The isolation and purification of the leaves of Kopsia singapurensisRidl. (Apocynaceae) revealed the presence of steroids, terpenes, and alkaloids. Stigmasterol 1 was isolated from the hexane crude extract of the leaves of this species. This phytochemical study involves extraction, separation by using various chromatographic methods and structural determination by spectroscopic technique such as IR, NMR including 1D-NMR (1H, 13C and DEPT), 2D-NMR (COSY, NOESY, HMQC/HSQC, and HMBC) and GCMS, involving also comparison with data from the literature..

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This study was aimed to extract and identify chemical compounds isolated from the leaves and barks of Kopsia singapurensis. The isolated compounds were evaluated for cytotoxic (MCF-7), antibacterial (Bacillus cereus) and antioxidant activity (DPPH). The isolation process was carried out using chromatographic techniques such as column chromatography and thin layer chromatography. The structures of isolated compounds were elucidated through spectroscopic analysis including 1D-NMR (1H, 13C and DEPT), 2D-NMR (1H-1H COSY, HSQC/HMQC and HMBC), IR, UV, MS (GCMS); also by comparison with previous literature data. Isolation study on the leaves of K. singapurensis has yielded lupeol 147, mixture of stigmasterol 148 and β- sitosterol 149, lupeol ester 150, and a mixture of lupeol 147, α-amyrin 151 and β- amyrin 152. Compounds β-amyrin 152, β-amyrenone 153, β-amyrin acetate 154 and lupeol acetate 155 were successfully isolated from the bark of K. singapurensis. These triterpenoids were isola.....

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In Malaysia, Alstonia spathulata Bl. is locally known as ‘Pulai Basong’ which distribute in peat forest. The separation of the chemical components from hexane and DCM crude extract of Alstonia spathulata was carried out using column chromatography (CC) and thin layer chromatography (TCL) techniques. A total of five known compound were isolated from the stem bark extracts and identified as: β-amyrin, β-amyrin acetate, lupeol acetate, stigmasterol and β-sitosterol. The elucidation structures of these compounds were established using 1D-NMR (1H, 13C and DEPT) and 2D-NMR (COSY, HSQC, HMBC) spectroscopic analysis, involving also comparison with data from the literature...

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Objectives: The aim of this review was to provide an overview of researches presenting evidence for a relationship between physical well-being and cognitive outcomes in 2-7 year old typically developing children. Design: A systematic review. Methods: Articles involved in this review were from Science Direct, EBSCO and WoS. In total, 21 articles were included in this review. Two reviewers assessed the methodological quality independently. Results: The evidence for or against the relationship between physical well-being and cognitive outcomes was not sufficient. However, there was weak-to-strong evidence for some relationships between underlying categories of physical well-being and cognitive outcomes, including complex motor skills and higher order cognitive skills. Conclusions: There were some relationships between motor and cognitive skills. It offered insight into possible interventions designed to complex motor skills which may be beneficial for both motor and higher order cognitive.....

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Electrocardiogram (ECG) is a practical medical test to diagnose arrhythmia. As a crucial computational application in clinical practice, ECG automatic classification can effectively detect the possible occurrence of cardiovascular disease. At present, the main problems in the automated classification of ECG are due to (1) the complexity of algorithms to capture heartbeats, (2) the complex changes of irregular heartbeats in rhythm or morphology leading to difficulties in the ECG feature recognition, and (3) the needs of large training samples and training time for a machine learning to achieve the ideal recognition accuracy. Given the problems in ECG automatic classification, this study proposes an effective automated classification approach for arrhythmia based on a representative convolution neural network that can decode ECG source files and identify heartbeats accurately based on the detection of QRS waveform from the ECG records. A one-dimensional convolutional neural ne.....

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