With the development of e-commerce, online shopping has become one of the most important consumer channels. However, the lack of government supervision, insufficient review of e-commerce platforms, illegal sales of online sellers and invalid consumer complaints have led to frequent green product quality problems during online shopping. Therefore, this paper considers that the online seller may be driven by interests, colluding with the e-commerce platform and selling low quality green product. At the same time, we introduce consumer feedback, and take the government supervision department, the online seller and the e-commerce platform as actors of the evolutionary game. In this paper, the evolutionary strategy choices of each actor were analyzed, and the influence of different factors on the evolutionary stability results was explored. Research indicates firstly, consumer complaints play an indirect regulatory role for the online seller; secondly, the enhancement of the loss-sharing relationship between the online seller and the e-commerce platform can promote the legal operation of the two and prevent collusion; thirdly, the impact of consumer complaints on the choice of the e-commerce platform depends on the government supervision department's penalty for the e-commerce platform; finally, the e-commerce platform establishes a reasonable reward system, which can make up for the defects of the online seller using advanced technology to avoid punishment. Our paper uses Matlab 2017 for simulation analysis and provides effective advices on how to urge the government supervision department to effectively supervise, promote the e-commerce platform to enhance review, urge the online seller to legal sale, and encourage consumers to legally defend their rights.BACKGROUND Mutations in the human desmin gene (DES) cause autosomal-dominant and -recessive cardiomyopathies, leading to heart failure, arrhythmias, and AV blocks. We analyzed the effects of vascular pressure overload in a patient-mimicking p.R349P desmin knock-in mouse model that harbors the orthologue of the frequent human DES missense mutation p.R350P. METHODS AND RESULTS Transverse aortic constriction (TAC) was performed on heterozygous (HET) DES-p.R349P mice and wild-type (WT) littermates. Echocardiography demonstrated reduced left ventricular ejection fraction in HET-TAC (WT-sham 69.5 ± 2.9%, HET-sham 64.5 ± 4.7%, WT-TAC 63.5 ± 4.9%, HET-TAC 55.7 ± 5.4%; p less then 0.01). Cardiac output was significantly reduced in HET-TAC (WT sham 13088 ± 2385 μl/min, HET sham 10391 ± 1349μl/min, WT-TAC 8097 ± 1903μl/min, HET-TAC 5793 ± 2517μl/min; p less then 0.01). Incidence and duration of AV blocks as well as the probability to induce ventricular tachycardias was highest in HET-TAC. We observed reduced mtDNA copy numbers in HET-TAC (WT-sham 12546 ± 406, HET-sham 13526 ± 781, WT-TAC 11155 ± 3315, HET-TAC 8649 ± 1582; p = 0.025), but no mtDNA deletions. The activity of respiratory chain complexes I and IV showed the greatest reductions in HET-TAC. CONCLUSION Pressure overload in HET mice aggravated the clinical phenotype of cardiomyopathy and resulted in mitochondrial dysfunction.  https://www.selleckchem.com/products/Cediranib.html  Preventive avoidance of pressure overload/arterial hypertension in desminopathy patients might represent a crucial therapeutic measure.Recent data highlights an imbalance in research grant success among groups underrepresented within the biomedical workforce, including racial/ethnic minorities and women. However, there is no data on grant success for researchers with disabilities. For these analyses, aggregate data on self-reported disability status for National Institute on Health (NIH) research grant applicants and awardees was obtained from 2008 to 2018, including disability category mobility/orthopedic, hearing, visual disabilities, and other disabilities. The percentage of applications and awards, as well as grant success rates (% of applicants receiving awards), by Principal Investigators (PIs) disability status were calculated. Data was desegregated, and logistic models determined trend of applicants reporting disability over time. The percentage of NIH grant applicants with PIs reporting a disability significantly declined from 1.9% in 2008, to 1.2% in 2018 (p less then 0.001). Data on grant awardees was similar, 1.9% of awards in 2008, declining to 1.2% in 2018 (p less then 0.001) had PIs reporting a disability. Across all years, the percentage of applications and awards with PIs reporting visual disabilities was lower than the percentage reporting mobility/orthopedic, or hearing disabilities (16.5%, 34.2%, and 37.8% in 2008, respectively). Overall grant success rates differed by disability status (27.2% for those reporting disability vs 29.7% in those reporting no disability, p less then 0.001). The lowest overall grant success rate was among PIs reporting unknown disability status or who withheld this status (18.6%). These results underscore the underrepresentation of researchers with disabilities among grant applicants and awardees, and indicate lower grant success rates among PIs reporting disabilities.The core element of machine learning is a flexible, universal function approximator that can be trained and fit into the data. One of the main challenges in modern machine learning is to understand the role of nonlinearity and complexity in these universal function approximators. In this research, we focus on nonlinear complex systems, and show their capability in representation and learning of different functions. Complex nonlinear dynamics and chaos naturally yield an almost infinite diversity of dynamical behaviors and functions. Physical, biological and engineered systems can utilize this diversity to implement adaptive, robust behaviors and operations. A nonlinear dynamical system can be considered as an embodiment of a collection of different possible behaviors or functions, from which different behaviors or functions can be chosen as a response to different conditions or problems. This process of selection can be manual in the sense that one can manually pick and choose the right function through directly setting parameters.