Latest Research

Article  |  2020-07-06

Super Resolution Perception for Improving Data Completeness in Smart Grid State Estimation

The smart grid is an evolving critical infrastructure, which combines renewable energy and the most advanced information and communication technologies to provide more economic and secure power supply services. To cope with the intermittency of ever-increasing renewable energy and ensure the security of the smart grid, state estimation, which serves as a basic tool for understanding the true states of a smart grid, should be performed with high frequency. More complete system state data are needed to support high-frequency state estimation. The data completeness problem for smart grid state estimation is therefore studied in this paper. The problem of improving data completeness by recovering high-frequency data from low-frequency data is formulated as a super resolution perception (SRP) problem in this paper. A novel machine-learning-based SRP approach is thereafter proposed. The proposed method, namely the Super Resolution Perception Net for State Estimation (SRPNSE), consists of three steps: feature extraction, information completion, and data reconstruction. Case studies have demonstrated the effectiveness and value of the proposed SRPNSE approach in recovering high-frequency data from low-frequency data for the state estimation.

Gaoqi Liang ,   Guolong Liu   et al.

Article  |  2020-07-11

The role played by traditional Chinese medicine in preventing and treating COVID-19 in China

Traditional Chinese medicine (TCM), an ancient system of alternative medicine, played an active role in the prevention and control of COVID-19 in China. It improved the clinical symptoms of patients, reduced the mortality rate, improved the recovery rate, and effectively relieved the operating pressure on the national medical system during critical conditions. In light of the current global pandemic, TCM-related measures might open up a new channel in the control of COVID-19 in other countries and regions. Here, we summarize the TCM-related measures that were widely used in China, including TCM guidelines, the Wuchang pattern, mobile cabin hospitals, integrated treatment of TCM and modern medicine for critical patients, and non-medicine therapy for convalescent patients, and describe how TCM effectively treated patients afflicted with the COVID-19. Effective TCM therapies could, therefore, be recommended and practiced based on the existing medical evidence from increased scientific studies.

Qingwei Li ,   Han Wang   et al.

Article  |  2020-07-10

Three-dimensional finite difference analysis of shallow sprayed concrete tunnels crossing a reverse fault or a normal fault: A parametric study

Urban tunnels crossing faults are always at the risk of severe damages. In this paper, the effects of a reverse and a normal fault movement on a transversely crossing shallow shotcreted tunnel are investigated by 3D finite difference analysis. After verifying the accuracy of the numerical simulation predictions with the centrifuge physical model results, a parametric study is then conducted. That is, the effects of various parameters such as the sprayed concrete thickness, the geo-mechanical properties of soil, the tunnel depth, and the fault plane dip angle are studied on the displacements of the ground surface and the tunnel structure, and on the plastic strains of the soil mass around tunnel. The results of each case of reverse and normal faulting are independently discussed and then compared with each other. It is obtained that deeper tunnels show greater displacements for both types of faulting.

Masoud RANJBARNIA ,   Milad ZAHERI   et al.

Article  |  2020-07-06

Use of angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers in context of COVID-19 outbreak: a retrospective analysis

The possible effects of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) on COVID-19 disease severity have generated considerable debate. We performed a single-center, retrospective analysis of hospitalized adult COVID-19 patients in Wuhan, China, who had definite clinical outcome (dead or discharged) by February 15, 2020. Patients on anti-hypertensive treatment with or without ACEI/ARB were compared on their clinical characteristics and outcomes. The medical records from 702 patients were screened. Among the 101 patients with a history of hypertension and taking at least one anti-hypertensive medication, 40 patients were receiving ACEI/ARB as part of their regimen, and 61 patients were on anti-hypertensive medication other than ACEI/ARB. We observed no statistically significant differences in percentages of in-hospital mortality (28% vs. 34%, =0.46), ICU admission (20% vs. 28%, =0.37) or invasive mechanical ventilation (18% vs. 26%, =0.31) between patients with or without ACEI/ARB treatment. Further multivariable adjustment of age and gender did not provide evidence for a significant association between ACEI/ARB treatment and severe COVID-19 outcomes. Our findings confirm the lack of an association between chronic receipt of renin-angiotensin system antagonists and severe outcomes of COVID-19. Patients should continue previous anti-hypertensive therapy until further evidence is available.

Jiuyang Xu ,   Chaolin Huang   et al.

Article  |  2020-07-06

Current applications of artificial intelligence for intraoperative decision support in surgery

Research into medical artificial intelligence (AI) has made significant advances in recent years, including surgical applications. This scoping review investigated AI-based decision support systems targeted at the intraoperative phase of surgery and found a wide range of technological approaches applied across several surgical specialties. Within the twenty-one ( =21) included papers, three main categories of motivations were identified for developing such technologies: (1) augmenting the information available to surgeons, (2) accelerating intraoperative pathology, and (3) recommending surgical steps. While many of the proposals hold promise for improving patient outcomes, important methodological shortcomings were observed in most of the reviewed papers that made it difficult to assess the clinical significance of the reported performance statistics. Despite limitations, the current state of this field suggests that a number of opportunities exist for future researchers and clinicians to work on AI for surgical decision support with exciting implications for improving surgical care.

Allison J. Navarrete-Welton ,   Daniel A. Hashimoto