Background: Psoriasis is a cutaneous disorder of multifactorial etiology influenced by both genetic and environmental factors such as infection. Methods: We conducted a genome analysis with 20 microsatellite markers spanning the long arm of chromosome 1 in 36 Chinese families with psoriasis and detected evidence for linkage at 1q21 with a nonparametric linkage score of 1.74, p = 0.03, and 1q32 with one of 1.84, p = 0.03. According to the positional and functional candidate principle, we further investigated the single-nucleotide polymorphisms of the HAX-1 gene (located in 1q21) and IL-20 gene (located in 1q32) in a case-control study including 340 sporadic patients and 199 controls. Results: We determined that the frequency of the G allele of IL-20 –1723C→G (rs1713239) was significantly higher among psoriatic patients (38.5% in cases vs. 31.2% in controls, p = 0.015, odds ratio, OR = 1.39, 95% confidence interval, CI = 1.07–1.80). When we stratified our analysis by psoriasis triggered or exacerbated by infection of the upper respiratory tract, a significant difference was detected (42.4% in stratified cases vs. 31.2% in controls, p = 0.005, OR = 1.63, 95% CI = 1.15–2.30). Conclusion: We assume that triggered or exacerbated by respiratory tract infection, the population with the G allele of IL-20 –1723C→G are predisposed to psoriasis.
Objective
To identify risk factors for postoperative sore throat (POST) after general anesthesia in oral and maxillOfacial surgery.
Material and Methods
This study is a retrospective cohort design study. We enrolled patients with oral and maxillofacial surgery who underwent endotracheal intubation under general anesthesia in the Stomatology Hospital, Zhejiang University School Of Medicine between April 2020 and April 2021. They were divided into the POST group and the without POST group. The distribution Of various characteristics in the two groups was firstly analyzed. Then, logistic regression analysis was performed to explore the independent predictors for POST occurrence. Following this, logistic regression and random forest models were constructed and their performance was evaluated to predict POST occurrence.
Results
A total of 891 participants were enrolled in the study. Female gender and cough during extubation were significantly associated with increased POST occurrence in multivariate analysis (all P <0.05). Stratified logistic regression analysis results showed that the female gender was an independent predictor for POST occurrence in the 4≤age≤14 and 14
Abstract. Wind resources are considered to be one of the most promising alternative energy sources. It is difficult to achieve the maximum utilization of wind energy by artificial maintenance scheduling, because of poor operating environment, poor site accessibility, and other objective factors such as randomness. According to health of turbines, wind power forecasting results, maintenance resource availability, weather and other factors, how to achieve the minimum maintenance cost and minimum wind power loss of offshore wind farms in the short-term maintenance task optimization scheduling is still a difficult problem facing the industry. This paper presented an optimization model for the scheduling of short term maintenance scheduling in offshore wind field, the optimization model belongs to nonlinear optimization problem with constraints, and uses the Gurobi to solve the optimization problem with the minimum wind field maintenance cost and the minimum wind power loss.
Abstract. In the production of stator cores, it is relied upon experienced engineers to make time sensitive decisions on the number of compensation sheets to be added to achieve uniform pressure distribution though out the laminations. However, this method yields inconsistent results as humans are unable to store and analyze large amounts of data. In this paper ANNs have been employed to help the engineers with the decision making process. The ANNs are trained using a hybrid Genetic Algorithm (GA) -Levenberg-Marquardt (LM) to avoid local convergence. When used on testing data sets, the ANNs displayed a high degree of prediction accuracy indicating their ability to simulate the decision making process of these experienced engineers.
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