ABSTRACT
This study investigated upper-room germicidal ultraviolet (UR-GUV) light application in a music rehearsal room with a high ceiling (7.5 m). The focus was on the influences of the elevation and height of UV zone on disinfection of airborne viruses. This study assumed a uniform UV fluence rate of 0.2 W/m2 in the UV irradiation zone. According to the Computational Fluid Dynamics (CFD) results, average viral concentrations (Ca), fraction remaining (FR), and equivalent air exchange rate (λe) attributed to GUV, have power relationships with UV zone height. Ca and FR decreased with UV zone height, while λe did the opposite. UV zone elevation showed little influence on UR-GUV performance, indicating well-mixed air in the rehearsal room. High ceiling makes it possible to achieve adequate UV dose by increasing both UV zone height and UV light intensity. Using open fixtures improved energy efficiency and reduced operational costs of the UR-GUV system. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
ABSTRACT
Most COVID-19 studies commonly report figures of the overall infection at a state- or county-level. This aggregation tends to miss out on fine details of virus propagation. In this paper, we analyze a high-resolution COVID-19 dataset in Cali, Colombia, that records the precise time and location of every confirmed case. We develop a non-stationary spatio-temporal point process equipped with a neural network-based kernel to capture the heterogeneous correlations among COVID-19 cases. The kernel is carefully crafted to enhance expressiveness while maintaining model interpretability. We also incorporate some exogenous influences imposed by city landmarks. Our approach outperforms the state-of-the-art in forecasting new COVID-19 cases with the capability to offer vital insights into the spatio-temporal interaction between individuals concerning the disease spread in a metropolis.
ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic has led an implementation of institutional infection control protocols. This study will determine the effects of these protocols on outcomes of acute ischemic stroke (AIS) patients treated with endovascular therapy (EVT). Methods: Uninterrupted time series analysis of the impact of COVID-19 safety protocols on AIS patients undergoing EVT. We analyze data from prospectively collected quality improvement databases at 9 centers from March 11, 2019 to March 10, 2021. The primary outcome is 90-day modified Rankin Score (mRS). The secondary outcomes are angiographic time metrics. Results: Preliminary analysis of one stroke center included 214 EVT patients (n=144 pre-pandemic). Baseline characteristics were comparable between the two periods. Time metrics "last seen normal to puncture” (305.7 vs 407.2 min;p=0.05) and "hospital arrival to puncture” (80.4 vs 121.2 min;p=0.04) were significantly longer during pandemic compared to pre-pandemic. We found no significant difference in 90-day mRS (2.0 vs 2.2;p=0.506) or successful EVT rate (89.6% vs 90%;p=0.93). Conclusions: Our results indicate an increase in key time metrics of EVT in AIS during the pandemic, likely related to infection control measures. Despite the delays, we found no difference in clinical outcomes between the two periods.
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The global pandemic of coronavirus disease 2019 (COVID-19) is still ongoing, and the literature concerning COVID-19 is growing exponentially. The existing data from case reports, retrospective cohort studies and bioinformatics have suggested the relationship between SARS-CoV-2 and acute pancreatitis (AP). The mechanism of how SARS-CoV-2 attacks pancreas remains unclear. However, the expression of the receptor of SARS-CoV-2 in pancreatic tissue has been confirmed, and the components of SARS-CoV-2 have been isolated in the pancreas from patients with COVID-19. These evidences indicate that there may be a causality between SARS-CoV-2 and AP. The SARS-CoV-2 associated acute pancreatitis (SAAP) is likely to be misdiagnosed in clinical settings. Its diagnosis, severity classification and prognosis have specificities that deserve special attention. © 2021 Authors. All rights reserved.
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The emergence of the SARS-CoV-2 Omicron variant raises concerns for school operations worldwide. The Omicron variant spread faster than other variants that cause COVID-19, and breakthrough infections are reported in vaccinated people. Schools are hotbeds for the transmission of the highly contagious virus. Therefore it is crucial to understand the risks of Omicron transmission and the effectiveness of different measures to prevent the surge of infection cases. This study estimates the risks of airborne transmission and fomite transmission of Omicron variants using simulations and the data of 11,485 public and private schools in the U.S. It also analyzes the impact of different mitigation measures on limiting airborne transmission and fomite transmission risks in schools. It was found that the Omicron variant caused relatively high infection risks in schools. The risk of airborne transmission is nine times higher than fomite transmission. The effective mitigation measures can significantly decrease the transmission risk. © 2022 IEEE.
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Bus operators have to make trade-offs between transporting more passengers and maintaining social distancing to reduce ridership congregation amid Corona Virus Disease 2019 (COVID-19) outbreak. The traditional bus boarding mode could easily lead passengers fully occupy the bus available capacity at one stop, and it would prevent subsequent passengers from boarding. It is crucial to establish a new operating mode and strategy to ensure all passengers have opportunities to ride and to collaboratively optimise the bus timetable. In this paper, the boarding limit strategy that considers the fairness of passenger boarding probability is proposed to address the inequitable problem with minimise the passenger travel time and the number of stranded passengers. The coupling relationship between bus dwell time and passenger flow is used to collaboratively optimise the bus timetable. Case studies are conducted to illustrate the performance of the boarding limit strategy in improving passenger boarding equity. © 2023 Hong Kong Society for Transportation Studies Limited.
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Cancer is a disease that predominantly affects older adults. The median age at diagnosis is 66 years and 62% of the 15.5 million American cancer survivors are age ≥65 years. Provision of supportive care after treatment is critical to this group due to their complex care needs;however, limited resources are available to them. As increasing numbers of older survivors adopt technology, digital health programs have significant potential to help them improve their health and communicate with their providers. Previously, we developed/tested a digital Cancer Survivorship Patient Engagement Toolkit program for older adults, CaS-PET Silver. The aim was to examine the preliminary impact of CaS-PET Silver on older survivors' health outcomes. This was a 2-armed RCT with two observations (baseline, 8 weeks) on a sample of 60 survivors age ≥65 years (mean age, 70.1±3.8), who were treated with curative intent within 12 months from enrollment (02/2020-01/2022, COVID-19 pandemic). Outcomes included health-related quality of life (HRQoL), self-efficacy for coping with cancer, symptom burden, health behaviors, and patient-provider communication. Data were analyzed using descriptive statistics, linear mixed models, and content analysis. The majority of participants were black (68.3%, n=41) and female (56.6%, n=34). At 8 weeks, CaS-PET Silver group showed significantly improved physical HRQoL (p < .001, ES=0.64) and symptom burden (p=.053, ES= -0.41). Self-efficacy (ES=0.56), mental HRQoL (ES=0.26), and communication (ES=0.40) showed a tendency to improve. Most participants reported benefits from the program on health management (mean, 19.41±2.6 [3–21]). Further research is needed with larger, diverse older cancer populations.
ABSTRACT
A clinical trial is a key step in the process of pharmaceutical research and development (R & D). It is a key indicator of the innovative potential of the pharmaceutical industry. ClinicalTrials.gov shows that the average annual growth rate of the total number of clinical trials globally in the past decade (2012-2021) was 20.7%, mainly distributed in Europe and the United States, and the total number of clinical trials registered in China accounted for 6% of the world. According to the statistics of IQVIA Institute for Human Data Science, the global proportion of early-stage R & D pipelines from China-headquartered companies increased from 1% in 2005 to 12% in 2020, which was still far behind that of European and American companies. Among 871 new active substances approved for marketing globally in the past two decades, 522 were for marketing in China, with the high number driven by regulatory acceleration mechanisms from National Medical Products Administration, such as breakthrough and orphan designations and priority reviews. Considering the gap in clinical research strength between China and developed countries such as Europe and the United States, the clinical trial research capacity and level should be improved to assist China in the R & D of innovative drugs. According to the Registration and Information Disclosure Platform for Drug Clinical Studies and the clinical trial institution filing management information platform in China, in the last five years (2017-2021), the average annual growth rates of the total number of new drug clinical trial registration and clinical trial units in China reached 26.9% and 12.6%, respectively. However, clinical trial resources are mainly concentrated in major institutions, municipalities, or provincial capital cities in the eastern and central regions of China, with distributions becoming increasingly polarised. Under the background of China's new medical reforms, the strategic direction of national political support is to motivate equitable access to high-quality clinical trial resources and cross-regional collaborative development of medical institutions by means of medical unions, national clinical medical research centres, Chinese national major projects for new drug innovation and so on. In the context of this background, clinical trial research unions (CTRUs) have been built in China. A CTRU is defined as a consortium formed by medical institutions, sponsors and third-party service institutions of various levels and functions, led by a national clinical medical research centre or clinical trial medical institutions undertaking major national science and technology projects or supporting projects of national key R & D plans, radiating and driving the improvement of clinical trial research capacity in multiple regions. CTRUs develop a multi-level clinical research centre system and collaborative network by vertically and horizontally combining multi-level medical institutions, sponsors and third-party service institutions. All participants of CTRUs are crucial. The leading clinical trial research medical institution, as the core, is responsible for establishing institutional system standards in CTRUs, designing and leading high-quality multi-centre clinical trials, central ethics and personality training. The major clinical trial research medical institutions are responsible for implementing high-quality, multi-centre, complex and high-risk clinical trials. The other member institutions are responsible for implementing basic clinical trials. The sponsors, contract research organizations (CROs), site management organizations (SMOs) and other enterprises are responsible for funding, supporting and promoting the construction of a clinical trial centre system and collaborative network. The specific construction contents of CTRUs include building a clinical trial research resource sharing platform, homogenising clinical trial quality management, constructing a rapid clinical trial process platform, diversified multi-level and multi-form talent training, information intercon ection, deepening strategic cooperation and designing and leading high-level trials. CTRUs have established the selection criteria and assessment exit mechanism and conducted work performance assessments from the dimensions of organisation and implementation, division of labour and cooperation, the connection of clinical trial resources from top to bottom, efficiency and benefit and sustainable development to ensure their good and sustainable development. Through CTRUs, we can achieve high-quality clinical trial resource sharing, improve the clinical trial research capability of member institutions, cultivate high-level skills, such as principal investigators (PIs), sub-investigators, institutional managers and clinical research coordinators (CRCs), and promote the development of clinical trials, economically and with high-quality. Through the trial operation with one member of CTRUs, it was found that the key points should be strengthened in deepening resource sharing, implementing central ethics review, interconnecting information platforms and leading high-quality clinical trials. The construction of CTRUs is an effective means for China's clinical trial research to solve the current problems and change from a `follow-on pattern' to leading high-level and high-quality international multi-centre trials. However, the construction of CTRUs is a complex systematic project. In addition to performing an excellent job in the top-level design and overall planning, CTRUs' specific implementation process and measures need to be continuously explored in the practice process.
ABSTRACT
The existing COVID-19 pandemic has driven personal protective equipment use and consumption surge, leading to plastic pollution as most waste goes to landfills. Biodegradable polypropylene (PP) gowns claimed to have similar production costs as standard PP film ones might be more environmentally friendly due to the degradability after landfilling. The illustration of their sustainable end-of-life waste disposal options is lacking and requires a systematic comparison of their environmental impacts. A holistic life cycle assessment approach based on full-spectrum environmental indicators identifies the environmentally sustainable waste disposal options. Results illustrate the environmental benefits of landfill gas capture and utilization incorporated to landfilling biodegradable gown wastes by reducing 48.81 % land-use, 9.35 % greenhouse gas emissions from fossil sources, and 5.67 % from land-use greenhouse gas emissions, respectively. Despite these environmental advantages, industrial composting embodies lower environmental emissions than sanitary landfills for treating biodegradable gowns. Fossil-based gowns treated by landfills can have lower environmental impacts than composting biodegradable gowns in full-spectrum environmental indicators. The standard gown landfilling is identified as the environmentally sustainable disposal option. Copyright © 2022, AIDIC Servizi S.r.l.
ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic has led the implementation of institutional infection control protocols. This study will determine the effects of these protocols on outcomes of acute ischemic stroke (AIS) patients treated with endovascular therapy (EVT). Methods: Uninterrupted time series analysis of the impact of COVID-19 safety protocols on AIS patients undergoing EVT. We analyze data from prospectively collected quality improvement databases at 6 centers from March 11, 2019 to March 10, 2021. The primary outcome is 90-day modified Rankin Score (mRS). The secondary outcomes are angiographic time metrics. Results: Preliminary analysis of one stroke center included 214 EVT patients (n=150 pre-pandemic). Baseline characteristics were comparable between the two periods. Time metrics last seen normal to puncture (305.7 vs 407.2 min;p=0.05) and hospital arrival to puncture (80.4 vs 121.2 min;p=0.04) were significantly longer during pandemic compared to pre-pandemic. We found no significant difference in 90-day mRS (2.0 vs 2.2;p=0.506) or successful EVT rate (89.6% vs 90%;p=0.93). Conclusions: Our results indicate an increase in key time metrics of EVT in AIS during pandemic, likely related to infection control measures. Despite the delays, we found no difference in clinical outcomes between the two periods.
ABSTRACT
Even though "Mainstream Media and E-Commerce Live Streaming"emerges as a new form of E-Commerce Live Streaming under the influence of the COVID-19 pandemic, its underlying mechanism in consumers' online shopping remains unexplored. Consequently, this paper explores this topic with a qualitative research through in-depth interviews with college students and graduate students. Based on the grounded theory and NVIVO 12.0 software, researchers explore the influences of mainstream media live streaming of consumers' purchase decision, and propose a framework of consumer purchased decision-making factors of 3 themes and 11 sub-themes. Overall, the findings contribute to the literature of E-Commerce Live Streaming and provide practical implications for mainstream media to better participate in E-Commerce live streaming platforms. © 2022 ACM.
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In this paper, we propose a novel convolutional neural network based on adaptive multi-scale feature aggregation and boundary-aware for lateral ventricle segmentation (MB-Net), which mainly includes three parts, i.e., an adaptive multi-scale feature aggregation module (AMSFM), an embedded boundary refinement module (EBRM), and a local feature extraction module (LFM). Specifically, the AMSFM is used to extract multi-scale features through the different receptive fields to effectively solve the problem of distinct target regions on magnetic resonance (MR) images. The EBRM is intended to extract boundary information to effectively solve blurred boundary problems. The LFM can make the extraction of local information based on spatial and channel attention mechanisms to solve the problem of irregular shapes. Finally, extensive experiments are conducted from different perspectives to evaluate the performance of the proposed MB-Net. Furthermore, we also verify the robustness of the model on other public datasets, i.e., COVID-SemiSeg and CHASE DB1. The results show that our MB-Net can achieve competitive results when compared with state-of-the-art methods. © 2022 IEEE
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The traditional SEIR (susceptible-exposed-infectious-recovered/removed) model is a simplified dynamical predictive model which does not consider the impact of changes in the anti-epidemic policy. We take the US anti-epidemic policy and the incubation period characteristic of COVID-19 into account to propose the TRP-SEAMRD(test-restricted-phased SEAMRD) model for the pandemic in US. The model fits well with the figures of COVID-19 infections, recovery and death in the United States during February ~ August 2020. According to the data generated from the model, some of the characteristics of COVID- 19 can be ed. Based on the TRP-SEAMRD model, we can analyze the impact of the improper anti¬epidemic policy at the early stage of the epidemic. The effect of the subsequent “stay at home”epidemic controlling measures is also considered and analyzed. Finally, future development of the pandemic in the US under different degrees of social control is simulated,offering a reference for formulating scientific anti¬epidemic measures. © 2020, Editorial Department of Journal of University of Science and Technology of China. All rights reserved.
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In this COVID-19 epidemic, due to insufficient awareness of the impact of sudden public health emergencies on agricultural logistics at this stage, agricultural products were left unsold, stocks were backlogged, and losses were severe. In the process of distribution, we should not only ensure a short time cycle and avoid the contamination of agricultural products by foreign bacteria, but also pay attention to the waste of human, material, and financial resources. Therefore, this study mainly adopts the combination of the petrochemical network and block chain to build an agricultural products emergency logistics model. This paper first shows the operation mechanism of the petri dish network and blockchain coupling in the form of a graph and then uses the culture network modelling and simulation tool PIPE to directly verify the construction model. It is proved that the structure and overall business process of the agricultural products logistics system constructed by combining the Petri net and block chain are reasonable, reliable, and feasible in practical application and development. It is hoped that this study can provide a reference direction for agricultural emergency logistics.
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Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease. Understanding the spatio-temporal dynamics of hotspot events is of great importance to support policy decisions and prevent large-scale outbreaks. This paper presents a spatio-temporal Bayesian framework for early detection of COVID-19 hotspots (at the county level) in the United States. We assume both the observed number of cases and hotspots depend on a class of latent random variables, which encode the underlying spatio-temporal dynamics of the transmission of COVID-19. Such latent variables follow a zero-mean Gaussian process, whose covariance is specified by a non-stationary kernel function. The most salient feature of our kernel function is that deep neural networks are introduced to enhance the model's representative power while still enjoying the interpretability of the kernel. We derive a sparse model and fit the model using a variational learning strategy to circumvent the computational intractability for large data sets. Our model demonstrates better interpretability and superior hotspot-detection performance compared to other baseline methods. IEEE
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From the perspective of economic geography, this paper studies the changing spatial pattern of world economy and China's role in different waves of economic globalization. Firstly, this study finds that the geographical pattern of world economy changes from "core-periphery" to "chain-reconfiguration", and to current "network-imbalance". Meanwhile the driving force of economic globalization shifts from "trade globalization" to "manufacturing globalization". At present, "multiple globalization" is involving into a new engine to driving the development of economic globalization. We then discuss that how China changes its role in economic globalization by changing modes of strategic coupling. We argue that the role transition of China breaks the traditional developing path which developed countries set for developing countries and theoretical spatial order put forward by classical industry gradient transfer, bringing new restructuring power and possibility for changing pattern of globalization. Finally, we discuss the impacts of COVID-19 pandemic on the development of economic globalization and the development trend of economic globalization in the post-pandemic era. Based on the analysis, we come up with some suggestions regarding to the potential development paths of China under the background of economic globalization. © 2022, Science Press. All right reserved.
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Under the background of the spread of COVID-19, there has been a shift from offline education to online education. Online education is rapidly becoming large-scale in a short time, and its related hardware and software markets are expanding rapidly. The development of this kind of online education hardware carrier represented by children’s robot has become a hot spot in the industry at this time, but there are still some problems in its design, such as ignoring the emotional needs of users. This study first focuses on the user’s function and emotional needs through market research and user research, then uses the method of Kansei engineering to select a certain sample of existing children’s robots, conducts Kansei vocabulary research through SD method, and analyzes the data results through SPSS, so as to summarize the modeling semantic keywords. Finally, from the perspective of Kansei Engineering, a new practical design scheme of children’s accompanying robot is proposed. The feasibility and effectiveness of the design practice are verified by the satisfaction survey. © 2021, Springer Nature Switzerland AG.
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We present an interpretable high-resolution spatio-temporal model to estimate COVID-19 deaths together with confirmed cases 1 week ahead of the current time, at the county level and weekly aggregated, in the United States. A notable feature of our spatio-temporal model is that it considers the (1) temporal auto- and pairwise correlation of the two local time series (confirmed cases and deaths from the COVID-19), (2) correlation between locations (propagation between counties), and (3) covariates such as local within-community mobility and social demographic factors. The within-community mobility and demographic factors, such as total population and the proportion of the elderly, are included as important predictors since they are hypothesized to be important in determining the dynamics of COVID-19. To reduce the model's high dimensionality, we impose sparsity structures as constraints and emphasize the impact of the top 10 metropolitan areas in the nation, which we refer to (and treat within our models) as hubs in spreading the disease. Our retrospective out-of-sample county-level predictions were able to forecast the subsequently observed COVID-19 activity accurately. The proposed multivariate predictive models were designed to be highly interpretable, with clear identification and quantification of the most important factors that determine the dynamics of COVID-19. Ongoing work involves incorporating more covariates, such as education and income, to improve prediction accuracy and model interpretability.