There are some problems in the photovoltaic microgrid system due to the solar irradiancechange environment, such as power fluctuation, which leads to larger power imbalance and affects the stable operation of the microgrid. Aiming at the problems of power mismatch loss under partial shading in photovoltaic microgrid systems, this paper proposed a distributed maximum power point tracking (DMPPT) approach based on an improved sparrow search algorithm (ISSA). First, used the center of gravity reverse learning mechanism to initialize the population, so that the population has a better spatial solution distribution; Secondly, the learning coefficient was introduced in the location update part of the discoverer to improve the global search ability of the algorithm; Simultaneously used the mutation operator to improve the position update of the joiner and avoid the algorithm falling into the local extreme value. The results of the model in Matlab showed that the ISSA can track the maximum power point(MPP) more accurately and quickly than the perturbation observation method (P&O) and the particle swarm optimization (PSO) algorithm, and had good steady-state performance.INDEX TERMS Distributed maximum power point tracking, photovoltaic microgrid, sparrow search algorithm, spatial solution distribution, steady-state.

Background Insulin resistance (IR), evaluation of which is difficult and complex, is closely associated with cardiovascular disease. Recently, various IR surrogates have been proposed and proved to be highly correlated with IR assessed by the gold standard. It remains indistinct whether different IR surrogates perform equivalently on prognostic prediction and stratification following percutaneous coronary intervention (PCI) in non-ST-segment elevation acute coronary syndrome (NSTE-ACS) patients with and without type 2 diabetes mellitus (T2DM). Methods The present study recruited patients who were diagnosed with NSTE-ACS and successfully underwent PCI. IR surrogates evaluated in the current study included triglyceride-glucose (TyG) index, visceral adiposity index, Chinese visceral adiposity index, lipid accumulation product, and triglyceride-to-high density lipoprotein cholesterol ratio, calculations of which were conformed to previous studies. The observational endpoint was defined as the major adverse cardiovascular and cerebrovascular events (MACCE), including cardiac death, non-fatal myocardial infarction, and non-fatal ischemic stroke. Results 2107 patients (60.02 ± 9.03 years, 28.0% female) were ultimately enrolled in the present study. A total of 187 (8.9%) MACCEs were documented during the 24-month follow-up. Despite regarding the lower median as reference [hazard ratio (HR) 3.805, 95% confidence interval (CI) 2.581–5.608, P < 0.001] or evaluating 1 normalized unit increase (HR 1.847, 95% CI 1.564–2.181, P < 0.001), the TyG index remained the strongest risk predictor for MACCE, independent of confounding factors. The TyG index showed the most powerful diagnostic value for MACCE with the highest area under the receiver operating characteristic curve of 0.715. The addition of the TyG index, compared with other IR surrogates, exhibited the maximum enhancement on risk stratification for MACCE on the basis of a baseline model (Harrell’s C-index: 0.708 for baseline model vs. 0.758 for baseline model + TyG index, P < 0.001; continuous net reclassification improvement: 0.255, P < 0.001; integrated discrimination improvement: 0.033, P < 0.001). The results were consistent in subgroup analysis where similar analyses were performed in patients with and without T2DM, respectively. Conclusion The TyG index, which is most strongly associated with the risk of MACCE, can be served as the most valuable IR surrogate for risk prediction and stratification in NSTE-ACS patients receiving PCI, with and without T2DM.

Fluorescence lifetime is not only associated with the molecular structure of fluorophores, but also strongly depends on the environment around them, which allows fluorescence lifetime imaging microscopy (FLIM) to be used as a tool for precise measurement of the cell or tissue microenvironment. This review introduces the basic principle of fluorescence lifetime imaging technology and its application in clinical medicine, including research and diagnosis of diseases in skin, brain, eyes, mouth, bone, blood vessels and cavity organs, and drug evaluation. As a noninvasive, nontoxic and nonionizing radiation technique, FLIM demonstrates excellent performance with high sensitivity and specificity, which allows to determine precise position of the lesion and, thus, has good potential for application in biomedical research and clinical diagnosis.