Search

The efficacy of vitamin D supplementation in patients with systemic lupus erythematosus (SLE) remains uncertain. This meta-analysis aimed to systematically evaluate the efficacy and safety of vitamin D supplementation in patients with SLE.Randomized controlled trials (RCTs) were searched in PubMed, Embase, Cochrane CENTRAL and Web of Science databases. The retrieved studies were subjected to meta-analysis using the fixed-effect or random-effect model.Five eligible RCTs enrolling 490 participants were included. Compared to the placebo treatment, vitamin D supplementation significantly increased the level of serum 25-hydroxyvitamin D (25(OH)D) (5 trials, 490 participants: standard mean difference (SMD) = 2.072, 95% CI: 1.078-3.066, P0.001). The pooled result from 2 RCTs showed that vitamin D supplementation decreased the fatigue severity scale scores in patients with SLE (2 trials, 79 participants: SMD = -1.179, 95% CI: -1.897 to -0.460, P = 0.001). The SLE disease activity index scores and positivity of anti-double-stranded DNA antibodies (anti-dsDNA) did not differ significantly (4 trials, 223 participants: SMD = -0.507, 95% CI: -1.055-0.041, P = 0.070; 3 trials, 361 participants: Risk ratio = 0.880, 95% CI: 0.734-1.054, P = 0.165) between the vitamin D supplementation group and the placebo treatment group. None of the included studies reported severe adverse events associated with vitamin D supplementation.This meta-analysis suggested that vitamin D supplementation is effective in increasing the serum 25(OH)D levels, may improve fatigue, and is well-tolerated in patients with SLE, however, it does not seem to have significant effects in decreasing the positivity of anti-dsDNA and disease activity.

This paper presents a hierarchical framework to solve the multi-robot temporal task planning problem. We assume that each robot has its individual task specification and the robots have to jointly satisfy a global collaborative task specification, both described in linear temporal logic. Specifically, a central server firstly extracts and decomposes a collaborative task sequence from the automaton corresponding to the collaborative task specification, and allocates the subtasks in the sequence to robots. The robots can then synthesize their initial execution strategies based on locally constructed product automatons, combining the assigned collaborative tasks and their individual task specifications. Furthermore, we propose a distributed execution strategy adjusting mechanism to iteratively improve the time efficiency, by reducing wait time in collaborations caused by potential synchronization constraints. We prove the completeness of the proposed framework under assumptions, and analyze its time complexity and optimality. Extensive simulation results verify the scalability and optimization efficiency of the proposed method., 14 pages, 6 figures. arXiv admin note: text overlap with arXiv:2108.11597

This paper investigates the distributed localization problem of sensor networks with mixed measurements. Each node holds a local coordinate system without a common orientation and is capable of measuring only one type of information (either distance, bearing, or relative position) to near-by nodes. Thus, three types of measurements are mixed in the sensor networks. Moreover, the communication topologies in the sensor networks may be time-varying due to unreliable communications. This paper develops a fully distributed algorithm called BCDL (Barycentric Coordinate based Distributed Localization) where each node starts from a random initial guess about its true coordinate and converges to the true coordinate via only local node interactions. The key idea in BCDL is to establish a unified linear equation constraints for the sensor coordinates by using the barycentric coordinates of each node with respect to its neighbors though the sensor nodes may have different types of measurements. Then a distributed iterative algorithm is proposed to solve the linear equations under time-varying communication networks. A necessary and sufficient graphical condition is obtained to ensure global convergence of the distributed algorithm.

This paper investigates the aggregated control problem of a large number of residential responsive loads for various demand response applications. A unified hybrid system model is proposed, capturing the dynamics of both TCLs (Thermostatically Controlled Loads) such as HVACs (Heating, Ventilating and Air Conditioning) and water heaters, and deferrable loads such as washers, dryers, and PHEVs (Plug-in Hybrid Electric Vehicle). Based on the unified hybrid system model, we formulate the aggregated control problem as an optimal control problem, which seeks for an optimal energy usage plan for a population of heterogeneous loads. We then propose a game-theoretic approach to develop a decentralized aggregated control algorithm. Convergence of the proposed algorithm is shown by employing potential game theory. The hybrid system modeling framework and the proposed decentralized aggregated control algorithm are validated through several realistic demand response simulations using GridLAB-D. The simulation results demonstrate that the aggregated power response can accurately track a reference trajectory, effectively reduce the peak power consumption, and efficiently save electricity cost.

This paper investigates the distributed circumnavigation problem by an autonomous underwater vehicle (AUV) team to enclose a target. When the AUVs do not have a global coordinate system or a common reference direction, moreover when some vehicles cannot detect the target, this circumnavigation problem becomes challenging. The above situation is common in underwater environments and is taken into account in this paper. Considering the kinematic and dynamic models of vehicles, this paper proposes a cascade-based distributed control law. The proposed control law via local relative position measurement can realize a desired circumnavigation formation around the target. Furthermore, we show that with a radius determinant mechanism, this control law enables the vehicles which do not detect the target to keep a specified pattern without exchanging the target position information. Finally, simulations are provided to illustrate the result.

Background The COVID-19 pandemic is putting healthcare workers across the world in an unprecedented situation. The purpose of this study was to evaluate the levels of depression, anxiety, and stress among Hubei pediatric nurses during the COVID-19 pandemic and to analyze the potential factors associated with them. Materials and methods A self-designed online questionnaire survey, which consisted of the demographic and selected features, the occupational protection knowledge, attitudes, and practices of COVID-19, and the Chinese version of Depression, Anxiety, and Stress Scale, were used to assess the levels of depression, anxiety, and stress among Hubei pediatric nurses during COVID-19 pandemic. The logistic regression analyses were performed to analyze the potential factors associated with depression, anxiety, and stress. Results A total of 617 pediatric nurses were included in the survey. A considerable proportion of pediatric nurses reported symptoms of depression (95 [15.4%]), anxiety (201 [32.6%]), and stress (111 [18.0%]). Results of multivariable logistic regression analyses indicated that the good occupational protection practices (for depression: OR = 0.455, 95%CI: 0.281 to 0.739; for anxiety: OR = 0.597, 95%CI: 0.419 to 0.851; for stress: OR = 0.269, 95%CI: 0.166 to 0.438) and the personal protective equipment (PPE) meeting work requirements (for depression: OR = 0.438, 95%CI: 0.246 to 0.778; for anxiety: OR = 0.581, 95%CI: 0.352 to 0.959; for stress: OR = 0.504, 95%CI: 0.283 to 0.898) were independent protective factors against depression, anxiety, and stress, respectively. Yet, working in an isolation ward or fever clinic was an independent risk factor associated with depression, anxiety, and stress, respectively (for depression: OR = 1.809, 95%CI: 1.103 to 2.966; for anxiety: OR = 1.864, 95%CI: 1.221 to 2.846; for stress: OR = 2.974, 95%CI: 1.866 to 4.741). Having suspected or confirmed COVID-19 patients in the departments (OR = 1.554, 95%CI: 1.053 to 2.294) and coming in contact with the patient's bodily fluids or blood (OR = 1.469, 95%CI: 1.031 to 2.095) were independent risk factors for anxiety, while >3 times of training for COVID-19 related information was an independent protective factor for depression (OR = 0.592, 95%CI: 0.360 to 0.974). Moreover, >10 years of working was an independent risk factor for stress (OR = 1.678, 95%CI: 1.075 to 2.618). Conclusion During the COVID-19 outbreak, a considerable proportion of Hubei pediatric nurses had psychological problems. The pediatric nurses endorsing the higher number of risk factors should be given special attention and necessary psychological intervention. Improving the levels of PPE so as to meet the work requirements and intensifying occupational protection practices might help safeguard pediatric nurses from depression, anxiety, and stress., Highlights • A considerable proportion of Hubei pediatric nurses had psychological problems during the COVID-19 pandemic. • This study identified certain independent factors associated with depression, anxiety, and stress for Hubei pediatric nurses. • Intensifying occupational protection practices might help safeguard pediatric nurses from depression, anxiety, and stress.

In this paper we explore the problem of scheduling parallel processes of Kalman filters to meet individual estimation error requirements. It is assumed that at each time-step measurements of only one process are received. We define real-time deadlines of transmissions and convert the problem into arranging sequence of tasks with corresponding deadlines. To reduce computations, cycles of transmissions are calculated and virtual processes are introduced into scheduling. A sliding window method is then designed to adjust the processes against real-time disturbances in applications. Compared with algorithms proposed in Lin and Wang (2013), the proposed algorithm is able to schedule a feasible sequence adaptively within a short scheduling window and requires little computation.

The paper studies the general circumnavigation problem for a team of unicycle-type agents, with the goal of achieving specific circular formations and circling on different orbits centered at a target of interest. A novel distributed solution is proposed, in which the control laws are heterogeneous for the agents such that some agents are repellant from the target while attractive to its unique neighbor and some agents are attractive to the target while repellant from its neighbor. A systematic procedure is developed to design the control parameters according to the specific radii of the orbits and the formations that the agents are desired to converge to. Moreover, this control scheme uses a minimum number of information flow links between the agents and local measurements of relative position only. Based on the block diagonalization of circulant matrices by a Fourier transform, asymptotic convergence properties are analyzed rigorously. The validity of the proposed control algorithm is also demonstrated through numerical simulations.

This paper addresses the problem of steering a single or a group of autonomous nonholonomic mobile robots to enclose a target of interest. We develop control schemes which require only local bearing measurements, and deal with encirclement of two types of targets: point target and disk target. When a single robot is used, circumnavigation schemes are proposed to achieve effective encirclement of the target. It is shown that under the proposed control schemes, the robot can circle the target from a prescribed distance without distance measurement. When multiple robots are deployed, the control schemes developed for single robot are modified by introducing a coordination mechanism, which drives the robots to distribute evenly around the target. We further discuss a control scheme that moves the robots to form a static circular formation around the target based on feedback linearization. All the proposed control schemes are validated in experiments on a group of two-wheeled differential drive mobile robots.

We study the rendezvous problem of multiple nonholonomic unicycle-type robots. Simple decentralized control laws are proposed in which each agent makes a decision only based upon the bearing angles of the other robots in its reference frame. The convergence is first proved when the interaction topology between robots is connected; then for the complete interaction case, it is proved that under the proposed control law, the perimeter of the convex hull defined by the positions of robots decays all the time. Consequently, all the robots converge to a common point. It is also proved that the meeting point is located in a bounded region which is determined by the robots’ initial positions. Simulations illustrate the theoretical results and the performance with measurement errors.

In this paper, a local feedback control strategy is devised to drive a group of nonholonomic unicycle-type vehicles to a rendezvous point. The proposed control law is continuous and time-invariant. Using tools from graph theory, convergence and ultimate boundedness properties of the overall system are examined. Similar to the results for the rendezvous problem for vehicles governed by linear dynamics, the convergence of the studied overall multi-agent system relies on the connectivity of the interaction graph. The validity of this control law is verified by computer simulations.

In cyclic pursuit a platoon of vehicles are coupled in a unidirectional ring at the interaction level according to some control scheme. In the paper, a new cyclic pursuit control law is proposed, where each vehicle's linear speed and angular speed are proportional to the projection of its prey's position on its forward direction and lateral direction respectively. Through these interactions a cooperative behavior emerges and vehicles in the platoon eventually move at a constant speed on a circle with constant inter-vehicle spacings. The control scheme ensures ultimate boundedness and leads to only two stable equilibrium polygons. This contrasts with other cyclic pursuit control schemes, where vehicles may diverge to infinity and there are more stable equilibrium polygons as the total number of vehicles increases. For this control scheme, ultimate boundedness is proved using the pseudo-linearization technique. Possible equilibrium polygons are analyzed and stability and convergence properties are established through root locus analysis of a complex characteristic polynomial. Design rules are discussed, showing how the radius of the circle they converge to is controlled by an appropriate choice of control parameters.