Destination Area: Data and Decisions (D&D)

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https://hdl.handle.net/10919/79524

The DA Data and Decisions advances the human condition and society with better decisions through data. D&D integrates all DAs and SGAs with data analytics and decision sciences. Work in this area embraces equity in the human condition by seeking the equitable distribution and availability of physical safety and well-being, psychological well-being, respect for human dignity, and access to crucial material and social resources throughout the world’s diverse communities. D&D also addresses policymaking and policy analysis, collaborating at the intersection of scientific evidence, governance, and analyses to translate scholarship into practice.

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A Model for a Smallpox-Vaccination Policy
Bozzette, Samuel A.; Boer, Rob; Bhatnagar, Vibha; Brower, Jennifer L.; Keeler, Emmett B.; Morton, Sally C.; Stoto, Michael A. (NEJM Group, 2003-01-30)
Background: The new reality of biologic terrorism and warfare has ignited a debate about whether to reintroduce smallpox vaccination. Methods: We developed scenarios of smallpox attacks and built a stochastic model of outcomes under various control policies. We conducted a systematic literature review and estimated model parameters on the basis of European and North American outbreaks since World War II. We assessed the trade-offs between vaccine-related harms and benefits. Results: Nations or terrorists possessing a smallpox weapon could feasibly mount attacks that vary with respect to tactical complexity and target size, and patterns of spread can be expected to vary according to whether index patients are hospitalized early. For acceptable results, vaccination of contacts must be accompanied by effective isolation. Vaccination of contacts plus isolation is expected to result in 7 deaths (from vaccine or smallpox) in a scenario involving the release of variola virus from a laboratory, 19 deaths in a human-vector scenario, 300 deaths in a building-attack scenario, 2735 deaths in a scenario involving a low-impact airport attack, and 54,729 deaths in a scenario involving a high-impact airport attack. Immediate vaccination of the public in an attacked region would provide little additional benefit. Prior vaccination of health care workers, who would be disproportionately affected, would save lives in large local or national attacks but would cause 25 deaths nationally. Prior vaccination of health care workers and the public would save lives in a national attack but would cause 482 deaths nationally. The expected net benefits of vaccination depend on the assessed probability of an attack. Prior vaccination of health care workers would be expected to save lives if the probability of a building attack exceeded 0.22 or if the probability of a high-impact airport attack exceeded 0.002. The probability would have to be much higher to make vaccination of the public life-saving. Conclusions: The analysis favors prior vaccination of health care workers unless the likelihood of any attack is very low, but it favors vaccination of the public only if the likelihood of a national attack or of multiple attacks is high.
Efficacy and Safety of Ephedra and Ephedrine for Weight Loss and Athletic Performance: A Meta-analysis
Shekelle, Paul G.; Hardy, Mary; Morton, Sally C.; Maglione, Margaret; Mojica, Walter A.; Suttorp, Marika J.; Rhodes, Shannon L.; Jungvig, Lara; Gagné, James (AMA, 2003-03-26)
CONTEXT: Ephedra and ephedrine sometimes are used for weight loss or enhanced athletic performance, but the efficacy and safety of these compounds are uncertain. OBJECTIVE: To assess the efficacy and safety of ephedra and ephedrine used for weight loss and enhanced athletic performance. DATA SOURCES: We searched 9 databases using the terms ephedra, ephedrine, adverse effect, side effect, efficacy, effective, and toxic. We included unpublished trials and non-English-language documents. Adverse events reported to the US Food and Drug Administration MedWatch program were assessed. STUDY SELECTION: Eligible studies were controlled trials of ephedra or ephedrine used for weight loss or athletic performance and case reports of adverse events associated with such use. Eligible studies for weight loss were human studies with at least 8 weeks of follow-up; and for athletic performance, those having no minimum follow-up. Eligible case reports documented that ephedra or ephedrine was consumed within 24 hours prior to an adverse event or that ephedrine or an associated product was found in blood or urine, and that other potential causes had been excluded. Of the 530 articles screened, 52 controlled trials and 65 case reports were included in the adverse events analysis. Of more than 18 000 other case reports screened, 284 underwent detailed review. DATA EXTRACTION: Two reviewers independently identified trials of efficacy and safety of ephedra and ephedrine on weight loss or athletic performance; disagreements were resolved by consensus. Case reports were reviewed with explicit and implicit methods. DATA SYNTHESIS: No weight loss trials assessed duration of treatment greater than 6 months. Pooled results for trials comparing placebo with ephedrine (n = 5), ephedrine and caffeine (n = 12), ephedra (n = 1), and ephedra and herbs containing caffeine (n = 4) yielded estimates of weight loss (more than placebo) of 0.6 (95% confidence interval, 0.2-1.0), 1.0 (0.7-1.3), 0.8 (0.4-1.2), and 1.0 (0.6-1.3) kg/mo, respectively. Sensitivity analyses did not substantially alter the latter 3 results. No trials of ephedra and athletic performance were found; 7 trials of ephedrine were too heterogeneous to synthesize. Safety data from 50 trials yielded estimates of 2.2- to 3.6-fold increases in odds of psychiatric, autonomic, or gastrointestinal symptoms, and heart palpitations. Data are insufficient to draw conclusions about adverse events occurring at a rate less than 1.0 per thousand. The majority of case reports are insufficiently documented to allow meaningful assessment. CONCLUSIONS: Ephedrine and ephedra promote modest short-term weight loss (approximately 0.9 kg/mo more than placebo) in clinical trials. There are no data regarding long-term weight loss, and evidence to support use of ephedra for athletic performance is insufficient. Use of ephedra or ephedrine and caffeine is associated with increased risk of psychiatric, autonomic, or gastrointestinal symptoms, and heart palpitations.
The molecular mechanism linking muscle fat accumulation to insulin resistance
Dohm, G. Lynis; Hulver, Matthew W. (The Nutrition Society, 2004)
Skeletal muscle insulin resistance is a co-morbidity of obesity and a risk factor for the development of type 2 diabetes mellitus. Insulin resistance is associated with the accumulation of intramyocellular lipids. Intramyocellular triacylglycerols do not appear to be the cause of insulin resistance but are more likely to be a marker of other lipid intermediates such as fatty acyl-CoA, ceramides or diacylglycerols. Fatty acyl-CoA, ceramides and diacylglycerols are known to directly alter various aspects of the insulin signalling cascade. Insulin signalling is inhibited by the phosphorylation of serine and threonine residues at the levels of the insulin receptor and insulin receptor substrate 1. Protein kinase C is responsible for the phosphorylation of the serine and threonine residues. Fatty acyl-CoA and diacylglycerols are known to activate protein kinase C. The cause of the intramyocellular accumulation of fatty acyl-CoA and diacylglycerols is unclear at this time. Reduced fatty acid oxidation does not appear to be responsible, as fatty acyl-CoA accumulates in skeletal muscle with a normal fatty acid oxidative capacity. Other potential mechanisms include oversupply of lipids to muscle and/or up regulated fatty acid transport.
Interventions for the prevention of falls in older adults: systematic review and meta-analysis of randomised clinical trials
Chang, John T.; Morton, Sally C.; Rubenstein, Laurence Z.; Mojica, Walter A.; Maglione, Margaret; Suttorp, Marika J.; Roth, Elizabeth A.; Shekelle, Paul G. (BMJ Publishing Group Ltd, 2004-03-20)
Objective: To assess the relative effectiveness of interventions to prevent falls in older adults to either a usual care group or control group. Design: Systematic review and meta-analyses. Data sources Medline, HealthSTAR, Embase, the Cochrane Library, other health related databases, and the reference lists from review articles and systematic reviews. Data extraction: Components of falls intervention: multifactorial falls risk assessment with management programme, exercise, environmental modifications, or education. Results: 40 trials were identified. A random effects analysis combining trials with risk ratio data showed a reduction in the risk of falling (risk ratio 0.88, 95% confidence interval 0.82 to 0.95), whereas combining trials with incidence rate data showed a reduction in the monthly rate of falling (incidence rate ratio 0.80, 0.72 to 0.88). The effect of individual components was assessed by meta-regression. A multifactorial falls risk assessment and management programme was the most effective component on risk of falling (0.82, 0.72 to 0.94, number needed to treat 11) and monthly fall rate (0.63, 0.49 to 0.83; 11.8 fewer falls in treatment group per 100 patients per month). Exercise interventions also had a beneficial effect on the risk of falling (0.86, 0.75 to 0.99, number needed to treat 16) and monthly fall rate (0.86, 0.73 to 1.01; 2.7). Conclusions: Interventions to prevent falls in older adults are effective in reducing both the risk of falling and the monthly rate of falling. The most effective intervention was a multifactorial falls risk assessment and management programme. Exercise programmes were also effective in reducing the risk of falling.
Ephedra
Morton, Sally C. (Institute of Mathematical Statistics, 2005-08)
In February 2004, the U.S. Food and Drug Administration (FDA) prohibited the sale of dietary supplements containing ephedrine alkaloids (ephedra), stating that such supplements present an unreasonable risk of illness or injury. The Dietary Supplement Health and Education Act (DSHEA) of 1994 (21 USC §301, 1994) governs dietary supplement regulation in the U.S. DSHEA places the burden of proof for safety on the government rather than on the manufacturer and thus differs significantly from regulations that govern the marketing of drugs. Part of the evidence the FDA used in reaching its decision was a systematic review of the efficacy and safety of ephedra conducted by the Southern California Evidence-Based Practice Center. In addition to a meta-analysis of controlled trial data, the review contained an evaluation of observational case report data, a study design that has limited inferential abilities regarding cause and effect. How did the FDA decide what data were relevant to its decision? How did the FDA argument for the ban differ from a decision based solely on statistical hypothesis testing? This paper will address these questions by describing the systematic review approach, the evidence presented, the interpretation of that evidence by those on both sides of the argument and the process by which the decision was made.
Are Ayurvedic herbs for diabetes effective?
Shekelle, Paul G.; Hardy, Mary; Morton, Sally C.; Coulter, Ian; Venuturupalli, Swamy; Favreau, Joya; Hilton, Lara K. (Frontline Medical Communications Inc., 2005-10)
Objective: To evaluate and synthesize the evidence on the effect of Ayurvedic therapies for diabetes mellitus. Design: Systematic review of trials. Measurements and main results: We found no study that assessed Ayurvedic as a system of care. Botanical therapy was by far the most commonly studied Ayurvedic treatment. Herbs were studied either singly or as formulas. In all, 993 titles in Western computerized databases and 318 titles identified by hand-searching journals in India were examined, yield ing 54 articles reporting the results of 62 studies. The most-studied herbs were G sylvestre, C indica, fenugreek, and Eugenia jambo/ana. A number of herbal formulas were tested, but Ayush- 82 and 0 -400 were most often studied. Thirty-five of the studies included came from the Western literature, 27 from the Indian. Seven were randomized controlled trials (RCTs) and 10 controlled clinical trials (CCTs) or natural experiments. Twenty-two studies went on to further analysis based on a set of criteria. Of these, 10 were RCTs, eCTs, or natural experiments, 12 were case series or cohort studies. There is evidence to suggest that the herbs C indica, holy basil, fenugreek, and G sylvestre, and the herbal formulas Ayush-82 and 0 -400 have a glucose-lowering effect and deserve further study. Evidence of effectiveness of several other herbs is less extensive (C tamala, E jambo/ana, and Momordica charantia). Conclusions: There is heterogeneity in the available literature on Ayurvedic treatment for diabetes. Most studies test herbal therapy. Heterogeneity exists in the herbs and formulas tested (more than 44 different interventions identified) and in the method of their preparation. Despite these limitations, there are sufficient data for several herbs or herbal formulas to warrant further studies.
Effects of Omega-3 Fatty Acids on Cancer Risk
MacLean, Catherine H.; Newberry, Sydne J.; Mojica, Walter A.; Khanna, Puja; Issa, Amalia M.; Suttorp, Marika J.; Lim, Yee-Wee; Traina, Shana B.; Hilton, Lara K.; Garland, Rena; Morton, Sally C. (AMA, 2006-04)
Context: Omega-3 fatty acids are purported to reduce the risk of cancer. Studies have reported mixed results. Objective: To synthesize published and unpublished evidence to determine estimates of the effect of omega-3 fatty acids on cancer risk in prospective cohort studies. Data Sources Articles published from 1966 to October 2005 identified through MEDLINE, PREMEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and CAB Health; unpublished literature sought through letters to experts in the neutraceutical industry. Study Selection: A total of 38 articles with a description of effects of consumption of omega-3 fatty acids on tumor incidence, prospective cohort study design, human study population; and description of effect of omega-3 among groups with different levels of exposure in the cohort were included. Two reviewers independently reviewed articles using structured abstraction forms; disagreements were resolved by consensus. Data Extraction: Two reviewers independently abstracted detailed data about the incidence of cancer, the type of cancer, the number and characteristics of the patients, details on the exposure to omega-3 fatty acids, and the elapsed time between the intervention and outcome measurements. Data about the methodological quality of the study were also abstracted. Data Synthesis: Across 20 cohorts from 7 countries for 11 different types of cancer and using up to 6 different ways to categorize omega-3 fatty acid consumption, 65 estimates of the association between omega-3 fatty acid consumption were reported. Among these, only 8 were statistically significant. The high degree of heterogeneity across these studies precluded pooling of data. For breast cancer 1 significant estimate was for increased risk (incidence risk ratio [IRR], 1.47; 95% confidence interval [CI], 1.10-1.98) and 3 were for decreased risk (RR, 0.68-0.72); 7 other estimates did not show a significant association. For colorectal cancer, there was 1 estimate of decreased risk (RR, 0.49; 95% CI, 0.27-0.89) and 17 estimates without association. For lung cancer one of the significant associations was for increased cancer risk (IRR, 3.0; 95% CI, 1.2-7.3), the other was for decreased risk (RR, 0.32; 95% CI, 0.13-0.76), and 4 other estimates were not significant. For prostate cancer, there was 1 estimate of decreased risk (RR, 0.43; 95% CI, 0.22-0.83) and 1 of increased risk (RR, 1.98; 95% CI, 1.34-2.93) for advanced prostate cancer; 15 other estimates did not show a significant association. The study that assessed skin cancer found an increased risk (RR, 1.13; 95% CI, 1.01-1.27). No significant associations between omega-3 fatty acid consumption and cancer incidence were found for aerodigestive cancer, bladder cancer, lymphoma, ovarian cancer, pancreatic cancer, or stomach cancer. Conclusions: A large body of literature spanning numerous cohorts from many countries and with different demographic characteristics does not provide evidence to suggest a significant association between omega-3 fatty acids and cancer incidence. Dietary supplementation with omega-3 fatty acids is unlikely to prevent cancer.
Unsupervised clustering of gene expression data points at hypoxia as possible trigger for metabolic syndrome
Ptitsyn, Andrey; Hulver, Matthew W.; Cefalu, William; York, David; Smith, Steven R. (2006-12-19)
Background Classification of large volumes of data produced in a microarray experiment allows for the extraction of important clues as to the nature of a disease. Results Using multi-dimensional unsupervised FOREL (FORmal ELement) algorithm we have re-analyzed three public datasets of skeletal muscle gene expression in connection with insulin resistance and type 2 diabetes (DM2). Our analysis revealed the major line of variation between expression profiles of normal, insulin resistant, and diabetic skeletal muscle. A cluster of most "metabolically sound" samples occupied one end of this line. The distance along this line coincided with the classic markers of diabetes risk, namely obesity and insulin resistance, but did not follow the accepted clinical diagnosis of DM2 as defined by the presence or absence of hyperglycemia. Genes implicated in this expression pattern are those controlling skeletal muscle fiber type and glycolytic metabolism. Additionally myoglobin and hemoglobin were upregulated and ribosomal genes deregulated in insulin resistant patients. Conclusion Our findings are concordant with the changes seen in skeletal muscle with altitude hypoxia. This suggests that hypoxia and shift to glycolytic metabolism may also drive insulin resistance.
Mining Novellas from PubMed Abstracts using a Storytelling Algorithm
Gresock, Joseph; Kumar, Deept; Helm, Richard F.; Potts, Malcolm; Ramakrishnan, Naren (Department of Computer Science, Virginia Polytechnic Institute & State University, 2007)
Motivation: There are now a multitude of articles published in a diversity of journals providing information about genes, proteins, pathways, and entire processes. Each article investigates particular subsets of a biological process, but to gain insight into the functioning of a system as a whole, we must computationally integrate information across multiple publications. This is especially important in problems such as modeling cross-talk in signaling networks, designing drug therapies for combinatorial selectivity, and unraveling the role of gene interactions in deleterious phenotypes, where the cost of performing combinatorial screens is exorbitant. Results: We present an automated approach to biological knowledge discovery from PubMed abstracts, suitable for unraveling combinatorial relationships. It involves the systematic application of a `storytelling' algorithm followed by compression of the stories into `novellas.' Given a start and end publication, typically with little or no overlap in content, storytelling identifies a chain of intermediate publications from one to the other, such that neighboring publications have significant content similarity. Stories discovered thus provide an argued approach to relate distant concepts through compositions of related concepts. The chains of links employed by stories are then mined to find frequently reused sub-stories, which can be compressed to yield novellas, or compact templates of connections. We demonstrate a successful application of storytelling and novella finding to modeling combinatorial relationships between introduction of extracellular factors and downstream cellular events. Availability: A story visualizer, suitable for interactive exploration of stories and novellas described in this paper, is available for demo/download at https://bioinformatics.cs.vt.edu/storytelling.
Compositional Mining of Multi-Relational Biological Datasets
Jin, Ying; Murali, T. M.; Ramakrishnan, Naren (Department of Computer Science, Virginia Polytechnic Institute & State University, 2007-08-01)
High-throughput biological screens are yielding ever-growing streams of information about multiple aspects of cellular activity. As more and more categories of datasets come online, there is a corresponding multitude of ways in which inferences can be chained across them, motivating the need for compositional data mining algorithms. In this paper, we argue that such compositional data mining can be effectively realized by functionally cascading redescription mining and biclustering algorithms as primitives. Both these primitives mirror shifts of vocabulary that can be composed in arbitrary ways to create rich chains of inferences. Given a relational database and its schema, we show how the schema can be automatically compiled into a compositional data mining program, and how different domains in the schema can be related through logical sequences of biclustering and redescription invocations. This feature allows us to rapidly prototype new data mining applications, yielding greater understanding of scientific datasets. We describe two applications of compositional data mining: (i) matching terms across categories of the Gene Ontology and (ii) understanding the molecular mechanisms underlying stress response in human cells.
Forecasting Model for Air Taxi, Commercial Airline, and Automobile Demand in the United States
Baik, Hojong; Trani, Antonio A.; Hinze, Nicolas; Swingle, Howard; Ashiabor, Senanu; Seshadri, Anand (Transportation Research Board of the National Academies, 2008)
A nationwide model predicts the annual county-to-county person roundtrips for air taxi, commercial airline, and automobile at 1-year intervals through 2030. The transportation systems analysis model (TSAM) uses the four-step transportation systems modeling process to calculate trip generation, trip distribution, and mode choice for each county origin–destination pair. Network assignment is formulated for commercial airline and air taxi demand. TSAM classifies trip rates by trip purpose, household income group, and type of metropolitan statistical area from which the round-trip started. A graphical user interface with geographic information systems capability is included in the model. Potential applications of the model are nationwide impact studies of transportation policies and technologies, such as those envisioned with the introduction of extensive air taxi service using very light jets, the next-generation air transportation system, and the introduction of new aerospace technologies.
Crisis, Tragedy, and Recovery Network (CTRnet)
Fox, Edward A. (2009-09-14)
This poster provides an overview of the Crisis, Tragedy, and Recovery Network (CTRnet). The objectives of CTRnet are to build a digital library and preserve information (in various formats like HTML, images, videos, etc.) relating to all kinds of community crises and tragedies, as well as to integrate communities, content, and services relating to CTR.
Systems Integration of Biodefense Omics Data for Analysis of Pathogen-Host Interactions and Identification of Potential Targets
McGarvey, Peter B.; Huang, Hongzhan; Mazumder, Raja; Zhang, Jian; Chen, Yongxing; Zhang, Chengdong; Cammer, Stephen; Will, Rebecca; Odle, Margie; Sobral, Bruno; Moore, Margaret; Wu, Cathy H. (Public Library of Science, 2009-09-25)
The NIAID (National Institute for Allergy and Infectious Diseases) Biodefense Proteomics program aims to identify targets for potential vaccines, therapeutics, and diagnostics for agents of concern in bioterrorism, including bacterial, parasitic, and viral pathogens. The program includes seven Proteomics Research Centers, generating diverse types of pathogen-host data, including mass spectrometry, microarray transcriptional profiles, protein interactions, protein structures and biological reagents. The Biodefense Resource Center (www.proteomicsresource.org) has developed a bioinformatics framework, employing a protein-centric approach to integrate and support mining and analysis of the large and heterogeneous data. Underlying this approach is a data warehouse with comprehensive protein + gene identifier and name mappings and annotations extracted from over 100 molecular databases. Value-added annotations are provided for key proteins from experimental findings using controlled vocabulary. The availability of pathogen and host omics data in an integrated framework allows global analysis of the data and comparisons across different experiments and organisms, as illustrated in several case studies presented here. (1) The identification of a hypothetical protein with differential gene and protein expressions in two host systems (mouse macrophage and human HeLa cells) infected by different bacterial (Bacillus anthracis and Salmonella typhimurium) and viral (orthopox) pathogens suggesting that this protein can be prioritized for additional analysis and functional characterization. (2) The analysis of a vaccinia-human protein interaction network supplemented with protein accumulation levels led to the identification of human Keratin, type II cytoskeletal 4 protein as a potential therapeutic target. (3) Comparison of complete genomes from pathogenic variants coupled with experimental information on complete proteomes allowed the identification and prioritization of ten potential diagnostic targets from Bacillus anthracis. The integrative analysis across data sets from multiple centers can reveal potential functional significance and hidden relationships between pathogen and host proteins, thereby providing a systems approach to basic understanding of pathogenicity and target identification.
Designing for Schadenfreude (or, how to express well-being and see if youʼre boring people)
André, Paul; Schraefel, M.C.; Dix, Alan; White, Ryen W.; Bernstein, Michael; Luther, Kurt (ACM, 2010)
This position paper presents two studies of content not normally expressed in status updates—well-being and status feedback—and considers how they may be processed, valued and used for potential quality-of-life benefits in terms of personal and social reflection and awareness. Do I Tweet Good? (poor grammar intentional) is a site investigating more nuanced forms of status feedback than current microblogging sites allow, towards understanding self-identity, reflection, and online perception. Healthii is a tool for sharing physical and emotional well-being via status updates, investigating concepts of self-reflection and social awareness. Together, these projects consider furthering the value of microblogging on two fronts: 1) refining the online personal/social networking experience, and 2) using the status update for enhancing the personal/social experience in the offline world, and considering how to leverage that online/offline split. We offer results from two different methods of study and target groups—one co-workers in an academic setting, the other followers on Twitter—to consider how microblogging can become more than just a communication medium if it facilitates these types of reflective practice.
Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)
Kopacz, M.; Jacob, D. J.; Fisher, J. A.; Logan, J. A.; Zhang, L.; Megretskaia, I. A.; Yantosca, R. M.; Singh, K.; Henze, Daven K.; Burrows, J. P.; Buchwitz, M.; Khlystova, I.; McMillan, W. W.; Gille, J. C.; Edwards, D. P.; Eldering, A.; Thouret, V.; Nedelec, P. (Copernicus Publications, 2010)
We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005) global inversion of CO sources at 4 degrees x 5 degrees spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a(-1). This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.
Data Mining and Gap Analysis for Weather Responsive Traffic Management Program
Krechmer, Daniel; Rakha, Hesham A.; Howard, Mark; Huang, Weimin; Zohdy, Ismail H.; Du, Jianhe (United States. Federal Highway Administration, 2010)
Weather causes a variety of impacts on the transportation system. An Oak Ridge National Laboratory study estimated the delay experienced by American drivers due to snow, ice, and fog in 1999 at 46 million hours. While severe winter storms, hurricanes, or flooding can result in major stoppages or evacuations of transportation systems and cost millions of dollars, the day-to-day weather events such as rain, fog, snow, and freezing rain can have a serious impact on the mobility and safety of the transportation system users. Despite the documented impacts of adverse weather on transportation, the linkages between inclement weather conditions and traffic flow in existing analysis tools remain tenuous. This is primarily a result of limitations on the data used in research activities. The overall goal of this research was to identify gaps in the data necessary to develop weather responsive traffic management studies. Activities conducted to achieve this included 1) A comprehensive search and documentation of traffic and weather data in the United States and abroad that could be used for WRTM; 2) surveys, phone calls and site visits with organizations that have suitable traffic data on inclement weather; 3) identification of critical gaps in regards to the collection and processing of traffic data on inclement weather conditions; and 4) recommendation of strategies for gathering and processing data that will be used in WRTM studies. The study found that there are a number of useful research efforts underway both domestically and internationally that are yielding useful data for WRTM analysis. In some cases the scopes are limited and confidentiality issues were found in a number of European studies. There is increasing availability of quality traffic and weather data being generated by transportation and public/private weather information sources in the U.S. The analysis conducted for this project found that this data can be helpful in identifying adverse weather impacts on speed and lane usage. The report recommends that FHWA work closely with agencies as they expand their RWIS to assure that weather data is of adequate quality for WRTM analysis. FHWA also should continue to fund specific research and evaluation activities in conjunction with the Integrated Corridor Management Program or other WRTM initiatives.
NSF Year 1 Report for CTRnet: Integrated Digital Library Support for Crisis, Tragedy, and Recovery
Fox, Edward A.; Shoemaker, Donald J.; Sheetz, Steven D.; Kavanaugh, Andrea L.; Ramakrishnan, Naren (2010-07-08)
The Crisis, Tragedy and Recovery network, or CTRnet, is a human and digital library network for providing a range of services relating to different kinds of tragic events. Through this digital library, we will collect and archive different types of CTR related information, and apply advanced information analysis methods to this domain. It is hoped that services provided through CTRnet can help communities, as they heal and recover from tragic events. We have taken several major steps towards our goal of building a digital library for CTR events. Different strategies for collecting comprehensive information surrounding various CTR events have been explored, using school shooting events as a testbed. Several GBs worth of school shootings related data has been collected using the web crawling tools and methodologies we developed. Several different methods for removing non-relevant pages (noise) from the crawled data have been explored. A focused crawler is being developed with the aim of providing users the ability to build high quality collections for CTR events focused on their interests. Use of social media for CTRnet related research is being explored. Software to integrate the popular social networking site Facebook with the CTRnet digital library has been prototyped, and is being developed further. Integration of the popular micro-blogging site Twitter with the CTRnet digital library is being explored.
Learning probabilistic models of connectivity from multiple spike train data
Patnaik, Debprakash; Laxman, Srivatsan; Ramakrishnan, Naren (2010-07-20)
Neuronal circuits or cell assemblies carry out brain function through complex coordinated firing patterns [1]. Inferring topology of neuronal circuits from simultaneously recorded spike train data is a challenging problem in neuroscience. In this work we present a new class of dynamic Bayesian networks to infer polysynaptic excitatory connectivity between spiking cortical neurons [2]. The emphasis on excitatory networks allows us to learn connectivity models by exploiting fast data mining algorithms. Specifically, we show that frequent episodes help identify nodes with high mutual information relationships and can be summarized into a dynamic Bayesian network (DBN).
Quantifying Interhospital Patient Sharing as a Mechanism for Infectious Disease Spread
Huang, Susan S.; Avery, Takuser R.; Song, Yeohan H.; Elkins, Kristen R.; Nguyen, Christopher C.; Nutter, Sandra K.; Nafday, Alaka. A.; Condon, Curtis J.; Chang, Michael T.; Chrest, David; Boos, John; Bobashev, Georgiy; Wheaton, William; Frank, Steven A.; Platt, Richard; Lipsitch, Marc; Bush, Robin M.; Eubank, Stephen; Burke, Donald S.; Lee, Bruce Y. (University of Chicago Press, 2010-11)
BACKGROUND. Assessments of infectious disease spread in hospitals seldom account for interfacility patient sharing. This is particularly important for pathogens with prolonged incubation periods or carrier states. METHODS. We quantified patient sharing among all 32 hospitals in Orange County (OC), California, using hospital discharge data. Same-day transfers between hospitals were considered "direct" transfers, and events in which patients were shared between hospitals after an intervening stay at home or elsewhere were considered "indirect" patient-sharing events. We assessed the frequency of readmissions to another OC hospital within various time points from discharge and examined interhospital sharing of patients with Clostridium difficile infection. RESULTS. In 2005, OC hospitals had 319,918 admissions. Twenty-nine percent of patients were admitted at least twice, with a median interval between discharge and readmission of 53 days. Of the patients with 2 or more admissions, 75% were admitted to more than 1 hospital. Ninety-four percent of interhospital patient sharing occurred indirectly. When we used 10 shared patients as a measure of potential interhospital exposure, 6 (19%) of 32 hospitals "exposed" more than 50% of all OC hospitals within 6 months, and 17 (53%) exposed more than 50% within 12 months. Hospitals shared 1 or more patient with a median of 28 other hospitals. When we evaluated patients with C. difficile infection, 25% were readmitted within 12 weeks; 41% were readmitted to different hospitals, and less than 30% of these readmissions were direct transfers. CONCLUSIONS. In a large metropolitan county, interhospital patient sharing was a potential avenue for transmission of infectious agents. Indirect sharing with an intervening stay at home or elsewhere composed the bulk of potential exposures and occurred unbeknownst to hospitals.
Aging, resistance training, and diabetes prevention
Flack, Kyle D.; Davy, Kevin P.; Hulver, Matthew W.; Winett, Richard A.; Frisard, Madlyn I.; Davy, Brenda M. (2010-12-15)
With the aging of the baby-boom generation and increases in life expectancy, the American population is growing older. Aging is associated with adverse changes in glucose tolerance and increased risk of diabetes; the increasing prevalence of diabetes among older adults suggests a clear need for effective diabetes prevention approaches for this population. The purpose of paper is to review what is known about changes in glucose tolerance with advancing age and the potential utility of resistance training (RT) as an intervention to prevent diabetes among middle-aged and older adults. Age-related factors contributing to glucose intolerance, which may be improved with RT, include improvements in insulin signaling defects, reductions in tumor necrosis factor-α, increases in adiponectin and insulin-like growth factor-1 concentrations, and reductions in total and abdominal visceral fat. Current RT recommendations and future areas for investigation are presented.

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