Predicting adverse pregnancy outcomes of pregnant mothers with syphilis based on a logistic regression model: a retrospective study.

Objective: Maternal syphilis could cause serious consequences. The aim of this study was to identify risk factors for maternal syphilis in order to predict an individual's risk of developing adverse pregnancy outcomes (APOs). Methods: A retrospective study was conducted on 768 pregnant women with syphilis. A questionnaire was completed and data analyzed. The data was divided into a training set and a testing set. Using logistic regression to establish predictive models in the training set, and its predictive performance was evaluated in the testing set. The probability of APOs occurrence is presented through a nomogram. Results: Compared with the APOs group, pregnant women in the non-APOs group participated in a longer treatment course. Course, time of the first antenatal care, gestation week at syphilis diagnosis, and gestation age at delivery in weeks were independent predictors of APOs, and they were used to establish the nomogram. Conclusions: Our study investigated the impact of various characteristics of syphilis pregnant women on pregnancy outcomes and established a prediction model of APOs in Suzhou. The incidence of APOs can be reduced by controlling for these risk factors.

Vibration Suppression of a High-Rise Building With Adaptive Iterative Learning Control.

This article considers the design of an adaptive iterative learning controller for high-rise buildings with active mass dampers (AMDs). High-rise buildings in this article are seen as distributed parameter systems, in which the characteristics of every point in buildings should be considered. Two partial differential equations (PDEs) and several ordinary differential equations are used to describe the model of buildings. To achieve the control target that is to suppress the vibration induced by high winds, an adaptive iterative learning controller is proposed for the flexible building system with boundary disturbance. The convergency of the adaptive iterative learning control (AILC) approach is proven by serious theory analysis. In simulations and experiments, this article uses both the analysis of figures and quantitative analysis (root-mean-square values) to illustrate the efficiency of the AILC scheme.

Neural Network-Based Cooperative Trajectory Tracking Control for a Mobile Dual Flexible Manipulator.

For a mobile dual flexible manipulator (MDFM) system, this article focuses on the problem of cooperative trajectory tracking under unknown dynamics and time-varying trajectories. The dynamic model of the wheeled mobile manipulator system in 2-D space is established. Taking into account the unmodeled dynamics of the system, unknown terms of the system are approximated by integrating the radial basis function neural network (RBFNN) structure. By introducing the servo system, the cooperative trajectory tracking control (CTTC) strategy is designed, which realizes the system's cooperative operation, time-varying trajectory tracking, and vibration suppression. The performance of the proposed control scheme is verified through theoretical analysis and numerical simulations.

Flight and Vibration Control of Flexible Air-Breathing Hypersonic Vehicles Under Actuator Faults.

The issue of modeling and fault-tolerant control (FTC) design for a class of flexible air-breathing hypersonic vehicles (FAHVs) with actuator faults is investigated in this article. Different from previous research, the shear deformation of the fuselage is considered, and an ordinary differential equations-partial differential equations (ODEs-PDEs) coupled model is established for the FAHVs. A feedback control is proposed to ensure flight stable and an adaptive FTC method is designed to deal with actuator faults while suppressing the system's vibrations. Besides, the stability analysis of the closed-loop system is given via the Lyapunov direct method and an algorithm that transfers the bilinear matrix inequalities (BMIs) feasibility problem to the linear matrix inequalities (LMIs) feasibility problem is provided for determining the control gains. Finally, the numerical simulation results show that the proposed controller can stabilize the flight states and suppresses the vibration of the fuselage efficiently.

Iterative Learning Control for a Flapping Wing Micro Aerial Vehicle Under Distributed Disturbances.

This paper addresses a flexible micro aerial vehicle (MAV) under spatiotemporally varying disturbances, which is composed of a rigid body and two flexible wings. Based on Hamilton's principle, a distributed parameter system coupling in bending and twisting, is modeled. Two iterative learning control (ILC) schemes are designed to suppress the vibrations in bending and twisting, reject the distributed disturbances and regulate the displacement of the rigid body to track a prescribed constant trajectory. At the basis of composite energy function, the boundedness and the learning convergence are proved for the closed-loop MAV system. Simulation results are provided to illustrate the effectiveness of the proposed ILC laws.

Investigation of prevention of mother to child HIV transmission program from 2011 to 2017 in Suzhou, China.

The vertical transmission of HIV, from mother to child remains one of the biggest challenges all over the world. This study evaluated the implementation and effectiveness of the prevention of mother to child HIV transmission (PMTCT) program from 2011 to 2017 in Suzhou. A total of 107 HIV positive women were enrolled in the program, of which 11 were diagnosed through premarital examination, and 96 women were diagnosed through prenatal examination. Among the 96 pregnant women, 67 gave birth to 68 live neonates. Only one infant was diagnosed HIV infected because the HIV positive mother did not enter the PMTCT program until delivery. The HIV prevalence in Suzhou city showed a low-level tendency. To increase the prenatal health utility and antiretroviral medication compliance of the migrant population in Suzhou, there are improvements to make in order to achieve the 90-90-90 targets.

Parallel Control of Distributed Parameter Systems.

In this paper, we study the control problems of distributed parameter systems, and discuss the limitations of traditional control methods. In recent years, social factors have gradually become an essential parameter of system modeling. For complex distributed parameter systems, the accurate modeling becomes difficult. With the rapid development of the network and the technology of big data and cloud computing, based on the advanced control theory of large-scale computing, we introduce the idea of parallel control to the control of distributed parameter systems. Parallel control is a method to accomplish tasks through the interaction of virtual and actual. Its core is to model the complex distributed parameter system on artificial society or artificial system, then analyze and evaluate it by computational experiment, and finally control and manage the distributed parameter system by parallel execution. Data-driven control and computational control are used in this method, which is a control idea that adapts to the rapid development of society.

Serum homocysteine level and gestational diabetes mellitus: A meta-analysis.

AIMS/INTRODUCTION: Homocysteine levels during pregnancy in women with gestational diabetes mellitus (GDM) have been studied; however, it remains unclear whether hyperhomocysteinemia is a useful predictor of insulin resistance. The present study aimed to evaluate the relationship between homocysteine level and GDM. MATERIALS AND METHODS: PubMed, Elsevier, Web of Science and CNKI were searched for relevant studies published up to January 2015. Manual searches of references of the relevant original studies were carried out. Meta-analysis was used to assessed the relationship between homocysteine level and GDM using the stata 12.0 software. RESULTS: Homocysteine levels were significantly elevated in women with GDM compared with those without GDM (weighted mean difference 0.77, 95% confidence interval 0.44-1.10). This evidence was more consistent during the second trimester measurement of homocysteine (weighted mean difference 0.95, 95% confidence interval 0.67-1.23) and for women aged older than 30 years (weighted mean difference 0.90, 95% confidence interval 0.63-1.17). CONCLUSIONS: The present meta-analysis shows that homocysteine level is significantly elevated among women with GDM compared with women with normal glucose tolerance, and this finding persists more during the second trimester.