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Background and Purpose-Early vascular events are an important cause of morbidity and mortality in the first 3 months after a stroke. We aimed to investigate the effects of MLC601 on the occurrence of early vascular events within 3 months of stroke onset. Methods-Post hoc analysis was performed on data from subjects included in the CHInese Medicine Neuroaid Efficacy on Stroke recovery (CHIMES) study, a randomized, placebo-controlled, double-blinded trial that compared MLC601 with placebo in 1099 subjects with ischemic stroke of intermediate severity in the preceding 72 hours. Early vascular events were defined as a composite of recurrent stroke, acute coronary syndrome, and vascular death occurring within 3 months of stroke onset. Results-The frequency of early vascular events during the 3-month follow-up was significantly less in the MLC601 group than in the placebo group (16 [

The objective of the study was to reduce musculoskeletal disorder risks by applying the NIOSH lifting equation variables include the horizontal location, the vertical location, the vertical travel distance, the asymmetric, the lifting frequency and the coupling classification. The 17 specific samples from 4W and ZECP division were selected by the weight of box 15.4-28.7 pounds. The standardized Nordic questionnaire for the analysis of musculoskeletal symptoms with pain scale from 0 (no pain) to 10 (worst pain) was used to self-report feeling. The ergonomics redesigns trained for the workers included: 1) brought the load closer to the worker by training; 2) raised the height of objects placed to reduce the vertical distance between the origin and destination of the lift; and 3) moved the origin and destination of lift closer together to reduce the angel twist. The new procedures were trained to all participated workers. The result found that the lifting index was safer (<1.0). For successful outcome, be supposed to monitoring is careful the data about a problem of the worker health, give the carefulness in case of specially exceed environment more than the LI advises and should do training continuously.

Abstract-This research is a research and development. It aims to develop Green University Resource Planning on cloud computing. The research is divided into two phases which are 1) document analysis related to Green University indicators, and 2) survey assessment to input data into the Green University Resource Planning System. The research samples are nine experts who are executives and have experience at green universities selected by purposive sampling. The research tool is the survey assessment to input data into the Green University Resource Planning System, which analyses data by considering the mean and standard deviation. According to the document analysis related to Green University Indicators, the research results showed that the categories based on the criteria of UI GreenMetric World University Ranking 2016 suggested that each university has different indicators in relevance to the context, geography, budget, location, internationality, and the survey assessment to input data into the Green University Resource Planning System. The experts found that the overall appropriateness of the survey was rated at the highest level ( X = 4.55, S.D. = 0.69).Index Terms-University resource planning, enterprise resource planning, green university, cloud computing. I. INTRODUCTION"Green University" refers to a higher education institution, in which a part of the university, or the university as a whole, encourages, manages, and participates in mitigating environmental, economic, social, and health problems arising from resource utilization as much as possible. At the present time, higher education institutions, both in Thailand and elsewhere, have increasingly acknowledged the importance of sustainable and environment-friendly development. Due to the increasing awareness and interest in such development, the author has conceptualized the idea of Green University Resource Planning in higher education institutions based on the idea of Enterprise Resource Planning. The construction of a data structure for higher education helps to save resources and reduce operational processes, as well as effectively deal with problems associated with data processing. As a result, resource allocation processes and related operations are reduced, while management and support services can respond to the teachers" and students" demands more productively. Universities, as is the case with other organizations, are currently being confronted with numerous problems such as resource coordination, budgetary control, personnel in charge of resource allocation, communications, and inter-departmental integration. Hence, University Resource Planning begins with the reconstruction of the university"s identity. This will lead to a further shift from traditional administration to more effective inter-departmental integration within the university. This is designed to resolve internal problems, integrating information, and improving the overall quality and productivity of the administration that represents the characteristics of each university [1].T...