Acupoint catgut embedding (ACE) was applied widely to antiweight in China. The aim of this review is to estimate the effectiveness and safety of ACE on obesity. A literature search was conducted in PubMed, Cochrane Library, EBASE, CNKI, and so forth, using combination subject terms of obesity (or overweight, weight loss, etc.) and acupoint catgut embedding (or catgut implantation, catgut embedding). Improvement rate, reduction of body weight and body mass index (BMI), and so forth were analyzed. 43 studies were included for systematic review and meta-analysis. Although with poor methodological quality, ACE was superior to manual acupuncture (MA), sham, and cupping in improvement rate and presented a better tendency (OR > 1) compared with drugs and electroacupuncture (EA). Mean values of weight loss by ACE were 1.14 kg, 1.26 kg, 1.79 kg, and 3.01 kg comparing with MA, drugs, EA, and sham, respectively. Mean of BMI reduced to 0.56 kg/m2, 0.83 kg/m2, 0.79 kg/m2, and 1.63 kg/m2 comparing with MA, drugs, EA, and sham. Less adverse effects were reported. Pooled outcomes presented a tendency of equal or superior effects to other interventions and fewer side effects. Future high quality trials with rigorous design and positive FDA approved drug as control are urgent to assess the effect of ACE for obesity. PROSPERO registration number is as follows: CRD42015016006.

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The existence of antibiotics in the environment can trigger a number of issues by fostering the widespread development of antimicrobial resistance. Currently, the most popular techniques for removing antibiotic pollutants from water include physical adsorption, flocculation, and chemical oxidation, however, these processes usually leave a significant quantity of chemical reagents and polymer electrolytes in the water, which can lead to difficulty post-treating unmanageable deposits. Furthermore, though cost-effectiveness, efficiency, reaction conditions, and nontoxicity during the degradation of antibiotics are hurdles to overcome, a variety of photocatalysts can be used to degrade pollutant residuals, allowing for a number of potential solutions to these issues. Thus, the urgent need for effective and rapid processes for photocatalytic degradation leads to an increased interest in finding more sustainable catalysts for antibiotic degradation. In this review, we provide an overview of the removal of pharmaceutical antibiotics through photocatalysis, and detail recent progress using different nanostructure-based photocatalysts. We also review the possible sources of antibiotic pollutants released through the ecological chain and the consequences and damages caused by antibiotics in wastewater on the environment and human health. The fundamental dynamic processes of nanomaterials and the degradation mechanisms of antibiotics are then discussed, and recent studies regarding different photocatalytic materials for the degradation of some typical and commonly used antibiotics are comprehensively summarized. Finally, major challenges and future opportunities for the photocatalytic degradation of commonly used antibiotics are highlighted.

In airborne MEMS SINS transfer alignment, the error of MEMS IMU is highly environment-dependent and the parameters of the system model are also uncertain, which may lead to large error and bad convergence of the Kalman filter. In order to solve this problem, an improved adaptive incremental Kalman filter (AIKF) algorithm is proposed. First, the model of SINS transfer alignment is defined based on the “Velocity and Attitude” matching method. Then the detailed algorithm progress of AIKF and its recurrence formulas are presented. The performance and calculation amount of AKF and AIKF are also compared. Finally, a simulation test is designed to verify the accuracy and the rapidity of the AIKF algorithm by comparing it with KF and AKF. The results show that the AIKF algorithm has better estimation accuracy and shorter convergence time, especially for the bias of the gyroscope and the accelerometer, which can meet the accuracy and rapidity requirement of transfer alignment.

Aiming at the problem that the strapdown imaging seeker cannot measure line-of-sight (LOS) rate directly, this paper presents an effective algorithm for LOS rate estimation. To address the problem, the reference frames and angles are defined. According to the relative kinematics and attitude relationship between missile and target, the nonlinear state equations and measurement equations of LOS rate are derived, and the estimation algorithm based on unscented Kalman filter (UKF) is proposed. Considering the estimation accuracy mainly depends on body LOS (BLOS) angle accuracy and gyro accuracy, the paper is unprecedented to research how these two factors impact the LOS angle and rate accuracy by simulation. Semiphysical simulation experiment verifies the correctness and accuracy of the algorithm, and the result shows that the estimation algorithm can meet the accuracy and real-time requirements of guidance system simultaneously. Thus LOS rate estimation algorithm based on UKF provides a theoretical basis for engineering applications of strapdown imaging seeker.