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Multi-motor systems have been widely applied in many fields such as industry and transportation. In this paper, a two coupling permanent magnet synchronous motors system is considered. First, the model of the system is established. Then, a novel state equation of the system is obtained by choosing suitable state variables. Based on the state equation, a robust synchronization controller is designed via a cross-coupling idea and interval matrix. In terms of bilinear matrix inequations, sufficient conditions for the existence of the robust controller are derived. Thanks to the suitable choice of state variables, the proposed controllers can deal with load uncertainty without a load observer, and have robustness for environmental and parameter disturbance. In order to verify the effectiveness of the proposed controller, simulations are carried out via Matlab/Simulink soft. Simulation results reflect that the controller has good dynamic, static, and synchronization performance. [ABSTRACT FROM AUTHOR]

This article investigates constrained online noncooperative games (NGs) of multiagent systems over unbalanced digraphs, where the cost functions of players are time-varying and are gradually revealed to corresponding players only after decisions are made. Moreover, in the problem, the players are subject to local convex set constraints and time-varying coupling nonlinear inequality constraints. To the best of our knowledge, no result about online games with unbalanced digraphs has been reported, let alone constrained online games. To seek the variational generalized Nash equilibrium (GNE) of the game online, a distributed learning algorithm is proposed based on gradient descent, projection, and primal-dual methods. Under the algorithm, sublinear dynamic regrets and constraint violations are established. Finally, online electricity market games illustrate the algorithm.

Diabetes mellitus (DM) is one of the largest epidemics the world has faced. Given the morbidity and mortality burden of DM, it is important to identify modifiable factors that affect the natural course of the disease. We carried out this meta-analysis of published studies to estimate the overall DM risk of intake of fermented dairy foods, and to reveal the dose-dependent effect on DM risk. We searched the PubMed, Embase and China National Knowledge Infrastructure databases for all articles published between the years 1980 to 2020 on the association between fermented dairy foods intake and DM risk. Fifteen studies met the inclusion criteria for our study, including a total of 485,992 participants and 20,207 incidences of diabetes. Overall, statistical evidence of significantly decreased diabetes risk was found to be associated with higher intake of fermented dairy foods (odds ratio [OR], 0.925; 95% confidence interval [CI], 0.856 to 0.999). In a subgroup analysis, higher yogurt consumption was significantly associated with decreased DM risk (OR, 0.828; 95% CI, 0.729 to 0.941). Our meta-analysis shows that intake of fermented dairy foods is associated with decreased DM risk, and the effect may be dose-dependent., (Copyright © 2021 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

Aim: We carried out this meta-analysis on all published studies to estimate the overall cancer risk of the use of metformin in T2DM patients., Methods: We searched the PubMed, Embase and CNKI databases for all articles within a range of published years from 2007 to 2019 on the association between the use of metformin and cancer risk in T2DM patients. The odds ratio (OR) corresponding to the 95% confidence interval (95% CI) was used to assess the association using a random-effect meta-analysis., Results: Finally, 67 studies met the inclusion criteria for this study, with 10,695,875 T2DM patients and 145,108 cancer cases. Overall, For T2DM patients of ever vs. never metformin users, there was statistical evidence of significantly decreased cancer risk was found to be associated with ever metformin users (OR=0.70, 95% CI=0.65-0.76). Considering T2DM may be a specific and independent risk factor for various forms of cancer, due to its particular metabolic characteristics of glucose intolerance and hyperinsulinemia, we performed a comparison to estimate the effects of metformin on cancer risk with other anti-diabetes medications (ADMs), our results found significantly decreased cancer risk to be associated with the use of metformin (OR=0.80, 95% CI=0.73-0.87)., Conclusion: Our meta-analysis indicated that metformin may be a independent protective factor for cancer risk in T2DM patients., (Copyright © 2020 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.)

Human identification is an important task in mass disaster and criminal investigations. Although several automatic dental identification systems have been proposed, accurate and fast identification from panoramic dental radiographs (PDRs) remains a challenging issue. In this study, an automatic human identification system (DENT-net) was developed using the customized convolutional neural network (CNN). The DENT-net was trained on 15,369 PDRs from 6300 individuals. The PDRs were preprocessed by affine transformation and histogram equalization. The DENT-net took 128 × 128 × 7 square patches as input, including the whole PDR and six details extracted from the PDR. Using the DENT-net, the feature extraction took around 10 milliseconds per image and the running time for retrieval was 33.03 milliseconds in a 2000-individual database, promising an application on larger databases. The visualization of CNN showed that the teeth, maxilla, and mandible all contributed to human identification. The DENT-net achieved Rank-1 accuracy of 85.16% and Rank-5 accuracy of 97.74% for human identification. The present results demonstrated that human identification can be achieved from PDRs by CNN with high accuracy and speed. The present system can be used without any special equipment or knowledge to generate the candidate images. While the final decision should be made by human specialists in practice. It is expected to aid human identification in mass disaster and criminal investigation., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The developmental patterns of the pelvic epiphyses are one of the anatomical markers used in the assessment of skeletal age and the legally relevant age threshold. In this study, four regression models and five classification models were developed for forensic age estimation and the determination of the 18-year threshold, respectively. A total of 2137 conventional pelvic radiographs (1215 males and 922 females) aged 10.00-25.99 years were analyzed, and the ossification and fusion of the iliac crest and ischial tuberosity epiphyses were scored separately. The epiphyses on both sides were used as inputs for all models. The accuracy of the regression models was compared using the mean absolute error (MAE) and root mean square error. The percentages of correct classifications were evaluated for the determination of the 18-year threshold. Support vector regression (SVR) and gradient boosting regression (GBR) showed higher accuracy for age estimation in both sexes. The lowest MAE was 1.38 years in males when using SVR and 1.16 years in females when using GBR. In the demarcation of minors and adults, the percentage of correct classification was over 92%, and the area under the receiver operating characteristic curves was over 0.91 in all models, except the Bernoulli naive Bayes classifier. This study demonstrated that the present models may be helpful for age estimation and the determination of the 18-year threshold. However, owing to the high effective dose of ionizing radiation used during conventional radiography of the pelvis, it is expected that these models will be tested with pelvic MRI for age estimation., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Introduction: Weight loss after bariatric surgery yields important health benefits. A multitude of observational studies have investigated the association of bariatric surgery for severe obesity with the risk of cancer. However, the results were debatable. The aim of the present study was to estimate the effect of bariatric surgery on overall cancer risk., Methods: A systematic literature search was performed to identify studies evaluating the association of bariatric surgery for severe obesity with the risk of cancer. Meta-analysis was performed to calculate combined prevalence., Results: Twenty-one cohort studies with 304,516 patients with obesity having under gone bariatric surgery and 8,492,408 patients with obesity as controls were included. Meta-analysis found decreased cancer risk to be associated with bariatric surgery (OR = 0.56, 95% CI = 0.48-0.66), both for the incidence of cancer (OR = 0.56, 95% CI = 0.46-0.68) and mortality of cancer (OR = 0.56, 95% CI = 0.41-0.75). In subgroup analysis, bariatric surgery was significantly associated with decreased breast cancer risk and endometrial cancer risk, but not associated with other cancer risk., Conclusions: Our meta-analysis indicated that bariatric surgery for severe obesity was associated with decreased cancer risk, both for cancer incidence and mortality. Moreover, further studies estimating the functional effect and side effects may eventually provide a better, comprehensive understanding.

Aim: Pharmacologic therapy for T2DM has proven benefits in terms of reducing elevated blood glucose levels and reducing microvascular complications. However, the impact of metformin on adverse cardiovascular outcomes and cardiovascular mortality is less clear. We carried out this meta-analysis on all published studies to estimate the overall cardiovascular risk following metformin treatment in patients with T2DM., Methods: We searched the PubMed, Embase and CNKI (China National Knowledge Infrastructure) databases for all articles. The odds ratio (OR) corresponding to the 95% confidence interval (95% CI) was used to assess the cardiovascular risk following metformin treatment in patients with T2DM. The statistical heterogeneity among studies was assessed with the Q-test and I 2 statistics., Results: We collected 16 studies including 25 comparisons with 1,160,254 patients of type 2 diabetes mellitus and 701,843 patients of T2DM following metformin treatment. Our results found statistical evidence of significantly decreased cardiovascular risk to be associated with following treatment with metformin in patients with type 2 diabetes mellitus (OR = 0.57, 95% CI = 0.48-0.68) (shown in Table 1 and Fig. 2), both with the mortality (OR = 0.44, 95% CI = 0.34-0.57) and incidence (OR = 0.73, 95% CI = 0.59-0.90)., Conclusions: Our meta-analysis indicated that following metformin treatment in patients with T2DM was associated with decreased cardiovascular risk, both with the mortality and incidence. However, the heterogeneity among studies may potentially affect the final results., Competing Interests: Declaration of Competing Interest The authors declared that there is no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The introduction of wheat into central China is thought to have been one of the significant contributions of interactions between China and Central Asia which began in the 3rd millennium bc. However, only a limited number of Neolithic wheat grains have been found in central China and even fewer have been directly radiocarbon dated, making the date when wheat was adopted in the region and its role in subsistence farming uncertain. Based on systematic archaeobotanical data and direct dating of wheat remains from the Xiazhai site in central China, as well as a critical review of all reported discoveries of Neolithic and Bronze Age wheat from this region, we conclude that many wheat finds are intrusive in Neolithic contexts. We argue that the role of wheat in the subsistence of the late Neolithic and early Bronze Age of central China was minimal, and that wheat only began to increase in its subsistence role in the later Bronze Age during the Zhou dynasty after ca. 1000 bc., (© The Author(s) 2019.)

Purpose: To develop a deep learning bone age assessment model based on pelvic radiographs for forensic age estimation and compare its performance to that of the existing cubic regression model., Materials and Method: A retrospective collection data of 1875 clinical pelvic radiographs between 10 and 25 years of age was obtained to develop the model. Model performance was assessed by comparing the testing results to estimated ages calculated directly using the existing cubic regression model based on ossification staging methods. The mean absolute error (MAE) and root-mean-squared error (RMSE) between the estimated ages and chronological age were calculated for both models., Results: For all test samples (between 10 and 25 years old), the mean MAE and RMSE between the automatic estimates using the proposed deep learning model and the reference standard were 0.94 and 1.30 years, respectively. For the test samples comparable to those of the existing cubic regression model (between 14 and 22 years old), the mean MAE and RMSE for the deep learning model were 0.89 and 1.21 years, respectively. For the existing cubic regression model, the mean MAE and RMSE were 1.05 and 1.61 years, respectively., Conclusion: The deep learning convolutional neural network model achieves performance on par with the existing cubic regression model, demonstrating predictive ability capable of automated skeletal bone assessment based on pelvic radiographic images., Key Points: • The pelvis has considerable value in determining the bone age. • Deep learning can be used to create an automated bone age assessment model based on pelvic radiographs. • The deep learning convolutional neural network model achieves performance on par with the existing cubic regression model.

Objective: An analysis of malpractice lawsuits judged in court compared with those mediated in court may help explain perceptions of malpractice risk., Methods: We conducted a retrospective study of malpractice lawsuits mediated and judged in court using data from district courts in Beijing from 2010 through 2014. We evaluated the number of cases, the payment amount, and the time to resolution, by resolution type. Patient age, sex, the severity of injury, and adverse event type were measured. Subsequently, a binary logistic regression identified factors associated with patients' pursuit of judgment., Results: Between 2010 and 2014, there were 1226 lawsuits (49.9%) mediated in court and 1259 (50.1%) judged in court. The proportion of the judged lawsuits varied significantly across the study period (p < 0.001). The mean payment amount and the time to resolution were significantly higher in judgment lawsuits (p < 0.001). The younger the patients, the greater the possibility of being judged in court (odds ratio [OR] = 0.831, p < 0.0001). Lawsuits where the adverse event type was treatment, obstetrics, or diagnostics were more likely to be judged than those where the adverse event type was surgical (OR = 2.311, p < 0.0001; OR = 2.311, p < 0.0001; OR = 3.302, p < 0.0001, respectively). When lawsuits were for a temporary injury, they were more likely to be judged in court than those for a permanent injury (OR = 0.723, p = 0.0139).results CONCLUSIONS: The patient-physician relationship may in fact not be particularly close in our country. Lawsuits with certain characteristics tend to be judged in court. Understanding these characteristics may be useful for predicting the outcome of lawsuits against physicians., (Copyright © 2018. Published by Elsevier Ltd.)