Analysis of opposed jet hydrogen-air counter flow diffusion flame

A computational simulation of the opposed-jet diffusion flame is performed to study its structure and extinction limits. The present analysis concentrates on the nitrogen-diluted hydrogen-air diffusion flame, which provides the basic information for many vehicle designs such as the aerospace plane for which hydrogen is a candidate as the fuel. The computer program uses the time-marching technique to solve the energy and species equations coupled with the momentum equation solved by the collocation method. The procedure is implemented in two stages. In the first stage, a one-step forward overal chemical reaction is chosen with the gas phase chemical reaction rate determined by comparison with experimental data. In the second stage, a complete chemical reaction mechanism is introduced with detailed thermodynamic and transport property calculations. Comparison between experimental extinction data and theoretical predictions is discussed. The effects of thermal diffusion as well as Lewis number and Prandtl number variations on the diffusion flame are also presented

On reliable computation over larger alphabets

We present two new positive results for reliable computation using formulas over physical alphabets of size $q > 2$. First, we show that for logical alphabets of size $\ell = q$ the threshold for denoising using gates subject to $q$-ary symmetric noise with error probability $\epsilon$ is strictly larger that possible for Boolean computation and we demonstrate a clone of $q$-ary functions that can be reliably computed up to this threshold. Secondly, we provide an example where $\ell < q$, showing that reliable Boolean computation can be performed using $2$-input ternary logic gates subject to symmetric ternary noise of strength $\epsilon < 1/6$ by using the additional alphabet element for error signalling.Comment: 14 pages, 2 figure

BridgeDb: standardized access to gene, protein and metabolite identifier mapping services

Many interesting problems in bioinformatics require integration of data from various sources. For example when combining microarray data with a pathway database, or merging co-citation networks with protein-protein interaction networks. Invariably this leads to an identifier mapping problem, where different datasets are annotated with identifiers that are related, but originate from different databases.&#xd;&#xa;&#xd;&#xa;Solutions for the identifier mapping problem exist, such as Biomart, Synergizer, Cronos, PICR, HMS and many more. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. BridgeDb provides such an interface layer, in the form of both a Java and REST API.&#xd;&#xa;&#xd;&#xa;Because of the standardized interface layer, BridgeDb is not tied to a specific source of mapping information. You can switch easily between flat files, relational databases and several different web services. Mapping services can be combined to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb isn&#x27;t just yet another mapping service: it tries to build further on existing work, and integrate multiple partial solutions. The framework is intended for customization and adaptation to any identifier mapping service. &#xd;&#xa;&#xd;&#xa;BridgeDb makes it easy to add an important capability to existing tools. BridgeDb has already been integrated into several popular bioinformatics applications, such as Cytoscape, WikiPathways, PathVisio, Vanted and Taverna. To encourage tool developers to start using BridgeDb, we&#x27;ve created code examples, online documentation, and a mailinglist to ask questions. &#xd;&#xa;&#xd;&#xa;We believe that, to meet the challenges that are encountered in bioinformatics today, the software development process should follow a few essential principles: user friendliness, code reuse, modularity and open source. BridgeDb adheres to these principles, and can serve as a useful model for others to follow. BridgeDb can function to increase user-friendliness of graphical applications. It re-uses work from other projects such as BioMart and MIRIAM. BridgeDb consists of several small modules, integrated through a common interface (API). Components of BridgeDb can be left out or replaced, for maximum flexibility. BridgeDb was open source from the very beginning of the project. The philosophy of open source is closely aligned to academic values, of building on top of the work of giants. &#xd;&#xa;&#xd;&#xa;Many interesting problems in bioinformatics require integration of data from various sources. For example when combining microarray data with a pathway database, or merging co-citation networks with protein-protein interaction networks. Invariably this leads to an identifier mapping problem, where different datasets are annotated with identifiers that are related, but originate from different databases.&#xd;&#xa;&#xd;&#xa;Solutions for the identifier mapping problem exist, such as Biomart, Synergizer, Cronos, PICR, HMS and many more. This creates an opportunity for bioinformatics tool developers. Tools can be made to flexibly support multiple mapping services or mapping services could be combined to get broader coverage. This approach requires an interface layer between tools and mapping services. BridgeDb provides such an interface layer, in the form of both a Java and REST API.&#xd;&#xa;&#xd;&#xa;Because of the standardized interface layer, BridgeDb is not tied to a specific source of mapping information. You can switch easily between flat files, relational databases and several different web services. Mapping services can be combined to support multi-omics experiments or to integrate custom microarray annotations. BridgeDb isn&#x27;t just yet another mapping service: it tries to build further on existing work, and integrate multiple partial solutions. The framework is intended for customization and adaptation to any identifier mapping service. &#xd;&#xa;&#xd;&#xa;BridgeDb makes it easy to add an important capability to existing tools. BridgeDb has already been integrated into several popular bioinformatics applications, such as Cytoscape, WikiPathways, PathVisio, Vanted and Taverna. To encourage tool developers to start using BridgeDb, we&#x27;ve created code examples, online documentation, and a mailinglist to ask questions. &#xd;&#xa;&#xd;&#xa;We believe that, to meet the challenges that are encountered in bioinformatics today, the software development process should follow a few essential principles: user friendliness, code reuse, modularity and open source. BridgeDb adheres to these principles, and can serve as a useful model for others to follow. BridgeDb can function to increase user-friendliness of graphical applications. It re-uses work from other projects such as BioMart and MIRIAM. BridgeDb consists of several small modules, integrated through a common interface (API). Components of BridgeDb can be left out or replaced, for maximum flexibility. BridgeDb was open source from the very beginning of the project. The philosophy of open source is closely aligned to academic values, of building on top of the work of giants. &#xd;&#xa;&#xd;&#xa;The BridgeDb library is available at &#x22;http://www.bridgedb.org&#x22;:http://www.bridgedb.org.&#xd;&#xa;A paper about BridgeDb was published in BMC _Bioinformatics_, 2010 Jan 4;11(1):5.&#xd;&#xa;&#xd;&#xa;BridgeDb blog: &#x22;http://www.helixsoft.nl/blog/?tag=bridgedb&#x22;:http://www.helixsoft.nl/blog/?tag=bridged

Neural Networks and Dynamic Complex Systems

We describe the use of neural networks for optimization and inference associated with a variety of complex systems. We show how a string formalism can be used for parallel computer decomposition, message routing and sequential optimizing compilers. We extend these ideas to a general treatment of spatial assessment and distributed artificial intelligence

Serotonin transporter polymorphisms and clinical response to sertraline across ethnicities

The aim of this pilot study was to examine the relationship between clinical response, adverse effects, sertraline (SERT) plasma concentrations and the genetic polymorphism of the serotonin transporter gene-linked polymorphic region (5HTTLPR) in 2 ethnic patient groups. The study involved 45 patients in a clinical trial who received a fixed dose regimen of 50 mg SERT for one week, then a variable-dose regimen for a further 6 weeks for major depressive disorder. At weeks 1 and 6, the following assessments were completed: Hamilton Depression Rating Scale (HDRS), Clinical Global Impression (CGI), drug adverse reaction scale and measurement of plasma SERT levels. Genomic analysis for the long and short allele variants of the 5HTTLPR polymorphism was also carried out. Caucasian subjects had a higher rate of l/l genotype while Chinese subjects had higher frequencies of l/s and s/s genotypes. Comparison of the subjects with the 5HTTLPR s/s genotype and those with the l/l and l/s genotypes found no significant differences in the HDRS scores, CGI scores, response rates, adverse effects and SERT plasma concentrations at week 6

Social Media Usage and Influenza Beliefs, Risk Perceptions and Behavioral Intentions Among Students at a University in Southeastern US

Background: To document social media usage for the retrieval of health information among college students; and to understand the beliefs, risk perceptions and behavioral intentions among participants who retrieved CDC influenza information via social media. Methods: We conducted an online survey to a convenience sample of students at a university in Southeastern United States during Spring 2015. The survey was self-administered and every matriculating student received an electronic invitation to participate at least once. Results: A total of 930 students completed the online survey. Most participants (n=905, 97.3%) reported that they had used a social networking site in the previous 12 months. However, only one-third (n=317, 34.1%) reported that they used social networking sites to read CDC health information or messages. Nearly one-fifth of participants (n=172, 18.5%) reported reading CDC influenza information during the 2014-15 influenza season. Among the subset of readers of CDC influenza information during the 2014-15 influenza season (N=153), 77 (50.99%) reported that it was likely they would get the influenza vaccine in the next 12 months. Women reported stronger risk perceptions and behavioral intentions than men. Blacks/African Americans reported more negative influenza-related beliefs and weaker risk perceptions compared to Whites. Conclusions: While social media penetration is high among university students in Southeastern US, only a minority of survey participants retrieved CDC influenza information via social media. Among these individuals, about half reported that they intended to vaccinate against influenza. Further research is needed to enhance CDC social media penetration among college students

HarvardX and MITx: The First Year of Open Online Courses, Fall 2012-Summer 2013

HarvardX and MITx are collaborative institutional efforts between Harvard University and MIT to enhance campus-based education, advance educational research, and increase access to online learning opportunities worldwide. Over the year from the fall of 2012 to the summer of 2013, HarvardX and MITx launched 17 courses on edX, a jointly founded platform for delivering massive open online courses (MOOCs). In that year, 43,196 registrants earned certificates of completion. Another 35,937 registrants explored half or more of course content without certification. An additional 469,702 registrants viewed less than half of the content. And 292,852 registrants never engaged with the online content. In total, there were 841,687 registrations from 597,692 unique users across the first year of HarvardX and MITx courses. This report is a joint effort by institutional units at Harvard and MIT to describe the registrant and course data provided by edX in the context of the diverse efforts and intentions of HarvardX and MITx instructor teams

Use of Preference Analysis to Identify Early Adopter Mind-Sets of Insect-Based Food Products

Insects may potentially provide an alternative protein source. However, consumers may not easily accept insects due to feelings of disgust. Therefore, identifying early adopters of insect-based food products may determine their future acceptance. This study was conducted to (1) identify early adopter Mind-Sets of insect-based food products, (2) determine product features early adopters would prefer in an insect-based food product, and (3) determine differences in Mind-Sets in different countries. Two studies were distributed online in the US and the Philippines. The first study included information about insects, while the second study had no information on insects. The experimental design included elements, or product features, regarding insect-based products that participants evaluated. Preference Analysis was used to segment the participants into Mind-Sets. Based on the results, participants neither liked nor disliked the elements used. Participants in the studies without insect information were found to have higher liking when comparing liking. Participants who were aware of the study being about insects may have had less interest when evaluating the elements, as the response times between the US studies were significantly different (p < 0.05). The role of information and segmentation of the participants demonstrates the importance of experimental design when using Preference Analysis

Social Media Usage and Influenza Beliefs, Risk Perceptions and Behavioral Intentions Among Students at a University in Southeastern US

Background: To document social media usage for the retrieval of health information among college students; and to understand the beliefs, risk perceptions and behavioral intentions among participants who retrieved CDC influenza information via social media. Methods: We conducted an online survey to a convenience sample of students at a university in Southeastern United States during Spring 2015. The survey was self-administered and every matriculating student received an electronic invitation to participate at least once. Results: A total of 930 students completed the online survey. Most participants (n=905, 97.3%) reported that they had used a social networking site in the previous 12 months. However, only one-third (n=317, 34.1%) reported that they used social networking sites to read CDC health information or messages. Nearly one-fifth of participants (n=172, 18.5%) reported reading CDC influenza information during the 2014-15 influenza season. Among the subset of readers of CDC influenza information during the 2014-15 influenza season (N=153), 77 (50.99%) reported that it was likely they would get the influenza vaccine in the next 12 months. Women reported stronger risk perceptions and behavioral intentions than men. Blacks/African Americans reported more negative influenza-related beliefs and weaker risk perceptions compared to Whites. Conclusions: While social media penetration is high among university students in Southeastern US, only a minority of survey participants retrieved CDC influenza information via social media. Among these individuals, about half reported that they intended to vaccinate against influenza. Further research is needed to enhance CDC social media penetration among college students