Qi, Wenya; Seshaiyer, Padmanabhan; Wang, Junping A FOUR-FIELD MIXED FINITE ELEMENT METHOD FOR BIOT'S CONSOLIDATION PROBLEMS Journal Article ELECTRONIC RESEARCH ARCHIVE, 29 (3), pp. 2517-2532, 2021. @article{ISI:000644468500014, title = {A FOUR-FIELD MIXED FINITE ELEMENT METHOD FOR BIOT'S CONSOLIDATION PROBLEMS}, author = {Wenya Qi and Padmanabhan Seshaiyer and Junping Wang}, doi = {10.3934/era.2020127}, year = {2021}, date = {2021-08-01}, journal = {ELECTRONIC RESEARCH ARCHIVE}, volume = {29}, number = {3}, pages = {2517-2532}, abstract = {This article presents a four-field mixed finite element method for Biot's consolidation problems, where the four fields include the displacement, total stress, flux and pressure for the porous medium component of the modeling system. The mixed finite element method involving Raviart-Thomas element is used for the fluid flow equation, while the Crank-Nicolson scheme is employed for the time discretization. The main contribution of this work is the derivation of the optimal order error estimates for semi-discrete and fully-discrete schemes for the unknowns in energy norm or L-2 norm. Numerical experiments are presented to validate the theoretical results.}, keywords = {}, pubstate = {published}, tppubtype = {article} } This article presents a four-field mixed finite element method for Biot's consolidation problems, where the four fields include the displacement, total stress, flux and pressure for the porous medium component of the modeling system. The mixed finite element method involving Raviart-Thomas element is used for the fluid flow equation, while the Crank-Nicolson scheme is employed for the time discretization. The main contribution of this work is the derivation of the optimal order error estimates for semi-discrete and fully-discrete schemes for the unknowns in energy norm or L-2 norm. Numerical experiments are presented to validate the theoretical results. |
Zhong, Shaobo; Sun, Ziheng; Di, Liping Characteristics of vegetation response to drought in the CONUS based on long-term remote sensing and meteorological data Journal Article ECOLOGICAL INDICATORS, 127 , 2021, ISSN: 1470-160X. @article{ISI:000659186200003, title = {Characteristics of vegetation response to drought in the CONUS based on long-term remote sensing and meteorological data}, author = {Shaobo Zhong and Ziheng Sun and Liping Di}, doi = {10.1016/j.ecolind.2021.107767}, issn = {1470-160X}, year = {2021}, date = {2021-08-01}, journal = {ECOLOGICAL INDICATORS}, volume = {127}, abstract = {Drought is one of the billion-dollar natural disasters and hard to trace and measure. In recent years drought monitoring becomes much easier with remote sensing. However, it is still difficult to pin vegetation variances on drought because of the delay of the caused vegetation stress. To assess vegetative drought, it is important to first understand the relationship between meteorological condition and vegetation condition, and measure the vegetation responses to meteorological drought. It would be very helpful for effective early warning about agricultural drought. This study uses the CONUS as the study area, and utilizes remote sensing products such as NDVI/VCI (normalized difference vegetation index/vegetation condition index) and SPI/SPEI (standardized precipitation index/standardized precipitation evapotranspiration index) to give a comparative evaluation to the vegetation's drought response. The used vegetation products and meteorological data are ensured to be consistent. The scale and lag of vegetation response to drought for various vegetation types and aridity levels were thoroughly investigated. The results show that: The AVHRR and MODIS NDVI series pairs and the meteorological drought index series pairs (SPEI and SPI) have fairly good consistencies. Among them, 69.5% and 84% have rho (correlation coefficient) values greater than 0.8 respectively. For the NDVI series pairs, the maximum rho value is 0.98, the minimum rho value is -0.47, and the mean rho value is 0.79, which are 0.97, 0.68, and 0.87 respectively for the meteorological index series pairs. Compared to rho values of the meteorological index series pairs, the rho values of the NDVI series pairs have more outliers indicating instability. The correlation between SPEI and VCI significantly relies on time lags and has high spatial inhomogeneity. 1- and 2-month lags of SPEI have more significant positive correlation with VCI in Arid, Semi-Arid and Dry sub-humid areas of central west CONUS with less precipitation and lower temperature. For various time scales (time scale is SPEI reference range), the most significant positive correlation between SPEI and VCI happens in the time scales of 6- to 12month in summer, the time scales of 3- and 6-month in spring and autumn, and the time scales of 2- and 3month in winter regardless of time lags. Despite of the different vegetation types and aridity levels, the maximum correlations between SPEI and VCI are observed in Hyper arid regions in January, Arid regions in April, Semi-arid regions in July, and Dry sub-humid regions in October. Shrub has prominent responses in January and April, grass responses appear in July and October, and Evergreen forest shows least responses in all seasons. The results add more insights of the connection between vegetation and climate, and guide the development of new technology leveraging remote sensing data for vegetation drought monitoring and earlywarning. The results are also helpful to provide important references for studying large-scale physiological and phenological properties of the vegetation under different climate conditions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Drought is one of the billion-dollar natural disasters and hard to trace and measure. In recent years drought monitoring becomes much easier with remote sensing. However, it is still difficult to pin vegetation variances on drought because of the delay of the caused vegetation stress. To assess vegetative drought, it is important to first understand the relationship between meteorological condition and vegetation condition, and measure the vegetation responses to meteorological drought. It would be very helpful for effective early warning about agricultural drought. This study uses the CONUS as the study area, and utilizes remote sensing products such as NDVI/VCI (normalized difference vegetation index/vegetation condition index) and SPI/SPEI (standardized precipitation index/standardized precipitation evapotranspiration index) to give a comparative evaluation to the vegetation's drought response. The used vegetation products and meteorological data are ensured to be consistent. The scale and lag of vegetation response to drought for various vegetation types and aridity levels were thoroughly investigated. The results show that: The AVHRR and MODIS NDVI series pairs and the meteorological drought index series pairs (SPEI and SPI) have fairly good consistencies. Among them, 69.5% and 84% have rho (correlation coefficient) values greater than 0.8 respectively. For the NDVI series pairs, the maximum rho value is 0.98, the minimum rho value is -0.47, and the mean rho value is 0.79, which are 0.97, 0.68, and 0.87 respectively for the meteorological index series pairs. Compared to rho values of the meteorological index series pairs, the rho values of the NDVI series pairs have more outliers indicating instability. The correlation between SPEI and VCI significantly relies on time lags and has high spatial inhomogeneity. 1- and 2-month lags of SPEI have more significant positive correlation with VCI in Arid, Semi-Arid and Dry sub-humid areas of central west CONUS with less precipitation and lower temperature. For various time scales (time scale is SPEI reference range), the most significant positive correlation between SPEI and VCI happens in the time scales of 6- to 12month in summer, the time scales of 3- and 6-month in spring and autumn, and the time scales of 2- and 3month in winter regardless of time lags. Despite of the different vegetation types and aridity levels, the maximum correlations between SPEI and VCI are observed in Hyper arid regions in January, Arid regions in April, Semi-arid regions in July, and Dry sub-humid regions in October. Shrub has prominent responses in January and April, grass responses appear in July and October, and Evergreen forest shows least responses in all seasons. The results add more insights of the connection between vegetation and climate, and guide the development of new technology leveraging remote sensing data for vegetation drought monitoring and earlywarning. The results are also helpful to provide important references for studying large-scale physiological and phenological properties of the vegetation under different climate conditions. |
Park, Minkyung; Jones, Tina Going Virtual: The Impact of COVID-19 on Internships in Tourism, Events, and Hospitality Education Journal Article JOURNAL OF HOSPITALITY & TOURISM EDUCATION, 33 (3, SI), pp. 176-193, 2021, ISSN: 1096-3758. @article{ISI:000637273200001, title = {Going Virtual: The Impact of COVID-19 on Internships in Tourism, Events, and Hospitality Education}, author = {Minkyung Park and Tina Jones}, doi = {10.1080/10963758.2021.1907198, Early Access Date = APR 2021}, issn = {1096-3758}, year = {2021}, date = {2021-07-01}, journal = {JOURNAL OF HOSPITALITY & TOURISM EDUCATION}, volume = {33}, number = {3, SI}, pages = {176-193}, abstract = {This study explored virtual internship practices and the adaptation to changes brought by the current COVID-19 pandemic crisis by interviewing a small group of interns and site supervisors to understand how virtual internships were practiced in the wake of COVID-19. The findings of the study provided several insights into virtual internships. Overall, just like the conventional fieldwork, well-planned and designed virtual internships could be an empowering learning experience that allows students to capitalize on the practical strengths while applying classroom learning experiences to actual management situations. The study also discussed the advantages and challenges of virtual internships perceived by the student interns. The implications of the study and suggestions for future research were addressed.}, keywords = {}, pubstate = {published}, tppubtype = {article} } This study explored virtual internship practices and the adaptation to changes brought by the current COVID-19 pandemic crisis by interviewing a small group of interns and site supervisors to understand how virtual internships were practiced in the wake of COVID-19. The findings of the study provided several insights into virtual internships. Overall, just like the conventional fieldwork, well-planned and designed virtual internships could be an empowering learning experience that allows students to capitalize on the practical strengths while applying classroom learning experiences to actual management situations. The study also discussed the advantages and challenges of virtual internships perceived by the student interns. The implications of the study and suggestions for future research were addressed. |
Aslani, Babak; Mohebbi, Shima; Axthelm, Hana Predictive analytics for water main breaks using spatiotemporal data Journal Article URBAN WATER JOURNAL, 18 (6), pp. 433-448, 2021, ISSN: 1573-062X. @article{ISI:000627018400001, title = {Predictive analytics for water main breaks using spatiotemporal data}, author = {Babak Aslani and Shima Mohebbi and Hana Axthelm}, doi = {10.1080/1573062X.2021.1893363, Early Access Date = MAR 2021}, issn = {1573-062X}, year = {2021}, date = {2021-07-01}, journal = {URBAN WATER JOURNAL}, volume = {18}, number = {6}, pages = {433-448}, abstract = {Water main breaks are a common recurring problem in water distribution networks, resulting in cascading effects in the whole system and the interconnected infrastructures such as transportation. Having integrated the physical features of pipes such as diameter and environmental factors like precipitation, we propose predictive models based on spatiotemporal data and machine learning methods. In this study, the dataset is the main breaks recorded from 2015 to 2020 in the city of Tampa, Florida. First, a spatial clustering is conducted to identify vulnerable areas to breaks. A time series analysis is also carried out for the temporal data. The result of these analyses informed the machine learning algorithms as independent variables. We then compared the predictive models based on information-based and rank-based criteria. Obtained results indicated that Boosted Regression Tree (BRT) model was superior to the others. Finally, we present predicted normalized failure rates for the water distribution network to inform rehabilitation and fortification decisions at the municipality level.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Water main breaks are a common recurring problem in water distribution networks, resulting in cascading effects in the whole system and the interconnected infrastructures such as transportation. Having integrated the physical features of pipes such as diameter and environmental factors like precipitation, we propose predictive models based on spatiotemporal data and machine learning methods. In this study, the dataset is the main breaks recorded from 2015 to 2020 in the city of Tampa, Florida. First, a spatial clustering is conducted to identify vulnerable areas to breaks. A time series analysis is also carried out for the temporal data. The result of these analyses informed the machine learning algorithms as independent variables. We then compared the predictive models based on information-based and rank-based criteria. Obtained results indicated that Boosted Regression Tree (BRT) model was superior to the others. Finally, we present predicted normalized failure rates for the water distribution network to inform rehabilitation and fortification decisions at the municipality level. |
Akerlof, Karen L; Bromser-Kloeden, Taryn; Timm, Kristin; Rowan, Katherine E; Olds, James L; Clarke, Chris; Rohring, Elizabeth Ban; Cloyd, Emily Therese; Curran, K; Duesterhoeft, Elizabeth C; Farooque, Mahmud; Goldman, Erica; Gring-Pemble, Lisa; Hampton, Stephanie E; Kim, Sojung Claire; Kotcher, John; Milligan, Darren; Brenes, Carlos Munoz L; Sandoval, Cynthia; Sklarew, Dann; Smith, Cynthia; Suhay, Elizabeth; Tomblin, David; Upperman, Crystal; Wingfield, Andrew; Zhao, Xiaoquan Categorizing Professionals' Perspectives on Environmental Communication with Implications for Graduate Education Journal Article ENVIRONMENTAL COMMUNICATION-A JOURNAL OF NATURE AND CULTURE, 15 (4), pp. 447-464, 2021, ISSN: 1752-4032. @article{ISI:000605692500001, title = {Categorizing Professionals' Perspectives on Environmental Communication with Implications for Graduate Education}, author = {Karen L Akerlof and Taryn Bromser-Kloeden and Kristin Timm and Katherine E Rowan and James L Olds and Chris Clarke and Elizabeth Ban Rohring and Emily Therese Cloyd and K Curran and Elizabeth C Duesterhoeft and Mahmud Farooque and Erica Goldman and Lisa Gring-Pemble and Stephanie E Hampton and Sojung Claire Kim and John Kotcher and Darren Milligan and Carlos L Munoz Brenes and Cynthia Sandoval and Dann Sklarew and Cynthia Smith and Elizabeth Suhay and David Tomblin and Crystal Upperman and Andrew Wingfield and Xiaoquan Zhao}, doi = {10.1080/17524032.2020.1862890, Early Access Date = JAN 2021}, issn = {1752-4032}, year = {2021}, date = {2021-05-01}, journal = {ENVIRONMENTAL COMMUNICATION-A JOURNAL OF NATURE AND CULTURE}, volume = {15}, number = {4}, pages = {447-464}, abstract = {The study of environmental communication originated as a diverse multidisciplinary field encompassing a wide array of communicator perspectives. However, as the field evolved, mass media and journalism became its perceived scholarly focus. As a result, environmental communication processes may be less well-understood across other settings, such as scientific and research institutions, non-governmental organizations, and federal agencies. To understand how communicators describe their goals, ethics, and strategies within these contexts, we conducted a three-part study of researchers and practitioners working on environmental issues in the Washington, DC, region between October 2019 and January 2020. Employing Q methodology, we identified four distinct perspectives: capacity-builders, translators, policy and decision-supporters, and cultural changemakers. Each of these perspectives is associated with a different range of goals, ethics, and strategic approaches. We describe graduate educational competencies for each of the perspectives and discuss implications for the design of communication research to meet practitioners' needs.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The study of environmental communication originated as a diverse multidisciplinary field encompassing a wide array of communicator perspectives. However, as the field evolved, mass media and journalism became its perceived scholarly focus. As a result, environmental communication processes may be less well-understood across other settings, such as scientific and research institutions, non-governmental organizations, and federal agencies. To understand how communicators describe their goals, ethics, and strategies within these contexts, we conducted a three-part study of researchers and practitioners working on environmental issues in the Washington, DC, region between October 2019 and January 2020. Employing Q methodology, we identified four distinct perspectives: capacity-builders, translators, policy and decision-supporters, and cultural changemakers. Each of these perspectives is associated with a different range of goals, ethics, and strategic approaches. We describe graduate educational competencies for each of the perspectives and discuss implications for the design of communication research to meet practitioners' needs. |
Qi, Wenya; Seshaiyer, Padmanabhan; Wang, Junping Finite element method with the total stress variable for Biot's consolidation model Journal Article NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS, 37 (3), pp. 2409-2428, 2021, ISSN: 0749-159X. @article{ISI:000599436800001, title = {Finite element method with the total stress variable for Biot's consolidation model}, author = {Wenya Qi and Padmanabhan Seshaiyer and Junping Wang}, doi = {10.1002/num.22721, Early Access Date = DEC 2020}, issn = {0749-159X}, year = {2021}, date = {2021-05-01}, journal = {NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS}, volume = {37}, number = {3}, pages = {2409-2428}, abstract = {In this work, semi-discrete and fully discrete error estimates are derived for the Biot's consolidation model described using a three-field finite element formulation. These fields include displacements, total stress and pressure. The model is implemented using a backward Euler discretization in time for the fully discrete scheme and validated for benchmark examples. Computational experiments are presented to verify the convergence orders for two finite elements with discontinuous and continuous approximations for the total stress.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In this work, semi-discrete and fully discrete error estimates are derived for the Biot's consolidation model described using a three-field finite element formulation. These fields include displacements, total stress and pressure. The model is implemented using a backward Euler discretization in time for the fully discrete scheme and validated for benchmark examples. Computational experiments are presented to verify the convergence orders for two finite elements with discontinuous and continuous approximations for the total stress. |
Gewa, Constance Awuor; Onyango, Agatha Christine; Opiyo, Rose Okoyo; Cheskin, Lawrence; Gittelsohn, Joel Food Environment in and around Primary School Children's Schools and Neighborhoods in Two Urban Settings in Kenya Journal Article INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 18 (10), 2021. @article{ISI:000654970900001, title = {Food Environment in and around Primary School Children's Schools and Neighborhoods in Two Urban Settings in Kenya}, author = {Constance Awuor Gewa and Agatha Christine Onyango and Rose Okoyo Opiyo and Lawrence Cheskin and Joel Gittelsohn}, doi = {10.3390/ijerph18105136}, year = {2021}, date = {2021-05-01}, journal = {INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH}, volume = {18}, number = {10}, abstract = {We conducted a cross-sectional study to provide an overview primary school children food environment in two urban settings in Kenya. Six schools, catering to children from low-, medium- and high-income households in the cities of Nairobi and Kisumu in Kenya, participated in the study. Data on types of food places and foods offered were collected and healthy and unhealthy food availability scores calculated for each place. We utilized prevalence ratio analysis to examine associations between food availability, food place characteristics and neighborhood income levels. Altogether, 508 food places, located within 1 km of the schools and the school children's neighborhoods were observed. Open-air market sellers and kiosks were most common. The proportion of food places with high healthy food availability was 2.2 times greater among food places in Nairobi compared to Kisumu, 1.9 times greater in food places with multiple cashpoints, 1.7 times greater in medium/large sized food places and 1.4 times greater in food places located in high income neighborhoods. These findings highlight differences in availability of healthy foods and unhealthy foods across types of food places and neighborhood income levels and inform public health interventions aimed at promoting healthy food environments in Kenya.}, keywords = {}, pubstate = {published}, tppubtype = {article} } We conducted a cross-sectional study to provide an overview primary school children food environment in two urban settings in Kenya. Six schools, catering to children from low-, medium- and high-income households in the cities of Nairobi and Kisumu in Kenya, participated in the study. Data on types of food places and foods offered were collected and healthy and unhealthy food availability scores calculated for each place. We utilized prevalence ratio analysis to examine associations between food availability, food place characteristics and neighborhood income levels. Altogether, 508 food places, located within 1 km of the schools and the school children's neighborhoods were observed. Open-air market sellers and kiosks were most common. The proportion of food places with high healthy food availability was 2.2 times greater among food places in Nairobi compared to Kisumu, 1.9 times greater in food places with multiple cashpoints, 1.7 times greater in medium/large sized food places and 1.4 times greater in food places located in high income neighborhoods. These findings highlight differences in availability of healthy foods and unhealthy foods across types of food places and neighborhood income levels and inform public health interventions aimed at promoting healthy food environments in Kenya. |
Furst, Kirin E; Bolorinos, Jose; Mitch, William A Use of trihalomethanes as a surrogate for haloacetonitrile exposure introduces misclassification bias Journal Article WATER RESEARCH X, 11 , 2021. @article{ISI:000647799000005, title = {Use of trihalomethanes as a surrogate for haloacetonitrile exposure introduces misclassification bias}, author = {Kirin E Furst and Jose Bolorinos and William A Mitch}, doi = {10.1016/j.wroa.2021.100089}, year = {2021}, date = {2021-05-01}, journal = {WATER RESEARCH X}, volume = {11}, abstract = {Epidemiologists have used trihalomethanes (THMs) as a surrogate for overall disinfection byproduct (DBP) exposure based on the assumption that THM concentrations are proportional to concentrations of other DBP classes. Toxicological evidence indicates THMs are less potent toxins than unregulated classes like haloacetonitriles (HANs). If THMs are not proportional to the DBPs driving toxicity, the use of THMs to measure exposure may introduce non-trivial exposure misclassification bias in epidemiologic studies. This study developed statistical models to evaluate the covariance and proportionality of HAN and THM concentrations in a dataset featuring over 9500 measurements from 248 public water systems. THMs only explain-30% of the variance in HANs, whether the data is pooled in a classic linear regression or hierarchically grouped by water system in a multilevel linear regression. The 95% prediction interval on HANs for the median THM concentration exceeds the interquartile range of HANs. Mean HAN:THM ratios range from -2.4% to-80% across water systems, and varied with source water category, season, disinfectant sequence and distribution system location. The HAN:THM ratio was 265% higher in groundwater systems than in surface water systems and declined by-40% between finished effluent and maximum residence times in surface water systems with chlorine-chlorine disinfection. A maximum likelihood approach was used to estimate the misclassification bias that may result from using THMs to construct risk-ratios, assuming that HANs represent the ``true'' DBP exposure risk. The results indicate an odds ratio of -2 estimated with THM concentrations could correspond to a true odds ratio of 4-5. These findings demonstrate the need for epidemiologic studies to evaluate exposure by measuring DBPs that are likely to drive toxicity. (C) 2021 The Author(s). Published by Elsevier Ltd.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Epidemiologists have used trihalomethanes (THMs) as a surrogate for overall disinfection byproduct (DBP) exposure based on the assumption that THM concentrations are proportional to concentrations of other DBP classes. Toxicological evidence indicates THMs are less potent toxins than unregulated classes like haloacetonitriles (HANs). If THMs are not proportional to the DBPs driving toxicity, the use of THMs to measure exposure may introduce non-trivial exposure misclassification bias in epidemiologic studies. This study developed statistical models to evaluate the covariance and proportionality of HAN and THM concentrations in a dataset featuring over 9500 measurements from 248 public water systems. THMs only explain-30% of the variance in HANs, whether the data is pooled in a classic linear regression or hierarchically grouped by water system in a multilevel linear regression. The 95% prediction interval on HANs for the median THM concentration exceeds the interquartile range of HANs. Mean HAN:THM ratios range from -2.4% to-80% across water systems, and varied with source water category, season, disinfectant sequence and distribution system location. The HAN:THM ratio was 265% higher in groundwater systems than in surface water systems and declined by-40% between finished effluent and maximum residence times in surface water systems with chlorine-chlorine disinfection. A maximum likelihood approach was used to estimate the misclassification bias that may result from using THMs to construct risk-ratios, assuming that HANs represent the ``true'' DBP exposure risk. The results indicate an odds ratio of -2 estimated with THM concentrations could correspond to a true odds ratio of 4-5. These findings demonstrate the need for epidemiologic studies to evaluate exposure by measuring DBPs that are likely to drive toxicity. (C) 2021 The Author(s). Published by Elsevier Ltd. |
Dabbagh, Deemah; He, Sijia; Hetrick, Brian; Chilin, Linda; Andalibi, Ali; Wu, Yuntao Identification of the SHREK Family of Proteins as Broad-Spectrum Host Antiviral Factors Journal Article VIRUSES-BASEL, 13 (5), 2021. @article{ISI:000654574000001, title = {Identification of the SHREK Family of Proteins as Broad-Spectrum Host Antiviral Factors}, author = {Deemah Dabbagh and Sijia He and Brian Hetrick and Linda Chilin and Ali Andalibi and Yuntao Wu}, doi = {10.3390/v13050832}, year = {2021}, date = {2021-05-01}, journal = {VIRUSES-BASEL}, volume = {13}, number = {5}, abstract = {Mucins and mucin-like molecules are highly glycosylated, high-molecular-weight cell surface proteins that possess a semi-rigid and highly extended extracellular domain. P-selectin glycoprotein ligand-1 (PSGL-1), a mucin-like glycoprotein, has recently been found to restrict HIV-1 infectivity through virion incorporation that sterically hinders virus particle attachment to target cells. Here, we report the identification of a family of antiviral cellular proteins, named the Surface-Hinged, Rigidly-Extended Killer (SHREK) family of virion inactivators (PSGL-1, CD43, TIM-1, CD34, PODXL1, PODXL2, CD164, MUC1, MUC4, and TMEM123) that share similar structural characteristics with PSGL-1. We demonstrate that SHREK proteins block HIV-1 infectivity by inhibiting virus particle attachment to target cells. In addition, we demonstrate that SHREK proteins are broad-spectrum host antiviral factors that block the infection of diverse viruses such as influenza A. Furthermore, we demonstrate that a subset of SHREKs also blocks the infectivity of a hybrid alphavirus-SARS-CoV-2 (Ha-CoV-2) pseudovirus. These results suggest that SHREK proteins may be a part of host innate immunity against enveloped viruses.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Mucins and mucin-like molecules are highly glycosylated, high-molecular-weight cell surface proteins that possess a semi-rigid and highly extended extracellular domain. P-selectin glycoprotein ligand-1 (PSGL-1), a mucin-like glycoprotein, has recently been found to restrict HIV-1 infectivity through virion incorporation that sterically hinders virus particle attachment to target cells. Here, we report the identification of a family of antiviral cellular proteins, named the Surface-Hinged, Rigidly-Extended Killer (SHREK) family of virion inactivators (PSGL-1, CD43, TIM-1, CD34, PODXL1, PODXL2, CD164, MUC1, MUC4, and TMEM123) that share similar structural characteristics with PSGL-1. We demonstrate that SHREK proteins block HIV-1 infectivity by inhibiting virus particle attachment to target cells. In addition, we demonstrate that SHREK proteins are broad-spectrum host antiviral factors that block the infection of diverse viruses such as influenza A. Furthermore, we demonstrate that a subset of SHREKs also blocks the infectivity of a hybrid alphavirus-SARS-CoV-2 (Ha-CoV-2) pseudovirus. These results suggest that SHREK proteins may be a part of host innate immunity against enveloped viruses. |
Lanoue, Matthew; Bollmann, Chad A; Michael, James Bret; Roth, John; Wijesekera, Duminda An Attack Vector Taxonomy for Mobile Telephony Security Vulnerabilities Journal Article COMPUTER, 54 (4), pp. 76-84, 2021, ISSN: 0018-9162. @article{ISI:000639652000012, title = {An Attack Vector Taxonomy for Mobile Telephony Security Vulnerabilities}, author = {Matthew Lanoue and Chad A Bollmann and James Bret Michael and John Roth and Duminda Wijesekera}, doi = {10.1109/MC.2021.3057059}, issn = {0018-9162}, year = {2021}, date = {2021-04-01}, journal = {COMPUTER}, volume = {54}, number = {4}, pages = {76-84}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Zhou, Chenhao; Xu, Jie; Miller-Hooks, Elise; Zhou, Weiwen; Chen, Chun-Hung; Lee, Loo Hay; Chew, Ek Peng; Li, Haobin Analytics with digital-twinning: A decision support system for maintaining a resilient port Journal Article DECISION SUPPORT SYSTEMS, 143 , 2021, ISSN: 0167-9236. @article{ISI:000634866100002, title = {Analytics with digital-twinning: A decision support system for maintaining a resilient port}, author = {Chenhao Zhou and Jie Xu and Elise Miller-Hooks and Weiwen Zhou and Chun-Hung Chen and Loo Hay Lee and Ek Peng Chew and Haobin Li}, doi = {10.1016/j.dss.2021.113496}, issn = {0167-9236}, year = {2021}, date = {2021-04-01}, journal = {DECISION SUPPORT SYSTEMS}, volume = {143}, abstract = {In this paper, a Decision Support System (DSS) with digital twinning-based resilience analysis is proposed as a modern tool for port resilience computation and updating. The proposed DSS assesses the resilience of a port under possible disruptive events given its design, operations and potential pre-defined post-event recovery actions to mitigate the impact of the disruption. Digital twinning provides the fidelity required to realistically predict port performance with taken post-event recovery actions under various possible disruptive events. In addition to hedging against impacts from probabilistically known disruption events, this approach also enables inclusion of ordinary operational uncertainties within the resilience evaluation. This is not generally feasible with other existing resilience quantification approaches. To tackle computational challenges of applying a digital twin for real-world size applications, an optimal computing budget allocation policy is adopted to improve computational efficiency. Results of numerical experiments using a real-world size port demonstrate the effectiveness of the proposed DSS and criticality of accounting for ordinary uncertainties in operations in resilience estimation.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In this paper, a Decision Support System (DSS) with digital twinning-based resilience analysis is proposed as a modern tool for port resilience computation and updating. The proposed DSS assesses the resilience of a port under possible disruptive events given its design, operations and potential pre-defined post-event recovery actions to mitigate the impact of the disruption. Digital twinning provides the fidelity required to realistically predict port performance with taken post-event recovery actions under various possible disruptive events. In addition to hedging against impacts from probabilistically known disruption events, this approach also enables inclusion of ordinary operational uncertainties within the resilience evaluation. This is not generally feasible with other existing resilience quantification approaches. To tackle computational challenges of applying a digital twin for real-world size applications, an optimal computing budget allocation policy is adopted to improve computational efficiency. Results of numerical experiments using a real-world size port demonstrate the effectiveness of the proposed DSS and criticality of accounting for ordinary uncertainties in operations in resilience estimation. |
Ji, Ran; Lejeune, Miguel A Data-driven distributionally robust chance-constrained optimization with Wasserstein metric Journal Article JOURNAL OF GLOBAL OPTIMIZATION, 79 (4), pp. 779-811, 2021, ISSN: 0925-5001. @article{ISI:000590007300001, title = {Data-driven distributionally robust chance-constrained optimization with Wasserstein metric}, author = {Ran Ji and Miguel A Lejeune}, doi = {10.1007/s10898-020-00966-0, Early Access Date = NOV 2020}, issn = {0925-5001}, year = {2021}, date = {2021-04-01}, journal = {JOURNAL OF GLOBAL OPTIMIZATION}, volume = {79}, number = {4}, pages = {779-811}, abstract = {We study distributionally robust chance-constrained programming (DRCCP) optimization problems with data-driven Wasserstein ambiguity sets. The proposed algorithmic and reformulation framework applies to all types of distributionally robust chance-constrained optimization problems subjected to individual as well as joint chance constraints, with random right-hand side and technology vector, and under two types of uncertainties, called uncertain probabilities and continuum of realizations. For the uncertain probabilities (UP) case, we provide new mixed-integer linear programming reformulations for DRCCP problems. For the continuum of realizations case with random right-hand side, we propose an exact mixed-integer second-order cone programming (MISOCP) reformulation and a linear programming (LP) outer approximation. For the continuum of realizations (CR) case with random technology vector, we propose two MISOCP and LP outer approximations. We show that all proposed relaxations become exact reformulations when the decision variables are binary or bounded general integers. For DRCCP with individual chance constraint and random right-hand side under both the UP and CR cases, we also propose linear programming reformulations which need the ex-ante derivation of the worst-case value-at-risk via the solution of a finite series of linear programs determined via a bisection-type procedure. We evaluate the scalability and tightness of the proposed MISOCP and (MI)LP formulations on a distributionally robust chance-constrained knapsack problem.}, keywords = {}, pubstate = {published}, tppubtype = {article} } We study distributionally robust chance-constrained programming (DRCCP) optimization problems with data-driven Wasserstein ambiguity sets. The proposed algorithmic and reformulation framework applies to all types of distributionally robust chance-constrained optimization problems subjected to individual as well as joint chance constraints, with random right-hand side and technology vector, and under two types of uncertainties, called uncertain probabilities and continuum of realizations. For the uncertain probabilities (UP) case, we provide new mixed-integer linear programming reformulations for DRCCP problems. For the continuum of realizations case with random right-hand side, we propose an exact mixed-integer second-order cone programming (MISOCP) reformulation and a linear programming (LP) outer approximation. For the continuum of realizations (CR) case with random technology vector, we propose two MISOCP and LP outer approximations. We show that all proposed relaxations become exact reformulations when the decision variables are binary or bounded general integers. For DRCCP with individual chance constraint and random right-hand side under both the UP and CR cases, we also propose linear programming reformulations which need the ex-ante derivation of the worst-case value-at-risk via the solution of a finite series of linear programs determined via a bisection-type procedure. We evaluate the scalability and tightness of the proposed MISOCP and (MI)LP formulations on a distributionally robust chance-constrained knapsack problem. |
Cassalho, Felicio; Miesse, Tyler W; de Lima, Andre S; Khalid, Arslaan; Ferreira, Celso M; Sutton-Grier, Ariana E Coastal Wetlands Exposure to Storm Surge and Waves in the Albemarle-Pamlico Estuarine System during Extreme Events Journal Article WETLANDS, 41 (4), 2021, ISSN: 0277-5212. @article{ISI:000639785800002, title = {Coastal Wetlands Exposure to Storm Surge and Waves in the Albemarle-Pamlico Estuarine System during Extreme Events}, author = {Felicio Cassalho and Tyler W Miesse and Andre S de Lima and Arslaan Khalid and Celso M Ferreira and Ariana E Sutton-Grier}, doi = {10.1007/s13157-021-01443-4}, issn = {0277-5212}, year = {2021}, date = {2021-04-01}, journal = {WETLANDS}, volume = {41}, number = {4}, abstract = {Coastal wetlands provide a series of ecosystem services, including flood risk reduction. However, the flood risk reduction from such a complex ecosystem is dependent on incoming extreme hurricane-driven hydrodynamic and wave conditions. This study develops a numerical modeling-based approach for investigating coastal wetlands exposure to storm surge and waves during hurricanes by combining maximum water depth (MWD) and significant wave height (MHs) model outputs with the National Wetland Inventory for the Albemarle-Pamlico Estuarine System. Results show that various hurricanes lead to similar bimodal and bidirectional spatiotemporal flood patterns as a function of the lagoon's geometry and storm track, with most overland hydrodynamic extremes impacting western Pamlico Sound and the bayside-Outer Banks. Clear positive dependency between MWD and MHS were observed over most wetland classes, with significantly higher magnitudes over estuarine emergent vegetation. In contrast to MWD, sharp MHS attenuation was found as the water propagates inland, leading to high MWD but lower MHS eventually reaching palustrine woody vegetation hundreds of meters away from the coastline. Improved understanding of how storm surge dynamics move across the bays and through the different wetland types, demonstrates the importance of considering the bay-side flood impacts over the coastal vegetation. The spatially distributed MWD and MHS estimates, along with the temporal patterns identified through the use of the T-Max, allow coastal managers and engineers to better understand where, when, and by how much, the estuarine APES wetlands are more likely to be exposed to high water depths and waves.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Coastal wetlands provide a series of ecosystem services, including flood risk reduction. However, the flood risk reduction from such a complex ecosystem is dependent on incoming extreme hurricane-driven hydrodynamic and wave conditions. This study develops a numerical modeling-based approach for investigating coastal wetlands exposure to storm surge and waves during hurricanes by combining maximum water depth (MWD) and significant wave height (MHs) model outputs with the National Wetland Inventory for the Albemarle-Pamlico Estuarine System. Results show that various hurricanes lead to similar bimodal and bidirectional spatiotemporal flood patterns as a function of the lagoon's geometry and storm track, with most overland hydrodynamic extremes impacting western Pamlico Sound and the bayside-Outer Banks. Clear positive dependency between MWD and MHS were observed over most wetland classes, with significantly higher magnitudes over estuarine emergent vegetation. In contrast to MWD, sharp MHS attenuation was found as the water propagates inland, leading to high MWD but lower MHS eventually reaching palustrine woody vegetation hundreds of meters away from the coastline. Improved understanding of how storm surge dynamics move across the bays and through the different wetland types, demonstrates the importance of considering the bay-side flood impacts over the coastal vegetation. The spatially distributed MWD and MHS estimates, along with the temporal patterns identified through the use of the T-Max, allow coastal managers and engineers to better understand where, when, and by how much, the estuarine APES wetlands are more likely to be exposed to high water depths and waves. |
Xiong, Quan; Di, Liping; Feng, Quanlong; Liu, Diyou; Liu, Wei; Zan, Xuli; Zhang, Lin; Zhu, Dehai; Liu, Zhe; Yao, Xiaochuang; Zhang, Xiaodong REMOTE SENSING, 13 (8), 2021. @article{ISI:000644671400001, title = {Deriving Non-Cloud Contaminated Sentinel-2 Images with RGB and Near-Infrared Bands from Sentinel-1 Images Based on a Conditional Generative Adversarial Network}, author = {Quan Xiong and Liping Di and Quanlong Feng and Diyou Liu and Wei Liu and Xuli Zan and Lin Zhang and Dehai Zhu and Zhe Liu and Xiaochuang Yao and Xiaodong Zhang}, doi = {10.3390/rs13081512}, year = {2021}, date = {2021-04-01}, journal = {REMOTE SENSING}, volume = {13}, number = {8}, abstract = {Sentinel-2 images have been widely used in studying land surface phenomena and processes, but they inevitably suffer from cloud contamination. To solve this critical optical data availability issue, it is ideal to fuse Sentinel-1 and Sentinel-2 images to create fused, cloud-free Sentinel-2-like images for facilitating land surface applications. In this paper, we propose a new data fusion model, the Multi-channels Conditional Generative Adversarial Network (MCcGAN), based on the conditional generative adversarial network, which is able to convert images from Domain A to Domain B. With the model, we were able to generate fused, cloud-free Sentinel-2-like images for a target date by using a pair of reference Sentinel-1/Sentinel-2 images and target-date Sentinel-1 images as inputs. In order to demonstrate the superiority of our method, we also compared it with other state-of-the-art methods using the same data. To make the evaluation more objective and reliable, we calculated the root-mean-square-error (RSME), R2, Kling-Gupta efficiency (KGE), structural similarity index (SSIM), spectral angle mapper (SAM), and peak signal-to-noise ratio (PSNR) of the simulated Sentinel-2 images generated by different methods. The results show that the simulated Sentinel-2 images generated by the MCcGAN have a higher quality and accuracy than those produced via the previous methods.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Sentinel-2 images have been widely used in studying land surface phenomena and processes, but they inevitably suffer from cloud contamination. To solve this critical optical data availability issue, it is ideal to fuse Sentinel-1 and Sentinel-2 images to create fused, cloud-free Sentinel-2-like images for facilitating land surface applications. In this paper, we propose a new data fusion model, the Multi-channels Conditional Generative Adversarial Network (MCcGAN), based on the conditional generative adversarial network, which is able to convert images from Domain A to Domain B. With the model, we were able to generate fused, cloud-free Sentinel-2-like images for a target date by using a pair of reference Sentinel-1/Sentinel-2 images and target-date Sentinel-1 images as inputs. In order to demonstrate the superiority of our method, we also compared it with other state-of-the-art methods using the same data. To make the evaluation more objective and reliable, we calculated the root-mean-square-error (RSME), R2, Kling-Gupta efficiency (KGE), structural similarity index (SSIM), spectral angle mapper (SAM), and peak signal-to-noise ratio (PSNR) of the simulated Sentinel-2 images generated by different methods. The results show that the simulated Sentinel-2 images generated by the MCcGAN have a higher quality and accuracy than those produced via the previous methods. |
Xiang, Tianyi; Gerber, Brian J; Zhang, Fengxiu Language access in emergency and disaster preparedness: An assessment of local government ? whole community ? efforts in the United States Journal Article INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 55 , 2021, ISSN: 2212-4209. @article{ISI:000632498400011, title = {Language access in emergency and disaster preparedness: An assessment of local government ? whole community ? efforts in the United States}, author = {Tianyi Xiang and Brian J Gerber and Fengxiu Zhang}, doi = {10.1016/j.ijdrr.2021.102072}, issn = {2212-4209}, year = {2021}, date = {2021-03-01}, journal = {INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION}, volume = {55}, abstract = {In 2011, the United States Federal Emergency Management Agency enunciated a ?whole community? strategic approach to emergency and disaster preparedness. Central to this approach is inclusion of the interests and concerns of all residents of a jurisdiction, including those with heightened vulnerabilities. However, relatively few studies have investigated how subnational governments have translated those federally-identified principles of access and inclusion into practice. Here, we ask: what is the current state of local government performance on language access, what might explain it, and what are its implications? While limited English proficiency (LEP) is both a key vulnerability indicator and important to emergency preparedness and operations, it is seldom studied systematically. We investigate how language accessibility is addressed in two distinct elements of community preparedness: emergency operations plans (EOPs) and household emergency preparedness guides (HPGs). Using a sample of 110 U S. counties, we find somewhat positive performance: nearly half the counties score high on language access in their EOPs, and two-thirds acknowledge the issue. Local HPGs are moderately language accessible. But our analysis also indicates that underlying demand (proportion LEP residents, community hazards profiles) does not correspond to specific efforts. Rather, other aspects of local administrative capacity might drive performance variation. Taken together, this suggests a policy challenge: emergency preparedness on language access remains relatively variable across U.S. communities and might depend primarily on local capacity and commitment. The findings imply uniform adoption of whole community principles in emergency preparedness actions across the U.S. is unlikely to occur reflexively.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In 2011, the United States Federal Emergency Management Agency enunciated a ?whole community? strategic approach to emergency and disaster preparedness. Central to this approach is inclusion of the interests and concerns of all residents of a jurisdiction, including those with heightened vulnerabilities. However, relatively few studies have investigated how subnational governments have translated those federally-identified principles of access and inclusion into practice. Here, we ask: what is the current state of local government performance on language access, what might explain it, and what are its implications? While limited English proficiency (LEP) is both a key vulnerability indicator and important to emergency preparedness and operations, it is seldom studied systematically. We investigate how language accessibility is addressed in two distinct elements of community preparedness: emergency operations plans (EOPs) and household emergency preparedness guides (HPGs). Using a sample of 110 U S. counties, we find somewhat positive performance: nearly half the counties score high on language access in their EOPs, and two-thirds acknowledge the issue. Local HPGs are moderately language accessible. But our analysis also indicates that underlying demand (proportion LEP residents, community hazards profiles) does not correspond to specific efforts. Rather, other aspects of local administrative capacity might drive performance variation. Taken together, this suggests a policy challenge: emergency preparedness on language access remains relatively variable across U.S. communities and might depend primarily on local capacity and commitment. The findings imply uniform adoption of whole community principles in emergency preparedness actions across the U.S. is unlikely to occur reflexively. |
Karuna, Prakruthi; Purohit, Hemant; Jajodia, Sushil; Ganesan, Rajesh; Uzuner, Ozlem Fake Document Generation for Cyber Deception by Manipulating Text Comprehensibility Journal Article IEEE SYSTEMS JOURNAL, 15 (1), pp. 835-845, 2021, ISSN: 1932-8184. @article{ISI:000628985900082, title = {Fake Document Generation for Cyber Deception by Manipulating Text Comprehensibility}, author = {Prakruthi Karuna and Hemant Purohit and Sushil Jajodia and Rajesh Ganesan and Ozlem Uzuner}, doi = {10.1109/JSYST.2020.2980177}, issn = {1932-8184}, year = {2021}, date = {2021-03-01}, journal = {IEEE SYSTEMS JOURNAL}, volume = {15}, number = {1}, pages = {835-845}, abstract = {Advanced cyber attackers can penetrate enterprise networks and steal critical documents containing intellectual property despite all access control measures. Cyber deception is one of many solutions to protect critical documents after an attacker penetrates the network. It requires the generation and deployment of decoys such as fake text. The comprehensibility of a fake text document can affect the required time and effort for an attack to succeed. However, existing cybersecurity research has given limited attention to exploring the comprehensibility features of text for fake document generation. This article presents a novel method to generate believable fake text documents by measuring and manipulating the comprehensibility of legit text within a genetic algorithm (GA) framework. For measuring text comprehensibility, we adopt a set of quantitative measures based on qualitative principles of psycholinguistics and reading comprehension: connectivity, dispersion, and sequentiality. Our user-study analysis indicates that the quantitative comprehensibility measures can approximate the degree of human effort required to comprehend a fake text document in contrast to a legit text. For manipulating text comprehensibility, we develop a multiobjective, multimutation GA that modifies a legit document to Pareto-optimally alter its comprehensibility measures and generate hard-to-comprehend, believable fake documents. Our experiments show that the proposed algorithm successfully generates fake documents for a broader class of legit documents with varied text characteristics when compared to baselines from previous research. Hence, the application of our method can help improve cyber deception systems by providing more believable yet hard-to-comprehend fake documents to mislead cyber attackers.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Advanced cyber attackers can penetrate enterprise networks and steal critical documents containing intellectual property despite all access control measures. Cyber deception is one of many solutions to protect critical documents after an attacker penetrates the network. It requires the generation and deployment of decoys such as fake text. The comprehensibility of a fake text document can affect the required time and effort for an attack to succeed. However, existing cybersecurity research has given limited attention to exploring the comprehensibility features of text for fake document generation. This article presents a novel method to generate believable fake text documents by measuring and manipulating the comprehensibility of legit text within a genetic algorithm (GA) framework. For measuring text comprehensibility, we adopt a set of quantitative measures based on qualitative principles of psycholinguistics and reading comprehension: connectivity, dispersion, and sequentiality. Our user-study analysis indicates that the quantitative comprehensibility measures can approximate the degree of human effort required to comprehend a fake text document in contrast to a legit text. For manipulating text comprehensibility, we develop a multiobjective, multimutation GA that modifies a legit document to Pareto-optimally alter its comprehensibility measures and generate hard-to-comprehend, believable fake documents. Our experiments show that the proposed algorithm successfully generates fake documents for a broader class of legit documents with varied text characteristics when compared to baselines from previous research. Hence, the application of our method can help improve cyber deception systems by providing more believable yet hard-to-comprehend fake documents to mislead cyber attackers. |
Kursuncu, Ugur; Purohit, Hemant; Agarwal, Nitin; Sheth, Amit When the Bad Is Good and the Good Is Bad: Understanding Cyber Social Health Through Online Behavioral Change: Part 2 Journal Article IEEE INTERNET COMPUTING, 25 (2), pp. 46-47, 2021, ISSN: 1089-7801. @article{ISI:000646900400006, title = {When the Bad Is Good and the Good Is Bad: Understanding Cyber Social Health Through Online Behavioral Change: Part 2}, author = {Ugur Kursuncu and Hemant Purohit and Nitin Agarwal and Amit Sheth}, doi = {10.1109/MIC.2021.3059262}, issn = {1089-7801}, year = {2021}, date = {2021-03-01}, journal = {IEEE INTERNET COMPUTING}, volume = {25}, number = {2}, pages = {46-47}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Girotto, Manuela; Reichle, Rolf; Rodell, Matthew; Maggioni, Viviana Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment Journal Article REMOTE SENSING, 13 (6), 2021. @article{ISI:000651961600001, title = {Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment}, author = {Manuela Girotto and Rolf Reichle and Matthew Rodell and Viviana Maggioni}, doi = {10.3390/rs13061223}, year = {2021}, date = {2021-03-01}, journal = {REMOTE SENSING}, volume = {13}, number = {6}, abstract = {The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model's precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model's precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques. |
Korostelina, Karina V; Uesugi, Yuji The impact of symbolic boundaries on perceptions of relations between Japan and South Korea Journal Article NATIONAL IDENTITIES, 23 (2), pp. 185-204, 2021, ISSN: 1460-8944. @article{ISI:000515276800001, title = {The impact of symbolic boundaries on perceptions of relations between Japan and South Korea}, author = {Karina V Korostelina and Yuji Uesugi}, doi = {10.1080/14608944.2020.1723513, Early Access Date = FEB 2020}, issn = {1460-8944}, year = {2021}, date = {2021-03-01}, journal = {NATIONAL IDENTITIES}, volume = {23}, number = {2}, pages = {185-204}, abstract = {This paper argues the perceptions of relations between two nations involve not only the institutionalized national-boundary but also the perspectives of multiple symbolic boundaries. Based on a qualitative study, this paper aims to explain how different symbolic boundaries impact Japanese experts' perception of interrelations between Japan and the Republic of Korea (South Korea). The paper includes an analysis of opinion surveys, 20 semi-structured interviews with experts, and three focus group interviews with university students of Peace Studies Departments conducted throughout June and July of 2018 in Tokyo, Japan. These results advance existing scholarship by showing that Japanese experts use the following four symbolic boundaries to comprehend relations between Japan and South Korea: boundaries between (1) victims and perpetrators; (2) `the West' and the Asian cultural and political space; (3) nationalistic and peaceful countries; and (4) a state and people.}, keywords = {}, pubstate = {published}, tppubtype = {article} } This paper argues the perceptions of relations between two nations involve not only the institutionalized national-boundary but also the perspectives of multiple symbolic boundaries. Based on a qualitative study, this paper aims to explain how different symbolic boundaries impact Japanese experts' perception of interrelations between Japan and the Republic of Korea (South Korea). The paper includes an analysis of opinion surveys, 20 semi-structured interviews with experts, and three focus group interviews with university students of Peace Studies Departments conducted throughout June and July of 2018 in Tokyo, Japan. These results advance existing scholarship by showing that Japanese experts use the following four symbolic boundaries to comprehend relations between Japan and South Korea: boundaries between (1) victims and perpetrators; (2) `the West' and the Asian cultural and political space; (3) nationalistic and peaceful countries; and (4) a state and people. |
Rouf, Tasnuva; Maggioni, Viviana; Mei, Yiwen; Houser, Paul Towards hyper-resolution land-surface modeling of surface and root zone soil moisture Journal Article JOURNAL OF HYDROLOGY, 594 , 2021, ISSN: 0022-1694. @article{ISI:000641589600052, title = {Towards hyper-resolution land-surface modeling of surface and root zone soil moisture}, author = {Tasnuva Rouf and Viviana Maggioni and Yiwen Mei and Paul Houser}, doi = {10.1016/j.jhydrol.2020.125945}, issn = {0022-1694}, year = {2021}, date = {2021-03-01}, journal = {JOURNAL OF HYDROLOGY}, volume = {594}, abstract = {The goal of this work is to estimate surface and root zone soil moisture at resolutions that are useful for decision making and water resources management. A 500-m atmospheric forcing dataset is developed from the 12.5-km NLDAS-2 (North America Land Data Assimilation System) products across Oklahoma, where high-quality observations are available for validation purposes. A land surface model is then forced with three combinations of input variables to simulate surface and root zone soil moisture: 1) NLDAS-2 atmospheric forcings at their original resolution; 2) downscaled NLDAS-2 atmospheric variables (i.e., near-surface air temperature and humidity, wind speed and direction, incident longwave and shortwave radiation, pressure) and original resolution NLDAS-2 precipitation; and 3) downscaled NLDAS-2 atmospheric variables and precipitation. Results show that the third simulation is able to bring modeled standard-normal deviates of both surface and root zone soil moisture closer to in-situ observations, whereas the second simulation only shows slight improvements with respect to one forced with original resolution NLDAS-2 data. This is particularly evident for negative values of standard-normal deviates, which correspond to drier than usual cases, due to the improved ability of the downscaled precipitation to detect missed events and no-rain cases. In summary, finer resolution forcings have the potential to improve simulations of soil moisture and the resolution of precipitation plays a critical role in improving time series of soil moisture standard-normal deviates.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The goal of this work is to estimate surface and root zone soil moisture at resolutions that are useful for decision making and water resources management. A 500-m atmospheric forcing dataset is developed from the 12.5-km NLDAS-2 (North America Land Data Assimilation System) products across Oklahoma, where high-quality observations are available for validation purposes. A land surface model is then forced with three combinations of input variables to simulate surface and root zone soil moisture: 1) NLDAS-2 atmospheric forcings at their original resolution; 2) downscaled NLDAS-2 atmospheric variables (i.e., near-surface air temperature and humidity, wind speed and direction, incident longwave and shortwave radiation, pressure) and original resolution NLDAS-2 precipitation; and 3) downscaled NLDAS-2 atmospheric variables and precipitation. Results show that the third simulation is able to bring modeled standard-normal deviates of both surface and root zone soil moisture closer to in-situ observations, whereas the second simulation only shows slight improvements with respect to one forced with original resolution NLDAS-2 data. This is particularly evident for negative values of standard-normal deviates, which correspond to drier than usual cases, due to the improved ability of the downscaled precipitation to detect missed events and no-rain cases. In summary, finer resolution forcings have the potential to improve simulations of soil moisture and the resolution of precipitation plays a critical role in improving time series of soil moisture standard-normal deviates. |
[last updated 28 June 2021]