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The association between subclinical hypothyroidism (SCH) and metabolic syndrome (MetS) has been widely discussed. This study aimed to conduct an update and comprehensive meta-analysis to reveal the risk of MetS and its components in SCH. PubMed, Embase and ISI Web of Knowledge were searched to identify relevant studies through February 20th, 2020. Review Manager 5.3 and Stata 14.0 were used to conduct the meta-analysis. Both fixed-effects and random-effects models were used. In total, 18 articles (19 studies) incorporating 79,727 participants were included. The pooled OR for MetS comparing subjects with SCH with euthyroid subjects was 1.28 (95% CI: 1.19 to 1.39, p = 0.04, I2 = 40%). Subgroup analysis results showed significant associations of SCH and MetS in the adult subgroup (OR = 1.28, 95% CI: 1.18-1.40), Asian population subgroup (OR = 1.30, 95% CI: 1.19-1.42) and cross-sectional study design subgroup (OR = 1.31, 95% CI: 1.16-1.47). Significant associations of SCH and MetS also existed in all MetS definition criteria subgroups except the Chinese Diabetes Society (CDS) subgroup. SCH was correlated with MetS and was not affected by the subgroup analysis stratified by the proportion of females in the total population, the TSH cutoff value in SCH diagnostic criteria, or the adjustment for confounding factors. SCH was identified to be associated with an increased risk of obesity, hypertension, high triglyceride (TG) levels and low high-density lipoprotein cholesterol (HDL-C) levels. In conclusion, SCH is significantly associated with an increased risk of MetS and four out of five components of MetS.

For problem of feature modeling on halftone image, three statistics methods, named gray-level co-occurrence matrix, autocorrelation function and spectrum statistics, are used to extract feature vector of various halftone images. Then, their classification performance is assessed by radial basis function neural network. A mass of experiments show the autocorrelation function is better than other two methods for classification on halftone image.

For the lack of self-adaptivity to environments, a measurement model based on weighted information fusion is presented in particle filter. Combined with color information and movement information of object, color histogram and motion Information histogram are built respectively, and then present a weighted linear model as the measurement model. The center-around method is adopted to compute the weight in the linear model. Lastly, a mass of experiments show the presented method be effective.

In real-time facial expression recognition, accurate and fast face tracking is a very important preparatory part to obtain the image sequence s of facial expressions. For this problem, an improved mean shift algorithm is proposed for real-time face tracking . F acial expression image sequence s are obtained with the method. The method is based on using pixel gray value distribution as the feature as well as combination of the density distribution of the objective gradient direction . A lternating iterative operation s can be carried through the iterative formula of these two features, and thus , we can make the human face rotation and translation movement tracking better . Then we used the geometric model based on human face to locate the region of facial expression features, and estimate the optical flow to calculate the Eigen-flow vectors. Finally , hidden semi-Markov model is used for facial expression recognition s . Experiments show that the proposed method can effectively track the face under rotation and translation movement of the head and it is very effective to obtain the facial expression image sequence s quickly and accurately.

In this paper, propose a method of face detection based on adaptive skin color and structure model for multi-pose color images in a complex background. First, a face skin color model is built, and an adaptive Gamma correction is used in the skin color segmentation, which improve the skin color model to adapt to different illumination and multi-poses of face. Then a triangular structure model is constructed specific to the face features. And finally use the structure model to locate the face precisely on the basis of face images of skin color. The experimental results show the approach raised on this paper can adapt to the face detection under the conditions of different illumination environment, various poses and complex background, and the algorithm is quick and effective.

TorsinA is an atypical ATPase that lacks intrinsic activity unless it is bound to its activators lamina-associated polypeptide 1 (LAP1) in the perinuclear space or luminal domain-like LAP1 (LULL1) throughout the endoplasmic reticulum. However, the interaction of torsinA with LAP1 and LULL1 has not yet been shown to modulate a defined physiological process in mammals in vivo . We previously demonstrated that depletion of torsinA from mouse hepatocytes leads to reduced liver triglyceride secretion and marked steatosis, whereas depletion of LAP1 had more modest similar effects. We now show that depletion of LULL1 alone does not significantly decrease liver triglyceride secretion or cause steatosis. However, simultaneous depletion of both LAP1 and LULL1 from hepatocytes leads to defective triglyceride secretion and marked steatosis similar to that observed with depletion of torsinA. Our results demonstrate that torsinA and its activators dynamically regulate a physiological process in mammals in vivo .