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Objective This study aims to explore the effect of exercise on obese female patients after laparoscopic sleeve gastrectom. Methods Sixteen obese women after weight loss were randomly divided into the exercise group (EG,n = 8) and the control group (CG,n = 8).The EG received aerobic combined resistance training for 4 weeks, 3 times a week (training every other day) for 70 minutes, while the CG did not participate in any exercise.The dietitian for each subject formulated the diet plan according to their postoperative diet management. Results The HC decreased more in the CG than in the EG, with a significant difference between the two groups (P

Background: bariatric surgery is one of the most popular weight-loss methods at present, which can significantly reduce the weight of obese patients and improve the complications. Through 4-week exercise intervention and routine postoperative management control, the changes of subjects' indexes were observed to provide reference for making scientific exercise plan.Methods: 17 subjects were randomly divided into two groups, EG (n=8) and CG (n=9). The exercise group received online exercise intervention for 4 weeks, 3 times a week, while the CG did not participate in exercise. The related indexes of EG and control group before and after exercise intervention were detected and analyzed.Results: The HC of the control group was better than that of the EG (P < 0.05). The improvement of WHR in EG is better than that in CG (P < 0.01). The decrease of TF in EG is better than that in CG (P < 0.05). The decrease of BMR was better than that of the CG (P < 0.05). The effect of lowering FBG in the CG is better than that in the EG (P < 0.01). EG improved HDL-C better than CG (P < 0.01).Conclusion: (1) the CG has a greater effect on reducing WC, and exercise has a more significant effect on reducing WHR and TF and BMR. (2) the CG has a greater effect on reducing FBG, but exercise can adjust the relative stability of FBG level. Exercise can improve HDL-C obviously.

A complex surface measurement is important for quality control and manufacturing processes. Articulated arm coordinate measuring machines (AACMMs) are widely used in measuring the complex surface. However, the AACMMs that are currently used always require manual operation, which reduces efficiency and introduces operator errors. This study presents a measuring device with a 6−DOF industrial robot holding a contact probe, which realizes the automation measurement of a complex surface and eliminates operator errors compared with the traditional measurement process of an AACMM. In order to explore the source of the measuring errors of the device, the influence of three measurement parameters (approaching velocity, contact angle, and measurement position) on the measurement error of the device is analyzed in this paper. A calibration ball measurement experiment is conducted for each parameter. The results show that the optimal approaching velocity of the measuring device is around 2 mm/s, the probe should be as perpendicular as possible to the surface being measured during the measurement, and the maximum measurement error at different positions is 0.1979 mm, with a maximum repeatability error of 0.0219 mm. This study will help improve the automation measuring errors of the AACMM by utilizing an industrial robot to hold the probe, pushing for a wider application of the AACMM.

Background Particular matter 2.5 (PM2.5) is one of the most important air pollutant, and it is positively associated with the development of chronic obstructive pulmonary disease (COPD). However, the precise underlying mechanisms through which PM2.5 promotes the development of COPD remains largely unknown. Methods Mouse alveolar destruction were determined by histological analysis of lung tissues and lung function test. Alveolar type II cells (AT2) to alveolar type I cells (AT1) transition in PM2.5-induced COPD mouse model was confirmed via immunofluorescence staining and qPCR analysis. The differentially expressed genes in PM2.5-induced COPD mouse model were identified by RNA-sequencing of alveolar epithelial organoids and generated by bioinformatics analysis. Results In this study, we found that 6 months exposure of PM2.5 induced a significantly decreased pulmonary compliance and resulted in pulmonary emphysema in mice. We showed that PM2.5 exposure significantly reduced the AT2 to AT1 cell transition in vitro and in vivo. In addition, we found a reduced expression of the intermediate AT2-AT1 cell process marker claudin 4 (CLDN4) at day 4 of differentiation in mouse alveolar organoids treated with PM2.5, suggesting that PM2.5 exposure inhibited AT2 cells from entering the transdifferentiation process. RNA-sequencing of mouse alveolar organoids showed that several key signaling pathways that involved in the AT2 to AT1 cell transition were significantly altered including the Wnt signaling, MAPK signaling and signaling pathways regulating pluripotency of stem cells following PM2.5 exposure. Conclusions In summary, these data demonstrate a critical role of AT2 to AT1 cell transition in PM2.5-induced COPD mouse model and reveal the signaling pathways that potentially regulate AT2 to AT1 cell transition during this process. Our findings therefore advance the current knowledge of PM2.5-induced COPD and may lead to a novel therapeutic strategy to treat this disease.

This paper studies the problem of finite-time H ∞ control for switched nonlinear systems (SNSs), where the powers of chained integrators associated with individual subsystems can be different posit...

In this paper, the adaptive stabilization issue for a class of state-constrained high-order switched nonlinear systems is concerned, where all subsystems are allowed to be unstabilizable. A novel adaptive control scheme is established by exploiting the effective coupling of the technique of adding a power integrator and the method of multiple barrier Lyapunov functions. Explicitly, a group of adaptive controllers and a proper switching law are designed to asymptotically regulate the states of the resulting closed-loop system in a domain and meanwhile guarantee that the violation of the constraints does not happen. Contrary to a common update law constructed for all subsystems in the literature, different update laws for individual subsystems are designed separately to reduce the conservativeness. Moreover, at the switching instants, the connection of two adjacent barrier Lyapunov functions is not be required and even a certain amount of grow is also allowed. Finally, a simulation example is performed to further illustrate the effectiveness of the provided control strategy. (C) 2018 Elsevier Ltd. All rights reserved. National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61773098, 61773100]; 111 Project, ChinaMinistry of Education, China - 111 Project [B16009] This work was supported by the National Natural Science Foundation of China under Grants 61773098 and 61773100 and the 111 Project, China (B16009).

In this paper, we study stability and L 1 -gain problems for switched positive systems, in which stability for any subsystems do not necessarily requirement. First, the sufficient condition for exponential stability is established. By exploiting the multiple linear co-positive Lyapunov function method, stabilization and L 1 -gain conditions of switched positive systems are proposed. To reduce the switching frequency, a mixed switching strategy is proposed, which is different from traditional state-dependent or time-dependent switching. Then, a set of state-feedback controllers and a mixed switching strategy are dual developed to stabilize the system, and the corresponding linear vector inequalities are examined in terms of linear programming. Furthermore, L 1 -gain is studied as well. Finally, a numerical example is provided to show the validity of the proposed techniques.

This paper addresses the issue of robust stabilisation for a class of state-constrained high-order switched nonlinear systems whose subsystems are allowed to be all unstabilizable. A novel ...

This paper addresses the passivity-based mean square exponential stabilization problem for switched stochastic nonlinear systems. A concept of generalized small-time normobservability is presented and an appropriate test condition is also provided. For pre-given passivity rate and average dwell time, a set of feedback controllers is designed by use of the passivity property. Then, combining with generalized small-time norm-observability, a sufficient condition to guarantee mean square exponential stabilization of a switched stochastic nonlinear system is given. As a special case, the switched stochastic linear system is also discussed. Finally, a numeral example shows the effectiveness of the proposed method.

A framework of regional passivity theory for switched systems is set up using multiple barrier storage functions. The "energy" stored in each subsystem is described by the corresponding individual barrier storage function which is only well defined on an open region associated with regional passivity. The key feature is that the "energy" grows to infinity when the trajectory tends to the region boundary. Firstly, a sufficient condition guaranteeing regional passivity for a switched system is derived under the designed switching law, where all subsystems are not assumed to be regionally passive. Secondly, asymptotic stability can be reached if a switched system is strictly regionally passive or regionally passive plus asymptotic detectability, and meanwhile the system trajectory remains in the corresponding open region. Thirdly, regional passivity is also shown to be preserved under feedback interconnection. Finally, as an application of the theory provided, the stabilization problem for state-constrained strict-feedback switched nonlinear systems is solved, where no subsystem is required to be stabilizable.

In this paper, the passivity-based stabilization problem of a strict-feedback nonlinear system under a proper state-dependent switching law is investigated. Here, the feedback passification problem of each subsystem does not need to be solvable. First, by using the recursive backstepping technique, a sufficient condition under which the closed-loop switched system with designed state feedback controllers is strictly passive from the new input to a designed virtual output is given under a state-dependent switching law. Moreover, the asymptotical stability property of the switched system is achieved by redesigning the introduced new input based on passivity. Finally, a numeral example shows the effectiveness of the proposed method.

In 2002, China began to inspire restructuring of the electric power sector to improve its performance. Especially, with the rapid increase of electricity demand in China, there is a need for non-utility generation investment that cannot be met by government finance alone. However, a first prerequisite is that regulators and decision-makers (DMs) should carefully consider how to balance the need to attract private investment against the policy objectives of minimizing monopoly power and fostering competitive markets. So in the interim term of electricity market, a decentralized decision-making process should eventually replace the centralized generation capacity expansion planning. In this paper, firstly, on the basis of the current situation, a model for evaluating generation projects by comprehensive utilization of fuzzy appraisal and analytic hierarchy process (AHP) is developed. Secondly, a case study of generation project evaluation in China is presented to illustrate the effectiveness of the model in selecting optimal generation projects and attracting private investors. In the case study, with considerations of attracting adequate private investment and promoting energy conservation in China, five most promising policy instruments selected as evaluation factors include project duration, project costs, predicted on-grid price level, environmental protection, enterprise credit grading and performance. Finally, a comprehensive framework that enables the DM to have better concentration and to make more sound decisions by combining the model proposed with modern computer science is designed.

A delayed Lotka-Volterra predator-prey system with time delayed feedback is studied by using the theory of functional differential equation and Hassard’s method. By choosing appropriate control parameter, we investigate the existence of Hopf bifurcation. An explicit algorithm is given to determine the directions and stabilities of the bifurcating periodic solutions. We find that these control laws can be applied to control Hopf bifurcation and chaotic attractor. Finally, some numerical simulations are given to illustrate the effectiveness of the results found.

In this paper the penalty term and momentum term are used in batch gradient method which improve the learning method for one-dimensional gray neural network model (GNNM(1,1)). Moreover, the convergence of the modified batch gradient method for GNNM(1,1) is proved.

Gray neural network GNNM(1,1) is a coupled model of gray system and neural network. In this note, the convergence of a batch gradient learning method for GNNM(1,1) is proved, and supporting numerical experiments are provided.