. MCAs acknowledged added value of providing additional information on topics that they address during the early postpartum period. MCAs as well as clinicians and administrators would guide parents to such a platform for additional support. All user groups experienced disadvantages of using an authentication procedure and filling out extra questionnaires to receive tailored information. Conclusions Our research shows that parents of newborns, MCAs, and clinicians and administrators foresee the additional value of a web-based postpartum platform for at least the whole postpartum period. The platform should be easily accessible and personalized. Content on the platform should contain information regarding breastfeeding, growth, and developmental milestones. A chat function with professionals could be considered as an option.Background Coronavirus disease (COVID-19) has affected more than 200 countries and territories worldwide. This disease poses an extraordinary challenge for public health systems because screening and surveillance capacity is often severely limited, especially during the beginning of the outbreak; this can fuel the outbreak, as many patients can unknowingly infect other people. Objective The aim of this study was to collect and analyze posts related to COVID-19 on Weibo, a popular Twitter-like social media site in China. To our knowledge, this infoveillance study employs the largest, most comprehensive, and most fine-grained social media data to date to predict COVID-19 case counts in mainland China. Methods We built a Weibo user pool of 250 million people, approximately half the entire monthly active Weibo user population. Using a comprehensive list of 167 keywords, we retrieved and analyzed around 15 million COVID-19-related posts from our user pool from November 1, 2019 to March 31, 2020. We developed a macion cases and inform timely responses. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. In addition to monitoring overall search and posting activities, leveraging machine learning approaches and theoretical understanding of information sharing behaviors is a promising approach to identify true disease signals and improve the effectiveness of infoveillance.Background The use of health apps to support the treatment of chronic pain is gaining importance. Most available pain management apps are still lacking in content quality and quantity as their developers neither involve health experts to ensure target group suitability nor use gamification to engage and motivate the user. To close this gap, we aimed to develop a gamified pain management app, Pain-Mentor. Objective To determine whether medical professionals would approve of Pain-Mentor's concept and content, this study aimed to evaluate the quality of the app's first prototype with experts from the field of chronic pain management and to discover necessary improvements. Methods A total of 11 health professionals with a background in chronic pain treatment and 2 mobile health experts participated in this study. Each expert first received a detailed presentation of the app. Afterward, they tested Pain-Mentor and then rated its quality using the mobile application rating scale (MARS) in a semistructured interviewep in the development of Pain-Mentor.This article deals with the problem of H∞ and l2-l∞ filtering for discrete-time Takagi-Sugeno fuzzy nonhomogeneous Markov jump systems with quantization effects, respectively. The time-varying transition probabilities are in a polytope set. To reduce conservativeness, a mode-dependent logarithmic quantizer is considered in this article. Based on the fuzzy-rule-dependent Lyapunov function, sufficient conditions are given such that the filtering error system is stochastically stable and has a prescribed H∞ or l2-l∞ performance index, respectively. Finally, a practical example is provided to illustrate the effectiveness of the proposed fuzzy filter design methods.In this article, the problem of distributed hierarchical fault-tolerant containment control for heterogeneous linear multiagent systems (MASs) is investigated. In most of the existing distributed methods for MASs with system failures, each agent broadcasts its state, or output, or the estimation of state to neighbors. Once an agent is subjected system failures, faults affect the dynamics of other agents over the network, that is, the influence of faults on the agent will propagate with the network. In order to overcome this drawback, a fault-tolerant hierarchical containment control protocol is developed, which includes two layers 1) the upper layer and 2) the lower layer. The upper layer consists of a virtual system and a cooperative controller to achieve a virtual containment objective. The lower layer consists of an actual system and a fault-tolerant controller to track the upper layer virtual system. Compared with the existing results, the phenomenon of fault propagation can be avoided by introducing the hierarchical design approach, that is, the fault of agent i only affects the dynamics of itself, and does not affect the dynamics of other agents through the network. It is shown that each follower converges asymptotically to a convex hull spanned by leaders with external input. https://www.selleckchem.com/products/h2dcfda.html Finally, the developed method is demonstrated by simulation results.This article is concerned with set-membership global estimation for a networked system under unknown-but-bounded process and measurement noises. First, a group of local set-membership estimators is deployed to obtain the local ellipsoidal estimate of the true system state. Each estimator is capable of communicating with its neighbors within its communication range. Second, a global estimation approach is proposed which generates a trace-maximal ellipsoid within the intersection of all the local estimation sets with an aim to improve the difference of the local estimate at each time instant. Sufficient conditions for providing a global estimate under both complete and incomplete measurement transmissions are derived. Third, as an application, a modified distributed photovoltaic grid-connected generation system is provided to verify the effectiveness of the developed set-membership global estimation approach. Furthermore, an islanding fault detection scheme is derived based on the calculated global ellipsoidal estimate.