28 research outputs found
FLY: Venue Recommendation using Limited Context
No full textRecommendation of publication venues is very much the need of the hour. There is a sea of options for research conferences and journals. As a result, it is often found that researchers are not even aware of many publication venues in their research area. Existing work uses information, such as all the references in a given paper, past publication venues of the author(s), co-Author relationships, and the paper content to do venue recommendation. However, in this paper, we propose a system that uses very limited context, namely the paper title, abstract, and a venue network, which is constructed using only a small subset of authors' publication history, to do venue recommendation. Our venue recommendation system, FLY, gives 30% higher accuracy compared to the current state-of-The-Art limited context venue recommendation system
Location Identification of the Individual based on Image Metadata
No full textAbstractNow-a-days an individual is directly or indirectly attached to many smart devices. One can find his or her whereabouts if we monitor the devices they are using by collecting the metadata of the photos posted by them in the social media. Some social media websites have a feature to post the place of their recent past. To provide a simple Android application, this will be using the feature of Geo tagging available with most of the smart phones. We can use this location based data to track the people based on longitude and latitude of Global positioning system(GPS). We can use this to collect the photos posted by individuals and to analyze them to know their present position. The proposed article verifies the metadata associated with image and track the individual country, city, route and street based on the GPS Altitude, GPS Latitude, GPS Longitude and GPS position
Effect of deposition temperature & oxygen pressure on mechanical properties of (0.5) BZT-(0.5)BCT ceramic thin films
No full textApplication of flat panel OLED display technology for the point-of-care detection of circulating cancer biomarkers
No full textabstract: Point-of-care molecular diagnostics can provide efficient and cost-effective medical care, and they have the potential to fundamentally change our approach to global health. However, most existing approaches are not scalable to include multiple biomarkers. As a solution, we have combined commercial flat panel OLED display technology with protein microarray technology to enable high-density fluorescent, programmable, multiplexed biorecognition in a compact and disposable configuration with clinical-level sensitivity. Our approach leverages advances in commercial display technology to reduce pre-functionalized biosensor substrate costs to pennies per cm[superscript 2]. Here, we demonstrate quantitative detection of IgG antibodies to multiple viral antigens in patient serum samples with detection limits for human IgG in the 10 pg/mL range. We also demonstrate multiplexed detection of antibodies to the HPV16 proteins E2, E6, and E7, which are circulating biomarkers for cervical as well as head and neck cancers.The final version of this article, as published in Scientific Reports, can be viewed online at: https://www.nature.com/articles/srep2905
Hundreds of variants clustered in genomic loci and biological pathways affect human height
No full textMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait(2,3). The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways
Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
No full textWaist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions
Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
No full textApproaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
No full textObesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and similar to 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation
Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models
No full text2017 Spring.Includes bibliographical references.Laboratory-based studies have shown that diesel-powered sources emit volatile organic compounds that can be photo-oxidized in the atmosphere to form secondary organic aerosol (SOA); in some cases, this SOA can exceed direct emissions of particulate matter (PM); PM is a criteria pollutant that is known to have adverse effects on air quality, climate, and human health. However, there are open questions surrounding how these laboratory experiments can be extrapolated to the real atmosphere and how they will help identify the most important species in diesel exhaust that contribute to SOA formation. Jathar et al. (2017) recently performed experiments using an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel) and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we will use two different SOA models, namely the volatility basis set (VBS) model and the statistical oxidation model (SOM), to simulate the formation, evolution and composition of SOA from the experiments of Jathar et al. (2017). Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA, SOA production from semi-volatile, intermediate-volatility and volatile organic compounds (SVOC, IVOC and VOC), NOx-dependent multigenerational gas-phase chemistry, and kinetic gas/particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass and elemental composition to agree with measurements across all engine load-fuel-aftertreatment combinations, it was necessary to (a) model the kinetically-limited gas/particle partitioning likely in OFRs and (b) account for SOA formation from IVOCs (IVOCs were found to account for more than four-fifths of the model-predicted SOA). Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements made using a Chemical Ionization Mass Spectrometer (CIMS) that, qualitatively, substantiated the semi-explicit chemistry captured by the SOM and the measurements made by the CIMS. Sensitivity simulations suggested that (a) IVOCs from diesel exhaust could be modeled using a single surrogate species with an SOA mass yield equivalent to a C15 or C17 linear alkane for use in large-scale models, (b) different diesel exhaust emissions profiles in the literature resulted in the same SOA production as long as IVOCs were included and (c) accounting for vapor wall loss parameterizations for the SOA precursors improved model performance. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, there is a need to develop models that can be used to interpret the OFR data. This work is one example of the model development and application relevant to the use of OFRs
A selective NIR-emitting zinc sensor by using Schiff base binding to turn-on excited-state intramolecular proton transfer
No full textA rational design has led to a highly selective and cell-permeable zinc sensor, which exhibits not only a large fluorescence turn-on at similar to 545 nm but also the desirable NIR emission (similar to 720 nm) with a large Stokes' shift, providing a practical sensor platform with two emission channels for reliable zinc detection.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000333094700010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Materials Science, BiomaterialsSCI(E)[email protected]
