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In this article, model predictive (MP) and deep belief net (DBN) are introduced to optimize and predict the dq -axis stator voltage of asynchronous motors for electric cars in the field-weakening region to achieve the optimal “speed–torque” (represents the optimization of speed and torque performance) control. First, the analytical model of the maximum torque output is established, and the effect of dq -axis voltage on the torque output is analyzed. Second, to reduce the influence of proportional–integral parameter tuning, optimize the dq -axis voltage, and achieve the accurate torque control, MP is introduced to establish an analytical model of MP controller tracking current loop for generating the dq -axis voltage. Third, the maximum torque vector control system based on the MP controller is built, and the influence of system parameters on control effect is analyzed. Fourth, the simulation data are collected, and the DBN voltage prediction model is established. The model is embedded in the field-oriented control to achieve optimal “speed–torque” control. Finally, the dynamometer experimental platform is established to collect the experimental data and establish the DBN voltage prediction model. The validity of the method is verified through the voltage data calibration, “speed–torque” characteristic calibration, motor efficiency calibration, “speed–torque” response, and ripple test.

This study focused on the mental health of people living with HIV(PLWHIV) and explored their relationship between loneliness and perceived social support, health related quality of life (HRQoL) with a method of structural equation model. We collected clinical and psychological data from consecutively enrolled PLWHIV. A total of 201 PLWHIVs were enrolled and measured with self-reporting survey instruments of UCLA Loneliness Scale, Self-Rating Depression Scale, Self-Rating Anxiety Scale, Social Support Ratio Scale and Short Form Health Survey-36. The levels of loneliness, depression, anxiety, perceived social support and HRQoL were assessed. PLWHIV enrolled were divided into two groups of loneliness and non-loneliness based on their UCLA Loneliness Scale scores. Multivariable analysis indicated that being married is a protective factor associated with loneliness (OR = 0.226; P = 0.032). We further found the loneliness group had a higher level of depression (P < 0.001) and anxiety (P < 0.001), but lower level of HRQoL (P < 0.001) than the non-loneliness group. We found there was a positive linear correlation between social support and HRQoL among the enrolled PLWHIVs (r2 = 0.0592; P = 0.0005). A structural equation model (SEM) was established to evaluate whether the loneliness played as a mediation role between social support and HRQoL. The model showed loneliness as a mediation from social support leading to a decrease of HRQoL. Our findings showed a potential psychological pathway from social support to HRQoL, suggesting the need for interventions focusing on social support may improve poor HRQoL lead by loneliness.

Supplemental material, sj-doc-1-taj-10.1177_20406223221102750 for A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy by Zhe Qian, Houji Wu, Yihua Wu, Wei Liao, Tao Yu, Xuwen Xu, Jie Peng and Shaohang Cai in Therapeutic Advances in Chronic Disease

The deterioration of environment, the aggravation of energy crisis and the exhaustion of non renewable energy promote the development of green new energy. Among them, wind power generation has become a research hotspot in the field of new energy at home and abroad. In this paper, the deflection double stator switched reluctance generator (DDSSRG) is taken as the research object, the basic modelling and analysis of DDSSRG are carried out, and the magnetic field of the generator is analyzed by using the finite element software. The structure of the generator is optimized by using the central composite design method (CCD). Finally, the experimental platform of the generator is built to verify the feasibility of the theory in structure.

To investigate the relation of blood arsenic concentration (BAC) with clinical effect and safety of arsenic-containing Qinghuang Powder (青黄散, QHP) in patients with myelodysplastic syndrome (MDS). Totally 163 patients with MDS were orally treated with QHP for 2 courses of treatment, 3 months as 1 course. The BACs of patients were detected by atomic fluorescence spectrophotometry at 1, 3, and 6 months during the treatment, and the effective rate, hematological improvement and safety in patients after treatment with QHP were analyzed. After 2 courses of treatment, the total effective rate was 89.6% (146/163), with 31.3% (51/163) of hematological improvement and 58.3% (95/163) of stable disease. The hemoglobin increased from 73.48 ± 19.30 g/L to 80.39 ± 26.56 g/L (P 0.05). Among 46 patients previously depended on blood transfusion, 28.3% (13/46) completely got rid of blood transfusion and 21.7% (10/46) reduced the volume of blood transfusion by more than 50% after treatment. The BACs were significantly increased in patients treated for 1 month with 32.17 ± 18.04 μ g/L (P 0.05). The adverse reactions of digestive tract during the treatment were mild abdominal pain and diarrhea in 14 cases (8.6%), and no patients discontinued the treatment. The BACs of patients with gastrointestinal adverse reactions were significantly lower than those without gastrointestinal adverse reactions (22.39 ± 10.38 vs. 37.89 ± 11.84, μ g/L, P

Objective. To establish the clinical safe and effective methods of arsenic-containing compound-Qinghuang Powder (compound-QHP) in the treatment of myelodysplastic syndrome (MDS). Methods. 200 patients with MDS were treated with compound-QHP (daily dose of 0.1 g realgar). The blood arsenic concentrations (BACs) were detected by atomic fluorescence spectrophotometry (HF-AFS). After treatment for 1 month, the patients were randomly divided into group A and group B when the BACs were less than 20 μg/L. Daily dose of realgar was maintained in group A and it was increased to that when the BACs were more than 20 μg/L in group B. The BAC and clinical efficacy and safety in two groups were compared at the end of the treatment with compound-QHP. Results. The average BAC of group B was significantly higher than that of group A (P<0.01). The rates of hematology improvement and reduced transfusion were significantly higher in group B than in group A (P<0.05). The HGB, ANC, and PLT significantly increased in group B after treatment (P>0.05). Conclusions. Monitoring the BAC and adjusting the daily dose of realgar to increase the effective BAC and then improving efficacy without increasing the clinical toxicity are the clinical safe and effective methods in the treatment of MDS.

Jiao-Tai-Wan (JTW), has been usually used for insomnia in traditional Chinese medicine (TCM). The previous study shown that JTW was benefit for depression-like behavior, but the possible mechanism is not clear. This study is to determine whether JTW was benefit for the treatment of lipopolysaccharide (LPS)-induced depression-like behavior in mice and explore its possible mechanism. All drugs were intragastrically administered once daily for 7 consecutive days. On the 7th day, LPS was injected into mice 30 min after drug administration. Behavioral tests were performed 24 h after LPS administration. Serum levels of interleukin (IL)-6 and tumor necrosis factor (TNF)-α were measured by enzyme-linked immunosorbent assay (ELISA). The 5-hydroxytryptamine (5-HT) and nor-epinephrine (NE) levels in prefrontal cortex were determined by UPLC-MS. The protein expressions of NF-κB signaling in prefrontal cortex were determined by western blot. Behavioral tests were measured via tail suspension test (TST), forced swimming test (FST), sucrose preference test (SPT) and open field test (OFT). In addition, effects of JTW on the TNF-α induced depressive-like behavior were also examined. Pretreatment with JTW (4.2 and 8.4 g/kg) or fluoxetine (20 mg/kg) effectively attenuated LPS-induced upregulations of the serum TNF-α and IL-6 contents and JTW (4.2 and 8.4 g/kg) or fluoxetine (20 mg/kg) effectively increased the contents of 5-HT and NE compared with LPS-treated group. Meanwhile, the western blot analysis results indicated the correlation between the antidepressant activity of JTW and the regulation of NF-κB signaling in brain. Besides, JTW (4.2 and 8.4 g/kg) or fluoxetine (20 mg/kg) significantly shortened LPS-induced increases in immobility time of TST, FST and weakened the reduction of the sucrose preference in SPT without significant alterations of locomotor activity in OFT. Additionally, JTW effectively reversed the depressive-like behavior induced by TNF-α (0.1 fg/site, i.c.v.). Our findings indicated that Jiao-Tai-Wan (JTW) played an important role in monoaminergic response and anti-inflammation in lipopolysaccharide (LPS)-induced mouse model, which may be therapeutically exploited to alleviate depression-like behavior.

Table S2. Primer sequences used in the study. (DOCX 18 kb)

Table S1. siRNAs sequences. (DOCX 15 kb)

GPR is a useful tool in non-destructive evaluation area. Time delay curve detection and target depth estimation are two key steps in GPR data processing procedure, as they can provide accurate target depth information, especially in multi-layer medium detection scenario. Traditional methods for time-delay curve are applicable to homogeneous medium and ideal environments. This paper presents a new time-delay curve extracting approximation hyperbola algorithm (TDC-AH) and target depth algorithm. By applying auto-detecting edge points criterion in detection scenario, an approximation hyperbola equation can be established and target depth can be estimated subsequently. Simulating experiment proves the proposed algorithm is suitable for multi-layer medium.

A new RF(radio frequency) stealth performance evaluation method of electronic equipment based on polarization status changing parameter is presented. By analyzing typical intercept receiving mechanism in electronic war, a key factor- the uncertainty of radiating signals of electronic equipment is extracted from “radiating-intercepting” scenario. A calculating formula is established to transfer this kind of uncertainty to RF stealth factor. This RF stealth factor can be used to evaluate electronic equipments RF stealth performance directly, without relying on traditional complex “radiating-intercepting” scenario. Simulation results show the effectiveness of this evaluation method.

Under ambient conditions, we directly observed NaCl crystals experimentally in the rGO membranes soaked in the salt solution with concentration below and far below the saturated concentration. Moreover, in most probability, the NaCl crystals show stoichiometries behavior. We attribute this unexpected crystallization to the cation-{\pi} interactions between the ions and the aromatic rings of the rGO., Comment: 5pages, 2 figures

Induction heating possesses wide application in surface hardening for steels. In recent years, the emergence of metal powder bonded magnetic flux concentrator (MPB-MFC) enables induction heating better capability, efficiency, and controllability, therefore the analytical understanding through modeling and simulation becomes necessary for process design and optimization. In this paper, the mechanism of the energy transformation in induction heating with magnetic flux concentrator is carried out. The MPB-MFC assisted induction heating for AISI 1045 steel is studied by comparing the finite element simulation with experimental results. The finite element model solves the coupled electro-magnetic-thermal computation problem, which also involves the consideration of the non-linear material magnetic properties in the process. To verify the simulation, middle-frequency induction heating experiments are conducted to compare with the simulated results. The comparison proves the efficacy of the FEM model, and discloses the inner-correlation of the thermal-magnetic-electric fields in the process.

Because they may provide ultrathin, high-flux, and energy-efficient membranes for precise ionic and molecular sieving in aqueous solution, GO membranes (partially oxidized, stacked sheets of graphene) have shown great potential in water desalination and purification, gas and ion separation, biosensors, proton conductors, lithium-based batteries and super-capacitors. Unlike carbon nanotube (CNT) membranes, in which the nanotube pores have fixed sizes, the pores of GO membranes - the interlayer spacing between GO sheets - are of variable size. This presents a challenge for using GO membranes for filtration. Despite the great efforts to tune and fix the interlayer spacing, it remains difficult both to reduce the interlayer spacing sufficiently to exclude small ions while keeping this separation constant against the tendency of GO membranes to swell when immersed in aqueous solution, which greatly affects the applications of GO membranes. Here, we demonstrate experimentally that highly efficient and selective ion rejection by GO membranes can be readily achieved by controlling the interlayer spacing of GO membranes using cations (K+, Na+, Ca2+, Li+ and Mg2+) themselves. The interspacing can be controlled with precision as small as 1 A, and GO membranes controlled by one kind of cation can exclude other cations with a larger hydrated volume, which can only be accommodated with a larger interlayer spacing. First-principles calculations reveal that the strong noncovalent cation-pi interactions between hydrated cations in solution and aromatic ring structures in GO are the cause of this unexpected behavior. These findings open up new avenues for using GO membranes for water desalination and purification, lithium-based batteries and super-capacitors, molecular sieves for separating ions or molecules, and many other applications., 11 pages, 4 figures

Based on electromagnetic and temperature field models of nonlinear ferromagnetic materials, this paper conducts a finite element analysis of the induction heating process of PC steel bar, thus obtaining the change curves of temperature, active power, heating efficiency and power density. The main factors and mechanisms affecting the heating efficiency and the temperature uniformity are analyzed systematically by a combination of the simulation result and the experimental fact. This work is expected to contribute significantly for optimizing the key parameters of induction heating production of PC steel bar.

Sitting posture is the position in which one holds his/her body upright against gravity while sitting. Poor sitting posture is regarded as an aggravating factor for various diseases. In this paper, we present an inverse piezoresistive nanocomposite sensor, and related deciphering neural network, as a new tool to identify human sitting postures accurately. As a low power consumption device, the proposed tool has simple structure, and is easy to use. The strain gauge is attached to the back of the user to acquire sitting data. A three-layer BP neural network is employed to distinguish normal sitting posture, slight hunchback and severe hunchback according to the acquired data. Experimental results show that our method is both realizable and effective, achieving 98.75% posture identification accuracy. This successful application of inverse piezoresistive nanocomposite sensors reveals that the method could potentially be used for monitoring of diverse physiological parameters in the future.