction. A software version of MTGO is available freely for non-commercial purposes at https://gitlab.com/d1vella/MTGO .
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