Notes

Share to look for: The consequences regarding Ailment Complexness about Wellbeing Information-Seeking Conduct.
Understanding the epidemiological characteristics of COVID-19 in South Korea and the government's successful efforts in managing the spread of the disease can provide important insights to other countries dealing with the ongoing pandemic.
Understanding the epidemiological characteristics of COVID-19 in South Korea and the government's successful efforts in managing the spread of the disease can provide important insights to other countries dealing with the ongoing pandemic.
In recent years, public health incidents that pose a serious threat to public life have occurred frequently in China. The use of social media by public health authorities has helped to reduce these threats by increasing effective risk communication between the government and the public.

The aim of this study is to reveal how China's Center for Disease Control and Prevention (CDC) uses social media to improve three aspects of health communication between the government and the public adoption, operation, and interaction.

To analyze the 134 CDC government Weibo accounts at the provincial- and prefecture-level administration regions in mainland China, we collected their account data and extracted 1215 Weibo tweets. We also supplemented the data to reveal the overall performance of the CDC's government Weibo use during the COVID-19 crisis.

The registration rate of the CDC's government Weibo accounts increased year by year, and the local authorities registered Weibo accounts before the central government aly manner.

China's CDC is using more social media to popularize daily health information and has taken the first step to improve communication between the government and the public. However, equal dialogue, two-way interactions, and effective communication with the public still need improvement.
China's CDC is using more social media to popularize daily health information and has taken the first step to improve communication between the government and the public. However, equal dialogue, two-way interactions, and effective communication with the public still need improvement.This article focuses on the problem of resilient H∞ filtering for Takagi-Sugeno fuzzy-model-based nonlinear networked systems with multisensors. A weighted fusion approach is adopted before information from multisensors is transmitted over the network. A novel event-triggered mechanism is proposed, which allows us not only to reduce the data-releasing rate but also to prevent abnormal data being potentially transmitted over the network due to sensor measurement or other practical factors. The problem of denial-of-service (DoS) attacks, which often occurs in a communication network, is also considered, where the DoS attack model is based on an assumption that the periodic attack includes active periods and sleeping periods. By employing the idea of the switching model for filtering error systems to deal with DoS attacks, sufficient conditions are derived to guarantee that the filtering error system is exponentially stable. Simulation results are given to demonstrate the effectiveness of the theoretical analysis and design method.With the development of the imaging technology of various sensors, multisource image classification has become a key challenge in the field of image interpretation. In this article, a novel classification method, called the deep multiview union learning network (DMULN), is proposed to classify multisensor data. First, an associated feature extractor is designed to process the multisource data by canonical correlation analysis (CCA) in the head of the network. Second, an improved deep learning architecture with two branches is presented to extract high-level view features from the associated features. Third, a novel pooling, called view union pooling, is proposed to fuse the multiview feature from the deep model. read more Finally, the fused feature is fed into the classifier. The proposed framework is easy to optimize since it is an end-to-end network. Extensive experiments and analysis on the datasets IEEE_grss_dfc_2017 and IEEE_grss_dfc_2018 show that the proposed method achieves comparable results. Our results demonstrate that abundant multisource information can improve the classification performance.In this article, an output regulation problem is considered for nonlinear multiagent systems with unity relative degree, in which nodes are coupled by dynamic edges. The inputs of the edge dynamic systems are determined by the error outputs of the node dynamic systems. Similarly, the neighboring inputs of the node dynamic systems are formed by the outputs of the edge dynamic systems and can influence node outputs. By introducing some coordinate transformations, we can transform the output regulation problem into a robust stabilization problem for an augmented system. Then, using the relative outputs of neighboring agents, we design a distributed output-feedback control law and suitable dynamic couplings between the nodes. Finally, it is shown that the global stabilization of the augmented system can be achieved using the proposed controller. An example is presented to demonstrate the effectiveness of our control strategy.We present results from an experiment in which 33 human subjects interact with a dynamic system 40 times over a one-week period. The subjects are divided into three groups. For each interaction, a subject performs a command-following task, where the reference command is the same for all trials and all subjects. However, each group interacts with a different dynamic system, which is represented by a transfer function. The transfer functions have the same poles but different zeros. One has a minimum-phase zero zₘ 0, and the last has a slower (i.e., closer to the imaginary axis) nonminimum-phase zero zsn ∈ (0,zₙ). The experimental results show that nonminimum-phase zeros tend to make dynamic systems more difficult for humans to learn to control. We use a subsystem identification algorithm to identify the control strategy that each subject uses on each trial. The identification results show that the identified feedforward controllers approximate the inverse dynamics of the system with which the subjects interact better on the last trial than on the first trial.
Homepage: https://www.selleckchem.com/products/deferiprone.html