Inferring latent task structure for Multitask Learning by Multiple Kernel Learning

<p>Abstract</p> <p>Background</p> <p>The lack of sufficient training data is the limiting factor for many Machine Learning applications in Computational Biology. If data is available for several different but related problem domains, Multitask Learning algorithms can be used to learn a model based on all available information. In Bioinformatics, many problems can be cast into the Multitask Learning scenario by incorporating data from several organisms. However, combining information from several tasks requires careful consideration of the degree of similarity between tasks. Our proposed method simultaneously learns or refines the similarity between tasks along with the Multitask Learning classifier. This is done by formulating the Multitask Learning problem as Multiple Kernel Learning, using the recently published <it>q</it>-Norm MKL algorithm.</p> <p>Results</p> <p>We demonstrate the performance of our method on two problems from Computational Biology. First, we show that our method is able to improve performance on a splice site dataset with given hierarchical task structure by refining the task relationships. Second, we consider an MHC-I dataset, for which we assume no knowledge about the degree of task relatedness. Here, we are able to learn the task similarities<it> ab initio</it> along with the Multitask classifiers. In both cases, we outperform baseline methods that we compare against.</p> <p>Conclusions</p> <p>We present a novel approach to Multitask Learning that is capable of learning task similarity along with the classifiers. The framework is very general as it allows to incorporate prior knowledge about tasks relationships if available, but is also able to identify task similarities in absence of such prior information. Both variants show promising results in applications from Computational Biology.</p

Development and Testing of the Miniaturized Pavement Pressuremeter for Use in Unbound Pavement Layers

BDV 28 977-04A small diameter pressuremeter (SDPMT) was developed, tested and used in numerous correlations at four testing sites on and near the campus of the Florida Institute of Technology. SDPMT probes were inserted directly in to the holes made with the drive pin used during nuclear density testing. SDPMT testing produced lift-off, and limit pressures along with elastic moduli that were all correlated to PENCEL PMT data. SDPMT data was acquired digitally using two types of strain-controlled tests; a conventional incremental volume injection test and a continuous volume injection test. Two probe lengths were developed and tested, one being 6-inches and a second being 12-inches long, to enable either 6- or 12-inch unbound pavement layers to be tested. Data from 159 SDPMT tests were correlated to stiffnesses from 96 Clegg Impact, and 141 Lightweight Deflectometer (LWD) tests, plus 107 dry densities from nuclear density testing. Finite element analyses were conducted so that SDPMT predicted deflections could be compared to LWD measured deflections at all four sites. The SDPMT probes that were developed can be used and repaired much more efficiently than other PMT probes, making them very desirable. The continuous volume injection testing with data acquisition, using the Automated PMT software (APMT) was completed in less than a minute, making it a very useful engineering tool. The correlations showed that both SDPMT stiffness and strength compare well to Clegg and LWD stiffnesses. They also showed a very strong correlation exists between the SDPMT strength and stiffness from the 12-inch SDPMT probe during incremental volume testing. The 12-inch SDPMT tests produced slightly more consistent results than the 6-inch SDPMT tests. The LWD measured and finite element SDPMT predicted deflections were similar, falling within about 10%. In summary, both the incremental and continuous volume injection process for the 6-and 12-inch SDPMT were proven to be useful. These new pressuremeters are recommended for use in conjunction with nuclear density test data to thoroughly categorize the strength-stiffness and density information along any unbound pavement roadway section

Virtual reality genres: Comparing preferences in immersive experiences and games

5 pagesEven though virtual reality (VR) shares features with video games, it offers a wider range of experiences. There is currently no cohesive classification for commercial VR offerings. As a first step to account for this deficiency, the work in progress considers the relationship between game genres and users’ ratings and downloads of VR experiences. We found Action, Shooter, and Simulation to be the most frequently downloaded genres; Action and Music/Rhythm the most highly rated; and Simulation and Music/Rhythm to occur at a statistically higher rate in VR compared to non-VR. Finally, we learned that VR experiences are less likely to receive positive ratings than 2D games. The findings can inform developers’ marketing decisions based on demand

Covariant description of inelastic electron--deuteron scattering:predictions of the relativistic impulse approximation

Using the covariant spectator theory and the transversity formalism, the unpolarized, coincidence cross section for deuteron electrodisintegration, $d(e,e'p)n$, is studied. The relativistic kinematics are reviewed, and simple theoretical formulae for the relativistic impulse approximation (RIA) are derived and discussed. Numerical predictions for the scattering in the high $Q^2$ region obtained from the RIA and five other approximations are presented and compared. We conclude that measurements of the unpolarized coincidence cross section and the asymmetry $A_\phi$, to an accuracy that will distinguish between different theoretical models, is feasible over most of the wide kinematic range accessible at Jefferson Lab.Comment: 54 pages and 24 figure

A Comparison of Two Measures of HIV Diversity in Multi-Assay Algorithms for HIV Incidence Estimation

Background: Multi-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence. Methods: Both MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies. Results: The proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion. Conclusions: MAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation

Data Generated during the 2018 LAPSE-RATE Campaign: An Introduction and Overview

Unmanned aircraft systems (UASs) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14 to 20 July 2018 the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign spanned a 1-week deployment to Colorado\u27s San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020)

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science During the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 °C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS

Surgical treatment for acromioclavicular joint osteoarthritis: patient selection, surgical options, complications, and outcome

Osteoarthritis is one of the most common causes of pain originating from the acromioclavicular (AC) joint. An awareness of appropriate diagnostic techniques is necessary in order to localize clinical symptoms to the AC joint. Initial treatments for AC joint osteoarthritis, which include non-steroidal anti-inflammatory drugs (NSAIDS) and corticosteroids, are recommended prior to surgical interventions. Distal clavicle excision, the main surgical treatment option, can be performed by various surgical approaches, such as open procedures, direct arthroscopic, and indirect arthroscopic techniques. When choosing the best surgical option, factors such as avoidance of AC ligament damage, clavicular instability, and post-operative pain must be considered. This article examines patient selection, complications, and outcomes of surgical treatment options for AC joint osteoarthritis

Biomarkers of exposure to new and emerging tobacco delivery products

Accurate and reliable measurements of exposure to tobacco products are essential for identifying and confirming patterns of tobacco product use and for assessing their potential biological effects in both human populations and experimental systems. Due to the introduction of new tobaccoderived products and the development of novel ways to modify and use conventional tobacco products, precise and specific assessments of exposure to tobacco are now more important than ever. Biomarkers that were developed and validated to measure exposure to cigarettes are being evaluated to assess their use for measuring exposure to these new products. Here, we review current methods for measuring exposure to new and emerging tobacco products, such as electronic cigarettes, little cigars, water pipes, and cigarillos. Rigorously validated biomarkers specific to these new products have not yet been identified. Here, we discuss the strengths and limitations of current approaches, including whether they provide reliable exposure estimates for new and emerging products. We provide specific guidance for choosing practical and economical biomarkers for different study designs and experimental conditions. Our goal is to help both new and experienced investigators measure exposure to tobacco products accurately and avoid common experimental errors. With the identification of the capacity gaps in biomarker research on new and emerging tobacco products, we hope to provide researchers, policymakers, and funding agencies with a clear action plan for conducting and promoting research on the patterns of use and health effects of these products