Rationale: The outbreak of coronavirus disease 2019 (COVID-19) in 2019 has become a global pandemic. It is not known whether the disease is associated with a higher risk of infection in pregnant women or whether intrauterine vertical transmission can occur. We report 2 cases of pregnant women diagnosed with COVID-19. Patient concerns: In all of Yichang city from January 20, 2020, to April 9, 2020, only 2 pregnant women, who were in the late stage of pregnancy, were diagnosed with COVID-19; one patient was admitted for fever with limb asthenia, and the other patient was admitted for abnormal chest computed tomography results. Diagnoses: Both pregnant women were diagnosed with COVID-19. Interventions: After the medical staff prepared for isolation and protection, the 2 pregnant women quickly underwent cesarean sections. A series of tests, such as laboratory, imaging, and SARS-CoV-2 nucleic acid examinations, were performed on the 2 women with COVID-19 and their newborns. Outcomes: One of the 2 infected pregnant women had severe COVID-19, and the other had mild disease. Both babies were delivered by cesarean section. Both of the women with COVID-19 worsened 3 to 6 days after delivery. Chest computed tomography suggested that the lesions due to SARS-CoV-2 infection increased. These women began to exhibit fever or reduced blood oxygen saturation again. One of the 2 newborns was born prematurely, and the other was born at full term. Neither infant was infected with COVID-19, but both had increased prothrombin time and fibrinogen, lactate dehydrogenase, phosphocreatine kinase, and creatine kinase isoenzyme contents. Lessons: SARS-CoV-2 infection was not found in the newborns born to the 2 pregnant women with COVID-19, but transient coagulation dysfunction and myocardial damage occurred in the 2 newborns. Effective management strategies for pregnant women with COVID-19 will help to control the outbreak of COVID-19 among pregnant women.
With the popularization of wireless networking and with the progress of mobile computing technology, the efficiency of handheld devices has been improved and more applications are possible. Combining handheld devices and E-learning will become an important way of learning in the future. This research uses access to a wireless network, handheld devices, and RFID tags to build a Context-Aware Writing System (C-Writing for short) for ubiquitous learning environments. Based on the practical use of C-Writing by students in a ubiquitous learning environment, we evaluated the learning results. We used a questionnaire to evaluate the learning situations regarding the users' attitudes, system acceptance, system quality, content quality, and interaction with the environment. The result of the research shows most of the students approve this system's benefit, and he/she is willing to use similar system for learning in the future. Moreover, students are able to efficiently improve their learning performance and students' attention and interest will be attracted to observe different things by using this system.
The recently proposed Competitive and Cooperative Learning algorithm(CCL) (Cheung 2004) has provided a promising way to perform the data clustering without knowing the number of clusters. Nevertheless, its performance is somewhat sensitive to the initialization of seed points. Also, its cooperative mechanism is applicable to the homogenous clusters only. In this paper, we will therefore suggest using the FSCL algorithm to initialize the seed points such that each cluster of data will at least have a seed point. Furthermore, we update the cooperation radius of seed points in CCL, whereby the improved CCL (ICCL for short) can be applicable to the heterogeneous clusters as well. Experiments show the efficacy of the proposed algorithm.
A novel method of multi-target charging is proposed in this paper, in the context of charging multiple indoor mobile phones simultaneously. Based on the laser wireless power transmission system, combined with machine vision technology, the traditional two-stage circuit is turned into a single-stage type, which realizes longer distance and more convenient charging. This article analyzes the working mode and circuit topology of the dc-dc converter in the multi-target charging mode, and analyzes the positioning and charging strategies for multi-targets based on machine vision. Under the strategy, the output voltage of the photovoltaic panel can be adjusted by modulating the pulsed light, so as to achieve the maximum power control for mobile phone charging. The simulation results are provided in this paper to validate the effectiveness of the proposed approach.
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