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SMGSA algorithm‑based MPPT control strategy
Yiping Xiao,Yunfeng Zhao,Zongtao Shen,Hongjian Jiao 전력전자학회 2024 JOURNAL OF POWER ELECTRONICS Vol.24 No.5
Under partial shading conditions (PSCs), photovoltaic arrays exhibit power–voltage curves with multiple peaks. This phenomenon complicates the task of traditional maximum power point tracking (MPPT) algorithms, since they often converge to local maximum power points. To tackle this challenge, a novel MPPT control strategy, termed the slime mold golden sine algorithm (SMGSA), was introduced in this paper. This strategy adeptly identifies and tracks the global maximum power point. The efficacy of the SMGSA algorithm was assessed through six test functions from IEEE CEC 2020. A comparative analysis underscored its superior performance in both convergence speed and accuracy. A simulation model for MPPT was developed in MATLAB/Simulink. Within this model, various algorithms such as particle swarm optimization (PSO), tuna swarm optimization (TSO), slime mold algorithm (SMA), and SMGSA were examined. Comparative simulations revealed that the SMGSA-based MPPT strategy showcased expedited convergence speed and heightened accuracy under scenarios of uniform irradiance intensity, partial static shading, and dynamic shading. Consequently, the implementation of an SMGSAbased MPPT system can notably enhance the power generation efficiency of photovoltaic arrays under PSCs.
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Zheng Yingyan,Xiao Anling,Yu Xiangrong,Zhao Yajing,Lu Yiping,Li Xuanxuan,Mei Nan,She Dejun,Wang Dongdong,Geng Daoying,Yin Bo 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.8
Objective: The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). Materials and Methods: The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone. Results: Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67–6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04–0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03–4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76–0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82–0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050). Conclusion: Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.
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Jun Ma,Xiao Song,Xiaowu Xu,Yiping Mou 대한암학회 2019 Cancer Research and Treatment Vol.51 No.1
Purpose Our aim was to detect the potential role of interleukin 11 (IL-11) in the development of chemo-resistance in gastric cancer and to reveal the mechanism involved in the process. Materials and Methods Here, we used flow cytometry to examine the percentage of cancer-associated-fibroblasts in tumor samples from chemo-resistant and -sensitive gastric cancer patients. Using MTT assay, we detected the cell viability under different conditions. Using quantitative real-time polymerase chain reaction and Western blotting, we determined the target expressions in mRNA and protein levels. We also performed immunohistochemistry and immunofluorescence to detect the target proteins under different conditions. Animal models were constructed to verify the potential role of IL-11 in chemo-resistant develop in vivo. Results Herein, we observed enriched cancer associated fibroblasts in drug resistant tumor tissues from gastric patients. Those fibroblasts facilitate the chemotherapeutic drugs resistance development through the secretion of IL-11, which activates the IL-11/IL-11R/gp130/ JAK/STAT3 anti-apoptosis signaling pathway in gastric cancer cells. We found that the combination of chemotherapeutic drugs and JAK inhibitor overcomes the resistance and increases the survival of mice with gastric cancer xenografts. Conclusion Our results demonstrated that IL-11 contributed to the obtain of resistance to chemotherapy drugs through gp130/JAK/STAT3/Bcl2 pathway, and targeting the IL-11 signaling pathway induced by fibroblasts might be a promising strategy to overcome the multi-drugs resistant cancer in clinic.
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Polymorphisms in the Perilipin Gene May Affect Carcass Traits of Chinese Meat-type Chickens
Lu Zhang,Qing Zhu,Yiping Liu,Elizabeth R. Gilbert,Diyan Li,Huadong Yin,Yan Wang,Zhiqin Yang,Zhen Wang,Yuncong Yuan,Xiao-Ling Zhao 아세아·태평양축산학회 2015 Animal Bioscience Vol.28 No.6
Improved meat quality and greater muscle yield are highly sought after in high-quality chicken breeding programs. Past studies indicated that polymorphisms of the Perilipin gene (PLIN1) are highly associated with adiposity in mammals and are potential molecular markers for improving meat quality and carcass traits in chickens. In the present study, we screened single nucleotide polymorphisms (SNPs) in all exons of the PLIN1 gene with a direct sequencing method in six populations with different genetic backgrounds (total 240 individuals). We evaluated the association between the polymorphisms and carcass and meat quality traits. We identified three SNPs, located on the 5′ flanking region and exon 1 of PLIN1 on chromosome 10 (rs315831750, rs313726543, and rs80724063, respectively). Eight main haplotypes were constructed based on these SNPs. We calculated the allelic and genotypic frequencies, and genetic diversity parameters of the three SNPs. The polymorphism information content (PIC) ranged from 0.2768 to 0.3750, which reflected an intermediate genetic diversity for all chickens. The CC, CT, and TT genotypes influenced the percentage of breast muscle (PBM), percentage of leg muscle (PLM) and percentage of abdominal fat at rs315831750 (p<0.05). Diplotypes (haplotype pairs) affected the percentage of eviscerated weight (PEW) and PBM (p<0.05). Compared with chickens carrying other diplotypes, H3H7 had the greatest PEW and H2H2 had the greatest PBM, and those with diplotype H7H7 had the smallest PEW and PBM. We conclude that PLIN1 gene polymorphisms may affect broiler carcass and breast muscle yields, and diplotypes H3H7 and H2H2 could be positive molecular markers to enhance PEW and PBM in chickens.
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