904 resultados para Next-App


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We present the third-order QCD prediction for the production of top antitop quark pairs in electron-positron collisions close to the threshold in the dominant S-wave state. We observe a significant reduction of the theoretical uncertainty and discuss the sensitivity to the top quark mass and width.

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The quadrupole mass spectrometer (QMS) has over 30 years of spaceflight heritage in making important neutral gas and low energy ion observations. Given their geometrical constraints, these instruments are currently operated at the extreme limit of their capabilities. However, a technique called higher order auxiliary excitation provides a set of novel, robust, electronics-based solutions for improving the performance of these sensors. By driving the quadrupole rods with an additional frequency nearly twice that of the normal RF operating frequency, substantially increased abundance sensitivity, maximum attainable mass resolution, and peak stability can be achieved through operation of voltage scan lines through the center of formed upper stability islands. Such improvements are modeled using numerical simulations of ion trajectories in a quadrupole field with and without applied higher order auxiliary excitation. When compared to a traditional QMS with a mass range up to 500Da, sensors can be designed with the same precision electronics to have expected mass ranges beyond 1500Da with a power increase of less than twice that of its heritage implementations.

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Do you pronounce the /r/ in 'arm'? Do you call a shelf a 'sheuf'? And what on earth is a 'hoddy-doddy'? There is extensive variation in English dialects: this is why your answers to such questions will allow this app to localize your broader dialect region on a map of England. Did your home dialect change over time? Our algorithm is based on historical data from the Survey of English Dialects. If it guesses where you are from correctly, your home dialect has probably remained stable over the past decades. If the guess is far off, however, it is probably because of dialect change. - Can we localize your dialect based on your pronunciation of 26 words? - Record your dialect and listen to recordings of other users and to historical dialect recordings! - Choose a pronunciation variant, e.g. 'sheuf', and discover where in England it is used...or choose a place and explore its dialect!

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Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

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Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

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Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

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Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

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Background: Zooplankton play an important role in our oceans, in biogeochemical cycling and providing a food source for commercially important fish larvae. However, difficulties in correctly identifying zooplankton hinder our understanding of their roles in marine ecosystem functioning, and can prevent detection of long term changes in their community structure. The advent of massively parallel Next Generation Sequencing technology allows DNA sequence data to be recovered directly from whole community samples. Here we assess the ability of such sequencing to quantify the richness and diversity of a mixed zooplankton assemblage from a productive monitoring site in the Western English Channel. Methodology/Principle Findings: Plankton WP2 replicate net hauls (200 µm) were taken at the Western Channel Observatory long-term monitoring station L4 in September 2010 and January 2011. These samples were analysed by microscopy and metagenetic analysis of the 18S nuclear small subunit ribosomal RNA gene using the 454 pyrosequencing platform. Following quality control a total of 419,042 sequences were obtained for all samples. The sequences clustered in to 205 operational taxonomic units using a 97% similarity cut-off. Allocation of taxonomy by comparison with the National Centre for Biotechnology Information database identified 138 OTUs to species level, 11 to genus level and 1 to order, <2.5% of sequences were classified as unknowns. By comparison a skilled microscopic analyst was able to routinely enumerate only 75 taxonomic groups. Conclusions: The percentage of OTUs assigned to major eukaryotic taxonomic groups broadly aligns between the metagenetic and morphological analysis and are dominated by Copepoda. However, the metagenetics reveals a previously hidden taxonomic richness, especially for Copepoda and meroplankton such as Bivalvia, Gastropoda and Polychaeta. It also reveals rare species and parasites. We conclude that Next Generation Sequencing of 18S amplicons is a powerful tool for estimating diversity and species richness of zooplankton communities.