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Articles 1 - 10 of 10
Full-Text Articles in Physical Sciences and Mathematics
Asian Hate Speech Detection On Twitter During Covid-19, Amir Toliyat, Sarah Ita Levitan, Zeng Peng, Ronak Etemadpour
Asian Hate Speech Detection On Twitter During Covid-19, Amir Toliyat, Sarah Ita Levitan, Zeng Peng, Ronak Etemadpour
Publications and Research
Coronavirus disease 2019 (COVID-19) started in Wuhan, China, in late 2019, and after being utterly contagious in Asian countries, it rapidly spread to other countries. This disease caused governments worldwide to declare a public health crisis with severe measures taken to reduce the speed of the spread of the disease. This pandemic affected the lives of millions of people. Many citizens that lost their loved ones and jobs experienced a wide range of emotions, such as disbelief, shock, concerns about health, fear about food supplies, anxiety, and panic. All of the aforementioned phenomena led to the spread of racism and …
The Temperature-Dependent Conformational Ensemble Of Sars-Cov-2 Main Protease (Mpro), Ali Ebrahim, Blake T. Riley, Desigan Kumaran, Babak Andi, Martin R. Fuchs, Sean Mcsweeney, Daniel A. Keedy
The Temperature-Dependent Conformational Ensemble Of Sars-Cov-2 Main Protease (Mpro), Ali Ebrahim, Blake T. Riley, Desigan Kumaran, Babak Andi, Martin R. Fuchs, Sean Mcsweeney, Daniel A. Keedy
Publications and Research
The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or Mpro, is a promising target for development of novel antiviral therapeutics. Previous X-ray crystal structures of Mpro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded Mpro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these datasets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a temperature-dependent conformational landscape for Mpro, including …
Modeling Covid-19 Spread In Small Colleges, Riti Bahl, Nicole Eikmeier, Alexandra Fraser, Matthew Junge, Felicia Keesing, Kukai Nakahata, Lily Reeves
Modeling Covid-19 Spread In Small Colleges, Riti Bahl, Nicole Eikmeier, Alexandra Fraser, Matthew Junge, Felicia Keesing, Kukai Nakahata, Lily Reeves
Publications and Research
We develop an agent-based model on a network meant to capture features unique to COVID-19 spread through a small residential college. We find that a safe reopening requires strong policy from administrators combined with cautious behavior from students. Strong policy includes weekly screening tests with quick turnaround and halving the campus population. Cautious behavior from students means wearing facemasks, socializing less, and showing up for COVID-19 testing. We also find that comprehensive testing and facemasks are the most effective single interventions, building closures can lead to infection spikes in other areas depending on student behavior, and faster return of test …
Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly
Decoding Clinical Biomarker Space Of Covid-19: Exploring Matrix Factorization-Based Feature Selection Methods, Farshad Saberi-Movahed, Mahyar Mohammadifard, Adel Mehrpooya, Mohammad Rezaei-Ravari, Kamal Berahmand, Mehrdad Rostami, Saeed Karami, Mohammad Najafzadeh, Davood Hajinezhad, Mina Jamshidi, Farshid Abedi, Mahtab Mohammadifard, Elnaz Farbod, Farinaz Safavi, Mohammadreza Dorvash, Shahrzad Vahedi, Mahdi Eftekhari, Farid Saberi-Movahed, Iman Tavassoly
Publications and Research
One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 …
Covid-19 Multi-Targeted Drug Repurposing Using Few-Shot Learning, Yang Liu, You Wu, Xiaoke Shen, Lei Xie
Covid-19 Multi-Targeted Drug Repurposing Using Few-Shot Learning, Yang Liu, You Wu, Xiaoke Shen, Lei Xie
Publications and Research
The life-threatening disease COVID-19 has inspired significant efforts to discover novel therapeutic agents through repurposing of existing drugs. Although multi-targeted (polypharmacological) therapies are recognized as the most efficient approach to system diseases such as COVID-19, computational multi-targeted compound screening has been limited by the scarcity of high-quality experimental data and difficulties in extracting information from molecules. This study introduces MolGNN , a new deep learning model for molecular property prediction. MolGNN applies a graph neural network to computational learning of chemical molecule embedding. Comparing to state-of-the-art approaches heavily relying on labeled experimental data, our method achieves equivalent or superior prediction …
Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environments, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore
Understanding Of Aerosol Transmission Of Covid 19 In Indoor Environments, Adama Barro, Cathal O'Toole, Jacob S. Lopez, Matthew Quinones, Sherene Moore
Publications and Research
Our reason for discussing severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) or 2019 novel corona virus (Covid-19), is to understand its aerosol transmission characteristics in indoor spaces and to mitigate further spread of this disease by designing a new HVAC system. The problem that we are tackling is the spread of covid-19 droplets through aerosol transmission by looking at potential engineering solutions to the existing HVAC systems. The purpose is to eradicate the spread of the COVID-19 by testing indoor spaces in an effort to understand the effectiveness of ventilation controls. We believe that scientists and engineers have not …
Open Data, Collaborative Working Platforms, And Interdisciplinary Collaboration: Building An Early Career Scientist Community Of Practice To Leverage Ocean Observatories Initiative Data To Address Critical Questions In Marine Science, Robert M. Levine, Kristen E. Fogaren, Johna E. Rudzin, Christopher J. Russoniello, Dax C. Soule, Justine M. Whitaker
Open Data, Collaborative Working Platforms, And Interdisciplinary Collaboration: Building An Early Career Scientist Community Of Practice To Leverage Ocean Observatories Initiative Data To Address Critical Questions In Marine Science, Robert M. Levine, Kristen E. Fogaren, Johna E. Rudzin, Christopher J. Russoniello, Dax C. Soule, Justine M. Whitaker
Publications and Research
Ocean observing systems are well-recognized as platforms for long-term monitoring of near-shore and remote locations in the global ocean. High-quality observatory data is freely available and accessible to all members of the global oceanographic community—a democratization of data that is particularly useful for early career scientists (ECS), enabling ECS to conduct research independent of traditional funding models or access to laboratory and field equipment. The concurrent collection of distinct data types with relevance for oceanographic disciplines including physics, chemistry, biology, and geology yields a unique incubator for cutting-edge, timely, interdisciplinary research. These data are both an opportunity and an incentive …
Protocol For A National Probability Survey Using Home Specimen Collection Methods To Assess Prevalence And Incidence Of Sars-Cov-2 Infection And Antibody Response, Aaron J. Siegler, Patrick S. Sullivan, Travis Sanchez, Ben Lopman, Mansour Fahimi, Charles Sailey, Martin Frankel, Richard Rothenberg, Colleen F. Kelley, Heather Bradley
Protocol For A National Probability Survey Using Home Specimen Collection Methods To Assess Prevalence And Incidence Of Sars-Cov-2 Infection And Antibody Response, Aaron J. Siegler, Patrick S. Sullivan, Travis Sanchez, Ben Lopman, Mansour Fahimi, Charles Sailey, Martin Frankel, Richard Rothenberg, Colleen F. Kelley, Heather Bradley
Publications and Research
Purpose: The U.S. response to the SARS-CoV-2 epidemic has been hampered by early and ongoing delays in testing for infection; without data on where infections were occurring and the magnitude of the epidemic, early public health responses were not data-driven. Understanding the prevalence of SARSCoV- 2 infections and immune response is critical to developing and implementing effective public health responses. Most serological surveys have been limited to localities that opted to conduct them and/or were based on convenience samples. Moreover, results of antibody testing might be subject to high false positive rates in the setting of low prevalence of immune …
Estimating Population Immunity Without Serological Testing, Andrew Lesniewski
Estimating Population Immunity Without Serological Testing, Andrew Lesniewski
Publications and Research
We propose an approximate methodology for estimating the overall level of immunity against COVID-19 in a population that has been affected by the recent epidemic. The methodology relies on the currently available mortality data and utilizes the properties of the SIR model. We illustrate the application of the method by estimating the recent levels of immunity in 10 US states with highest case numbers of COVID-19.
Impact Of Meteorological Factors On The Covid-19 Transmission: A Multicity Study In China, Jiangtao Liu, Ji Zhou, Jinxi Yao, Xiuxia Zhang, Lanyu Li, Xiaocheng Xu, Xiaotao He, Bo Wang, Shihua Fu, Tingting Niu, Jun Yan, Yanjun Shi, Xiaowei Ren, Jingping Niu, Weihao Zhu, Sheng Li, Bin Luo, Kai Zhang
Impact Of Meteorological Factors On The Covid-19 Transmission: A Multicity Study In China, Jiangtao Liu, Ji Zhou, Jinxi Yao, Xiuxia Zhang, Lanyu Li, Xiaocheng Xu, Xiaotao He, Bo Wang, Shihua Fu, Tingting Niu, Jun Yan, Yanjun Shi, Xiaowei Ren, Jingping Niu, Weihao Zhu, Sheng Li, Bin Luo, Kai Zhang
Publications and Research
The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID- 19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In …