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Objective To evaluate the effect and safety of acupuncture for the treatment of irritable bowel syndrome (IBS) through comparisons with those of polyethylene glycol (PEG) 4000 and pinaverium bromide. Patients and Methods This multicenter randomized controlled trial was conducted at 7 hospitals in China and enrolled participants who met the Rome III diagnostic criteria for IBS between May 3, 2015, and June 29, 2018. Participants were first stratified into constipation-predominant or diarrhea-predominant IBS group. Participants in each group were randomly assigned in a 2:1 ratio to receive acupuncture (18 sessions) or PEG 4000 (20 g/d, for IBS-C)/pinaverium bromide (150 mg/d, for IBS-D) over a 6-week period, followed by a 12-week follow-up. The primary outcome was change in total IBS-Symptom Severity Score from baseline to week 6. Results Of 531 patients with IBS who were randomized, 519 (344 in the acupuncture group and 175 in the PEG 4000/ pinaverium bromide group) were included in the full analysis set. From baseline to 6 weeks, the total IBS-Symptom Severity Score decreased by 123.51 (95% CI, 116.61 to 130.42) in the acupuncture group and 94.73 (95% CI, 85.03 to 104.43) in the PEG 4000/pinaverium bromide group. The between-group difference was 28.78 (95% CI, 16.84 to 40.72; P Conclusion Acupuncture may be more effective than PEG 4000 or pinaverium bromide for the treatment of IBS, with effects lasting up to 12 weeks. Trial Registration Chinese Clinical Trials Register, ChiCTR-IOR-15006259.

The slope of the west working side of the south mining area of the open-pit coal mine where a landslide has occurred is taken as the research object. The paper selects Mohr-Coulomb elastoplastic model to analyze the slope stability of the western working side of the southern mining area of the open-pit coal mine by Finite Element Method. The numerical simulation results show that the rear edge of the sliding slope area is still in an unstable state and the front landslide mass is still in a creep state, and the local step plastic zone of the slope body is penetrated. On the basis of this, slope safeguard measures of slope cutting, backfilling and Drainage engineering to protect the slope stability are put forward. The research results provide a theoretical basis for the treatment of deformation and failure of similar slopes.

In this study, we aimed to investigate the changes of lymphocyte subsets (CD3+, CD4+, CD8+) and inflammatory factors (interleukin‐6 [IL‐6], hypersensitive C‐reactive protein [HS‐CRP], and procalcitonin [PCT]) of alveolar lavage fluid in patients with severe corona virus‐2019 (COVID‐19) pneumonia and their clinical impact on the assessment of disease severity and prognosis. Twenty‐four patients with severe COVID‐19 pneumonia were admitted to the intensive care unit (ICU) of the Ezhou Central Hospital from February 1 to March 22, 2020. According to the 28‐day prognosis, they were assigned to a death group and a survival group. On the 3rd day of ICU admission, peripheral blood and alveolar lavage fluid were collected for examination of lymphocyte subsets and inflammatory factors by flow cytometry and immunoturbidimetry, respectively. The CD3+, CD4+, and CD8+ cell counts in alveolar lavage fluid and serum were significantly higher in the survival group than those of the death group (p

This paper presents a novel three-dimensional active frequency selective surfaces loading a varactor diode to achieve electrically controllable, by loading different values of paranoid voltage to control the variable capacitance diode. Simulation results show that the structure has excellent resonant characteristics in the range of 3.34GHz-1.59GHz, and has certain sensitivity for the change of the capacitance value,so it can achieve electrical controllable in the frequency band. The simulation results also show that this structure can satisfy characteristics for multiple perspectives in the whole plane, and be suitable to reduce radar cross section,when it is used on radomeofweapon systems in practical war.

In this paper, the modal analysis was carried out on the core and cavity of a 160KVA dry-type transformer based on the finite element analysis software of ANSYS. And the simulation results of the natural frequencies and modal shapes were obtained, which provided a theoretical guidance to the design of the transformer structure, and were meaningful to reduce the vibration and noise level of the transformer.

DC bias would cause the half-wave saturation of transformer, distortion of the exaction current, generation of high harmonic and the vibration and noise increases rapidly, which harm the safe operation of the transformers. In this paper, simulation of magnetic vibration and noise of a 160KVA dry-type transformer with DC bias and modal analysis with the finite element software comsol multiphysics is obtained. The software conduct multi-physical field coupling analysis to electric field, magnetic field, structural stress field and acoustic field, calculate the distribution of the noise and the natural frequency of transformer and propose effective measures to reduce the noise and vibration of transformer with DC bias.

The paper proposed a new reinforcement technique-planting steel technique. By numerical simulation analysis of planting steel, the load – slip curve, the load – stress curve and others were obtained. Meanwhile, ultimate bearing capacity of angle was calculated, and the ultimate bearing capacities with the same model at different anchorage depths were compared. With the anchorage depth increased, the ultimate bearing capacity increased too. But while the anchorage depth increased to a certain value, the ultimate bearing capacity no longer increased. All these provided a theoretical basis for the engineering application of planting steel technique.

In this paper, a new design of microstrippatch antenna based on grid structure in the Ka-band is proposed which can realize optical and microwave coaxial detection. Both the patch and ground boardis designed into dense grids, at the same time, using the transparent glass as the medium plate. As is shownin the simulation results, in this concerned wave band, compared with ordinary microstrip patch antenna, furthermore, the antenna designedachieve a good antenna radiation characteristics, while realize the barrier-free transmission of light, make the light transmission rate over 90% which achieve the goal of optical and microwave coaxial detection.

Measurement accuracy of moisture is influenced by conventional linear regression mainly using microwave resonator. Based on improved BP arithmetic, a regression is presented to calibrate the measurement results. First, GA is used to pre-optimize the regressive neural network for its global search ability, parallel processing and strong robust. Then the gradient descent method of BP arithmetic is integrated to avoid getting into infinitesimal locally effectively and keep the merits of high prediction precision and rapid convergence. The experiment shows there is a great improvement between the predicted value and the real one.

TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. The technique presented has merits in little prior knowledge, rapid convergence and concise fuzzy model. Example of function approximation shows the technique's validity.

BP algorithm has been widely used in calibrating measurement results detected by microwave resonator for improvement of accuracy. Conventional BP algorithm tends to get into infinitesimal locally, which worsens the stability of the measurement accuracy. An evolutionary neural network model based on IA-BP optimal algorithm is proposed in this paper. In the model, IA algorithm is first used for global search and then BP algorithm for local search. Experiments indicated that the IA-BP optimal algorithm effectively avoid getting into infinitesimal locally and has the merits of high prediction precision, rapid convergence, global superiority and accuracy for optimization, which improves the measurement accuracy with the mean squared error 0.0125, the mean absolute error 0.0715, the mean relative error 0.1186 and the certain coefficient 0.9965 between the predicted moisture content and the real value.

This work aims at predicting the secondary structure of proteins, which is a complex nonlinear-mode classified problem. It proposes an algorithm which synchronises Bayesian network and hidden Markov model. It refers more neighbouring information of amino acid residue sequences for predicting secondary structure of the protein. Moreover it discusses data selection, network parameter determination and network performance in searching an algorithm of predicting protein secondary structure. The experimental results show feasibility and validity of the algorithm.

This paper analyzes the Bayesian model that is used to predict secondary structure of proteins, introduces an artificial neural networks based on this model, and then give out an improved new artificial neural network model. The author's motivation is to refer more neighboring information of amino acid residue sequences so that higher accuracy can be obtained for predicting secondary structure of the protein. We discuss data selection, network parameter determination and network performance in researching algorithm of prediction protein secondary structure. The experimental results show that the model can well cope with the problem of predicting secondary structure of proteins.

The linear regression that founds the function between the moisture content and the detecting parameters brings significant errors which can be reduced by BP algorithm. There is one fatal disadvantage that conventional BP algorithm tends to get into infinitesimal locally, which worsens the stability of the measurement precision. An evolutionary neural network model based on optimal IA-BP algorithm is presented in this paper. In the model, IA algorithm is first used for global search and then BP algorithm for local search. The optimal IA-BP algorithm has the merits of high prediction precision, rapid convergence, global superiority and accuracy for optimization compared with conventional BP algorithm. Experiments shows the remarkable improvements in the measurement with the mean squared error 0.0125, the mean absolute error 0.0715, the mean relative error 0.1186 and the certain coefficient 0.9965 between the predicted moisture content and the real value.