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Aiming at the problem that the output of distributed generators (DG) of new energy sources such as wind power and photovoltaic is uncertain due to changes in environmental factors, and the transaction price of the existing carbon trading model is fixed, resulting in increased carbon reduction costs, an integrated energy system optimization planning method that takes into account dynamic carbon emission constraints and DG uncertainty was proposed. Firstly, a DG output model based on matrix affine algorithm was established according to environmental conditions to reduce the impact of DG output uncertainty on the optimization planning of the integrated energy system. Secondly, carbon emissions was introduced as a punitive measure into the optimization planning of the integrated energy system to improve the traditional carbon trading model and reduce the carbon emissions of the integrated energy system. Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. Finally, the simulation results on an IEEE 33 node system show that the proposed planning method reduces the total investment cost by 8.68% and 2.93% respectively compared with the traditional stochastic optimization and interval optimization planning methods. Compared with the traditional fixed carbon trading price model, carbon emissions are reduced by 6.28%.

Aiming at the problem that the output of distributed generators (DG) of new energy sources such as wind power and photovoltaic is uncertain due to changes in environmental factors, and the transaction price of the existing carbon trading model is fixed, resulting in increased carbon reduction costs, an integrated energy system optimization planning method that takes into account dynamic carbon emission constraints and DG uncertainty was proposed. Firstly, a DG output model based on matrix affine algorithm was established according to environmental conditions to reduce the impact of DG output uncertainty on the optimization planning of the integrated energy system. Secondly, carbon emissions was introduced as a punitive measure into the optimization planning of the integrated energy system to improve the traditional carbon trading model and reduce the carbon emissions of the integrated energy system. Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. Finally, the simulation results on an IEEE 33 node system show that the proposed planning method reduces the total investment cost by 8.68% and 2.93% respectively compared with the traditional stochastic optimization and interval optimization planning methods. Compared with the traditional fixed carbon trading price model, carbon emissions are reduced by 6.28%.

In this research, a chronoamperometric biosensor based on zinc oxide (ZnO)-graphene oxide (GO) nanocomposite material was designed and employed for lactate determination. The ZnO-GO hybrid proved to be a suitable substrate for the immobilization of lactate oxidase (LOD). The presence of ZnO and GO components in hybrid material led to synergistic effects and facilitates the LOD loading and electron transfer between the receptor and screen printed carbon electrode (SPCE) surface. The LOD-GO-ZnO modified SCPE exhibits excellent lactate sensing capabilities thanks to the uniform dispersion of ultrafine ZnO nanoparticles and enhanced mass-transfer kinetics. In phosphate buffer solution (pH=7.4), this novel electrochemical lactate biosensor demonstrates a linear response to lactate within the concentration range of 0.015–1.25 mM. Limit of detection (based on S/N=3) of the assay was estimated to be 9 µM. More importantly, the presence method is a highly selective device for the analysis of lactate in biological fluids. The lactate level in saliva samples was successfully measured before and after exercise of athletes using the suggested biosensor. This method offers a simple, cost-effective, fast, and effective platform for lactate determination in typical diagnostic applications.

Objective: To evaluate the antiobesity effect and underlying mechanism of Andrias davidianus peptide (ADP) supplementation combined with treadmill exercise. Methods: A mouse model of obesity was established by feeding mice a high-fat diet (HFD), and the obese mice were randomly divided into four groups: model, treadmill exercise (Ex), ADP and ADP combined with treadmill exercise (ADP + Ex). The rats in the Ex group were subjected to a six-week treadmill exercise training. The rates in the ADP group were gavaged with ADP for six weeks. The rats in the ADP + Ex group were treated with ADP supplementation combined with treadmill exercise training. Normal Sprague Dawley (SD) rats were used as the control (CN) group. Body mass and food intake were recorded each week, and the serum levels of glucagon-like peptide-1 (GLP-1), neuropeptide Y (NPY), irisin, leptin, triglycerides (TG), total cholesterol (TC), low density lipoprotein (LDL) and high density lipoprotein (HDL) were investigated by enzyme-linked immunosorbent assay (ELISA). Western blot was used to detect the expression of appetite-regulated proteins (NPY and proopiomelanocortin (POMC)) and energy metabolism-related proteins. Results: Body mass, inguinal and epididymal fat accumulation, food intake, and serum TG, TC and LDL levels significantly decreased in the ADP + Ex group compared with the model group. In addition, ELISA results revealed that combination of ADP supplementation with treadmill exercise reduced the serum levels of NPY and leptin but increased the serum concentrations of GLP-1 and irisin in obese rats. Western blot analysis showed that ADP supplementation combined with treadmill exercise greatly up-regulated the expression of POMC and energy metabolism related proteins (irisin, phospho-adenosine monophosphate-activated protein kinase, peroxisome proliferator-activated receptor γ co-activated factor-1α, and fibronectin type III domain containing protein 5), but down-regulated the expression of NPY. Conclusion: The combination of ADP with aerobic exercise can effectively alleviate HFD-induced obesity, thereby providing a new promising strategy to alleviate HFD-induced obesity.