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Background: Cardiac rehabilitation (CR) is a multidisciplinary medical program. Most studies have emphasized the effect of exercise-based CR in lowering lipid levels; however, the effect of CR as a comprehensive program on lipid levels remains unclear. Methods: Electronic database were searched up to 2022. Randomized controlled trials with lipid profile indicators were included. Standardized mean differences (SMDs) and 95% CIs were used to evaluate the effect size. Begg's funnel plot and Egger's linear regression test were used to assess publication bias. Results: CR remarkably reduced low-density lipoprotein cholesterol (LDL-C) levels (SMD = --0.23; 95%CI: [--0.38, --0.08]; P < 0.001), triglyceride (TG) levels (SMD = --0.17; 95%CI: [--0.28, --0.06]; P < 0.001), and total cholesterol (TC) levels (SMD = --0.30; 95%CI: [--0.43, --0.16]; P < 0.001) and increased high-density lipoprotein cholesterol (HDL-C) levels (SMD = 0.19; 95%CI: [0.10, 0.29]; P < 0.001). Conclusions: CR reduce TC, TG, and LDL-C levels while improving HDL-C levels. CR should be promoted and more trials should be conducted for long-term CR. [ABSTRACT FROM AUTHOR]

Urbanization is a process of land use change dominated by human beings. The rapid urbanization process has changed the underlying surface conditions and affected the hydrological cycle process of the underlying surface of the basin. Based on the analysis of a long series of hydrological data over the past 35 years, combined with the underlying surface data of satellite images in this area, the hydrological effect caused by rapid urbanization in Yitong River Basin is analyzed. The results show that during the period of 1980-2015, the proportion of unused land represented by wetlands and bare sands decreased from 3.84% to 0.48%, cultivated land decreased from 71.34% to 67.9%, and forest land decreased by 14.9% to 11.7%. Urban land increased from 6.75% to 15.25%, and grassland increased from 0.5% to 1.03. Through the SWAT t model we explore influence of change in the underlying surface on the runoff. The results show that the runoff changes are significant from 1980 to 2000, while the runoff changes from 2000 to 2015 are not obvious. The change of the underlying surface reflects the urbanization of the basin in different periods.and the impact on runoff. [ABSTRACT FROM AUTHOR]

Using all national meteorological stations and regional automatic stations in the basin, data such as hourly precipitation, process precipitation and precipitation area forecast, digital elevation model, land use, soil type and field disaster investigation, etc. Based on the flood area model, the flood inundation simulation and effect test were carried out on the historical heavy rainfall period in the Datong River basin, which occurred at 20: 00 hours on July 5, 2013, at 20: 00 hours on July 5, 2017, and at 20: 00 o'clock in Datong River Basin. The simulation results show that the water level in the middle and upper reaches of the Datong River basin rises obviously, the water level in most areas exceeds 1 m, the water level in some tributaries is more than 3 m, and the water level in some areas of Zhuyang Township, Y ouhua Township and Qiaomu Township is more than 6 m. The results of disaster investigation show that the simulated values of flood flood area and flood area are in good agreement with the actual values, which indicates that the flood area model has better simulation effect in Datong River basin. It can be used for risk assessment and early warning of torrential rain and flood disaster. [ABSTRACT FROM AUTHOR]

Long-term time series of Normalized Difference Vegetation Index datasets is key for the monitoring of land surface dynamics and vegetation change. We evaluated the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) NDVI and the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI for the same time period from 2000 to 2006 for a comparative analysis. Prior to use, both datasets have been processed using the Savitzky-Golay filter to reduce the effects of clouds, atmosphere, sensor properties and behaviour and the surface Bidirectional Distribution Reflectance Function (BDRF). The average Normalized Difference Vegetation Index, monthly Coefficient of Variation and trends of GIMMS and MODIS datasets are typically in alignment. A high correlation of 98.1% pixels (r≥0.9, P<0.05) are observed between the GIMMS and MODIS datasets. The correlation coefficient, intercept and slope parameters using the two datasets have been calculated to derive a new GIMMS dataset (1982-2006). A long-term series dataset (1982 to 2013) was subsequently produced at 8 km spatial resolution for the Northeast of China by integrating the new GIMMS (1982-2000) and MODIS (2001-2013) datasets. The expanded Normalized Difference Vegetation Index dataset passed consistency tests based on the linear regression for each pixel and was utilized for the 1982-2013 long-term series analysis. Significant correlations were detected between the monthly Normalized Difference Vegetation Index trends and regional climatic change. [ABSTRACT FROM AUTHOR]