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Abstract Objective This study aims to assess the relationship between NHHR (non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio) and Type 2 diabetes mellitus (T2DM) in US adults, using National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2018. Methods This study explored the connection between NHHR and T2DM by analyzing a sample reflecting the adult population of the United States (n = 10,420; NHANES 2007–2018). NHHR was characterized as the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol. T2DM was defined based on clinical guidelines. This research used multivariable logistic models to examine the connection between NHHR and T2DM. Additionally, it included subgroup and interaction analyses to assess variations among different groups. Generalized additive models, smooth curve fitting, and threshold effect analysis were also employed to analyze the data further. Results The study included 10,420 subjects, with 2160 diagnosed with T2DM and 8260 without. The weighted multivariate logistic regression model indicated an 8% higher probability of T2DM for each unit increase in NHHR (OR: 1.08, 95% CI: 1.01–1.15) after accounting for all covariates. Subgroup analysis outcomes were uniform across various categories, demonstrating a significant positive relationship between NHHR and T2DM. Interaction tests showed that the positive link between NHHR and T2DM remained consistent regardless of age, body mass index, smoking status, moderate recreational activities, hypertension, or stroke history, with all interaction P-values exceeding 0.05. However, participants’ sex appeared to affect the magnitude of the connection between NHHR and T2DM (interaction P-value

Aiming at the problems of insufficient knowledge distillation efficiency,single stage training methods,complex training processes and difficult convergence of traditional knowledge distillation methods in image classification tasks,this paper designs a mutual learning knowledge distillation based on multi-stage multi-generative adversarial networks(MS-MGANs).Firstly,the whole training process is divided into several stages,teacher models of different stages are obtained to guide student models to achieve better accuracy.Secondly,the layer-wise greedy strategy is introduced to replace the traditional end-to-end training mode,and the layer-wise training strategy based on convolution block is adopted to reduce the number of parameters to be optimized in each iteration process,and further improve the distillation efficiency of the model.Finally,a generative adversarial structure is introduced into the knowledge distillation framework,with the teacher model as the feature discriminator and the student model as the feature generator,so that the student model can better follow or even surpass the performance of the teacher model in the process of continuously imitating the teacher model.The proposed method is compared with other advanced knowledge distillation methods on several public image classification data sets,and the experimental results show that the new knowledge distillation method has better performance in image classification.

Objective: To explore the working mode of continuous malaria elimination., Methods: Judong Village in Congjiang County, Guizhou Province, which had the highest record of malaria incidence in the history of Guizhou Province, was selected as a pilot, a comprehensive prevention and control intervention was carried out aiming at the malaria epidemic, transmission and influencing factors, and the effect was evaluated after the intervention., Results: From 2015 to 2016, through those intensive measures of constructing system, improving environment and health education, the people's awareness of malaria prevention was increased, the people's enthusiasm and initiatives to participate in the prevention and control of malaria were improved in Judong Village. Meanwhile, the roads were hardened and beautified, the dispose of sewage, feces and garbage was centralized. The awareness rate of malaria prevention knowledge of residents increased to 85% to 95%, and the formation rate of anti-mosquito behavior increased to 89.66%. The density of media Anopheles reduced from 0.56 to 0.07 mosquitoes per hour each mosquito catching platform., Conclusions: A long-term mechanism for malaria prevention and control has been almost constructed in Judong Village, which facilitates the consolidation of malaria control achievements, and the progress towards malaria elimination.