Scholarly Works, Computer Science

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The Abridgment and Relaxation Time for a Linear Multi-Scale Model Based on Multiple Site Phosphorylation
Wang, Shuo; Cao, Yang (PLOS, 2015-08-11)
Random effect in cellular systems is an important topic in systems biology and often simulated with Gillespie’s stochastic simulation algorithm (SSA). Abridgment refers to model reduction that approximates a group of reactions by a smaller group with fewer species and reactions. This paper presents a theoretical analysis, based on comparison of the first exit time, for the abridgment on a linear chain reaction model motivated by systems with multiple phosphorylation sites. The analysis shows that if the relaxation time of the fast subsystem is much smaller than the mean firing time of the slow reactions, the abridgment can be applied with little error. This analysis is further verified with numerical experiments for models of bistable switch and oscillations in which linear chain system plays a critical role.
Access to Autism Spectrum Disorder Services for Rural Appalachian Citizens
Scarpa, Angela; Jensen, Laura S.; Gracanin, Denis; Ramey, Sharon L.; Dahiya, Angela V.; Ingram, L. Maria; Albright, Jordan; Gatto, Alyssa J.; Scott, Jen Pollard; Ruble, Lisa (2020-01)
Background: Low-resource rural communities face significant challenges regarding availability and adequacy of evidence-based services. Purposes: With respect to accessing evidence-based services for Autism Spectrum Disorder (ASD), this brief report summarizes needs of rural citizens in the South-Central Appalachian region, an area notable for persistent health disparities. Methods: A mixed-methods approach was used to collect quantitative and qualitative data during focus groups with 33 service providers and 15 caregivers of children with ASD in rural southwest Virginia. Results: Results supported the barriers of availability and affordability of ASD services in this region, especially relating to the need for more ASD-trained providers, better coordination and navigation of services, and addition of programs to assist with family financial and emotional stressors. Results also suggested cultural attitudes related to autonomy and trust towards outside professionals that may prevent families from engaging in treatment. Implications: Relevant policy recommendations are discussed related to provider incentives, insurance coverage, and telehealth. Integration of autism services into already existing systems and multicultural sensitivity of providers are also implicated.
Acoustic differences between healthy and depressed people: a cross-situation study
Wang, Jingying; Zhang, Lei; Liu, Tianli; Pan, Wei; Hu, Bin; Zhu, Tingshao (2019-10-15)
Background Abnormalities in vocal expression during a depressed episode have frequently been reported in people with depression, but less is known about if these abnormalities only exist in special situations. In addition, the impacts of irrelevant demographic variables on voice were uncontrolled in previous studies. Therefore, this study compares the vocal differences between depressed and healthy people under various situations with irrelevant variables being regarded as covariates. Methods To examine whether the vocal abnormalities in people with depression only exist in special situations, this study compared the vocal differences between healthy people and patients with unipolar depression in 12 situations (speech scenarios). Positive, negative and neutral voice expressions between depressed and healthy people were compared in four tasks. Multiple analysis of covariance (MANCOVA) was used for evaluating the main effects of variable group (depressed vs. healthy) on acoustic features. The significances of acoustic features were evaluated by both statistical significance and magnitude of effect size. Results The results of multivariate analysis of covariance showed that significant differences between the two groups were observed in all 12 speech scenarios. Although significant acoustic features were not the same in different scenarios, we found that three acoustic features (loudness, MFCC5 and MFCC7) were consistently different between people with and without depression with large effect magnitude. Conclusions Vocal differences between depressed and healthy people exist in 12 scenarios. Acoustic features including loudness, MFCC5 and MFCC7 have potentials to be indicators for identifying depression via voice analysis. These findings support that depressed people’s voices include both situation-specific and cross-situational patterns of acoustic features.
AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
Liang, Xiao; Akers, Kyle; Keenum, Ishi M.; Wind, Lauren L.; Gupta, Suraj; Chen, Chaoqi; Aldaihani, Reem; Pruden, Amy; Zhang, Liqing; Knowlton, Katharine F.; Xia, Kang; Heath, Lenwood S. (2021-03-10)
Background Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance. Results Here we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis. Conclusion AgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/ .
Analysis and remedy of negativity problem in hybrid stochastic simulation algorithm and its application
Chen, Minghan; Cao, Yang (2019-06-20)
Background The hybrid stochastic simulation algorithm, proposed by Haseltine and Rawlings (HR), is a combination of differential equations for traditional deterministic models and Gillespie’s algorithm (SSA) for stochastic models. The HR hybrid method can significantly improve the efficiency of stochastic simulations for multiscale biochemical networks. Previous studies on the accuracy analysis for a linear chain reaction system showed that the HR hybrid method is accurate if the scale difference between fast and slow reactions is above a certain threshold, regardless of population scales. However, the population of some reactant species might be driven negative if they are involved in both deterministic and stochastic systems. Results This work investigates the negativity problem of the HR hybrid method, analyzes and tests it with several models including a linear chain system, a nonlinear reaction system, and a realistic biological cell cycle system. As a benchmark, the second slow reaction firing time is used to measure the effect of negative populations on the accuracy of the HR hybrid method. Our analysis demonstrates that usually the error caused by negative populations is negligible compared with approximation errors of the HR hybrid method itself, and sometimes negativity phenomena may even improve the accuracy. But for systems where negative species are involved in nonlinear reactions or some species are highly sensitive to negative species, the system stability will be influenced and may lead to system failure when using the HR hybrid method. In those circumstances, three remedies are studied for the negativity problem. Conclusions The results of different models and examples suggest that the Zero-Reaction rule is a good remedy for nonlinear and sensitive systems considering its efficiency and simplicity.
Apigenin Impacts the Growth of the Gut Microbiota and Alters the Gene Expression of Enterococcus
Wang, Minqian; Firrman, Jenni; Zhang, Liqing; Arango-Argoty, Gustavo; Tomasula, Peggy; Liu, Lin Shu; Xiao, Weidong; Yam, Kit (MDPI, 2017-08-03)
Apigenin is a major dietary flavonoid with many bioactivities, widely distributed in plants. Apigenin reaches the colon region intact and interacts there with the human gut microbiota, however there is little research on how apigenin affects the gut bacteria. This study investigated the effect of pure apigenin on human gut bacteria, at both the single strain and community levels. The effect of apigenin on the single gut bacteria strains Bacteroides galacturonicus, Bifidobacterium catenulatum, Lactobacillus rhamnosus GG, and Enterococcus caccae, was examined by measuring their anaerobic growth profiles. The effect of apigenin on a gut microbiota community was studied by culturing a fecal inoculum under in vitro conditions simulating the human ascending colon. 16S rRNA gene sequencing and GC-MS analysis quantified changes in the community structure. Single molecule RNA sequencing was used to reveal the response of Enterococcus caccae to apigenin. Enterococcus caccae was effectively inhibited by apigenin when cultured alone, however, the genus Enterococcus was enhanced when tested in a community setting. Single molecule RNA sequencing found that Enterococcus caccae responded to apigenin by up-regulating genes involved in DNA repair, stress response, cell wall synthesis, and protein folding. Taken together, these results demonstrate that apigenin affects both the growth and gene expression of Enterococcus caccae.
Application and Evaluation of Surrogate Models for Radiation Source Search
Cook, Jared A.; Smith, Ralph C.; Hite, Jason M.; Stefanescu, Razvan; Mattingly, John (MDPI, 2019-12-12)
Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate models whose discontinuous derivatives preclude the use of gradient-based optimization or data assimilation algorithms. We consider the problem of inferring the 2D location and intensity of a radiation source in an urban environment using a ray-tracing model based on Boltzmann transport theory. Whereas the code implementing this model is relatively efficient, extension to 3D Monte Carlo transport simulations precludes subsequent Bayesian inference to infer source locations, which typically requires thousands to millions of simulations. Additionally, the resulting likelihood exhibits discontinuous derivatives due to the presence of buildings. To address these issues, we discuss the construction of surrogate models for optimization, Bayesian inference, and uncertainty propagation. Specifically, we consider surrogate models based on Legendre polynomials, multivariate adaptive regression splines, radial basis functions, Gaussian processes, and neural networks. We detail strategies for computing training points and discuss the merits and deficits of each method.
Application of approximate matrix factorization to high order linearly implicit Runge-Kutta methods
Zhang, H.; Sandu, Adrian; Tranquilli, Paul (Elsevier, 2015-10-01)
Applications and Security of Next-Generation, User-Centric Wireless Systems
Ramstetter, Jerry Rick; Yang, Yaling; Yao, Danfeng (Daphne) (MDPI, 2010-07-28)
Pervasive wireless systems have significantly improved end-users quality of life. As manufacturing costs decrease, communications bandwidth increases, and contextual information is made more readily available, the role of next generation wireless systems in facilitating users daily activities will grow. Unique security and privacy issues exist in these wireless, context-aware, often decentralized systems. For example, the pervasive nature of such systems allows adversaries to launch stealthy attacks against them. In this review paper, we survey several emergent personal wireless systems and their applications. These systems include mobile social networks, active implantable medical devices, and consumer products. We explore each systems usage of contextual information and provide insight into its security vulnerabilities. Where possible, we describe existing solutions for defendingagainst these vulnerabilities. Finally, we point out promising future research directions for improving these systems robustness and security
Applying GIS and Text Mining Methods to Twitter Data to Explore the Spatiotemporal Patterns of Topics of Interest in Kuwait
G. Almatar, Muhammad; Alazmi, Huda S.; Li, Liuqing; Fox, Edward A. (MDPI, 2020-11-25)
Researchers have developed various approaches for exploring the spatial information, temporal patterns, and Twitter content in topics of interest in order to generate a better understanding of human behavior; however, few investigations have integrated these three dimensions simultaneously. This study analyzes the content of tweets in order to conduct a spatiotemporal exploration of the main topics of interest in Kuwait in order to provide a deeper understanding of the topics people think about, when they think about them, and where they tweet about them. To this end, we collect, process, and analyze tweets from nearly 120 areas in Kuwait over a 10-month period. The study’s results indicate that religion, emotions, education, and public policy are the most popular topics of interest in Kuwait. Regarding the spatiotemporal analysis, people post more tweets regarding religion on Fridays, a holy day for Muslims in Kuwait. Moreover, people are more likely to tweet about policy and education on weekdays rather than weekends. In contrast, people tweet about emotional expressions more often on weekends. From the spatial perspectives, spatial clustering in topics occurs across the days of the week. The findings are applicable to further topic analysis and similar research in other countries.
Approximate Exponential Algorithms to Solve the Chemical Master Equation
Mooasvi, A.; Sandu, Adrian (Vilnius Gediminas Tech Univ, 2015-05-04)
An Atlas of the Speed of Copy Number Changes in Animal Gene Families and Its Implications
Pan, Deng; Zhang, Liqing (PLOS, 2009-10-23)
The notion that gene duplications generating new genes and functions is commonly accepted in evolutionary biology. However, this assumption is more speculative from theory rather than well proven in genome-wide studies. Here, we generated an atlas of the rate of copy number changes (CNCs) in all the gene families of ten animal genomes. We grouped the gene families with similar CNC dynamics into rate pattern groups (RPGs) and annotated their function using a novel bottom-up approach. By comparing CNC rate patterns, we showed that most of the species-specific CNC rates groups are formed by gene duplication rather than gene loss, and most of the changes in rates of CNCs may be the result of adaptive evolution. We also found that the functions of many RPGs match their biological significance well. Our work confirmed the role of gene duplication in generating novel phenotypes, and the results can serve as a guide for researchers to connect the phenotypic features to certain gene duplications.
Automatic layout and visualization of biclusters
Grothaus, Gregory A.; Mufti, Adeel; Murali, T. M. (2006-09-04)
Background Biclustering has emerged as a powerful algorithmic tool for analyzing measurements of gene expression. A number of different methods have emerged for computing biclusters in gene expression data. Many of these algorithms may output a very large number of biclusters with varying degrees of overlap. There are no systematic methods that create a two-dimensional layout of the computed biclusters and display overlaps between them. Results We develop a novel algorithm for laying out biclusters in a two-dimensional matrix whose rows (respectively, columns) are rows (respectively, columns) of the original dataset. We display each bicluster as a contiguous submatrix in the layout. We allow the layout to have repeated rows and/or columns from the original matrix as required, but we seek a layout of the smallest size. We also develop a web-based search interface for the user to query the genes and samples of interest and visualise the layout of biclusters matching the queries. Conclusion We demonstrate the usefulness of our approach on gene expression data for two types of leukaemia and on protein-DNA binding data for two growth conditions in Saccharomyces cerevisiae. The software implementing the layout algorithm is available at http://bioinformatics.cs.vt.edu/~murali/papers/bivoc.
AVIST: A GPU-Centric Design for Visual Exploration of Large Multidimensional Datasets
Mi, Peng; Sun, Maoyuan; Masiane, Moeti; Cao, Yong; North, Christopher L. (MDPI, 2016-10-07)
This paper presents the Animated VISualization Tool (AVIST), an exploration-oriented data visualization tool that enables rapidly exploring and filtering large time series multidimensional datasets. AVIST highlights interactive data exploration by revealing fine data details. This is achieved through the use of animation and cross-filtering interactions. To support interactive exploration of big data, AVIST features a GPU (Graphics Processing Unit)-centric design. Two key aspects are emphasized on the GPU-centric design: (1) both data management and computation are implemented on the GPU to leverage its parallel computing capability and fast memory bandwidth; (2) a GPU-based directed acyclic graph is proposed to characterize data transformations triggered by users’ demands. Moreover, we implement AVIST based on the Model-View-Controller (MVC) architecture. In the implementation, we consider two aspects: (1) user interaction is highlighted to slice big data into small data; and (2) data transformation is based on parallel computing. Two case studies demonstrate how AVIST can help analysts identify abnormal behaviors and infer new hypotheses by exploring big datasets. Finally, we summarize lessons learned about GPU-based solutions in interactive information visualization with big data.
Bare-hand volume cracker for raw volume data analysis
Socha, John J.; Laha, Bireswar; Bowman, Douglas A. (2016-09-28)
Analysis of raw volume data generated from different scanning technologies faces a variety of challenges, related to search, pattern recognition, spatial understanding, quantitative estimation, and shape description. In a previous study, we found that the volume cracker (VC) 3D interaction (3DI) technique mitigated some of these problems, but this result was from a tethered glove-based system with users analyzing simulated data. Here, we redesigned the VC by using untethered bare-hand interaction with real volume datasets, with a broader aim of adoption of this technique in research labs. We developed symmetric and asymmetric interfaces for the bare-hand VC (BHVC) through design iterations with a biomechanics scientist. We evaluated our asymmetric BHVC technique against standard 2D and widely used 3DI techniques with experts analyzing scanned beetle datasets. We found that our BHVC design significantly outperformed the other two techniques. This study contributes a practical 3DI design for scientists, documents lessons learned while redesigning for bare-hand trackers and provides evidence suggesting that 3DI could improve volume data analysis for a variety of visual analysis tasks. Our contribution is in the realm of 3D user interfaces tightly integrated with visualization for improving the effectiveness of visual analysis of volume datasets. Based on our experience, we also provide some insights into hardware-agnostic principles for design of effective interaction techniques.
A Bayesian approach to multivariate adaptive localization in ensemble-based data assimilation with time-dependent extensions
Popov, Andrey A.; Sandu, Adrian (Copernicus Publications, 2019-06-14)
Ever since its inception, the ensemble Kalman filter (EnKF) has elicited many heuristic approaches that sought to improve it. One such method is covariance localization, which alleviates spurious correlations due to finite ensemble sizes by using relevant spatial correlation information. Adaptive localization techniques account for how correlations change in time and space, in order to obtain improved covariance estimates. This work develops a Bayesian approach to adaptive Schur-product localization for the deterministic ensemble Kalman filter (DEnKF) and extends it to support multiple radii of influence. We test the proposed adaptive localization using the toy Lorenz’96 problem and a more realistic 1.5-layer quasi-geostrophic model. Results with the toy problem show that the multivariate approach informs us that strongly observed variables can tolerate larger localization radii. The univariate approach leads to markedly improved filter performance for the realistic geophysical model, with a reduction in error by as much as 33 %.
‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators
Ramakrishnan, Naren; Butler, Patrick; Self, Nathan; Khandpur, Rupinder P.; Saraf, Parang; Wang, Wei; Cadena, Jose; Vullikanti, Anil Kumar S.; Korkmaz, Gizem; Kuhlman, Christopher J.; Marathe, Achla; Zhao, Liang; Ting, Hua; Huang, Bert; Srinivasan, Aravind; Trinh, Khoa; Getoor, Lise; Katz, Graham; Doyle, Andy; Ackermann, Chris; Zavorin, Ilya; Ford, Jim; Summers, Kristen; Fayed, Youssef; Arredondo, Jaime; Gupta, Dipak; Mares, David; Muthia, Sathappan; Chen, Feng; Lu, Chang-Tien (2014)
We describe the design, implementation, and evaluation of EMBERS, an automated, 24x7 continuous system for forecasting civil unrest across 10 countries of Latin America using open source indicators such as tweets, news sources, blogs, economic indicators, and other data sources. Unlike retrospective studies, EMBERS has been making forecasts into the future since Nov 2012 which have been (and continue to be) evaluated by an independent T&E team (MITRE). Of note, EMBERS has successfully forecast the uptick and downtick of incidents during the June 2013 protests in Brazil. We outline the system architecture of EMBERS, individual models that leverage specific data sources, and a fusion and suppression engine that supports trading off specific evaluation criteria. EMBERS also provides an audit trail interface that enables the investigation of why specific predictions were made along with the data utilized for forecasting. Through numerous evaluations, we demonstrate the superiority of EMBERS over baserate methods and its capability to forecast significant societal happenings.
Beyond Finding Change: multitemporal Landsat for forest monitoring and management
Wynne, Randolph H.; Thomas, Valerie A.; Brooks, Evan B.; Coulston, J. O.; Derwin, Jill M.; Liknes, Greg C.; Yang, Z.; Fox, Thomas R.; Ghannam, S.; Abbott, A. Lynn; House, M. N.; Saxena, R.; Watson, Layne T.; Gopalakrishnan, Ranjith (2017-07)
Take homes

Tobler’s Law still in effect with time series – spatial autocorrelation in temporal coherence can help in both preprocessing and estimation

Continual process improvement in extant algorithms needed

Need additional means by which variations within (parameterization) and across algorithms addressed (the Reverend…)

Time series improving higher order products (example with NLCD TCC) enabling near continuous monitoring
Beyond the stony veil: Reconstructing the Earth’s earliest large animal traces via computed tomography X-ray imaging
Meyer, Mike; Polys, Nicholas F.; Yaqoob, Humza; Hinnov, Linda; Xiao, Shuhai (2017-09)
Trace fossils are superb lines of evidence for examining the ancient biologic world because they offer an opportunity to infer behavioral ecology of organisms. However, traces can be difficult to parse from their matrix, which leads to the loss of important morphological and behavioral data. This is especially true for the earliest marine animal traces from the Ediacaran Period (635–541 Ma), which are usually small (<5 mm in diameter) and simple (mostly small horizontal trails and burrows), and are sometimes difficult to be distinguished from co-existing tubular body fossils. There is also evidence that the prevalence of microbial substrates in Ediacaran oceans may have influenced emerging trace makers in nonactualistic ways from a late Phanerozoic perspective (e.g., microbial mats may have facilitated a strong geochemical gradient across the sediment-water interface). Therefore, the discovery of the relatively large traces of Lamonte trevallis from the Ediacaran Shibantan Member of the Denying Formation (~551–541 Ma) in the Yangtze Gorges area of South China provides a unique opportunity to study early bioturbators. These trace fossils are large enough and have sufficient compositional contrast (relative to the matrix) for in situ analysis via X-ray computed tomography (CT) and microcomputed tomography (microCT). Each analytical method has its own advantages and disadvantages. CT scans can image larger specimens, but cannot adequately resolve small features of interest. MicroC scans can achieve higher resolution, but can only be used with small samples and may involve more post-processing than CT scans. As demonstrated in this study, X-ray CT and microCT in combination with other 3D imaging techniques and resources have the potential to resolve the 3D morphology of Ediacaran trace fossils. A new Volumetric Bioturbation Intensity (VBI) is also proposed, which quantifies whole rock bioturbation using 3D analysis of subsurface traces. Combined with the ability to examine trace fossils in situ, the VBI can enhance our view of ancient ecologies and life’s enduring relationship with sediments.
Brain-wide cellular resolution imaging of Cre transgenic zebrafish lines for functional circuit-mapping
Tabor, Kathryn M.; Marquart, Gregory D.; Hurt, Christopher; Smith, Trevor S.; Geoca, Alexandra K.; Bhandiwad, Ashwin A.; Subedi, Abhignya; Sinclair, Jennifer L.; Rose, Hannah M.; Polys, Nicholas F.; Burgess, Harold A. (2019-02-08)
Decoding the functional connectivity of the nervous system is facilitated by transgenic methods that express a genetically encoded reporter or effector in specific neurons; however, most transgenic lines show broad spatiotemporal and cell-type expression. Increased specificity can be achieved using intersectional genetic methods which restrict reporter expression to cells that co-express multiple drivers, such as Gal4 and Cre. To facilitate intersectional targeting in zebrafish, we have generated more than 50 new Cre lines, and co-registered brain expression images with the Zebrafish Brain Browser, a cellular resolution atlas of 264 transgenic lines. Lines labeling neurons of interest can be identified using a web-browser to perform a 3D spatial search (zbbrowser.com). This resource facilitates the design of intersectional genetic experiments and will advance a wide range of precision circuit-mapping studies.

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