Covid-19 and investment-cash flow sensitivity: A cross-country analysis.

This study investigates investment-cash flow sensitivity during the COVID-19 economic crisis. Using an international sample of publicly listed firms, we find that the sensitivity of capital expenditures to cash flows is significantly reduced during the crisis. When we split the sample into strongly and weakly affected countries, we find that firms in countries affected more seriously by COVID-19 exhibit lower investment responsiveness to cash flows. We further find that investment-cash flow sensitivity is diminished when government aid is greater, firms have more cash on hand, and investment opportunities decline. Our results survive a host of robustness checks. This study contributes to the discussion on the impact of COVID-19 on corporate policies within an international framework.

Control of an outbreak of COVID-19 at a tertiary hospital in Taiwan.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has circulated in Taiwan since late 2019. Healthcare facilities are vulnerable to COVID-19 outbreaks due to clusters of symptomatic patients and susceptible hosts. Prompt control of outbreaks is crucial. In May 2021, an index case of COVID-19 was detected at Far Eastern Memorial Hospital (FEMH) in New Taipei City, Taiwan, 3 days after hospital admission, spreading to 26 patients and staff. Herein we evaluate control of this COVID-1 outbreak. METHODS: To control the outbreak, the index case ward was closed, and large-scale COVID-19 testing (RT PCR) was performed for all inpatients, caregivers and healthcare workers (HCWs). All exposed persons were quarantined. Thorough investigation was conducted to analyze the transmission route. RESULTS: The outbreak comprised 12 patients, 12 caregivers, and 3 HCWs. Seven patients expired and the remaining cases recovered. Overall, 456 patients/caregivers and 169 HCWs were quarantined. Analysis showed that longer exposure time was the main cause of HCW infection; all three infected HCWs were primary-care nurses related to the index case. To diminish hidden cases, all hospitalized patients/caregivers received PCR examinations and all results were negative. Thereafter, all patients/caregivers routinely received PCR examination on admission. Hospital-wide PCR screening for HCW detected 4 positive HCWs unrelated to this outbreak, and a second-round of screening detected 2 more cases, with no additional cases during the following 6 months. CONCLUSION: Prompt infection control measures and large-scale PCR screening can control a COVID-19 outbreak within 2 weeks. Exposure time is the major risk factor for HCW infection.

Virtual screening of approved clinic drugs with main protease (3CLpro) reveals potential inhibitory effects on SARS-CoV-2.

3CLpro is the main protease of the novel coronavirus (SARS-CoV-2) responsible for their intracellular duplication. Based on virtual screening technology and molecular dynamics simulation, we found 23 approved clinical drugs such as Viomycin, Capastat, Carfilzomib and Saquinavir, which showed high affinity with the 3CLpro active sites. These findings showed that there were potential drugs that inhibit SARS-Cov-2's 3CLpro in the current clinical drug library, and these drugs can be further tested or chemically modified for the treatment of COVID-19.Communicated by Ramaswamy H. Sarma.

Study on contaminant distribution in a mobile BSL-4 laboratory based on multi-region directional airflow.

The outbreak of COVID-19 has caused increasing public attention to laboratory-acquired infections (LAIs), especially for a mobile Bio-Safety Level 4 Lab (BSL-4) with high potential of exposure. In this paper, the distribution and removal mechanism of bioaerosols in the biosafety laboratory were studied. A simulation model of airflow distribution in the opening and closing state of air-tight door was established and verified. The results showed that the airflow entrainment velocity during the opening of the door was approximately 0.12 m/s. It increased the probability of vortex generation in the laboratory. The deposition rate of particles was doubled when the air-tight door opening is compared with air-tight door closing. Besides, nearly 80% of the particles deposited on the surface of the wall and ceiling, increasing the possibility of LAIs. The findings of this paper could provide new scientific methods for high-level biosafety laboratories to avoid cross-infection. Moreover, future work regarding air-tight door rotation speed regulation and control should be emphasized.

DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images (preprint)

The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy. Rapid and accurate diagnosis of COVID-19 is crucial to prevent the further spread of the disease and reduce its mortality. Chest Computed tomography (CT) is an effective tool for the early diagnosis of lung diseases including pneumonia. However, detecting COVID-19 from CT is demanding and prone to human errors as some early-stage patients may have negative findings on images. Recently, many deep learning methods have achieved impressive performance in this regard. Despite their effectiveness, most of these methods underestimate the rich spatial information preserved in the 3D structure or suffer from the propagation of errors. To address this problem, we propose a Dual-Attention Residual Network (DARNet) to automatically identify COVID-19 from other common pneumonia (CP) and healthy people using 3D chest CT images. Specifically, we design a dual-attention module consisting of channel-wise attention and depth-wise attention mechanisms. The former is utilized to enhance channel independence, while the latter is developed to recalibrate the depth-level features. Then, we integrate them in a unified manner to extract and refine the features at different levels to further improve the diagnostic performance. We evaluate DARNet on a large public CT dataset and obtain superior performance. Besides, the ablation study and visualization analysis prove the effectiveness and interpretability of the proposed method.