Shear wave velocity variation across the Taupo Volcanic Zone, New Zealand, from receiver function inversion

USGS Publications Warehouse

Bannister, S.; Bryan, C.J.; Bibby, H.M.

2004-01-01

The Taupo Volcanic Zone (TVZ), New Zealand is a region characterized by very high magma eruption rates and extremely high heat flow, which is manifest in high-temperature geothermal waters. The shear wave velocity structure across the region is inferred using non-linear inversion of receiver functions, which were derived from teleseismic earthquake data. Results from the non-linear inversion, and from forward synthetic modelling, indicate low S velocities at ???6- 16 km depth near the Rotorua and Reporoa calderas. We infer these low-velocity layers to represent the presence of high-level bodies of partial melt associated with the volcanism. Receiver functions at other stations are complicated by reverberations associated with near-surface sedimentary layers. The receiver function data also indicate that the Moho lies between 25 and 30 km, deeper than the 15 ?? 2 km depth previously inferred for the crust-mantle boundary beneath the TVZ. ?? 2004 RAS.

A wave equation migration method for receiver function imaging: 2. Application to the Japan subduction zone

NASA Astrophysics Data System (ADS)

Chen, Ling; Wen, Lianxing; Zheng, Tianyu

2005-11-01

The newly developed wave equation poststack depth migration method for receiver function imaging is applied to study the subsurface structures of the Japan subduction zone using the Fundamental Research on Earthquakes and Earth's Interior Anomalies (FREESIA) broadband data. Three profiles are chosen in the subsurface imaging, two in northeast (NE) Japan to study the subducting Pacific plate and one in southwest (SW) Japan to study the Philippine Sea plate. The descending Pacific plate in NE Japan is well imaged within a depth range of 50-150 km. The slab image exhibits a little more steeply dipping angle (˜32°) in the south than in the north (˜27°), although the general characteristics between the two profiles in NE Japan are similar. The imaged Philippine Sea plate in eastern SW Japan, in contrast, exhibits a much shallower subduction angle (˜19°) and is only identifiable at the uppermost depths of no more than 60 km. Synthetic tests indicate that the top 150 km of the migrated images of the Pacific plate is well resolved by our seismic data, but the resolution of deep part of the slab images becomes poor due to the limited data coverage. Synthetic tests also suggest that the breakdown of the Philippine Sea plate at shallow depths reflects the real structural features of the subduction zone, rather than caused by insufficient coverage of data. Comparative studies on both synthetics and real data images show the possibility of retrieval of fine-scale structures from high-frequency contributions if high-frequency noise can be effectively suppressed and a small bin size can be used in future studies. The derived slab geometry and image feature also appear to have relatively weak dependence on overlying velocity structure. The observed seismicity in the region confirms the geometries inferred from the migrated images for both subducting plates. Moreover, the deep extent of the Pacific plate image and the shallow breakdown of the Philippine Sea plate image are observed to correlate well with the depth extent of the seismicity beneath NE and SW Japan. Such a correlation supports the inference that the specific appearance of slabs and intermediate-depth earthquakes are a consequence of temperature-dependent dehydration induced metamorphism occurring in the hydrated descending oceanic crust.

Field emission energy distributions of hydrogen and deuterium on the /100/ and /110/ planes of tungsten.

NASA Technical Reports Server (NTRS)

Plummer, E. W.; Bell, A. E.

1972-01-01

Total energy distributions of field emitted electrons from the tungsten (110) and (100) planes as a function of coverage by hydrogen and deuterium have been recorded utilizing a spherical deflection energy analyzer. The elastic tunneling resonance spectrum gives a plot of the 'local density of states' in the adsorbate. The inelastic tunneling spectrum reveals those discrete excitation energies available in the adsorbate-substrate complex. These spectroscopic data have been used to infer the chemical nature of the binding states which have been observed in the flash desorption spectrum of hydrogen from tungsten.

Haplotype estimation using sequencing reads.

PubMed

Delaneau, Olivier; Howie, Bryan; Cox, Anthony J; Zagury, Jean-François; Marchini, Jonathan

2013-10-03

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5-20 kb read with 4%-15% error per base), phasing performance was substantially improved. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Mind the gap! The mitochondrial control region and its power as a phylogenetic marker in echinoids.

PubMed

Bronstein, Omri; Kroh, Andreas; Haring, Elisabeth

2018-05-30

In Metazoa, mitochondrial markers are the most commonly used targets for inferring species-level molecular phylogenies due to their extremely low rate of recombination, maternal inheritance, ease of use and fast substitution rate in comparison to nuclear DNA. The mitochondrial control region (CR) is the main non-coding area of the mitochondrial genome and contains the mitochondrial origin of replication and transcription. While sequences of the cytochrome oxidase subunit 1 (COI) and 16S rRNA genes are the prime mitochondrial markers in phylogenetic studies, the highly variable CR is typically ignored and not targeted in such analyses. However, the higher substitution rate of the CR can be harnessed to infer the phylogeny of closely related species, and the use of a non-coding region alleviates biases resulting from both directional and purifying selection. Additionally, complete mitochondrial genome assemblies utilizing next generation sequencing (NGS) data often show exceptionally low coverage at specific regions, including the CR. This can only be resolved by targeted sequencing of this region. Here we provide novel sequence data for the echinoid mitochondrial control region in over 40 species across the echinoid phylogenetic tree. We demonstrate the advantages of directly targeting the CR and adjacent tRNAs to facilitate complementing low coverage NGS data from complete mitochondrial genome assemblies. Finally, we test the performance of this region as a phylogenetic marker both in the lab and in phylogenetic analyses, and demonstrate its superior performance over the other available mitochondrial markers in echinoids. Our target region of the mitochondrial CR (1) facilitates the first thorough investigation of this region across a wide range of echinoid taxa, (2) provides a tool for complementing missing data in NGS experiments, and (3) identifies the CR as a powerful, novel marker for phylogenetic inference in echinoids due to its high variability, lack of selection, and high compatibility across the entire class, outperforming conventional mitochondrial markers.

Studies of high coverage oxidation of the Cu(100) surface using low energy positrons

NASA Astrophysics Data System (ADS)

Fazleev, N. G.; Maddox, W. B.; Weiss, A. H.

2012-02-01

The study of oxidation of single crystal metal surfaces is important in understanding the corrosive and catalytic processes associated with thin film metal oxides. The structures formed on oxidized transition metal surfaces vary from simple adlayers of chemisorbed oxygen to more complex structures which result from the diffusion of oxygen into subsurface regions. In this work we present the results of theoretical studies of positron surface and bulk states and annihilation probabilities of surface-trapped positrons with relevant core electrons at the oxidized Cu(100) surface under conditions of high oxygen coverage. Calculations are performed for various high coverage missing row structures ranging between 0.50 and 1.50 ML oxygen coverage. The results of calculations of positron binding energy, positron work function, and annihilation characteristics of surface trapped positrons with relevant core electrons as function of oxygen coverage are compared with experimental data obtained from studies of oxidation of the Cu(100) surface using positron annihilation induced Auger electron spectroscopy (PAES).

Inference of Gorilla Demographic and Selective History from Whole-Genome Sequence Data

PubMed Central

McManus, Kimberly F.; Kelley, Joanna L.; Song, Shiya; Veeramah, Krishna R.; Woerner, August E.; Stevison, Laurie S.; Ryder, Oliver A.; Ape Genome Project, Great; Kidd, Jeffrey M.; Wall, Jeffrey D.; Bustamante, Carlos D.; Hammer, Michael F.

2015-01-01

Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection. PMID:25534031

Variant calling in low-coverage whole genome sequencing of a Native American population sample.

PubMed

Bizon, Chris; Spiegel, Michael; Chasse, Scott A; Gizer, Ian R; Li, Yun; Malc, Ewa P; Mieczkowski, Piotr A; Sailsbery, Josh K; Wang, Xiaoshu; Ehlers, Cindy L; Wilhelmsen, Kirk C

2014-01-30

The reduction in the cost of sequencing a human genome has led to the use of genotype sampling strategies in order to impute and infer the presence of sequence variants that can then be tested for associations with traits of interest. Low-coverage Whole Genome Sequencing (WGS) is a sampling strategy that overcomes some of the deficiencies seen in fixed content SNP array studies. Linkage-disequilibrium (LD) aware variant callers, such as the program Thunder, may provide a calling rate and accuracy that makes a low-coverage sequencing strategy viable. We examined the performance of an LD-aware variant calling strategy in a population of 708 low-coverage whole genome sequences from a community sample of Native Americans. We assessed variant calling through a comparison of the sequencing results to genotypes measured in 641 of the same subjects using a fixed content first generation exome array. The comparison was made using the variant calling routines GATK Unified Genotyper program and the LD-aware variant caller Thunder. Thunder was found to improve concordance in a coverage dependent fashion, while correctly calling nearly all of the common variants as well as a high percentage of the rare variants present in the sample. Low-coverage WGS is a strategy that appears to collect genetic information intermediate in scope between fixed content genotyping arrays and deep-coverage WGS. Our data suggests that low-coverage WGS is a viable strategy with a greater chance of discovering novel variants and associations than fixed content arrays for large sample association analyses.

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Enhanced Methods for Local Ancestry Assignment in Sequenced Admixed Individuals

PubMed Central

Brown, Robert; Pasaniuc, Bogdan

2014-01-01

Inferring the ancestry at each locus in the genome of recently admixed individuals (e.g., Latino Americans) plays a major role in medical and population genetic inferences, ranging from finding disease-risk loci, to inferring recombination rates, to mapping missing contigs in the human genome. Although many methods for local ancestry inference have been proposed, most are designed for use with genotyping arrays and fail to make use of the full spectrum of data available from sequencing. In addition, current haplotype-based approaches are very computationally demanding, requiring large computational time for moderately large sample sizes. Here we present new methods for local ancestry inference that leverage continent-specific variants (CSVs) to attain increased performance over existing approaches in sequenced admixed genomes. A key feature of our approach is that it incorporates the admixed genomes themselves jointly with public datasets, such as 1000 Genomes, to improve the accuracy of CSV calling. We use simulations to show that our approach attains accuracy similar to widely used computationally intensive haplotype-based approaches with large decreases in runtime. Most importantly, we show that our method recovers comparable local ancestries, as the 1000 Genomes consensus local ancestry calls in the real admixed individuals from the 1000 Genomes Project. We extend our approach to account for low-coverage sequencing and show that accurate local ancestry inference can be attained at low sequencing coverage. Finally, we generalize CSVs to sub-continental population-specific variants (sCSVs) and show that in some cases it is possible to determine the sub-continental ancestry for short chromosomal segments on the basis of sCSVs. PMID:24743331

On Galactic Density Modeling in the Presence of Dust Extinction

NASA Astrophysics Data System (ADS)

Bovy, Jo; Rix, Hans-Walter; Green, Gregory M.; Schlafly, Edward F.; Finkbeiner, Douglas P.

2016-02-01

Inferences about the spatial density or phase-space structure of stellar populations in the Milky Way require a precise determination of the effective survey volume. The volume observed by surveys such as Gaia or near-infrared spectroscopic surveys, which have good coverage of the Galactic midplane region, is highly complex because of the abundant small-scale structure in the three-dimensional interstellar dust extinction. We introduce a novel framework for analyzing the importance of small-scale structure in the extinction. This formalism demonstrates that the spatially complex effect of extinction on the selection function of a pencil-beam or contiguous sky survey is equivalent to a low-pass filtering of the extinction-affected selection function with the smooth density field. We find that the angular resolution of current 3D extinction maps is sufficient for analyzing Gaia sub-samples of millions of stars. However, the current distance resolution is inadequate and needs to be improved by an order of magnitude, especially in the inner Galaxy. We also present a practical and efficient method for properly taking the effect of extinction into account in analyses of Galactic structure through an effective selection function. We illustrate its use with the selection function of red-clump stars in APOGEE using and comparing a variety of current 3D extinction maps.

Making Inferences: Comprehension of Physical Causality, Intentionality, and Emotions in Discourse by High-Functioning Older Children, Adolescents, and Adults with Autism

ERIC Educational Resources Information Center

Bodner, Kimberly E.; Engelhardt, Christopher R.; Minshew, Nancy J.; Williams, Diane L.

2015-01-01

Studies investigating inferential reasoning in autism spectrum disorder (ASD) have focused on the ability to make socially-related inferences or inferences more generally. Important variables for intervention planning such as whether inferences depend on physical experiences or the nature of social information have received less consideration. A…

Inferring probabilistic stellar rotation periods using Gaussian processes

NASA Astrophysics Data System (ADS)

Angus, Ruth; Morton, Timothy; Aigrain, Suzanne; Foreman-Mackey, Daniel; Rajpaul, Vinesh

2018-02-01

Variability in the light curves of spotted, rotating stars is often non-sinusoidal and quasi-periodic - spots move on the stellar surface and have finite lifetimes, causing stellar flux variations to slowly shift in phase. A strictly periodic sinusoid therefore cannot accurately model a rotationally modulated stellar light curve. Physical models of stellar surfaces have many drawbacks preventing effective inference, such as highly degenerate or high-dimensional parameter spaces. In this work, we test an appropriate effective model: a Gaussian Process with a quasi-periodic covariance kernel function. This highly flexible model allows sampling of the posterior probability density function of the periodic parameter, marginalizing over the other kernel hyperparameters using a Markov Chain Monte Carlo approach. To test the effectiveness of this method, we infer rotation periods from 333 simulated stellar light curves, demonstrating that the Gaussian process method produces periods that are more accurate than both a sine-fitting periodogram and an autocorrelation function method. We also demonstrate that it works well on real data, by inferring rotation periods for 275 Kepler stars with previously measured periods. We provide a table of rotation periods for these and many more, altogether 1102 Kepler objects of interest, and their posterior probability density function samples. Because this method delivers posterior probability density functions, it will enable hierarchical studies involving stellar rotation, particularly those involving population modelling, such as inferring stellar ages, obliquities in exoplanet systems, or characterizing star-planet interactions. The code used to implement this method is available online.

Dynamics of Phenanthrenequinone on Carbon Nano-Onion Surfaces Probed by Quasielastic Neutron Scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anjos, Daniela M; Mamontov, Eugene; Brown, Gilbert M

We used quasielastic neutron scattering (QENS) to study the dynamics of phenanthrenequinone (PQ) on the surface of onion-like carbon (OLC), or so called carbon onions, as a function of surface coverage and temperature. For both the high- and low-coverage samples, we observed two diffusion processes; a faster process and nearly an order of magnitude slower process. On the high-coverage surface, the slow diffusion process is of long-range translational character, whereas the fast diffusion process is spatially localized on the length scale of ~ 4.7 . On the low-coverage surface, both diffusion processes are spatially localized; on the same length scalemore » of ~ 4.7 for the fast diffusion and a somewhat larger length scale for the slow diffusion. Arrhenius temperature dependence is observed except for the long-range diffusion on the high-coverage surface. We attribute the fast diffusion process to the generic localized in-cage dynamics of PQ molecules, and the slow diffusion process to the long-range translational dynamics of PQ molecules, which, depending on the coverage, may be either spatially restricted, or long-range. On the low-coverage surface, uniform surface coverage is not attained, and the PQ molecules experience the effect of spatial constraints on their long-range translational dynamics. Unexpectedly, the dynamics of PQ molecules on OLC as a function of temperature and surface coverage bears qualitative resemblance to the dynamics of water molecules on oxide surfaces, including practically temperature-independent residence times for the low-coverage surface. The dynamics features that we observed may be universal across different classes of surface adsorbates.« less

Phylogenetic Conflict in Bears Identified by Automated Discovery of Transposable Element Insertions in Low-Coverage Genomes

PubMed Central

Gallus, Susanne; Janke, Axel

2017-01-01

Abstract Phylogenetic reconstruction from transposable elements (TEs) offers an additional perspective to study evolutionary processes. However, detecting phylogenetically informative TE insertions requires tedious experimental work, limiting the power of phylogenetic inference. Here, we analyzed the genomes of seven bear species using high-throughput sequencing data to detect thousands of TE insertions. The newly developed pipeline for TE detection called TeddyPi (TE detection and discovery for Phylogenetic Inference) identified 150,513 high-quality TE insertions in the genomes of ursine and tremarctine bears. By integrating different TE insertion callers and using a stringent filtering approach, the TeddyPi pipeline produced highly reliable TE insertion calls, which were confirmed by extensive in vitro validation experiments. Analysis of single nucleotide substitutions in the flanking regions of the TEs shows that these substitutions correlate with the phylogenetic signal from the TE insertions. Our phylogenomic analyses show that TEs are a major driver of genomic variation in bears and enabled phylogenetic reconstruction of a well-resolved species tree, despite strong signals for incomplete lineage sorting and introgression. The analyses show that the Asiatic black, sun, and sloth bear form a monophyletic clade, in which phylogenetic incongruence originates from incomplete lineage sorting. TeddyPi is open source and can be adapted to various TE and structural variation callers. The pipeline makes it possible to confidently extract thousands of TE insertions even from low-coverage genomes (∼10×) of nonmodel organisms. This opens new possibilities for biologists to study phylogenies and evolutionary processes as well as rates and patterns of (retro-)transposition and structural variation. PMID:28985298

Category inference as a function of correlational structure, category discriminability, and number of available cues.

PubMed

Lancaster, Matthew E; Shelhamer, Ryan; Homa, Donald

2013-04-01

Two experiments investigated category inference when categories were composed of correlated or uncorrelated dimensions and the categories overlapped minimally or moderately. When the categories minimally overlapped, the dimensions were strongly correlated with the category label. Following a classification learning phase, subsequent transfer required the selection of either a category label or a feature when one, two, or three features were missing. Experiments 1 and 2 differed primarily in the number of learning blocks prior to transfer. In each experiment, the inference of the category label or category feature was influenced by both dimensional and category correlations, as well as their interaction. The number of cues available at test impacted performance more when the dimensional correlations were zero and category overlap was high. However, a minimal number of cues were sufficient to produce high levels of inference when the dimensions were highly correlated; additional cues had a positive but reduced impact, even when overlap was high. Subjects were generally more accurate in inferring the category label than a category feature regardless of dimensional correlation, category overlap, or number of cues available at test. Whether the category label functioned as a special feature or not was critically dependent upon these embedded correlations, with feature inference driven more strongly by dimensional correlations.

Emergence and Evolution of Hominidae-Specific Coding and Noncoding Genomic Sequences

PubMed Central

Saber, Morteza Mahmoudi; Adeyemi Babarinde, Isaac; Hettiarachchi, Nilmini; Saitou, Naruya

2016-01-01

Family Hominidae, which includes humans and great apes, is recognized for unique complex social behavior and intellectual abilities. Despite the increasing genome data, however, the genomic origin of its phenotypic uniqueness has remained elusive. Clade-specific genes and highly conserved noncoding sequences (HCNSs) are among the high-potential evolutionary candidates involved in driving clade-specific characters and phenotypes. On this premise, we analyzed whole genome sequences along with gene orthology data retrieved from major DNA databases to find Hominidae-specific (HS) genes and HCNSs. We discovered that Down syndrome critical region 4 (DSCR4) is the only experimentally verified gene uniquely present in Hominidae. DSCR4 has no structural homology to any known protein and was inferred to have emerged in several steps through LTR/ERV1, LTR/ERVL retrotransposition, and transversion. Using the genomic distance as neutral evolution threshold, we identified 1,658 HS HCNSs. Polymorphism coverage and derived allele frequency analysis of HS HCNSs showed that these HCNSs are under purifying selection, indicating that they may harbor important functions. They are overrepresented in promoters/untranslated regions, in close proximity of genes involved in sensory perception of sound and developmental process, and also showed a significantly lower nucleosome occupancy probability. Interestingly, many ancestral sequences of the HS HCNSs showed very high evolutionary rates. This suggests that new functions emerged through some kind of positive selection, and then purifying selection started to operate to keep these functions. PMID:27289096

Identification of copy number variants in whole-genome data using Reference Coverage Profiles

PubMed Central

Glusman, Gustavo; Severson, Alissa; Dhankani, Varsha; Robinson, Max; Farrah, Terry; Mauldin, Denise E.; Stittrich, Anna B.; Ament, Seth A.; Roach, Jared C.; Brunkow, Mary E.; Bodian, Dale L.; Vockley, Joseph G.; Shmulevich, Ilya; Niederhuber, John E.; Hood, Leroy

2015-01-01

The identification of DNA copy numbers from short-read sequencing data remains a challenge for both technical and algorithmic reasons. The raw data for these analyses are measured in tens to hundreds of gigabytes per genome; transmitting, storing, and analyzing such large files is cumbersome, particularly for methods that analyze several samples simultaneously. We developed a very efficient representation of depth of coverage (150–1000× compression) that enables such analyses. Current methods for analyzing variants in whole-genome sequencing (WGS) data frequently miss copy number variants (CNVs), particularly hemizygous deletions in the 1–100 kb range. To fill this gap, we developed a method to identify CNVs in individual genomes, based on comparison to joint profiles pre-computed from a large set of genomes. We analyzed depth of coverage in over 6000 high quality (>40×) genomes. The depth of coverage has strong sequence-specific fluctuations only partially explained by global parameters like %GC. To account for these fluctuations, we constructed multi-genome profiles representing the observed or inferred diploid depth of coverage at each position along the genome. These Reference Coverage Profiles (RCPs) take into account the diverse technologies and pipeline versions used. Normalization of the scaled coverage to the RCP followed by hidden Markov model (HMM) segmentation enables efficient detection of CNVs and large deletions in individual genomes. Use of pre-computed multi-genome coverage profiles improves our ability to analyze each individual genome. We make available RCPs and tools for performing these analyses on personal genomes. We expect the increased sensitivity and specificity for individual genome analysis to be critical for achieving clinical-grade genome interpretation. PMID:25741365

[National Health and Nutrition Survey 2012: design and coverage].

PubMed

Romero-Martínez, Martín; Shamah-Levy, Teresa; Franco-Núñez, Aurora; Villalpando, Salvador; Cuevas-Nasu, Lucía; Gutiérrez, Juan Pablo; Rivera-Dommarco, Juan Ángel

2013-01-01

To describe the design and population coverage of the National Health and Nutrition Survey 2012 (NHNS 2012). The design of the NHNS 2012 is reported, as a probabilistic population based survey with a multi-stage and stratified sampling, as well as the sample inferential properties, the logistical procedures, and the obtained coverage. Household response rate for the NHNS 2012 was 87%, completing data from 50,528 households, where 96 031 individual interviews selected by age and 14,104 of ambulatory health services users were also obtained. The probabilistic design of the NHNS 2012 as well as its coverage allowed to generate inferences about health and nutrition conditions, health programs coverage, and access to health services. Because of their complex designs, all estimations from the NHNS 2012 must use the survey design: weights, primary sampling units, and stratus variables.

Independence of Hot and Cold Executive Function Deficits in High-Functioning Adults with Autism Spectrum Disorder.

PubMed

Zimmerman, David L; Ownsworth, Tamara; O'Donovan, Analise; Roberts, Jacqueline; Gullo, Matthew J

2016-01-01

Individuals with autistic spectrum disorder (ASD) display diverse deficits in social, cognitive and behavioral functioning. To date, there has been mixed findings on the profile of executive function deficits for high-functioning adults (IQ > 70) with ASD. A conceptual distinction is commonly made between "cold" and "hot" executive functions. Cold executive functions refer to mechanistic higher-order cognitive operations (e.g., working memory), whereas hot executive functions entail cognitive abilities supported by emotional awareness and social perception (e.g., social cognition). This study aimed to determine the independence of deficits in hot and cold executive functions for high-functioning adults with ASD. Forty-two adults with ASD (64% male, aged 18-66 years) and 40 age and gender matched controls were administered The Awareness of Social Inference Test (TASIT; emotion recognition and social inference), Letter Number Sequencing (working memory) and Hayling Sentence Completion Test (response initiation and suppression). Between-group analyses identified that the ASD group performed significantly worse than matched controls on all measures of cold and hot executive functions (d = 0.54 - 1.5). Hierarchical multiple regression analyses revealed that the ASD sample performed more poorly on emotion recognition and social inference tasks than matched controls after controlling for cold executive functions and employment status. The findings also indicated that the ability to recognize emotions and make social inferences was supported by working memory and response initiation and suppression processes. Overall, this study supports the distinction between hot and cold executive function impairments for adults with ASD. Moreover, it advances understanding of higher-order impairments underlying social interaction difficulties for this population which, in turn, may assist with diagnosis and inform intervention programs.

Independence of Hot and Cold Executive Function Deficits in High-Functioning Adults with Autism Spectrum Disorder

PubMed Central

Zimmerman, David L.; Ownsworth, Tamara; O'Donovan, Analise; Roberts, Jacqueline; Gullo, Matthew J.

2016-01-01

Individuals with autistic spectrum disorder (ASD) display diverse deficits in social, cognitive and behavioral functioning. To date, there has been mixed findings on the profile of executive function deficits for high-functioning adults (IQ > 70) with ASD. A conceptual distinction is commonly made between “cold” and “hot” executive functions. Cold executive functions refer to mechanistic higher-order cognitive operations (e.g., working memory), whereas hot executive functions entail cognitive abilities supported by emotional awareness and social perception (e.g., social cognition). This study aimed to determine the independence of deficits in hot and cold executive functions for high-functioning adults with ASD. Forty-two adults with ASD (64% male, aged 18–66 years) and 40 age and gender matched controls were administered The Awareness of Social Inference Test (TASIT; emotion recognition and social inference), Letter Number Sequencing (working memory) and Hayling Sentence Completion Test (response initiation and suppression). Between-group analyses identified that the ASD group performed significantly worse than matched controls on all measures of cold and hot executive functions (d = 0.54 − 1.5). Hierarchical multiple regression analyses revealed that the ASD sample performed more poorly on emotion recognition and social inference tasks than matched controls after controlling for cold executive functions and employment status. The findings also indicated that the ability to recognize emotions and make social inferences was supported by working memory and response initiation and suppression processes. Overall, this study supports the distinction between hot and cold executive function impairments for adults with ASD. Moreover, it advances understanding of higher-order impairments underlying social interaction difficulties for this population which, in turn, may assist with diagnosis and inform intervention programs. PMID:26903836

The Biogeography of Putative Microbial Antibiotic Production

PubMed Central

Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.

2015-01-01

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275

Demographic history and rare allele sharing among human populations.

PubMed

Gravel, Simon; Henn, Brenna M; Gutenkunst, Ryan N; Indap, Amit R; Marth, Gabor T; Clark, Andrew G; Yu, Fuli; Gibbs, Richard A; Bustamante, Carlos D

2011-07-19

High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2-4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ∼1,000 sequenced chromosomes per population, whereas ∼2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence.

Demographic history and rare allele sharing among human populations

PubMed Central

Gravel, Simon; Henn, Brenna M.; Gutenkunst, Ryan N.; Indap, Amit R.; Marth, Gabor T.; Clark, Andrew G.; Yu, Fuli; Gibbs, Richard A.; Bustamante, Carlos D.; Altshuler, David L.; Durbin, Richard M.; Abecasis, Gonçalo R.; Bentley, David R.; Chakravarti, Aravinda; Clark, Andrew G.; Collins, Francis S.; De La Vega, Francisco M.; Donnelly, Peter; Egholm, Michael; Flicek, Paul; Gabriel, Stacey B.; Gibbs, Richard A.; Knoppers, Bartha M.; Lander, Eric S.; Lehrach, Hans; Mardis, Elaine R.; McVean, Gil A.; Nickerson, Debbie A.; Peltonen, Leena; Schafer, Alan J.; Sherry, Stephen T.; Wang, Jun; Wilson, Richard K.; Gibbs, Richard A.; Deiros, David; Metzker, Mike; Muzny, Donna; Reid, Jeff; Wheeler, David; Wang, Jun; Li, Jingxiang; Jian, Min; Li, Guoqing; Li, Ruiqiang; Liang, Huiqing; Tian, Geng; Wang, Bo; Wang, Jian; Wang, Wei; Yang, Huanming; Zhang, Xiuqing; Zheng, Huisong; Lander, Eric S.; Altshuler, David L.; Ambrogio, Lauren; Bloom, Toby; Cibulskis, Kristian; Fennell, Tim J.; Gabriel, Stacey B.; Jaffe, David B.; Shefler, Erica; Sougnez, Carrie L.; Bentley, David R.; Gormley, Niall; Humphray, Sean; Kingsbury, Zoya; Koko-Gonzales, Paula; Stone, Jennifer; McKernan, Kevin J.; Costa, Gina L.; Ichikawa, Jeffry K.; Lee, Clarence C.; Sudbrak, Ralf; Lehrach, Hans; Borodina, Tatiana A.; Dahl, Andreas; Davydov, Alexey N.; Marquardt, Peter; Mertes, Florian; Nietfeld, Wilfiried; Rosenstiel, Philip; Schreiber, Stefan; Soldatov, Aleksey V.; Timmermann, Bernd; Tolzmann, Marius; Egholm, Michael; Affourtit, Jason; Ashworth, Dana; Attiya, Said; Bachorski, Melissa; Buglione, Eli; Burke, Adam; Caprio, Amanda; Celone, Christopher; Clark, Shauna; Conners, David; Desany, Brian; Gu, Lisa; Guccione, Lorri; Kao, Kalvin; Kebbel, Andrew; Knowlton, Jennifer; Labrecque, Matthew; McDade, Louise; Mealmaker, Craig; Minderman, Melissa; Nawrocki, Anne; Niazi, Faheem; Pareja, Kristen; Ramenani, Ravi; Riches, David; Song, Wanmin; Turcotte, Cynthia; Wang, Shally; Mardis, Elaine R.; Wilson, Richard K.; Dooling, David; Fulton, Lucinda; Fulton, Robert; Weinstock, George; Durbin, Richard M.; Burton, John; Carter, David M.; Churcher, Carol; Coffey, Alison; Cox, Anthony; Palotie, Aarno; Quail, Michael; Skelly, Tom; Stalker, James; Swerdlow, Harold P.; Turner, Daniel; De Witte, Anniek; Giles, Shane; Gibbs, Richard A.; Wheeler, David; Bainbridge, Matthew; Challis, Danny; Sabo, Aniko; Yu, Fuli; Yu, Jin; Wang, Jun; Fang, Xiaodong; Guo, Xiaosen; Li, Ruiqiang; Li, Yingrui; Luo, Ruibang; Tai, Shuaishuai; Wu, Honglong; Zheng, Hancheng; Zheng, Xiaole; Zhou, Yan; Li, Guoqing; Wang, Jian; Yang, Huanming; Marth, Gabor T.; Garrison, Erik P.; Huang, Weichun; Indap, Amit; Kural, Deniz; Lee, Wan-Ping; Leong, Wen Fung; Quinlan, Aaron R.; Stewart, Chip; Stromberg, Michael P.; Ward, Alistair N.; Wu, Jiantao; Lee, Charles; Mills, Ryan E.; Shi, Xinghua; Daly, Mark J.; DePristo, Mark A.; Altshuler, David L.; Ball, Aaron D.; Banks, Eric; Bloom, Toby; Browning, Brian L.; Cibulskis, Kristian; Fennell, Tim J.; Garimella, Kiran V.; Grossman, Sharon R.; Handsaker, Robert E.; Hanna, Matt; Hartl, Chris; Jaffe, David B.; Kernytsky, Andrew M.; Korn, Joshua M.; Li, Heng; Maguire, Jared R.; McCarroll, Steven A.; McKenna, Aaron; Nemesh, James C.; Philippakis, Anthony A.; Poplin, Ryan E.; Price, Alkes; Rivas, Manuel A.; Sabeti, Pardis C.; Schaffner, Stephen F.; Shefler, Erica; Shlyakhter, Ilya A.; Cooper, David N.; Ball, Edward V.; Mort, Matthew; Phillips, Andrew D.; Stenson, Peter D.; Sebat, Jonathan; Makarov, Vladimir; Ye, Kenny; Yoon, Seungtai C.; Bustamante, Carlos D.; Clark, Andrew G.; Boyko, Adam; Degenhardt, Jeremiah; Gravel, Simon; Gutenkunst, Ryan N.; Kaganovich, Mark; Keinan, Alon; Lacroute, Phil; Ma, Xin; Reynolds, Andy; Clarke, Laura; Flicek, Paul; Cunningham, Fiona; Herrero, Javier; Keenen, Stephen; Kulesha, Eugene; Leinonen, Rasko; McLaren, William M.; Radhakrishnan, Rajesh; Smith, Richard E.; Zalunin, Vadim; Zheng-Bradley, Xiangqun; Korbel, Jan O.; Stütz, Adrian M.; Humphray, Sean; Bauer, Markus; Cheetham, R. Keira; Cox, Tony; Eberle, Michael; James, Terena; Kahn, Scott; Murray, Lisa; Chakravarti, Aravinda; Ye, Kai; De La Vega, Francisco M.; Fu, Yutao; Hyland, Fiona C. L.; Manning, Jonathan M.; McLaughlin, Stephen F.; Peckham, Heather E.; Sakarya, Onur; Sun, Yongming A.; Tsung, Eric F.; Batzer, Mark A.; Konkel, Miriam K.; Walker, Jerilyn A.; Sudbrak, Ralf; Albrecht, Marcus W.; Amstislavskiy, Vyacheslav S.; Herwig, Ralf; Parkhomchuk, Dimitri V.; Sherry, Stephen T.; Agarwala, Richa; Khouri, Hoda M.; Morgulis, Aleksandr O.; Paschall, Justin E.; Phan, Lon D.; Rotmistrovsky, Kirill E.; Sanders, Robert D.; Shumway, Martin F.; Xiao, Chunlin; McVean, Gil A.; Auton, Adam; Iqbal, Zamin; Lunter, Gerton; Marchini, Jonathan L.; Moutsianas, Loukas; Myers, Simon; Tumian, Afidalina; Desany, Brian; Knight, James; Winer, Roger; Craig, David W.; Beckstrom-Sternberg, Steve M.; Christoforides, Alexis; Kurdoglu, Ahmet A.; Pearson, John V.; Sinari, Shripad A.; Tembe, Waibhav D.; Haussler, David; Hinrichs, Angie S.; Katzman, Sol J.; Kern, Andrew; Kuhn, Robert M.; Przeworski, Molly; Hernandez, Ryan D.; Howie, Bryan; Kelley, Joanna L.; Melton, S. Cord; Abecasis, Gonçalo R.; Li, Yun; Anderson, Paul; Blackwell, Tom; Chen, Wei; Cookson, William O.; Ding, Jun; Kang, Hyun Min; Lathrop, Mark; Liang, Liming; Moffatt, Miriam F.; Scheet, Paul; Sidore, Carlo; Snyder, Matthew; Zhan, Xiaowei; Zöllner, Sebastian; Awadalla, Philip; Casals, Ferran; Idaghdour, Youssef; Keebler, John; Stone, Eric A.; Zilversmit, Martine; Jorde, Lynn; Xing, Jinchuan; Eichler, Evan E.; Aksay, Gozde; Alkan, Can; Hajirasouliha, Iman; Hormozdiari, Fereydoun; Kidd, Jeffrey M.; Sahinalp, S. Cenk; Sudmant, Peter H.; Mardis, Elaine R.; Chen, Ken; Chinwalla, Asif; Ding, Li; Koboldt, Daniel C.; McLellan, Mike D.; Dooling, David; Weinstock, George; Wallis, John W.; Wendl, Michael C.; Zhang, Qunyuan; Durbin, Richard M.; Albers, Cornelis A.; Ayub, Qasim; Balasubramaniam, Senduran; Barrett, Jeffrey C.; Carter, David M.; Chen, Yuan; Conrad, Donald F.; Danecek, Petr; Dermitzakis, Emmanouil T.; Hu, Min; Huang, Ni; Hurles, Matt E.; Jin, Hanjun; Jostins, Luke; Keane, Thomas M.; Le, Si Quang; Lindsay, Sarah; Long, Quan; MacArthur, Daniel G.; Montgomery, Stephen B.; Parts, Leopold; Stalker, James; Tyler-Smith, Chris; Walter, Klaudia; Zhang, Yujun; Gerstein, Mark B.; Snyder, Michael; Abyzov, Alexej; Balasubramanian, Suganthi; Bjornson, Robert; Du, Jiang; Grubert, Fabian; Habegger, Lukas; Haraksingh, Rajini; Jee, Justin; Khurana, Ekta; Lam, Hugo Y. K.; Leng, Jing; Mu, Xinmeng Jasmine; Urban, Alexander E.; Zhang, Zhengdong; Li, Yingrui; Luo, Ruibang; Marth, Gabor T.; Garrison, Erik P.; Kural, Deniz; Quinlan, Aaron R.; Stewart, Chip; Stromberg, Michael P.; Ward, Alistair N.; Wu, Jiantao; Lee, Charles; Mills, Ryan E.; Shi, Xinghua; McCarroll, Steven A.; Banks, Eric; DePristo, Mark A.; Handsaker, Robert E.; Hartl, Chris; Korn, Joshua M.; Li, Heng; Nemesh, James C.; Sebat, Jonathan; Makarov, Vladimir; Ye, Kenny; Yoon, Seungtai C.; Degenhardt, Jeremiah; Kaganovich, Mark; Clarke, Laura; Smith, Richard E.; Zheng-Bradley, Xiangqun; Korbel, Jan O.; Humphray, Sean; Cheetham, R. Keira; Eberle, Michael; Kahn, Scott; Murray, Lisa; Ye, Kai; De La Vega, Francisco M.; Fu, Yutao; Peckham, Heather E.; Sun, Yongming A.; Batzer, Mark A.; Konkel, Miriam K.; Walker, Jerilyn A.; Xiao, Chunlin; Iqbal, Zamin; Desany, Brian; Blackwell, Tom; Snyder, Matthew; Xing, Jinchuan; Eichler, Evan E.; Aksay, Gozde; Alkan, Can; Hajirasouliha, Iman; Hormozdiari, Fereydoun; Kidd, Jeffrey M.; Chen, Ken; Chinwalla, Asif; Ding, Li; McLellan, Mike D.; Wallis, John W.; Hurles, Matt E.; Conrad, Donald F.; Walter, Klaudia; Zhang, Yujun; Gerstein, Mark B.; Snyder, Michael; Abyzov, Alexej; Du, Jiang; Grubert, Fabian; Haraksingh, Rajini; Jee, Justin; Khurana, Ekta; Lam, Hugo Y. K.; Leng, Jing; Mu, Xinmeng Jasmine; Urban, Alexander E.; Zhang, Zhengdong; Gibbs, Richard A.; Bainbridge, Matthew; Challis, Danny; Coafra, Cristian; Dinh, Huyen; Kovar, Christie; Lee, Sandy; Muzny, Donna; Nazareth, Lynne; Reid, Jeff; Sabo, Aniko; Yu, Fuli; Yu, Jin; Marth, Gabor T.; Garrison, Erik P.; Indap, Amit; Leong, Wen Fung; Quinlan, Aaron R.; Stewart, Chip; Ward, Alistair N.; Wu, Jiantao; Cibulskis, Kristian; Fennell, Tim J.; Gabriel, Stacey B.; Garimella, Kiran V.; Hartl, Chris; Shefler, Erica; Sougnez, Carrie L.; Wilkinson, Jane; Clark, Andrew G.; Gravel, Simon; Grubert, Fabian; Clarke, Laura; Flicek, Paul; Smith, Richard E.; Zheng-Bradley, Xiangqun; Sherry, Stephen T.; Khouri, Hoda M.; Paschall, Justin E.; Shumway, Martin F.; Xiao, Chunlin; McVean, Gil A.; Katzman, Sol J.; Abecasis, Gonçalo R.; Blackwell, Tom; Mardis, Elaine R.; Dooling, David; Fulton, Lucinda; Fulton, Robert; Koboldt, Daniel C.; Durbin, Richard M.; Balasubramaniam, Senduran; Coffey, Allison; Keane, Thomas M.; MacArthur, Daniel G.; Palotie, Aarno; Scott, Carol; Stalker, James; Tyler-Smith, Chris; Gerstein, Mark B.; Balasubramanian, Suganthi; Chakravarti, Aravinda; Knoppers, Bartha M.; Abecasis, Gonçalo R.; Bustamante, Carlos D.; Gharani, Neda; Gibbs, Richard A.; Jorde, Lynn; Kaye, Jane S.; Kent, Alastair; Li, Taosha; McGuire, Amy L.; McVean, Gil A.; Ossorio, Pilar N.; Rotimi, Charles N.; Su, Yeyang; Toji, Lorraine H.; TylerSmith, Chris; Brooks, Lisa D.; Felsenfeld, Adam L.; McEwen, Jean E.; Abdallah, Assya; Juenger, Christopher R.; Clemm, Nicholas C.; Collins, Francis S.; Duncanson, Audrey; Green, Eric D.; Guyer, Mark S.; Peterson, Jane L.; Schafer, Alan J.; Abecasis, Gonçalo R.; Altshuler, David L.; Auton, Adam; Brooks, Lisa D.; Durbin, Richard M.; Gibbs, Richard A.; Hurles, Matt E.; McVean, Gil A.

2011-01-01

High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2–4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ∼1,000 sequenced chromosomes per population, whereas ∼2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence. PMID:21730125

Improving Microbial Genome Annotations in an Integrated Database Context

PubMed Central

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

Urbanization reduces and homogenizes trait diversity in stream macroinvertebrate communities.

PubMed

Barnum, Thomas R; Weller, Donald E; Williams, Meghan

2017-12-01

More than one-half of the world's population lives in urban areas, so quantifying the effects of urbanization on ecological communities is important for understanding whether anthropogenic stressors homogenize communities across environmental and climatic gradients. We examined the relationship of impervious surface coverage (a marker of urbanization) and the structure of stream macroinvertebrate communities across the state of Maryland and within each of Maryland's three ecoregions: Coastal Plain, Piedmont, and Appalachian, which differ in stream geomorphology and community composition. We considered three levels of trait organization: individual traits, unique combinations of traits, and community metrics (functional richness, functional evenness, and functional divergence) and three levels of impervious surface coverage (low [<2.5%], medium [2.5% to 10%], and high [>10%]). The prevalence of an individual trait differed very little between low impervious surface and high impervious surface sites. The arrangement of trait combinations in community trait space for each ecoregion differed when impervious surface coverage was low, but the arrangement became more similar among ecoregions as impervious surface coverage increased. Furthermore, trait combinations that occurred only at low or medium impervious surface coverage were clustered in a subset of the community trait space, indicating that impervious surface affected the presence of only a subset of trait combinations. Functional richness declined with increasing impervious surface, providing evidence for environmental filtering. Community metrics that include abundance were also sensitive to increasing impervious surface coverage: functional divergence decreased while functional evenness increased. These changes demonstrate that increasing impervious surface coverage homogenizes the trait diversity of macroinvertebrate communities in streams, despite differences in initial community composition and stream geomorphology among ecoregions. Community metrics were also more sensitive to changes in the abundance rather than the gain or loss of trait combinations, showing the potential for trait-based approaches to serve as early warning indicators of environmental stress for monitoring and biological assessment programs. © 2017 by the Ecological Society of America.

Inference of gorilla demographic and selective history from whole-genome sequence data.

PubMed

McManus, Kimberly F; Kelley, Joanna L; Song, Shiya; Veeramah, Krishna R; Woerner, August E; Stevison, Laurie S; Ryder, Oliver A; Ape Genome Project, Great; Kidd, Jeffrey M; Wall, Jeffrey D; Bustamante, Carlos D; Hammer, Michael F

2015-03-01

Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Dosimetric feasibility of 4DCT-ventilation imaging guided proton therapy for locally advanced non-small-cell lung cancer.

PubMed

Huang, Qijie; Jabbour, Salma K; Xiao, Zhiyan; Yue, Ning; Wang, Xiao; Cao, Hongbin; Kuang, Yu; Zhang, Yin; Nie, Ke

2018-04-25

The principle aim of this study is to incorporate 4DCT ventilation imaging into functional treatment planning that preserves high-functioning lung with both double scattering and scanning beam techniques in proton therapy. Eight patients with locally advanced non-small-cell lung cancer were included in this study. Deformable image registration was performed for each patient on their planning 4DCTs and the resultant displacement vector field with Jacobian analysis was used to identify the high-, medium- and low-functional lung regions. Five plans were designed for each patient: a regular photon IMRT vs. anatomic proton plans without consideration of functional ventilation information using double scattering proton therapy (DSPT) and intensity modulated proton therapy (IMPT) vs. functional proton plans with avoidance of high-functional lung using both DSPT and IMPT. Dosimetric parameters were compared in terms of tumor coverage, plan heterogeneity, and avoidance of normal tissues. Our results showed that both DSPT and IMPT plans gave superior dose advantage to photon IMRTs in sparing low dose regions of the total lung in terms of V5 (volume receiving 5Gy). The functional DSPT only showed marginal benefit in sparing high-functioning lung in terms of V5 or V20 (volume receiving 20Gy) compared to anatomical plans. Yet, the functional planning in IMPT delivery, can further reduce the low dose in high-functioning lung without degrading the PTV dosimetric coverages, compared to anatomical proton planning. Although the doses to some critical organs might increase during functional planning, the necessary constraints were all met. Incorporating 4DCT ventilation imaging into functional proton therapy is feasible. The functional proton plans, in intensity modulated proton delivery, are effective to further preserve high-functioning lung regions without degrading the PTV coverage.

Heart failure disease management programs: a cost-effectiveness analysis.

PubMed

Chan, David C; Heidenreich, Paul A; Weinstein, Milton C; Fonarow, Gregg C

2008-02-01

Heart failure (HF) disease management programs have shown impressive reductions in hospitalizations and mortality, but in studies limited to short time frames and high-risk patient populations. Current guidelines thus only recommend disease management targeted to high-risk patients with HF. This study applied a new technique to infer the degree to which clinical trials have targeted patients by risk based on observed rates of hospitalization and death. A Markov model was used to assess the incremental life expectancy and cost of providing disease management for high-risk to low-risk patients. Sensitivity analyses of various long-term scenarios and of reduced effectiveness in low-risk patients were also considered. The incremental cost-effectiveness ratio of extending coverage to all patients was $9700 per life-year gained in the base case. In aggregate, universal coverage almost quadrupled life-years saved as compared to coverage of only the highest quintile of risk. A worst case analysis with simultaneous conservative assumptions yielded an incremental cost-effectiveness ratio of $110,000 per life-year gained. In a probabilistic sensitivity analysis, 99.74% of possible incremental cost-effectiveness ratios were <$50,000 per life-year gained. Heart failure disease management programs are likely cost-effective in the long-term along the whole spectrum of patient risk. Health gains could be extended by enrolling a broader group of patients with HF in disease management.

Developing spectral, structural, and phenological diversity proxies for monitoring biodiversity change across space and time using ESA's Sentinel satellites

NASA Astrophysics Data System (ADS)

Ma, X.; Mahecha, M. D.; Migliavacca, M.; Luo, Y.; Urban, M.; Bohn, F. J.; Huth, A.; Reichstein, M.

2017-12-01

A key challenge for monitoring biodiversity change is the lack of consistent measures of biodiversity across space and time. This challenge may be addressed by exploring the potentials provided by novel remote sensing observations. By continuously observing broad-scale patterns of vegetation and land surface parameters, remote sensing can complement the restricted coverage afforded by field measurements. Here we develop methods to infer spatial patterns of biodiversity at ecosystem level from ESA's next-generation Sentinel sensors (Sentinel-1: C-band radar & Sentinel-2: multispectral). Both satellites offer very high spatial (10 m) and temporal resolutions (5 days) measurements with global coverage. We propose and test several ecosystem biodiversity proxies, including landscape spectral diversity, phenological diversity, and canopy structural diversity. These diversity proxies are highly related to some key aspects of essential biodiversity variables (EBVs) as defined by GEO-BON, such as habitat structure, community composition, ecosystem function and structure. We verify spaceborne retrievals of these biodiversity proxies with in situ measurements from drone (spectral diversity), phenocam (phenological diversity), and airborne LiDAR (canopy structural diversity) over multiple flux tower sites within the Mediterranean region. We further compare our remote sensing retrievals of biodiversity proxies against several biodiversity indices as derived from field measurements (incl. ⍺-/β- diversity and Shannon-index) to explore the limitations and potentials of extending the RS proxies to a greater spatial extent. We expect the new concept as to maximize the potential of remote sensing information might help to monitor key aspects of EBVs on a global scale.

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks

PubMed Central

Juan, David; Pazos, Florencio; Valencia, Alfonso

2008-01-01

Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology. PMID:18199838

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks.

PubMed

Juan, David; Pazos, Florencio; Valencia, Alfonso

2008-01-22

Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology.

Constructing an integrated gene similarity network for the identification of disease genes.

PubMed

Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

PubMed Central

Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

2015-01-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

Variable Selection for Confounder Control, Flexible Modeling and Collaborative Targeted Minimum Loss-Based Estimation in Causal Inference.

PubMed

Schnitzer, Mireille E; Lok, Judith J; Gruber, Susan

2016-05-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010 [27]) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low- and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios.

Effect of hydrogen coverage on hydrogenation of o-cresol on Pt(111)

NASA Astrophysics Data System (ADS)

Li, Yaping; Liu, Zhimin; Crossley, Steven P.; Jentoft, Friederike C.; Wang, Sanwu

2018-06-01

The conversion of phenolics over metal catalysts is an important process for upgrading biofuels. With density functional calculations, hydrogenation of o-cresol on the hydrogen-covered Pt(111) surface was investigated. The results show that the coverage of hydrogen plays a significant role in the reaction rate while it does not affect the reaction selectivity. The reaction barriers of the hydrogenation process leading to the formation of both 2-methyl-cyclohexanone (the intermediate product) and 2-methyl-cyclohexanol (the final product) at high H coverages (∼1 ML) are found to be smaller by 0.14-0.69 eV than those at lower H coverages (∼1/25 ML). After both hydrogen and cresol are adsorbed on Pt(111) from their initial gas phase state, the reaction energy of each hydrogenation step on the surface is also dependent on the hydrogen coverage. On the H-covered Pt(111) surface, most steps of hydrogenation involve exothermic reactions when the hydrogen coverage is high while they are endothermic reactions at low hydrogen coverages. The differences in reaction rate and reaction energy between high and low H coverages can be understood with the coverage-dependent bonding strength and configurations.

Synthesis of regional crust and upper-mantle structure from seismic and gravity data

NASA Technical Reports Server (NTRS)

Alexander, S. S.; Lavin, P. M.

1979-01-01

Available seismic and ground based gravity data are combined to infer the three dimensional crust and upper mantle structure in selected regions. This synthesis and interpretation proceeds from large-scale average models suitable for early comparison with high-altitude satellite potential field data to more detailed delineation of structural boundaries and other variations that may be significant in natural resource assessment. Seismic and ground based gravity data are the primary focal point, but other relevant information (e.g. magnetic field, heat flow, Landsat imagery, geodetic leveling, and natural resources maps) is used to constrain the structure inferred and to assist in defining structural domains and boundaries. The seismic data consists of regional refraction lines, limited reflection coverage, surface wave dispersion, teleseismic P and S wave delay times, anelastic absorption, and regional seismicity patterns. The gravity data base consists of available point gravity determinations for the areas considered.

Phylogenetic Conflict in Bears Identified by Automated Discovery of Transposable Element Insertions in Low-Coverage Genomes.

PubMed

Lammers, Fritjof; Gallus, Susanne; Janke, Axel; Nilsson, Maria A

2017-10-01

Phylogenetic reconstruction from transposable elements (TEs) offers an additional perspective to study evolutionary processes. However, detecting phylogenetically informative TE insertions requires tedious experimental work, limiting the power of phylogenetic inference. Here, we analyzed the genomes of seven bear species using high-throughput sequencing data to detect thousands of TE insertions. The newly developed pipeline for TE detection called TeddyPi (TE detection and discovery for Phylogenetic Inference) identified 150,513 high-quality TE insertions in the genomes of ursine and tremarctine bears. By integrating different TE insertion callers and using a stringent filtering approach, the TeddyPi pipeline produced highly reliable TE insertion calls, which were confirmed by extensive in vitro validation experiments. Analysis of single nucleotide substitutions in the flanking regions of the TEs shows that these substitutions correlate with the phylogenetic signal from the TE insertions. Our phylogenomic analyses show that TEs are a major driver of genomic variation in bears and enabled phylogenetic reconstruction of a well-resolved species tree, despite strong signals for incomplete lineage sorting and introgression. The analyses show that the Asiatic black, sun, and sloth bear form a monophyletic clade, in which phylogenetic incongruence originates from incomplete lineage sorting. TeddyPi is open source and can be adapted to various TE and structural variation callers. The pipeline makes it possible to confidently extract thousands of TE insertions even from low-coverage genomes (∼10×) of nonmodel organisms. This opens new possibilities for biologists to study phylogenies and evolutionary processes as well as rates and patterns of (retro-)transposition and structural variation. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

NASA Technical Reports Server (NTRS)

Cornhill, Dennis; Bharadwaj, Raj; Mylaraswamy, Dinkar

2013-01-01

This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.

ON GALACTIC DENSITY MODELING IN THE PRESENCE OF DUST EXTINCTION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bovy, Jo; Rix, Hans-Walter; Schlafly, Edward F.

Inferences about the spatial density or phase-space structure of stellar populations in the Milky Way require a precise determination of the effective survey volume. The volume observed by surveys such as Gaia or near-infrared spectroscopic surveys, which have good coverage of the Galactic midplane region, is highly complex because of the abundant small-scale structure in the three-dimensional interstellar dust extinction. We introduce a novel framework for analyzing the importance of small-scale structure in the extinction. This formalism demonstrates that the spatially complex effect of extinction on the selection function of a pencil-beam or contiguous sky survey is equivalent to amore » low-pass filtering of the extinction-affected selection function with the smooth density field. We find that the angular resolution of current 3D extinction maps is sufficient for analyzing Gaia sub-samples of millions of stars. However, the current distance resolution is inadequate and needs to be improved by an order of magnitude, especially in the inner Galaxy. We also present a practical and efficient method for properly taking the effect of extinction into account in analyses of Galactic structure through an effective selection function. We illustrate its use with the selection function of red-clump stars in APOGEE using and comparing a variety of current 3D extinction maps.« less

Predicting Protein Function by Genomic Context: Quantitative Evaluation and Qualitative Inferences

PubMed Central

Huynen, Martijn; Snel, Berend; Lathe, Warren; Bork, Peer

2000-01-01

Various new methods have been proposed to predict functional interactions between proteins based on the genomic context of their genes. The types of genomic context that they use are Type I: the fusion of genes; Type II: the conservation of gene-order or co-occurrence of genes in potential operons; and Type III: the co-occurrence of genes across genomes (phylogenetic profiles). Here we compare these types for their coverage, their correlations with various types of functional interaction, and their overlap with homology-based function assignment. We apply the methods to Mycoplasma genitalium, the standard benchmarking genome in computational and experimental genomics. Quantitatively, conservation of gene order is the technique with the highest coverage, applying to 37% of the genes. By combining gene order conservation with gene fusion (6%), the co-occurrence of genes in operons in absence of gene order conservation (8%), and the co-occurrence of genes across genomes (11%), significant context information can be obtained for 50% of the genes (the categories overlap). Qualitatively, we observe that the functional interactions between genes are stronger as the requirements for physical neighborhood on the genome are more stringent, while the fraction of potential false positives decreases. Moreover, only in cases in which gene order is conserved in a substantial fraction of the genomes, in this case six out of twenty-five, does a single type of functional interaction (physical interaction) clearly dominate (>80%). In other cases, complementary function information from homology searches, which is available for most of the genes with significant genomic context, is essential to predict the type of interaction. Using a combination of genomic context and homology searches, new functional features can be predicted for 10% of M. genitalium genes. PMID:10958638

Stochastic inference with spiking neurons in the high-conductance state

NASA Astrophysics Data System (ADS)

Petrovici, Mihai A.; Bill, Johannes; Bytschok, Ilja; Schemmel, Johannes; Meier, Karlheinz

2016-10-01

The highly variable dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference but stand in apparent contrast to the deterministic response of neurons measured in vitro. Based on a propagation of the membrane autocorrelation across spike bursts, we provide an analytical derivation of the neural activation function that holds for a large parameter space, including the high-conductance state. On this basis, we show how an ensemble of leaky integrate-and-fire neurons with conductance-based synapses embedded in a spiking environment can attain the correct firing statistics for sampling from a well-defined target distribution. For recurrent networks, we examine convergence toward stationarity in computer simulations and demonstrate sample-based Bayesian inference in a mixed graphical model. This points to a new computational role of high-conductance states and establishes a rigorous link between deterministic neuron models and functional stochastic dynamics on the network level.

Inferring Selective Constraint from Population Genomic Data Suggests Recent Regulatory Turnover in the Human Brain

PubMed Central

Schrider, Daniel R.; Kern, Andrew D.

2015-01-01

The comparative genomics revolution of the past decade has enabled the discovery of functional elements in the human genome via sequence comparison. While that is so, an important class of elements, those specific to humans, is entirely missed by searching for sequence conservation across species. Here we present an analysis based on variation data among human genomes that utilizes a supervised machine learning approach for the identification of human-specific purifying selection in the genome. Using only allele frequency information from the complete low-coverage 1000 Genomes Project data set in conjunction with a support vector machine trained from known functional and nonfunctional portions of the genome, we are able to accurately identify portions of the genome constrained by purifying selection. Our method identifies previously known human-specific gains or losses of function and uncovers many novel candidates. Candidate targets for gain and loss of function along the human lineage include numerous putative regulatory regions of genes essential for normal development of the central nervous system, including a significant enrichment of gain of function events near neurotransmitter receptor genes. These results are consistent with regulatory turnover being a key mechanism in the evolution of human-specific characteristics of brain development. Finally, we show that the majority of the genome is unconstrained by natural selection currently, in agreement with what has been estimated from phylogenetic methods but in sharp contrast to estimates based on transcriptomics or other high-throughput functional methods. PMID:26590212

Emergence and Evolution of Hominidae-Specific Coding and Noncoding Genomic Sequences.

PubMed

Saber, Morteza Mahmoudi; Adeyemi Babarinde, Isaac; Hettiarachchi, Nilmini; Saitou, Naruya

2016-07-12

Family Hominidae, which includes humans and great apes, is recognized for unique complex social behavior and intellectual abilities. Despite the increasing genome data, however, the genomic origin of its phenotypic uniqueness has remained elusive. Clade-specific genes and highly conserved noncoding sequences (HCNSs) are among the high-potential evolutionary candidates involved in driving clade-specific characters and phenotypes. On this premise, we analyzed whole genome sequences along with gene orthology data retrieved from major DNA databases to find Hominidae-specific (HS) genes and HCNSs. We discovered that Down syndrome critical region 4 (DSCR4) is the only experimentally verified gene uniquely present in Hominidae. DSCR4 has no structural homology to any known protein and was inferred to have emerged in several steps through LTR/ERV1, LTR/ERVL retrotransposition, and transversion. Using the genomic distance as neutral evolution threshold, we identified 1,658 HS HCNSs. Polymorphism coverage and derived allele frequency analysis of HS HCNSs showed that these HCNSs are under purifying selection, indicating that they may harbor important functions. They are overrepresented in promoters/untranslated regions, in close proximity of genes involved in sensory perception of sound and developmental process, and also showed a significantly lower nucleosome occupancy probability. Interestingly, many ancestral sequences of the HS HCNSs showed very high evolutionary rates. This suggests that new functions emerged through some kind of positive selection, and then purifying selection started to operate to keep these functions. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Methodology for the inference of gene function from phenotype data.

PubMed

Ascensao, Joao A; Dolan, Mary E; Hill, David P; Blake, Judith A

2014-12-12

Biomedical ontologies are increasingly instrumental in the advancement of biological research primarily through their use to efficiently consolidate large amounts of data into structured, accessible sets. However, ontology development and usage can be hampered by the segregation of knowledge by domain that occurs due to independent development and use of the ontologies. The ability to infer data associated with one ontology to data associated with another ontology would prove useful in expanding information content and scope. We here focus on relating two ontologies: the Gene Ontology (GO), which encodes canonical gene function, and the Mammalian Phenotype Ontology (MP), which describes non-canonical phenotypes, using statistical methods to suggest GO functional annotations from existing MP phenotype annotations. This work is in contrast to previous studies that have focused on inferring gene function from phenotype primarily through lexical or semantic similarity measures. We have designed and tested a set of algorithms that represents a novel methodology to define rules for predicting gene function by examining the emergent structure and relationships between the gene functions and phenotypes rather than inspecting the terms semantically. The algorithms inspect relationships among multiple phenotype terms to deduce if there are cases where they all arise from a single gene function. We apply this methodology to data about genes in the laboratory mouse that are formally represented in the Mouse Genome Informatics (MGI) resource. From the data, 7444 rule instances were generated from five generalized rules, resulting in 4818 unique GO functional predictions for 1796 genes. We show that our method is capable of inferring high-quality functional annotations from curated phenotype data. As well as creating inferred annotations, our method has the potential to allow for the elucidation of unforeseen, biologically significant associations between gene function and phenotypes that would be overlooked by a semantics-based approach. Future work will include the implementation of the described algorithms for a variety of other model organism databases, taking full advantage of the abundance of available high quality curated data.

Coverage and timing of children's vaccination: an evaluation of the expanded programme on immunisation in The Gambia.

PubMed

Scott, Susana; Odutola, Aderonke; Mackenzie, Grant; Fulford, Tony; Afolabi, Muhammed O; Lowe Jallow, Yamundow; Jasseh, Momodou; Jeffries, David; Dondeh, Bai Lamin; Howie, Stephen R C; D'Alessandro, Umberto

2014-01-01

To evaluate the coverage and timeliness of the Expanded Programme on Immunisation (EPI) in The Gambia. Vaccination data were obtained between January 2005 and December 2012 from the Farafenni Health and Demographic Surveillance System (FHDSS), the Basse Health and Demographic Surveillance System (BHDSS), the Kiang West Demographic surveillance system (KWDSS), a cluster survey in the more urban Western Health Region (WR) and a cross sectional study in four clinics in the semi-urban Greater Banjul area of WR. Kaplan-Meier survival function was used to estimate the proportion vaccinated by age and to assess timeliness to vaccination. BCG vaccine uptake was over 95% in all regions. Coverage of DPT1 ranged from 93.2% in BHDSS to 99.8% in the WR. Coverage decreased with increasing number of DPT doses; DPT3 coverage ranged from 81.7% in BHDSS to 99.0% in WR. Measles vaccination coverage ranged from 83.3% in BHDSS to 97.0% in WR. DPT4 booster coverage was low and ranged from 43.9% in the WR to 82.8% in KWDSS. Across all regions, delaying on previous vaccinations increased the likelihood of being delayed for the subsequent vaccination. The Gambia health system achieves high vaccine coverage in the first year of life. However, there continues to be a delay to vaccination which may impact on the introduction of new vaccines. Examples of effectively functioning EPI programmes such as The Gambia one may well be important models for other low income countries struggling to achieve high routine vaccination coverage.

Evolution of the Olympus Mons Caldera, Mars

NASA Technical Reports Server (NTRS)

Mouginis-Mark, Peter J.; Robinson, Mark S.; Zuber, Maria T.

1990-01-01

Extensive high-resolution (15 to 20 m/pixel) coverage of Olympus Mons volcano permits the investigation of the sequence of events associated with the evolution of the nested summit caldera. The sequence of the intra-caldera events is well illustrated by image data collected on orbits 473S and 474S of Viking Orbiter 1. These data cover both the oldest and youngest portions of the caldera floor. The chronology inferred from the observations is presented which in turn can be interpreted in terms of the internal structure of the volcano (i.e., magma chamber depth and the existence of dikes).

A Continuous Method for Gene Flow

PubMed Central

Palczewski, Michal; Beerli, Peter

2013-01-01

Most modern population genetics inference methods are based on the coalescence framework. Methods that allow estimating parameters of structured populations commonly insert migration events into the genealogies. For these methods the calculation of the coalescence probability density of a genealogy requires a product over all time periods between events. Data sets that contain populations with high rates of gene flow among them require an enormous number of calculations. A new method, transition probability-structured coalescence (TPSC), replaces the discrete migration events with probability statements. Because the speed of calculation is independent of the amount of gene flow, this method allows calculating the coalescence densities efficiently. The current implementation of TPSC uses an approximation simplifying the interaction among lineages. Simulations and coverage comparisons of TPSC vs. MIGRATE show that TPSC allows estimation of high migration rates more precisely, but because of the approximation the estimation of low migration rates is biased. The implementation of TPSC into programs that calculate quantities on phylogenetic tree structures is straightforward, so the TPSC approach will facilitate more general inferences in many computer programs. PMID:23666937

SU-E-J-86: Functional Conformal Planning for Stereotactic Body Radiation Therapy with CT-Pulmonary Ventilation Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurosawa, T; Moriya, S; Sato, M

2015-06-15

Purpose: To evaluate the functional planning using CT-pulmonary ventilation imaging for conformal SBRT. Methods: The CT-pulmonary ventilation image was generated using the Jacobian metric in the in-house program with the NiftyReg software package. Using the ventilation image, the normal lung was split into three lung regions for functionality (high, moderate and low). The anatomical plan (AP) and functional plan (FP) were made for ten lung SBRT patients. For the AP, the beam angles were optimized with the dose-volume constraints for the normal lung sparing and the PTV coverage. For the FP, the gantry angles were also optimized with the additionalmore » constraint for high functional lung. The MLC aperture shapes were adjusted to the PTV with the additional 5 mm margin. The dosimetric parameters for PTV, the functional volumes, spinal cord and so on were compared in both plans. Results: Compared to the AP, the FP showed better dose sparing for high- and moderate-functional lungs with similar PTV coverage while not taking care of the low functional lung (High:−12.9±9.26% Moderate: −2.0±7.09%, Low: +4.1±12.2%). For the other normal organs, the FP and AP showed similar dose sparing in the eight patients. However, the FP showed that the maximum doses for spinal cord were increased with the significant increment of 16.4Gy and 21.0Gy in other two patients, respectively. Because the beam direction optimizer chose the unexpected directions passing through the spinal cord. Conclusion: Even the functional conformal SBRT can selectively reduce high- and moderatefunctional lung while keeping the PTV coverage. However, it would be careful that the optimizer would choose unexpected beam angles and the dose sparing for the other normal organs can be worse. Therefore, the planner needs to control the dose-volume constraints and also limit the beam angles in order to achieve the expected dose sparing and coverage.« less

Inference of Vohradský's Models of Genetic Networks by Solving Two-Dimensional Function Optimization Problems

PubMed Central

Kimura, Shuhei; Sato, Masanao; Okada-Hatakeyama, Mariko

2013-01-01

The inference of a genetic network is a problem in which mutual interactions among genes are inferred from time-series of gene expression levels. While a number of models have been proposed to describe genetic networks, this study focuses on a mathematical model proposed by Vohradský. Because of its advantageous features, several researchers have proposed the inference methods based on Vohradský's model. When trying to analyze large-scale networks consisting of dozens of genes, however, these methods must solve high-dimensional non-linear function optimization problems. In order to resolve the difficulty of estimating the parameters of the Vohradský's model, this study proposes a new method that defines the problem as several two-dimensional function optimization problems. Through numerical experiments on artificial genetic network inference problems, we showed that, although the computation time of the proposed method is not the shortest, the method has the ability to estimate parameters of Vohradský's models more effectively with sufficiently short computation times. This study then applied the proposed method to an actual inference problem of the bacterial SOS DNA repair system, and succeeded in finding several reasonable regulations. PMID:24386175

An improved method for bivariate meta-analysis when within-study correlations are unknown.

PubMed

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the sample size is relatively small, we recommend the use of the robust method under the working independence assumption. We illustrate the proposed method through 2 meta-analyses. Copyright © 2017 John Wiley & Sons, Ltd.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

Modeling coverage gaps in haplotype frequencies via Bayesian inference to improve stem cell donor selection.

PubMed

Louzoun, Yoram; Alter, Idan; Gragert, Loren; Albrecht, Mark; Maiers, Martin

2018-05-01

Regardless of sampling depth, accurate genotype imputation is limited in regions of high polymorphism which often have a heavy-tailed haplotype frequency distribution. Many rare haplotypes are thus unobserved. Statistical methods to improve imputation by extending reference haplotype distributions using linkage disequilibrium patterns that relate allele and haplotype frequencies have not yet been explored. In the field of unrelated stem cell transplantation, imputation of highly polymorphic human leukocyte antigen (HLA) genes has an important application in identifying the best-matched stem cell donor when searching large registries totaling over 28,000,000 donors worldwide. Despite these large registry sizes, a significant proportion of searched patients present novel HLA haplotypes. Supporting this observation, HLA population genetic models have indicated that many extant HLA haplotypes remain unobserved. The absent haplotypes are a significant cause of error in haplotype matching. We have applied a Bayesian inference methodology for extending haplotype frequency distributions, using a model where new haplotypes are created by recombination of observed alleles. Applications of this joint probability model offer significant improvement in frequency distribution estimates over the best existing alternative methods, as we illustrate using five-locus HLA frequency data from the National Marrow Donor Program registry. Transplant matching algorithms and disease association studies involving phasing and imputation of rare variants may benefit from this statistical inference framework.

Surface radiant flux densities inferred from LAC and GAC AVHRR data

NASA Astrophysics Data System (ADS)

Berger, F.; Klaes, D.

To infer surface radiant flux densities from current (NOAA-AVHRR, ERS-1/2 ATSR) and future meteorological (Envisat AATSR, MSG, METOP) satellite data, the complex, modular analysis scheme SESAT (Strahlungs- und Energieflüsse aus Satellitendaten) could be developed (Berger, 2001). This scheme allows the determination of cloud types, optical and microphysical cloud properties as well as surface and TOA radiant flux densities. After testing of SESAT in Central Europe and the Baltic Sea catchment (more than 400scenes U including a detailed validation with various surface measurements) it could be applied to a large number of NOAA-16 AVHRR overpasses covering the globe.For the analysis, two different spatial resolutions U local area coverage (LAC) andwere considered. Therefore, all inferred results, like global area coverage (GAC) U cloud cover, cloud properties and radiant properties, could be intercompared. Specific emphasis could be made to the surface radiant flux densities (all radiative balance compoments), where results for different regions, like Southern America, Southern Africa, Northern America, Europe, and Indonesia, will be presented. Applying SESAT, energy flux densities, like latent and sensible heat flux densities could also be determined additionally. A statistical analysis of all results including a detailed discussion for the two spatial resolutions will close this study.

Analysis of uncertainties in GOSAT-inferred regional CO2 fluxes

NASA Astrophysics Data System (ADS)

Ishizawa, M.; Shirai, T.; Maksyutov, S. S.; Yoshida, Y.; Morino, I.; Inoue, M.; Nakatsuru, T.; Uchino, O.; Mabuchi, K.

2016-12-01

Satellite-based CO2 measurements have potential for improving our understanding global carbon cycle because of more spatiotemporal coverage than those from ground-based observations. Since the Greenhouse gases Observing Satellite (GOSAT) was launched in January 2009, it has been measuring the column-average dry air-mole function of CO2 (XCO2) from the space. To utilize the GOSAT XCO2 for better CO2 flux estimates, several challenges should be overcome. Systematic errors (biases) in XCO2 retrievals are a major factor which leads to large differences among inverted CO2 fluxes. Temporally variable data coverage and density are also taken into account when interpreting the estimated surface fluxes. In this study, we employ an atmospheric inverse model to investigate the impacts of retrievals biases and temporally varying global distribution of GOSAT XCO2 on surface CO2 flux estimates. Inversions are performed for 2009-2013, with several subsets of the 5-year record of GOSAT XCO2 (v2.21) and its bias-corrected XCO2. GOSAT XCO2 data consist of three types: H-gain for vegetated lands, M-gain for bright surfaces (desert areas), and sun-glint for ocean surface. The results show that the global spatial distributions of estimated CO2 fluxes depend on the subset of XCO2 used. M-gain XCO2 results in unrealistically high CO2 emissions in and around the Middle East, including the neighboring ocean regions. On the other hand, M-gain XCO2 causes compensating unrealistic uptakes far beyond M-gain regions in low latitudes, also partially contributing on the summer uptake in Europe. The joint inversions with both surface measurements and GOSAT XCO2 data obtain larger flux gradient between the northern extra-tropics and the tropics than the inversion with surface measurements only for the first 2 years. Recently, these North-South gradients seem to be gradually reducing as the tropics become a weaker source or turn into a sink, while the net emission strength in East Asia is increasing. The 5-year XCO2 data allows us detailed analysis of uncertainties in GOSAT-inferred fluxes and assessment of GOSAT XCO2 biases.

Mineral and Geochemical Classification From Spectroscopy/Diffraction Through Neural Networks

NASA Astrophysics Data System (ADS)

Ferralis, N.; Grossman, J.; Summons, R. E.

2017-12-01

Spectroscopy and diffraction techniques are essential for understanding structural, chemical and functional properties of geological materials for Earth and Planetary Sciences. Beyond data collection, quantitative insight relies on experimentally assembled, or computationally derived spectra. Inference on the geochemical or geophysical properties (such as crystallographic order, chemical functionality, elemental composition, etc.) of a particular geological material (mineral, organic matter, etc.) is based on fitting unknown spectra and comparing the fit with consolidated databases. The complexity of fitting highly convoluted spectra, often limits the ability to infer geochemical characteristics, and limits the throughput for extensive datasets. With the emergence of heuristic approaches to pattern recognitions though machine learning, in this work we investigate the possibility and potential of using supervised neural networks trained on available public spectroscopic database to directly infer geochemical parameters from unknown spectra. Using Raman, infrared spectroscopy and powder x-ray diffraction from the publicly available RRUFF database, we train neural network models to classify mineral and organic compounds (pure or mixtures) based on crystallographic structure from diffraction, chemical functionality, elemental composition and bonding from spectroscopy. As expected, the accuracy of the inference is strongly dependent on the quality and extent of the training data. We will identify a series of requirements and guidelines for the training dataset needed to achieve consistent high accuracy inference, along with methods to compensate for limited of data.

Characterization of Polar Stratospheric Clouds With Spaceborne Lidar: CALIPSO and the 2006 Antarctic Season

NASA Technical Reports Server (NTRS)

Pitts, Michael C.; Thomason, L. W.; Poole, Lamont R.; Winker, David M.

2007-01-01

The role of polar stratospheric clouds in polar ozone loss has been well documented. The CALIPSO satellite mission offers a new opportunity to characterize PSCs on spatial and temporal scales previously unavailable. A PSC detection algorithm based on a single wavelength threshold approach has been developed for CALIPSO. The method appears to accurately detect PSCs of all opacities, including tenuous clouds, with a very low rate of false positives and few missed clouds. We applied the algorithm to CALIPSO data acquired during the 2006 Antarctic winter season from 13 June through 31 October. The spatial and temporal distribution of CALIPSO PSC observations is illustrated with weekly maps of PSC occurrence. The evolution of the 2006 PSC season is depicted by time series of daily PSC frequency as a function of altitude. Comparisons with virtual solar occultation data indicate that CALIPSO provides a different view of the PSC season than attained with previous solar occultation satellites. Measurement-based time series of PSC areal coverage and vertically-integrated PSC volume are computed from the CALIPSO data. The observed area covered with PSCs is significantly smaller than would be inferred from a temperature-based proxy such as TNAT but is similar in magnitude to that inferred from TSTS. The potential of CALIPSO measurements for investigating PSC microphysics is illustrated using combinations of lidar backscatter coefficient and volume depolarization to infer composition for two CALIPSO PSC scenes.

High precision multi-genome scale reannotation of enzyme function by EFICAz

PubMed Central

Arakaki, Adrian K; Tian, Weidong; Skolnick, Jeffrey

2006-01-01

Background The functional annotation of most genes in newly sequenced genomes is inferred from similarity to previously characterized sequences, an annotation strategy that often leads to erroneous assignments. We have performed a reannotation of 245 genomes using an updated version of EFICAz, a highly precise method for enzyme function prediction. Results Based on our three-field EC number predictions, we have obtained lower-bound estimates for the average enzyme content in Archaea (29%), Bacteria (30%) and Eukarya (18%). Most annotations added in KEGG from 2005 to 2006 agree with EFICAz predictions made in 2005. The coverage of EFICAz predictions is significantly higher than that of KEGG, especially for eukaryotes. Thousands of our novel predictions correspond to hypothetical proteins. We have identified a subset of 64 hypothetical proteins with low sequence identity to EFICAz training enzymes, whose biochemical functions have been recently characterized and find that in 96% (84%) of the cases we correctly identified their three-field (four-field) EC numbers. For two of the 64 hypothetical proteins: PA1167 from Pseudomonas aeruginosa, an alginate lyase (EC 4.2.2.3) and Rv1700 of Mycobacterium tuberculosis H37Rv, an ADP-ribose diphosphatase (EC 3.6.1.13), we have detected annotation lag of more than two years in databases. Two examples are presented where EFICAz predictions act as hypothesis generators for understanding the functional roles of hypothetical proteins: FLJ11151, a human protein overexpressed in cancer that EFICAz identifies as an endopolyphosphatase (EC 3.6.1.10), and MW0119, a protein of Staphylococcus aureus strain MW2 that we propose as candidate virulence factor based on its EFICAz predicted activity, sphingomyelin phosphodiesterase (EC 3.1.4.12). Conclusion Our results suggest that we have generated enzyme function annotations of high precision and recall. These predictions can be mined and correlated with other information sources to generate biologically significant hypotheses and can be useful for comparative genome analysis and automated metabolic pathway reconstruction. PMID:17166279

Making Inferences: Comprehension of Physical Causality, Intentionality, and Emotions in Discourse by High-Functioning Older Children, Adolescents, and Adults with Autism.

PubMed

Bodner, Kimberly E; Engelhardt, Christopher R; Minshew, Nancy J; Williams, Diane L

2015-09-01

Studies investigating inferential reasoning in autism spectrum disorder (ASD) have focused on the ability to make socially-related inferences or inferences more generally. Important variables for intervention planning such as whether inferences depend on physical experiences or the nature of social information have received less consideration. A measure of bridging inferences of physical causation, mental states, and emotional states was administered to older children, adolescents, and adults with and without ASD. The ASD group had more difficulty making inferences, particularly related to emotional understanding. Results suggest that individuals with ASD may not have the stored experiential knowledge that specific inferences depend upon or have difficulties accessing relevant experiences due to linguistic limitations. Further research is needed to tease these elements apart.

Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference.

PubMed

Krishnan, Neeraja M; Seligmann, Hervé; Stewart, Caro-Beth; De Koning, A P Jason; Pollock, David D

2004-10-01

Reconstruction of ancestral DNA and amino acid sequences is an important means of inferring information about past evolutionary events. Such reconstructions suggest changes in molecular function and evolutionary processes over the course of evolution and are used to infer adaptation and convergence. Maximum likelihood (ML) is generally thought to provide relatively accurate reconstructed sequences compared to parsimony, but both methods lead to the inference of multiple directional changes in nucleotide frequencies in primate mitochondrial DNA (mtDNA). To better understand this surprising result, as well as to better understand how parsimony and ML differ, we constructed a series of computationally simple "conditional pathway" methods that differed in the number of substitutions allowed per site along each branch, and we also evaluated the entire Bayesian posterior frequency distribution of reconstructed ancestral states. We analyzed primate mitochondrial cytochrome b (Cyt-b) and cytochrome oxidase subunit I (COI) genes and found that ML reconstructs ancestral frequencies that are often more different from tip sequences than are parsimony reconstructions. In contrast, frequency reconstructions based on the posterior ensemble more closely resemble extant nucleotide frequencies. Simulations indicate that these differences in ancestral sequence inference are probably due to deterministic bias caused by high uncertainty in the optimization-based ancestral reconstruction methods (parsimony, ML, Bayesian maximum a posteriori). In contrast, ancestral nucleotide frequencies based on an average of the Bayesian set of credible ancestral sequences are much less biased. The methods involving simpler conditional pathway calculations have slightly reduced likelihood values compared to full likelihood calculations, but they can provide fairly unbiased nucleotide reconstructions and may be useful in more complex phylogenetic analyses than considered here due to their speed and flexibility. To determine whether biased reconstructions using optimization methods might affect inferences of functional properties, ancestral primate mitochondrial tRNA sequences were inferred and helix-forming propensities for conserved pairs were evaluated in silico. For ambiguously reconstructed nucleotides at sites with high base composition variability, ancestral tRNA sequences from Bayesian analyses were more compatible with canonical base pairing than were those inferred by other methods. Thus, nucleotide bias in reconstructed sequences apparently can lead to serious bias and inaccuracies in functional predictions.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Building Coverage Ratio at the Eastern Corridor of Jalan Ir. H. Djuanda Bandung

NASA Astrophysics Data System (ADS)

Megayanti, T.; Widaningsih, L.; Minggra, R.; Dewi, N. I. K.

2018-01-01

Historically in the Colonial period, the Corridor of Jalan Ir. H. Juanda or better known as Jalan Dago was designed as a residential area. As the high development of commercial activity along of Bandung City, almost all of buildings in this area are turned its’ function to supported commercial activity. The change is shown in many aspects from the shape of the building and even occur in changing the old building into a new one due to a high intensity of this commercial activity. This paper investigates the use of Building Coverage Ratio regulation related to functional change in the Corridor of Jalan Ir. H. Juanda Bandung. The aim is to what extent the regulations related to Building Coverage area are implemented. This study used a descriptive qualitative method by conducting observation to identify buildings on the Corridor by dividing it into three segments. The results show quantitatively there is a lot of irrelevancies to Building Coverage Ratio regulation which is shown in the second and third segment. Most of the building in the first segment has in compliance with the regulation. However, to build a harmony in characters of City corridor is not only created by Building Coverage Ratio but also others parameters such as the land use, the shape of buildings, façade, and design concept. Thus, it is highly recommended to create a detail regulation regarding those parameters.

The study of human Y chromosome variation through ancient DNA.

PubMed

Kivisild, Toomas

2017-05-01

High throughput sequencing methods have completely transformed the study of human Y chromosome variation by offering a genome-scale view on genetic variation retrieved from ancient human remains in context of a growing number of high coverage whole Y chromosome sequence data from living populations from across the world. The ancient Y chromosome sequences are providing us the first exciting glimpses into the past variation of male-specific compartment of the genome and the opportunity to evaluate models based on previously made inferences from patterns of genetic variation in living populations. Analyses of the ancient Y chromosome sequences are challenging not only because of issues generally related to ancient DNA work, such as DNA damage-induced mutations and low content of endogenous DNA in most human remains, but also because of specific properties of the Y chromosome, such as its highly repetitive nature and high homology with the X chromosome. Shotgun sequencing of uniquely mapping regions of the Y chromosomes to sufficiently high coverage is still challenging and costly in poorly preserved samples. To increase the coverage of specific target SNPs capture-based methods have been developed and used in recent years to generate Y chromosome sequence data from hundreds of prehistoric skeletal remains. Besides the prospects of testing directly as how much genetic change in a given time period has accompanied changes in material culture the sequencing of ancient Y chromosomes allows us also to better understand the rate at which mutations accumulate and get fixed over time. This review considers genome-scale evidence on ancient Y chromosome diversity that has recently started to accumulate in geographic areas favourable to DNA preservation. More specifically the review focuses on examples of regional continuity and change of the Y chromosome haplogroups in North Eurasia and in the New World.

The total satellite population of the Milky Way

NASA Astrophysics Data System (ADS)

Newton, Oliver; Cautun, Marius; Jenkins, Adrian; Frenk, Carlos S.; Helly, John C.

2018-05-01

The total number and luminosity function of the population of dwarf galaxies of the Milky Way (MW) provide important constraints on the nature of the dark matter and on the astrophysics of galaxy formation at low masses. However, only a partial census of this population exists because of the flux limits and restricted sky coverage of existing Galactic surveys. We combine the sample of satellites recently discovered by the Dark Energy Survey (DES) survey with the satellites found in Sloan Digital Sky Survey (SDSS) Data Release 9 (together these surveys cover nearly half the sky) to estimate the total luminosity function of satellites down to MV = 0. We apply a new Bayesian inference method in which we assume that the radial distribution of satellites independently of absolute magnitude follows that of subhaloes selected according to their peak maximum circular velocity. We find that there should be at least 124^{+40}_{-27}(68% CL, statistical error) satellites brighter than MV = 0 within 300kpc of the Sun. As a result of our use of new data and better simulations, and a more robust statistical method, we infer a much smaller population of satellites than reported in previous studies using earlier SDSS data only; we also address an underestimation of the uncertainties in earlier work by accounting for stochastic effects. We find that the inferred number of faint satellites depends only weakly on the assumed mass of the MW halo and we provide scaling relations to extend our results to different assumed halo masses and outer radii. We predict that half of our estimated total satellite population of the MW should be detected by the Large Synoptic Survey Telescope (LSST). The code implementing our estimation method is available online.†

Ground penetrating radar documents short-term near-surface hydrological changes around Old Faithful Geyser, Yellowstone National Park, USA

NASA Astrophysics Data System (ADS)

Lynne, Bridget Y.; Heasler, Henry; Jaworowski, Cheryl; Smith, Gary J.; Smith, Isaac J.; Foley, Duncan

2018-04-01

In April 2015, Ground Penetrating Radar (GPR) was used to characterize the shallow subsurface (< 5 m depth) of the western sinter slope immediately adjacent to Old Faithful Geyser and near the north side of an inferred geyser cavity. A series of time-sequence images were collected between two eruptions of Old Faithful Geyser. Each set of time-sequence GPR recordings consisted of four transects aligned to provide coverage near the potential location of the inferred 15 m deep geyser chamber. However, the deepest penetration we could achieve with a 200 MHz GPR antennae was 5 m. Seven time-sequence events were collected over a 48-minute interval to image changes in the near-surface, during pre- and post-eruptive cycles. Time-sequence GPR images revealed a series of possible micro-fractures in a highly porous siliceous sinter in the near-surface that fill and drain repetitively, immediately after an eruption and during the recharge period prior to the next main eruptive event.

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roux, Simon; Emerson, Joanne B.; Eloe-Fadrosh, Emiley A.

BackgroundViral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we usedin silicomock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates. ResultsTools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, andmore » IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates. ConclusionsThese simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.« less

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

DOE PAGES

Roux, Simon; Emerson, Joanne B.; Eloe-Fadrosh, Emiley A.; ...

2017-09-21

BackgroundViral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we usedin silicomock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates. ResultsTools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, andmore » IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates. ConclusionsThese simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.« less

High-dimensional inference with the generalized Hopfield model: principal component analysis and corrections.

PubMed

Cocco, S; Monasson, R; Sessak, V

2011-05-01

We consider the problem of inferring the interactions between a set of N binary variables from the knowledge of their frequencies and pairwise correlations. The inference framework is based on the Hopfield model, a special case of the Ising model where the interaction matrix is defined through a set of patterns in the variable space, and is of rank much smaller than N. We show that maximum likelihood inference is deeply related to principal component analysis when the amplitude of the pattern components ξ is negligible compared to √N. Using techniques from statistical mechanics, we calculate the corrections to the patterns to the first order in ξ/√N. We stress the need to generalize the Hopfield model and include both attractive and repulsive patterns in order to correctly infer networks with sparse and strong interactions. We present a simple geometrical criterion to decide how many attractive and repulsive patterns should be considered as a function of the sampling noise. We moreover discuss how many sampled configurations are required for a good inference, as a function of the system size N and of the amplitude ξ. The inference approach is illustrated on synthetic and biological data.

Functional networks inference from rule-based machine learning models.

PubMed

Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

2016-01-01

Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The implementation of our network inference protocol is available at: http://ico2s.org/software/funel.html.

Using CTX Image Features to Predict HiRISE-Equivalent Rock Density

NASA Technical Reports Server (NTRS)

Serrano, Navid; Huertas, Andres; McGuire, Patrick; Mayer, David; Ardvidson, Raymond

2010-01-01

Methods have been developed to quantitatively assess rock hazards at candidate landing sites with the aid of images from the HiRISE camera onboard NASA s Mars Reconnaissance Orbiter. HiRISE is able to resolve rocks as small as 1-m in diameter. Some sites of interest do not have adequate coverage with the highest resolution sensors and there is a need to infer relevant information (like site safety or underlying geomorphology). The proposed approach would make it possible to obtain rock density estimates at a level close to or equal to those obtained from high-resolution sensors where individual rocks are discernable.

High-frequency source radiation during the 2011 Tohoku-Oki earthquake, Japan, inferred from KiK-net strong-motion seismograms

NASA Astrophysics Data System (ADS)

Kumagai, Hiroyuki; Pulido, Nelson; Fukuyama, Eiichi; Aoi, Shin

2013-01-01

investigate source processes of the 2011 Tohoku-Oki earthquake, we utilized a source location method using high-frequency (5-10 Hz) seismic amplitudes. In this method, we assumed far-field isotropic radiation of S waves, and conducted a spatial grid search to find the best fitting source locations along the subducted slab in each successive time window. Our application of the method to the Tohoku-Oki earthquake resulted in artifact source locations at shallow depths near the trench caused by limited station coverage and noise effects. We then assumed various source node distributions along the plate, and found that the observed seismograms were most reasonably explained when assuming deep source nodes. This result suggests that the high-frequency seismic waves were radiated at deeper depths during the earthquake, a feature which is consistent with results obtained from teleseismic back-projection and strong-motion source model studies. We identified three high-frequency subevents, and compared them with the moment-rate function estimated from low-frequency seismograms. Our comparison indicated that no significant moment release occurred during the first high-frequency subevent and the largest moment-release pulse occurred almost simultaneously with the second high-frequency subevent. We speculated that the initial slow rupture propagated bilaterally from the hypocenter toward the land and trench. The landward subshear rupture propagation consisted of three successive high-frequency subevents. The trenchward propagation ruptured the strong asperity and released the largest moment near the trench.

sick: The Spectroscopic Inference Crank

NASA Astrophysics Data System (ADS)

Casey, Andrew R.

2016-03-01

There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal-to-noise ratio spectra of M67 stars reveals atomic diffusion processes on the order of 0.05 dex, previously only measurable with differential analysis techniques in high-resolution spectra. sick is easy to use, well-tested, and freely available online through GitHub under the MIT license.

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

PubMed Central

Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not necessarily imply that one detection methodology was better or worse, but rather that, to a large extent, the insights reflected the methodological biases themselves. Consequently, interpreting the protein interaction data within their experimental or cellular context provided the best avenue for overcoming biases and inferring biological knowledge. PMID:21876202

Population genetic inference from personal genome data: impact of ancestry and admixture on human genomic variation.

PubMed

Kidd, Jeffrey M; Gravel, Simon; Byrnes, Jake; Moreno-Estrada, Andres; Musharoff, Shaila; Bryc, Katarzyna; Degenhardt, Jeremiah D; Brisbin, Abra; Sheth, Vrunda; Chen, Rong; McLaughlin, Stephen F; Peckham, Heather E; Omberg, Larsson; Bormann Chung, Christina A; Stanley, Sarah; Pearlstein, Kevin; Levandowsky, Elizabeth; Acevedo-Acevedo, Suehelay; Auton, Adam; Keinan, Alon; Acuña-Alonzo, Victor; Barquera-Lozano, Rodrigo; Canizales-Quinteros, Samuel; Eng, Celeste; Burchard, Esteban G; Russell, Archie; Reynolds, Andy; Clark, Andrew G; Reese, Martin G; Lincoln, Stephen E; Butte, Atul J; De La Vega, Francisco M; Bustamante, Carlos D

2012-10-05

Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas-70% of the European ancestry in today's African Americans dates back to European gene flow happening only 7-8 generations ago. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Population Genetic Inference from Personal Genome Data: Impact of Ancestry and Admixture on Human Genomic Variation

PubMed Central

Kidd, Jeffrey M.; Gravel, Simon; Byrnes, Jake; Moreno-Estrada, Andres; Musharoff, Shaila; Bryc, Katarzyna; Degenhardt, Jeremiah D.; Brisbin, Abra; Sheth, Vrunda; Chen, Rong; McLaughlin, Stephen F.; Peckham, Heather E.; Omberg, Larsson; Bormann Chung, Christina A.; Stanley, Sarah; Pearlstein, Kevin; Levandowsky, Elizabeth; Acevedo-Acevedo, Suehelay; Auton, Adam; Keinan, Alon; Acuña-Alonzo, Victor; Barquera-Lozano, Rodrigo; Canizales-Quinteros, Samuel; Eng, Celeste; Burchard, Esteban G.; Russell, Archie; Reynolds, Andy; Clark, Andrew G.; Reese, Martin G.; Lincoln, Stephen E.; Butte, Atul J.; De La Vega, Francisco M.; Bustamante, Carlos D.

2012-01-01

Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas—70% of the European ancestry in today’s African Americans dates back to European gene flow happening only 7–8 generations ago. PMID:23040495

Ionospheric and Birkeland current distributions inferred from the MAGSAT magnetometer data

NASA Technical Reports Server (NTRS)

Zanetti, L. J.; Potemra, T. A.; Baumjohann, W.

1983-01-01

Ionospheric and field-aligned sheet current density distributions are presently inferred by means of MAGSAT vector magnetometer data, together with an accurate magnetic field model. By comparing Hall current densities inferred from the MAGSAT data and those inferred from simultaneously recorded ground based data acquired by the Scandinavian magnetometer array, it is determined that the former have previously been underestimated due to high damping of magnetic variations with high spatial wave numbers between the ionosphere and the MAGSAT orbit. Among important results of this study is noted the fact that the Birkeland and electrojet current systems are colocated. The analyses have shown a tendency for triangular rather than constant electrojet current distributions as a function of latitude, consistent with the statistical, uniform regions 1 and 2 Birkeland current patterns.

Accounting for GC-content bias reduces systematic errors and batch effects in ChIP-seq data.

PubMed

Teng, Mingxiang; Irizarry, Rafael A

2017-11-01

The main application of ChIP-seq technology is the detection of genomic regions that bind to a protein of interest. A large part of functional genomics' public catalogs is based on ChIP-seq data. These catalogs rely on peak calling algorithms that infer protein-binding sites by detecting genomic regions associated with more mapped reads (coverage) than expected by chance, as a result of the experimental protocol's lack of perfect specificity. We find that GC-content bias accounts for substantial variability in the observed coverage for ChIP-seq experiments and that this variability leads to false-positive peak calls. More concerning is that the GC effect varies across experiments, with the effect strong enough to result in a substantial number of peaks called differently when different laboratories perform experiments on the same cell line. However, accounting for GC content bias in ChIP-seq is challenging because the binding sites of interest tend to be more common in high GC-content regions, which confounds real biological signals with unwanted variability. To account for this challenge, we introduce a statistical approach that accounts for GC effects on both nonspecific noise and signal induced by the binding site. The method can be used to account for this bias in binding quantification as well to improve existing peak calling algorithms. We use this approach to show a reduction in false-positive peaks as well as improved consistency across laboratories. © 2017 Teng and Irizarry; Published by Cold Spring Harbor Laboratory Press.

Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

NASA Astrophysics Data System (ADS)

Serafimovich, Andrei; Metzger, Stefan; Hartmann, Jörg; Kohnert, Katrin; Zona, Donatella; Sachs, Torsten

2018-03-01

The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June-July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

Rare variation facilitates inferences of fine-scale population structure in humans.

PubMed

O'Connor, Timothy D; Fu, Wenqing; Mychaleckyj, Josyf C; Logsdon, Benjamin; Auer, Paul; Carlson, Christopher S; Leal, Suzanne M; Smith, Joshua D; Rieder, Mark J; Bamshad, Michael J; Nickerson, Deborah A; Akey, Joshua M

2015-03-01

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European-American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genomic analyses inform on migration events during the peopling of Eurasia

NASA Astrophysics Data System (ADS)

Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; Mörseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; Degiorgio, Michael; Saag, Lauri; Wall, Jeffrey D.; Cardona, Alexia; Mägi, Reedik; Sayres, Melissa A. Wilson; Kaewert, Sarah; Inchley, Charlotte; Scheib, Christiana L.; Järve, Mari; Karmin, Monika; Jacobs, Guy S.; Antao, Tiago; Iliescu, Florin Mircea; Kushniarevich, Alena; Ayub, Qasim; Tyler-Smith, Chris; Xue, Yali; Yunusbayev, Bayazit; Tambets, Kristiina; Mallick, Chandana Basu; Saag, Lehti; Pocheshkhova, Elvira; Andriadze, George; Muller, Craig; Westaway, Michael C.; Lambert, David M.; Zoraqi, Grigor; Turdikulova, Shahlo; Dalimova, Dilbar; Sabitov, Zhaxylyk; Sultana, Gazi Nurun Nahar; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Isakova, Jainagul; Damba, Larisa D.; Gubina, Marina; Nymadawa, Pagbajabyn; Evseeva, Irina; Atramentova, Lubov; Utevska, Olga; Ricaut, François-Xavier; Brucato, Nicolas; Sudoyo, Herawati; Letellier, Thierry; Cox, Murray P.; Barashkov, Nikolay A.; Škaro, Vedrana; Mulaha´, Lejla; Primorac, Dragan; Sahakyan, Hovhannes; Mormina, Maru; Eichstaedt, Christina A.; Lichman, Daria V.; Abdullah, Syafiq; Chaubey, Gyaneshwer; Wee, Joseph T. S.; Mihailov, Evelin; Karunas, Alexandra; Litvinov, Sergei; Khusainova, Rita; Ekomasova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Marjanović, Damir; Yepiskoposyan, Levon; Behar, Doron M.; Balanovska, Elena; Metspalu, Andres; Derenko, Miroslava; Malyarchuk, Boris; Voevoda, Mikhail; Fedorova, Sardana A.; Osipova, Ludmila P.; Lahr, Marta Mirazón; Gerbault, Pascale; Leavesley, Matthew; Migliano, Andrea Bamberg; Petraglia, Michael; Balanovsky, Oleg; Khusnutdinova, Elza K.; Metspalu, Ene; Thomas, Mark G.; Manica, Andrea; Nielsen, Rasmus; Villems, Richard; Willerslev, Eske; Kivisild, Toomas; Metspalu, Mait

2016-10-01

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

Genomic analyses inform on migration events during the peopling of Eurasia.

PubMed

Pagani, Luca; Lawson, Daniel John; Jagoda, Evelyn; Mörseburg, Alexander; Eriksson, Anders; Mitt, Mario; Clemente, Florian; Hudjashov, Georgi; DeGiorgio, Michael; Saag, Lauri; Wall, Jeffrey D; Cardona, Alexia; Mägi, Reedik; Wilson Sayres, Melissa A; Kaewert, Sarah; Inchley, Charlotte; Scheib, Christiana L; Järve, Mari; Karmin, Monika; Jacobs, Guy S; Antao, Tiago; Iliescu, Florin Mircea; Kushniarevich, Alena; Ayub, Qasim; Tyler-Smith, Chris; Xue, Yali; Yunusbayev, Bayazit; Tambets, Kristiina; Mallick, Chandana Basu; Saag, Lehti; Pocheshkhova, Elvira; Andriadze, George; Muller, Craig; Westaway, Michael C; Lambert, David M; Zoraqi, Grigor; Turdikulova, Shahlo; Dalimova, Dilbar; Sabitov, Zhaxylyk; Sultana, Gazi Nurun Nahar; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Isakova, Jainagul; Damba, Larisa D; Gubina, Marina; Nymadawa, Pagbajabyn; Evseeva, Irina; Atramentova, Lubov; Utevska, Olga; Ricaut, François-Xavier; Brucato, Nicolas; Sudoyo, Herawati; Letellier, Thierry; Cox, Murray P; Barashkov, Nikolay A; Skaro, Vedrana; Mulahasanovic, Lejla; Primorac, Dragan; Sahakyan, Hovhannes; Mormina, Maru; Eichstaedt, Christina A; Lichman, Daria V; Abdullah, Syafiq; Chaubey, Gyaneshwer; Wee, Joseph T S; Mihailov, Evelin; Karunas, Alexandra; Litvinov, Sergei; Khusainova, Rita; Ekomasova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Marjanović, Damir; Yepiskoposyan, Levon; Behar, Doron M; Balanovska, Elena; Metspalu, Andres; Derenko, Miroslava; Malyarchuk, Boris; Voevoda, Mikhail; Fedorova, Sardana A; Osipova, Ludmila P; Lahr, Marta Mirazón; Gerbault, Pascale; Leavesley, Matthew; Migliano, Andrea Bamberg; Petraglia, Michael; Balanovsky, Oleg; Khusnutdinova, Elza K; Metspalu, Ene; Thomas, Mark G; Manica, Andrea; Nielsen, Rasmus; Villems, Richard; Willerslev, Eske; Kivisild, Toomas; Metspalu, Mait

2016-10-13

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

Pipeline for inferring protein function from dynamics using coarse-grained molecular mechanics forcefield.

PubMed

Bhadra, Pratiti; Pal, Debnath

2017-04-01

Dynamics is integral to the function of proteins, yet the use of molecular dynamics (MD) simulation as a technique remains under-explored for molecular function inference. This is more important in the context of genomics projects where novel proteins are determined with limited evolutionary information. Recently we developed a method to match the query protein's flexible segments to infer function using a novel approach combining analysis of residue fluctuation-graphs and auto-correlation vectors derived from coarse-grained (CG) MD trajectory. The method was validated on a diverse dataset with sequence identity between proteins as low as 3%, with high function-recall rates. Here we share its implementation as a publicly accessible web service, named DynFunc (Dynamics Match for Function) to query protein function from ≥1 µs long CG dynamics trajectory information of protein subunits. Users are provided with the custom-developed coarse-grained molecular mechanics (CGMM) forcefield to generate the MD trajectories for their protein of interest. On upload of trajectory information, the DynFunc web server identifies specific flexible regions of the protein linked to putative molecular function. Our unique application does not use evolutionary information to infer molecular function from MD information and can, therefore, work for all proteins, including moonlighting and the novel ones, whenever structural information is available. Our pipeline is expected to be of utility to all structural biologists working with novel proteins and interested in moonlighting functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hypersaline sapropels act as hotspots for microbial dark matter

DOE PAGES

Andrei, Adrian -Stefan; Baricz, Andreea; Robeson, Michael Scott; ...

2017-07-21

Present-day terrestrial analogue sites are crucial ground truth proxies for studying life in geochemical conditions close to those assumed to be present on early Earth or inferred to exist on other celestial bodies (e.g. Mars, Europa). Although hypersaline sapropels are border-of-life habitats with moderate occurrence, their microbiological and physicochemical characterization lags behind. Here, we study the diversity of life under low water activity by describing the prokaryotic communities from two disparate hypersaline sapropels (Transylvanian Basin, Romania) in relation to geochemical milieu and pore water chemistry, while inferring their role in carbon cycling by matching taxa to known taxon-specific biogeochemical functions.more » Furthermore, the polyphasic approach combined deep coverage SSU rRNA gene amplicon sequencing and bioinformatics with RT-qPCR and physicochemical investigations. We found that sapropels developed an analogous elemental milieu and harbored prokaryotes affiliated with fifty-nine phyla, among which the most abundant were Proteobacteria, Bacteroidetes and Chloroflexi. Containing thirty-two candidate divisions and possibly undocumented prokaryotic lineages, the hypersaline sapropels were found to accommodate one of the most diverse and novel ecosystems reported to date and may contribute to completing the phylogenetic branching of the tree of life.« less

Hypersaline sapropels act as hotspots for microbial dark matter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrei, Adrian -Stefan; Baricz, Andreea; Robeson, Michael Scott

Present-day terrestrial analogue sites are crucial ground truth proxies for studying life in geochemical conditions close to those assumed to be present on early Earth or inferred to exist on other celestial bodies (e.g. Mars, Europa). Although hypersaline sapropels are border-of-life habitats with moderate occurrence, their microbiological and physicochemical characterization lags behind. Here, we study the diversity of life under low water activity by describing the prokaryotic communities from two disparate hypersaline sapropels (Transylvanian Basin, Romania) in relation to geochemical milieu and pore water chemistry, while inferring their role in carbon cycling by matching taxa to known taxon-specific biogeochemical functions.more » Furthermore, the polyphasic approach combined deep coverage SSU rRNA gene amplicon sequencing and bioinformatics with RT-qPCR and physicochemical investigations. We found that sapropels developed an analogous elemental milieu and harbored prokaryotes affiliated with fifty-nine phyla, among which the most abundant were Proteobacteria, Bacteroidetes and Chloroflexi. Containing thirty-two candidate divisions and possibly undocumented prokaryotic lineages, the hypersaline sapropels were found to accommodate one of the most diverse and novel ecosystems reported to date and may contribute to completing the phylogenetic branching of the tree of life.« less

Tuning the tunneling magnetoresistance by using fluorinated graphene in graphene based magnetic junctions

NASA Astrophysics Data System (ADS)

Meena, Shweta; Choudhary, Sudhanshu

2017-12-01

Spin polarized properties of fluorinated graphene as tunnel barrier with CrO2 as two HMF electrodes are studied using first principle methods based on density functional theory. Fluorinated graphene with different fluorine coverages is explored as tunnel barriers in magnetic tunnel junctions. Density functional computation for different fluorine coverages imply that with increase in fluorine coverages, there is increase in band gap (Eg) of graphene, Eg ˜ 3.466 e V was observed when graphene sheet is fluorine adsorbed on both-side with 100% coverage (CF). The results of CF graphene are compared with C4F (fluorination on one-side of graphene sheet with 25% coverage) and out-of-plane graphene based magnetic tunnel junctions. On comparison of the results it is observed that CF graphene based structure offers high TMR ˜100%, and the transport of carrier is through tunneling as there are no transmission states near Fermi level. This suggests that graphene sheet with both-side fluorination with 100% coverages acts as a perfect insulator and hence a better barrier to the carriers which is due to negligible spin down current (I ↓ ) in both Parallel Configuration (PC) and Antiparallel Configuration (APC).

Detective Questions: A Strategy for Improving Inference-Making in Children With Mild Disabilities

ERIC Educational Resources Information Center

Jiménez-Fernández, Gracia

2015-01-01

One of the most frequent problems in reading comprehension is the difficulty in making inferences from the text, especially for students with mild disabilities (i.e., children with learning disabilities or with high-functioning autism). It is essential, therefore, that educators include the teaching of reading strategies to improve their students'…

Inference of gene regulatory networks from time series by Tsallis entropy

PubMed Central

2011-01-01

Background The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 ≤ q ≤ 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/. PMID:21545720

Statistical inference for extended or shortened phase II studies based on Simon's two-stage designs.

PubMed

Zhao, Junjun; Yu, Menggang; Feng, Xi-Ping

2015-06-07

Simon's two-stage designs are popular choices for conducting phase II clinical trials, especially in the oncology trials to reduce the number of patients placed on ineffective experimental therapies. Recently Koyama and Chen (2008) discussed how to conduct proper inference for such studies because they found that inference procedures used with Simon's designs almost always ignore the actual sampling plan used. In particular, they proposed an inference method for studies when the actual second stage sample sizes differ from planned ones. We consider an alternative inference method based on likelihood ratio. In particular, we order permissible sample paths under Simon's two-stage designs using their corresponding conditional likelihood. In this way, we can calculate p-values using the common definition: the probability of obtaining a test statistic value at least as extreme as that observed under the null hypothesis. In addition to providing inference for a couple of scenarios where Koyama and Chen's method can be difficult to apply, the resulting estimate based on our method appears to have certain advantage in terms of inference properties in many numerical simulations. It generally led to smaller biases and narrower confidence intervals while maintaining similar coverages. We also illustrated the two methods in a real data setting. Inference procedures used with Simon's designs almost always ignore the actual sampling plan. Reported P-values, point estimates and confidence intervals for the response rate are not usually adjusted for the design's adaptiveness. Proper statistical inference procedures should be used.

Sociodemographic characteristics of members of a large, integrated health care system: comparison with US Census Bureau data.

PubMed

Koebnick, Corinna; Langer-Gould, Annette M; Gould, Michael K; Chao, Chun R; Iyer, Rajan L; Smith, Ning; Chen, Wansu; Jacobsen, Steven J

2012-01-01

Data from the memberships of large, integrated health care systems can be valuable for clinical, epidemiologic, and health services research, but a potential selection bias may threaten the inference to the population of interest. We reviewed administrative records of members of Kaiser Permanente Southern California (KPSC) in 2000 and 2010, and we compared their sociodemographic characteristics with those of the underlying population in the coverage area on the basis of US Census Bureau data. We identified 3,328,579 KPSC members in 2000 and 3,357,959 KPSC members in 2010, representing approximately 16% of the population in the coverage area. The distribution of sex and age of KPSC members appeared to be similar to the census reference population in 2000 and 2010 except with a slightly higher proportion of 40 to 64 year olds. The proportion of Hispanics/Latinos was comparable between KPSC and the census reference population (37.5% vs 38.2%, respectively, in 2000 and 45.2% vs 43.3% in 2010). However, KPSC members included more blacks (14.9% vs 7.0% in 2000 and 10.8% vs 6.5% in 2010). Neighborhood educational levels and neighborhood household incomes were generally similar between KPSC members and the census reference population, but with a marginal underrepresentation of individuals with extremely low income and high education. The membership of KPSC reflects the socioeconomic diversity of the Southern California census population, suggesting that findings from this setting may provide valid inference for clinical, epidemiologic, and health services research.

Estimation of insurance premiums for coverage against natural disaster risk: an application of Bayesian Inference

NASA Astrophysics Data System (ADS)

Paudel, Y.; Botzen, W. J. W.; Aerts, J. C. J. H.

2013-03-01

This study applies Bayesian Inference to estimate flood risk for 53 dyke ring areas in the Netherlands, and focuses particularly on the data scarcity and extreme behaviour of catastrophe risk. The probability density curves of flood damage are estimated through Monte Carlo simulations. Based on these results, flood insurance premiums are estimated using two different practical methods that each account in different ways for an insurer's risk aversion and the dispersion rate of loss data. This study is of practical relevance because insurers have been considering the introduction of flood insurance in the Netherlands, which is currently not generally available.

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma

PubMed Central

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S.; Theis, Fabian J.

2015-01-01

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method “miRlastic”, which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic. PMID:26694379

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma.

PubMed

Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S; Theis, Fabian J

2015-12-18

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method "miRlastic", which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic.

Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue.

PubMed

Kislinger, Thomas; Gramolini, Anthony O; MacLennan, David H; Emili, Andrew

2005-08-01

An optimized analytical expression profiling strategy based on gel-free multidimensional protein identification technology (MudPIT) is reported for the systematic investigation of biochemical (mal)-adaptations associated with healthy and diseased heart tissue. Enhanced shotgun proteomic detection coverage and improved biological inference is achieved by pre-fractionation of excised mouse cardiac muscle into subcellular components, with each organellar fraction investigated exhaustively using multiple repeat MudPIT analyses. Functional-enrichment, high-confidence identification, and relative quantification of hundreds of organelle- and tissue-specific proteins are achieved readily, including detection of low abundance transcriptional regulators, signaling factors, and proteins linked to cardiac disease. Important technical issues relating to data validation, including minimization of artifacts stemming from biased under-sampling and spurious false discovery, together with suggestions for further fine-tuning of sample preparation, are discussed. A framework for follow-up bioinformatic examination, pattern recognition, and data mining is also presented in the context of a stringent application of MudPIT for probing fundamental aspects of heart muscle physiology as well as the discovery of perturbations associated with heart failure.

An evaluation of the suitability of ERTS data for the purposes of petroleum exploration

NASA Technical Reports Server (NTRS)

Collins, R. J., Jr. (Principal Investigator); Mccown, F. P.; Stonis, L. P.; Petzel, G.

1973-01-01

The author has identified the following significant results. ERTS-1 imagery seems to be good to excellent for reconnaissance level investigations of large sedimentary basins such as the Anadarko Basin. Many lithologic boundaries, and geomorphic features, and linear features inferred to be indicative of geologic structure are visible in the imagery. This imagery in conjunction with high altitude photography seems to be useful as a tool for intermediate level geologic exploration. Several types of crudely circular anomalous features, such as geomorphic/structural anomalies, hazy areas and tonal anomalies, are identifiable in the imagery. There seems to be a strong correlation between the geomorphic/structural and hazy anomalies and known structurally controlled oil and gas fields. The features recognizable on ERTS-1 imagery and their ease of recognition vary from area to area even in imagery acquired at the same time under essentially uniform atmospheric conditions. Repeated coverage is exceedingly valuable in geologic applications. One time complete coverage even for the various seasons does not reveal all the features that ERTS-1 can reveal.

Light Scattering by Lunar Exospheric Dust: What could be Learned from LRO LAMP and LADEE UVS?

NASA Astrophysics Data System (ADS)

Glenar, D. A.; Stubbs, T. J.; Richard, D. T.; Stern, S. A.; Retherford, K. D.; Gladstone, R.; Feldman, P. D.; Colaprete, A.; Delory, G. T.

2011-12-01

Two complementary spectrometers, namely the Lunar Reconnaissance Orbiter, Lyman Alpha Mapping Project (LAMP) and the planned Lunar Atmosphere and Dust Environment Explorer (LADEE) Ultraviolet Explorer (UVS) will carry out sensitive searches for high altitude exospheric dust, via detection of scattered sunlight. The combined spectral coverage of these instruments extends from far-UV to near-IR wavelengths. Over this wavelength range, grain size parameter (X=2πr/λ, with r the grain radius and λ the wavelength) changes dramatically, which makes broad wavelength coverage a good diagnostic of grain size. Utilizing different pointing geometries, both LAMP and UVS are able to observe dust over a range of scattering angles, as well as measure the dust vertical profile via limb measurements at multiple tangent heights. We summarize several categories of information that can be inferred from the data sets, using broadband simulations of horizon glow as observed at the limb. Grain scattering properties used in these simulations were computed for multiple grain shapes using Discrete-Dipole theory. Some cautionary remarks are included regarding the use of Mie theory to interpret scattering measurements.

Surface kinetics for catalytic combustion of hydrogen-air mixtures on platinum at atmospheric pressure in stagnation flows

NASA Astrophysics Data System (ADS)

Ikeda, H.; Sato, J.; Williams, F. A.

1995-03-01

Experimental studies of the combustion of premixed hydrogen-air mixtures impinging on the surface of a heated platinum plate at normal atmospheric pressure were performed and employed to draw inferences concerning surface reaction mechanisms and rate parameters applicable under practical conditions of catalytic combustion. Plate and gas temperatures were measured by thermocouples, and concentration profiles of major stable species in the gas were measured by gas-chromatographic analyses of samples withdrawn by quartz probes. In addition, ignition and extinction phenomena were recorded and interpreted with the aid of a heat balance at the surface and a previous flow-field analysis of the stagnation-point boundary layer. From the experimental and theoretical results, conclusions were drawn concerning the surface chemical-kinetic mechanisms and values of the elementary rate parameters that are consistent with the observations. In particular, the activation energy for the surface oxidation step H + OH → H 2O is found to be appreciably less at these high surface coverages than in the low-coverage limit.

Pragmatic Inferences in High-Functioning Adults with Autism and Asperger Syndrome

ERIC Educational Resources Information Center

Pijnacker, Judith; Hagoort, Peter; Buitelaar, Jan; Teunisse, Jan-Pieter; Geurts, Bart

2009-01-01

Although people with autism spectrum disorders (ASD) often have severe problems with pragmatic aspects of language, little is known about their pragmatic reasoning. We carried out a behavioral study on high-functioning adults with autistic disorder (n = 11) and Asperger syndrome (n = 17) and matched controls (n = 28) to investigate whether they…

FuncPatch: a web server for the fast Bayesian inference of conserved functional patches in protein 3D structures.

PubMed

Huang, Yi-Fei; Golding, G Brian

2015-02-15

A number of statistical phylogenetic methods have been developed to infer conserved functional sites or regions in proteins. Many methods, e.g. Rate4Site, apply the standard phylogenetic models to infer site-specific substitution rates and totally ignore the spatial correlation of substitution rates in protein tertiary structures, which may reduce their power to identify conserved functional patches in protein tertiary structures when the sequences used in the analysis are highly similar. The 3D sliding window method has been proposed to infer conserved functional patches in protein tertiary structures, but the window size, which reflects the strength of the spatial correlation, must be predefined and is not inferred from data. We recently developed GP4Rate to solve these problems under the Bayesian framework. Unfortunately, GP4Rate is computationally slow. Here, we present an intuitive web server, FuncPatch, to perform a fast approximate Bayesian inference of conserved functional patches in protein tertiary structures. Both simulations and four case studies based on empirical data suggest that FuncPatch is a good approximation to GP4Rate. However, FuncPatch is orders of magnitudes faster than GP4Rate. In addition, simulations suggest that FuncPatch is potentially a useful tool complementary to Rate4Site, but the 3D sliding window method is less powerful than FuncPatch and Rate4Site. The functional patches predicted by FuncPatch in the four case studies are supported by experimental evidence, which corroborates the usefulness of FuncPatch. The software FuncPatch is freely available at the web site, http://info.mcmaster.ca/yifei/FuncPatch golding@mcmaster.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Understanding advanced theory of mind and empathy in high-functioning adults with autism spectrum disorder.

PubMed

Mathersul, Danielle; McDonald, Skye; Rushby, Jacqueline A

2013-01-01

It has been argued that higher functioning individuals with autism spectrum disorders (ASDs) have specific deficits in advanced but not simple theory of mind (ToM), yet the questionable ecological validity of some tasks reduces the strength of this assumption. The present study employed The Awareness of Social Inference Test (TASIT), which uses video vignettes to assess comprehension of subtle conversational inferences (sarcasm, lies/deception). Given the proposed relationships between advanced ToM and cognitive and affective empathy, these associations were also investigated. As expected, the high-functioning adults with ASDs demonstrated specific deficits in comprehending the beliefs, intentions, and meaning of nonliteral expressions. They also had significantly lower cognitive and affective empathy. Cognitive empathy was related to ToM and group membership whereas affective empathy was only related to group membership.

The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes.

PubMed

Schwartenbeck, Philipp; FitzGerald, Thomas H B; Mathys, Christoph; Dolan, Ray; Friston, Karl

2015-10-01

Dopamine plays a key role in learning; however, its exact function in decision making and choice remains unclear. Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, dopamine discharges reflect the confidence that a chosen policy will lead to desired outcomes. We designed a novel task to test this hypothesis, where subjects played a "limited offer" game in a functional magnetic resonance imaging experiment. Subjects had to decide how long to wait for a high offer before accepting a low offer, with the risk of losing everything if they waited too long. Bayesian model comparison showed that behavior strongly supported active inference, based on surprise minimization, over classical utility maximization schemes. Furthermore, midbrain activity, encompassing dopamine projection neurons, was accurately predicted by trial-by-trial variations in model-based estimates of precision. Our findings demonstrate that human subjects infer both optimal policies and the precision of those inferences, and thus support the notion that humans perform hierarchical probabilistic Bayesian inference. In other words, subjects have to infer both what they should do as well as how confident they are in their choices, where confidence may be encoded by dopaminergic firing. © The Author 2014. Published by Oxford University Press.

The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes

PubMed Central

Schwartenbeck, Philipp; FitzGerald, Thomas H. B.; Mathys, Christoph; Dolan, Ray; Friston, Karl

2015-01-01

Dopamine plays a key role in learning; however, its exact function in decision making and choice remains unclear. Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, dopamine discharges reflect the confidence that a chosen policy will lead to desired outcomes. We designed a novel task to test this hypothesis, where subjects played a “limited offer” game in a functional magnetic resonance imaging experiment. Subjects had to decide how long to wait for a high offer before accepting a low offer, with the risk of losing everything if they waited too long. Bayesian model comparison showed that behavior strongly supported active inference, based on surprise minimization, over classical utility maximization schemes. Furthermore, midbrain activity, encompassing dopamine projection neurons, was accurately predicted by trial-by-trial variations in model-based estimates of precision. Our findings demonstrate that human subjects infer both optimal policies and the precision of those inferences, and thus support the notion that humans perform hierarchical probabilistic Bayesian inference. In other words, subjects have to infer both what they should do as well as how confident they are in their choices, where confidence may be encoded by dopaminergic firing. PMID:25056572

Detecting false positive sequence homology: a machine learning approach.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Bybee, Seth M

2016-02-24

Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging from building phylogenies to predicting functional gene annotations. There are many existing heuristic tools, most commonly based on bidirectional BLAST searches that are used to identify homologous genes and combine them into two fundamentally distinct classes: orthologs and paralogs. Due to only using heuristic filtering based on significance score cutoffs and having no cluster post-processing tools available, these methods can often produce multiple clusters constituting unrelated (non-homologous) sequences. Therefore sequencing data extracted from incomplete genome/transcriptome assemblies originated from low coverage sequencing or produced by de novo processes without a reference genome are susceptible to high false positive rates of homology detection. In this paper we develop biologically informative features that can be extracted from multiple sequence alignments of putative homologous genes (orthologs and paralogs) and further utilized in context of guided experimentation to verify false positive outcomes. We demonstrate that our machine learning method trained on both known homology clusters obtained from OrthoDB and randomly generated sequence alignments (non-homologs), successfully determines apparent false positives inferred by heuristic algorithms especially among proteomes recovered from low-coverage RNA-seq data. Almost ~42 % and ~25 % of predicted putative homologies by InParanoid and HaMStR respectively were classified as false positives on experimental data set. Our process increases the quality of output from other clustering algorithms by providing a novel post-processing method that is both fast and efficient at removing low quality clusters of putative homologous genes recovered by heuristic-based approaches.

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Iteratively Refined Guide Trees Help Improving Alignment and Phylogenetic Inference in the Mushroom Family Bolbitiaceae

PubMed Central

Tóth, Annamária; Hausknecht, Anton; Krisai-Greilhuber, Irmgard; Papp, Tamás; Vágvölgyi, Csaba; Nagy, László G.

2013-01-01

Reconciling traditional classifications, morphology, and the phylogenetic relationships of brown-spored agaric mushrooms has proven difficult in many groups, due to extensive convergence in morphological features. Here, we address the monophyly of the Bolbitiaceae, a family with over 700 described species and examine the higher-level relationships within the family using a newly constructed multilocus dataset (ITS, nrLSU rDNA and EF1-alpha). We tested whether the fast-evolving Internal Transcribed Spacer (ITS) sequences can be accurately aligned across the family, by comparing the outcome of two iterative alignment refining approaches (an automated and a manual) and various indel-treatment strategies. We used PRANK to align sequences in both cases. Our results suggest that – although PRANK successfully evades overmatching of gapped sites, referred previously to as alignment overmatching – it infers an unrealistically high number of indel events with natively generated guide-trees. This 'alignment undermatching' could be avoided by using more rigorous (e.g. ML) guide trees. The trees inferred in this study support the monophyly of the core Bolbitiaceae, with the exclusion of Panaeolus, Agrocybe, and some of the genera formerly placed in the family. Bolbitius and Conocybe were found monophyletic, however, Pholiotina and Galerella require redefinition. The phylogeny revealed that stipe coverage type is a poor predictor of phylogenetic relationships, indicating the need for a revision of the intrageneric relationships within Conocybe. PMID:23418526

Global analysis of population stratification using a smart panel of 27 continental ancestry-informative SNPs.

PubMed

Jiang, Li; Wei, Yi-Liang; Zhao, Lei; Li, Na; Liu, Tao; Liu, Hai-Bo; Ren, Li-Jie; Li, Jiu-Ling; Hao, Hui-Fang; Li, Qing; Li, Cai-Xia

2018-07-01

Over the last decade, several panels of ancestry-informative markers have been proposed for the analysis of population genetic structure. The differentiation efficiency depends on the discriminatory ability of the included markers and the reference population coverage. We previously developed a small set of 27 autosomal single nucleotide polymorphisms (SNPs) for analyzing African, European, and East Asian ancestries. In the current study, we gathered a high-coverage reference database of 110 populations (10,350 individuals) from across the globe. The discrimination power of the panel was re-evaluated using four continental ancestry groups (as well as Indigenous Americans). We observed that all the 27 SNPs demonstrated stratified population specificity leading to a striking ancestral discrimination. Five markers (rs728404, rs7170869, rs2470102, rs1448485, and rs4789193) showed differences (δ > 0.3) in the frequency profiles between East Asian and Indigenous American populations. Ancestry components of all involved populations were accurately accessed compared with those from previous genome-wide analyses, thereafter achieved broadly population separation. Thus, our ancestral inference panel of a small number of highly informative SNPs in combination with a large-scale reference database provides a high-resolution in estimating ancestry compositions and distinguishing individual origins. We propose extensive usage in biomedical studies and forensics. Copyright © 2018 Elsevier B.V. All rights reserved.

flyDIVaS: A Comparative Genomics Resource for Drosophila Divergence and Selection

PubMed Central

Stanley, Craig E.; Kulathinal, Rob J.

2016-01-01

With arguably the best finished and expertly annotated genome assembly, Drosophila melanogaster is a formidable genetics model to study all aspects of biology. Nearly a decade ago, the 12 Drosophila genomes project expanded D. melanogaster’s breadth as a comparative model through the community-development of an unprecedented genus- and genome-wide comparative resource. However, since its inception, these datasets for evolutionary inference and biological discovery have become increasingly outdated, outmoded, and inaccessible. Here, we provide an updated and upgradable comparative genomics resource of Drosophila divergence and selection, flyDIVaS, based on the latest genomic assemblies, curated FlyBase annotations, and recent OrthoDB orthology calls. flyDIVaS is an online database containing D. melanogaster-centric orthologous gene sets, CDS and protein alignments, divergence statistics (% gaps, dN, dS, dN/dS), and codon-based tests of positive Darwinian selection. Out of 13,920 protein-coding D. melanogaster genes, ∼80% have one aligned ortholog in the closely related species, D. simulans, and ∼50% have 1–1 12-way alignments in the original 12 sequenced species that span over 80 million yr of divergence. Genes and their orthologs can be chosen from four different taxonomic datasets differing in phylogenetic depth and coverage density, and visualized via interactive alignments and phylogenetic trees. Users can also batch download entire comparative datasets. A functional survey finds conserved mitotic and neural genes, highly diverged immune and reproduction-related genes, more conspicuous signals of divergence across tissue-specific genes, and an enrichment of positive selection among highly diverged genes. flyDIVaS will be regularly updated and can be freely accessed at www.flydivas.info. We encourage researchers to regularly use this resource as a tool for biological inference and discovery, and in their classrooms to help train the next generation of biologists to creatively use such genomic big data resources in an integrative manner. PMID:27226167

flyDIVaS: A Comparative Genomics Resource for Drosophila Divergence and Selection.

PubMed

Stanley, Craig E; Kulathinal, Rob J

2016-08-09

With arguably the best finished and expertly annotated genome assembly, Drosophila melanogaster is a formidable genetics model to study all aspects of biology. Nearly a decade ago, the 12 Drosophila genomes project expanded D. melanogaster's breadth as a comparative model through the community-development of an unprecedented genus- and genome-wide comparative resource. However, since its inception, these datasets for evolutionary inference and biological discovery have become increasingly outdated, outmoded, and inaccessible. Here, we provide an updated and upgradable comparative genomics resource of Drosophila divergence and selection, flyDIVaS, based on the latest genomic assemblies, curated FlyBase annotations, and recent OrthoDB orthology calls. flyDIVaS is an online database containing D. melanogaster-centric orthologous gene sets, CDS and protein alignments, divergence statistics (% gaps, dN, dS, dN/dS), and codon-based tests of positive Darwinian selection. Out of 13,920 protein-coding D. melanogaster genes, ∼80% have one aligned ortholog in the closely related species, D. simulans, and ∼50% have 1-1 12-way alignments in the original 12 sequenced species that span over 80 million yr of divergence. Genes and their orthologs can be chosen from four different taxonomic datasets differing in phylogenetic depth and coverage density, and visualized via interactive alignments and phylogenetic trees. Users can also batch download entire comparative datasets. A functional survey finds conserved mitotic and neural genes, highly diverged immune and reproduction-related genes, more conspicuous signals of divergence across tissue-specific genes, and an enrichment of positive selection among highly diverged genes. flyDIVaS will be regularly updated and can be freely accessed at www.flydivas.info We encourage researchers to regularly use this resource as a tool for biological inference and discovery, and in their classrooms to help train the next generation of biologists to creatively use such genomic big data resources in an integrative manner. Copyright © 2016 Stanley and Kulathinal.

78 FR 39493 - Patient Protection and Affordable Care Act; Exchange Functions: Eligibility for Exemptions...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-01

...This final rule implements certain functions of the Affordable Insurance Exchanges (``Exchanges''). These specific statutory functions include determining eligibility for and granting certificates of exemption from the individual shared responsibility payment described in section 5000A of the Internal Revenue Code. Additionally, this final rule implements the responsibilities of the Secretary of Health and Human Services, in coordination with the Secretary of the Treasury, to designate other health benefits coverage as minimum essential coverage by providing that certain coverage be designated as minimum essential coverage. It also outlines substantive and procedural requirements that other types of individual coverage must fulfill in order to be certified as minimum essential coverage.

Estimating the Area Under ROC Curve When the Fitted Binormal Curves Demonstrate Improper Shape.

PubMed

Bandos, Andriy I; Guo, Ben; Gur, David

2017-02-01

The "binormal" model is the most frequently used tool for parametric receiver operating characteristic (ROC) analysis. The binormal ROC curves can have "improper" (non-concave) shapes that are unrealistic in many practical applications, and several tools (eg, PROPROC) have been developed to address this problem. However, due to the general robustness of binormal ROCs, the improperness of the fitted curves might carry little consequence for inferences about global summary indices, such as the area under the ROC curve (AUC). In this work, we investigate the effect of severe improperness of fitted binormal ROC curves on the reliability of AUC estimates when the data arise from an actually proper curve. We designed theoretically proper ROC scenarios that induce severely improper shape of fitted binormal curves in the presence of well-distributed empirical ROC points. The binormal curves were fitted using maximum likelihood approach. Using simulations, we estimated the frequency of severely improper fitted curves, bias of the estimated AUC, and coverage of 95% confidence intervals (CIs). In Appendix S1, we provide additional information on percentiles of the distribution of AUC estimates and bias when estimating partial AUCs. We also compared the results to a reference standard provided by empirical estimates obtained from continuous data. We observed up to 96% of severely improper curves depending on the scenario in question. The bias in the binormal AUC estimates was very small and the coverage of the CIs was close to nominal, whereas the estimates of partial AUC were biased upward in the high specificity range and downward in the low specificity range. Compared to a non-parametric approach, the binormal model led to slightly more variable AUC estimates, but at the same time to CIs with more appropriate coverage. The improper shape of the fitted binormal curve, by itself, ie, in the presence of a sufficient number of well-distributed points, does not imply unreliable AUC-based inferences. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

SICK: THE SPECTROSCOPIC INFERENCE CRANK

DOE Office of Scientific and Technical Information (OSTI.GOV)

Casey, Andrew R., E-mail: arc@ast.cam.ac.uk

2016-03-15

There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of itsmore » source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal-to-noise ratio spectra of M67 stars reveals atomic diffusion processes on the order of 0.05 dex, previously only measurable with differential analysis techniques in high-resolution spectra. sick is easy to use, well-tested, and freely available online through GitHub under the MIT license.« less

Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology

NASA Astrophysics Data System (ADS)

Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen

2018-07-01

Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper, we use massive asymptotically optimal data compression to reduce the dimensionality of the data space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parametrized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate DELFI with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological data sets.

Assessing Advanced Theory of Mind in Children and Adolescents with High-Functioning Autism: The Spanish Version of the "Stories of Everyday Life"

ERIC Educational Resources Information Center

Lera-Miguel, Sara; Rosa, Mireia; Puig, Olga; Kaland, Nils; Lázaro, Luisa; Castro-Formieles, Josefina; Calvo, Rosa

2016-01-01

Most individuals with autism spectrum disorders often fail in tasks of theory of mind (ToM). However, those with normal intellectual functioning known as high functioning ASD (HF-ASD) sometimes succeed in mentalizing inferences. Some tools have been developed to more accurately test their ToM abilities. The aims of this study were to examine the…

The coverage of a random sample from a biological community.

PubMed

Engen, S

1975-03-01

A taxonomic group will frequently have a large number of species with small abundances. When a sample is drawn at random from this group, one is therefore faced with the problem that a large proportion of the species will not be discovered. A general definition of quantitative measures of "sample coverage" is proposed, and the problem of statistical inference is considered for two special cases, (1) the actual total relative abundance of those species that are represented in the sample, and (2) their relative contribution to the information index of diversity. The analysis is based on a extended version of the negative binomial species frequency model. The results are tabulated.

Optimal Dosing and Dynamic Distribution of Vaccines in an Influenza Pandemic

PubMed Central

McCaw, James; Becker, Niels; Nolan, Terry; MacIntyre, C. Raina

2009-01-01

Limited production capacity and delays inherent in vaccine development are major hurdles to the widespread use of vaccines to mitigate the effects of a new influenza pandemic. Antigen-sparing vaccines have the most potential to increase population coverage but may be less efficacious. The authors explored this trade-off by applying simple models of influenza transmission and dose response to recent clinical trial data. In this paper, these data are used to illustrate an approach to comparing vaccines on the basis of antigen supply and inferred efficacy. The effects of delays in matched vaccine availability and seroconversion on epidemic size during pandemic phase 6 were also studied. The authors infer from trial data that population benefits stem from the use of low-antigen vaccines. Delayed availability of a matched vaccine could be partially alleviated by using a 1-dose vaccination program with increased coverage and reduced time to full protection. Although less immunogenic, an overall attack rate of up to 6% lower than a 2-dose program could be achieved. However, if prevalence at vaccination is above 1%, effectiveness is much reduced, emphasizing the need for other control measures. PMID:19395691

Rough surfaces: Is the dark stuff just shadow?. ;Who knows what evil lurks in the hearts of men? The shadow knows!;☆

NASA Astrophysics Data System (ADS)

Cuzzi, Jeffrey N.; Chambers, Lindsey B.; Hendrix, Amanda R.

2017-06-01

Remote observations of the surfaces of airless planetary objects are fundamental to inferring the physical structure and compositional makeup of the surface material. A number of forward models have been developed to reproduce the photometric behavior of these surfaces, based on specific, assumed structural properties such as macroscopic roughness and associated shadowing. Most work of this type is applied to geometric albedos, which are affected by complicated effects near zero phase angle that represent only a tiny fraction of the net energy reflected by the object. Other applications include parameter fits to resolved portions of some planetary surface as viewed over a range of geometries. The spherical albedo of the entire object (when it can be determined) captures the net energy balance of the particle more robustly than the geometric albedo. In most treatments involving spherical albedos, spherical albedos and particle phase functions are often treated as if they are independent, neglecting the effects of roughness. In this paper we take a different approach. We note that whatever function captures the phase angle dependence of the brightness of a realistic rough, shadowed, flat surface element relative to that of a smooth granular surface of the same material, it is manifested directly in both the integral phase function and the spherical albedo of the object. We suggest that, where broad phase angle coverage is possible, spherical albedos may be easily corrected for the effects of shadowing using observed (or assumed) phase functions, and then modeled more robustly using smooth-surface regolith radiative transfer models without further imposed (forward-modeled) shadowing corrections. Our approach attributes observed "powerlaw" phase functions of various slope (and "linear" ranges of magnitude-vs.-phase angle) to shadowing, as have others, and goes in to suggest that regolith-model-based inferences of composition based on shadow-uncorrected spherical albedos overestimate the amount of absorbing material contained in the regolith.

Rough Surfaces: Is the Dark Stuff Just Shadow?: "Who knows what evil lurks in the hearts of men? The shadow knows!"

NASA Technical Reports Server (NTRS)

Cuzzi, Jeffrey N.; Chambers, Lindsey B.; Hendrix, Amanda R.

2016-01-01

Remote observations of the surfaces of airless planetary objects are fundamental to inferring the physical structure and compositional makeup of the surface material. A number of forward models have been developed to reproduce the photometric behavior of these surfaces, based on specific, assumed structural properties such as macroscopic roughness and associated shadowing. Most work of this type is applied to geometric albedos, which are affected by complicated effects near zero phase angle that represent only a tiny fraction of the net energy reflected by the object. Other applications include parameter fits to resolved portions of some planetary surface as viewed over a range of geometries. The spherical albedo of the entire object (when it can be determined) captures the net energy balance of the particle more robustly than the geometric albedo. In most treatments involving spherical albedos, spherical albedos and particle phase functions are often treated as if they are independent, neglecting the effects of roughness. In this paper we take a different approach. We note that whatever function captures the phase angle dependence of the brightness of a realistic rough, shadowed, flat surface element relative to that of a smooth granular surface of the same material, it is manifested directly in both the integral phase function and the spherical albedo of the object. We suggest that, where broad phase angle coverage is possible, spherical albedos may be easily corrected for the effects of shadowing using observed (or assumed) phase functions, and then modeled more robustly using smooth-surface regolith radiative transfer models without further imposed (forward-modeled) shadowing corrections. Our approach attributes observed "power law" phase functions of various slope (and "linear" ranges of magnitude-vs.-phase angle) to shadowing, as have others, and goes on to suggest that regolith-model-based inferences of composition based on shadow-uncorrected spherical albedos overestimate the amount of absorbing material contained in the regolith.

The large impact process inferred from the geology of lunar multiring basins

NASA Technical Reports Server (NTRS)

Spudis, Paul D.

1992-01-01

The nature of the impact process has been inferred through the study of the geology of a wide variety of impact crater types and sizes. Some of the largest craters known are the multiring basins found in ancient terrains of the terrestrial planets. Of these features, those found on the Moon possess the most extensive and diverse data coverage, including morphological, geochemical, geophysical, and sample data. The study of the geology of lunar basins over the past 10 years has given us a rudimentary understanding of how these large structures have formed and evolved. The topics covered include basin morphology, basin ejecta, basin excavation, and basin ring formation.

Theoretical studies of positron states and annihilation characteristics at the oxidized Cu(100) surface

NASA Astrophysics Data System (ADS)

Fazleev, N. G.; Weiss, A. H.

2013-04-01

In this work we present the results of theoretical studies of positron surface and bulk states and annihilation probabilities of surface-trapped positrons with relevant core electrons at the oxidized Cu(100) surface under conditions of high oxygen coverage. An ab-initio study of the electronic properties of the Cu(100) missing row reconstructed surface at various on surface and sub-surface oxygen coverages has been performed on the basis of the density functional theory (DFT) using the Dmol3 code and the generalized gradient approximation (GGA). Surface structures in calculations have been constructed by adding oxygen atoms to various surface hollow and sub-surface octahedral sites of the 0.5 monolayer (ML) missing row reconstructed phase of the Cu(100) surface with oxygen coverages ranging from 0.5 to 1.5 ML. The charge redistribution at the surface and variations in atomic structure and chemical composition of the topmost layers associated with oxidation and surface reconstruction have been found to affect the spatial extent and localization of the positron surface state wave function and annihilation probabilities of surface trapped positrons with relevant core electrons. Theoretical results are compared with experimental data obtained from studies of oxidation of the Cu(100) surface using positron annihilation induced Auger electron spectroscopy (PAES). It has been shown that positron annihilation probabilities with Cu 3s and 3p core electrons decrease when total (on-surface and sub-surface) oxygen coverage of the Cu(100) surface increases up to 1 ML. The calculations show that for high oxygen coverage when total oxygen coverage is 1. 5 ML the positron is not bound to the surface.

Theoretical studies of positron states and annihilation characteristics at the oxidized Cu(100) surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fazleev, N. G.; Weiss, A. H.

2013-04-19

In this work we present the results of theoretical studies of positron surface and bulk states and annihilation probabilities of surface-trapped positrons with relevant core electrons at the oxidized Cu(100) surface under conditions of high oxygen coverage. An ab-initio study of the electronic properties of the Cu(100) missing row reconstructed surface at various on surface and sub-surface oxygen coverages has been performed on the basis of the density functional theory (DFT) using the Dmol3 code and the generalized gradient approximation (GGA). Surface structures in calculations have been constructed by adding oxygen atoms to various surface hollow and sub-surface octahedral sitesmore » of the 0.5 monolayer (ML) missing row reconstructed phase of the Cu(100) surface with oxygen coverages ranging from 0.5 to 1.5 ML. The charge redistribution at the surface and variations in atomic structure and chemical composition of the topmost layers associated with oxidation and surface reconstruction have been found to affect the spatial extent and localization of the positron surface state wave function and annihilation probabilities of surface trapped positrons with relevant core electrons. Theoretical results are compared with experimental data obtained from studies of oxidation of the Cu(100) surface using positron annihilation induced Auger electron spectroscopy (PAES). It has been shown that positron annihilation probabilities with Cu 3s and 3p core electrons decrease when total (on-surface and sub-surface) oxygen coverage of the Cu(100) surface increases up to 1 ML. The calculations show that for high oxygen coverage when total oxygen coverage is 1. 5 ML the positron is not bound to the surface.« less

On the Inference of Functional Circadian Networks Using Granger Causality

PubMed Central

Pourzanjani, Arya; Herzog, Erik D.; Petzold, Linda R.

2015-01-01

Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals. PMID:26413748

Extensive gene tree discordance and hemiplasy shaped the genomes of North American columnar cacti.

PubMed

Copetti, Dario; Búrquez, Alberto; Bustamante, Enriquena; Charboneau, Joseph L M; Childs, Kevin L; Eguiarte, Luis E; Lee, Seunghee; Liu, Tiffany L; McMahon, Michelle M; Whiteman, Noah K; Wing, Rod A; Wojciechowski, Martin F; Sanderson, Michael J

2017-11-07

Few clades of plants have proven as difficult to classify as cacti. One explanation may be an unusually high level of convergent and parallel evolution (homoplasy). To evaluate support for this phylogenetic hypothesis at the molecular level, we sequenced the genomes of four cacti in the especially problematic tribe Pachycereeae, which contains most of the large columnar cacti of Mexico and adjacent areas, including the iconic saguaro cactus ( Carnegiea gigantea ) of the Sonoran Desert. We assembled a high-coverage draft genome for saguaro and lower coverage genomes for three other genera of tribe Pachycereeae ( Pachycereus , Lophocereus , and Stenocereus ) and a more distant outgroup cactus, Pereskia We used these to construct 4,436 orthologous gene alignments. Species tree inference consistently returned the same phylogeny, but gene tree discordance was high: 37% of gene trees having at least 90% bootstrap support conflicted with the species tree. Evidently, discordance is a product of long generation times and moderately large effective population sizes, leading to extensive incomplete lineage sorting (ILS). In the best supported gene trees, 58% of apparent homoplasy at amino sites in the species tree is due to gene tree-species tree discordance rather than parallel substitutions in the gene trees themselves, a phenomenon termed "hemiplasy." The high rate of genomic hemiplasy may contribute to apparent parallelisms in phenotypic traits, which could confound understanding of species relationships and character evolution in cacti. Published under the PNAS license.

Extensive gene tree discordance and hemiplasy shaped the genomes of North American columnar cacti

PubMed Central

Búrquez, Alberto; Bustamante, Enriquena; Charboneau, Joseph L. M.; Childs, Kevin L.; Eguiarte, Luis E.; Lee, Seunghee; Liu, Tiffany L.; McMahon, Michelle M.; Whiteman, Noah K.; Wing, Rod A.; Wojciechowski, Martin F.; Sanderson, Michael J.

2017-01-01

Few clades of plants have proven as difficult to classify as cacti. One explanation may be an unusually high level of convergent and parallel evolution (homoplasy). To evaluate support for this phylogenetic hypothesis at the molecular level, we sequenced the genomes of four cacti in the especially problematic tribe Pachycereeae, which contains most of the large columnar cacti of Mexico and adjacent areas, including the iconic saguaro cactus (Carnegiea gigantea) of the Sonoran Desert. We assembled a high-coverage draft genome for saguaro and lower coverage genomes for three other genera of tribe Pachycereeae (Pachycereus, Lophocereus, and Stenocereus) and a more distant outgroup cactus, Pereskia. We used these to construct 4,436 orthologous gene alignments. Species tree inference consistently returned the same phylogeny, but gene tree discordance was high: 37% of gene trees having at least 90% bootstrap support conflicted with the species tree. Evidently, discordance is a product of long generation times and moderately large effective population sizes, leading to extensive incomplete lineage sorting (ILS). In the best supported gene trees, 58% of apparent homoplasy at amino sites in the species tree is due to gene tree-species tree discordance rather than parallel substitutions in the gene trees themselves, a phenomenon termed “hemiplasy.” The high rate of genomic hemiplasy may contribute to apparent parallelisms in phenotypic traits, which could confound understanding of species relationships and character evolution in cacti. PMID:29078296

Seismic receiver function interpretation: Ps splitting or anisotropic underplating?

NASA Astrophysics Data System (ADS)

Liu, Z.; Park, J. J.

2016-12-01

Crustal anisotropy is crucial to understanding the evolutionary history of Earth's lithosphere. Shear-wave splitting of Moho P-to-s converted phases in receiver functions has often been used to infer crustal anisotropy. In addition to estimating birefringence directly, the harmonic variations of Moho Ps phases in delay times can be used to infer splitting parameters of averaged anisotropy in the crust. However, crustal anisotropy may localize at various levels within the crust due to complex deformational processes. Layered anisotropy requires careful investigation of the distribution of anisotropy before interpreting Moho Ps splitting. In this study, we show results from stations ARU in Russia, KIP in Hawaiian Islands and LSA in Tibetan Plateau, where layered anisotropy is well constrained by intra-crust Ps conversions at high frequencies using harmonic decomposition of multiple-taper correlation receiver functions. Anisotropic velocity models are inferred by forward-modeling decomposed RF waveforms. Our results of ARU and KIP show that the harmonic behavior of Moho Ps phases can be explained by a uniformly anisotropic crust model at lower cut-off frequencies, but higher-resolution RF-signals reveal a thin, highly anisotropic layer at the base of the crust. Station LSA tells a similar story with a twist: a modest Ps birefringence is revealed at high frequencies to stem from multiple thin (5-10-km) layers of localized anisotropy within the middle crust, but no strongly-sheared basal layer is inferred. We suggest that the harmonic variation of Moho Ps phases should always be investigated as a result of anisotropic layering using RFs with frequency content above 1Hz, rather than simply reporting averaged anisotropy of the whole crust.

Estimating diversifying selection and functional constraint in the presence of recombination.

PubMed

Wilson, Daniel J; McVean, Gilean

2006-03-01

Models of molecular evolution that incorporate the ratio of nonsynonymous to synonymous polymorphism (dN/dS ratio) as a parameter can be used to identify sites that are under diversifying selection or functional constraint in a sample of gene sequences. However, when there has been recombination in the evolutionary history of the sequences, reconstructing a single phylogenetic tree is not appropriate, and inference based on a single tree can give misleading results. In the presence of high levels of recombination, the identification of sites experiencing diversifying selection can suffer from a false-positive rate as high as 90%. We present a model that uses a population genetics approximation to the coalescent with recombination and use reversible-jump MCMC to perform Bayesian inference on both the dN/dS ratio and the recombination rate, allowing each to vary along the sequence. We demonstrate that the method has the power to detect variation in the dN/dS ratio and the recombination rate and does not suffer from a high false-positive rate. We use the method to analyze the porB gene of Neisseria meningitidis and verify the inferences using prior sensitivity analysis and model criticism techniques.

Estimating Diversifying Selection and Functional Constraint in the Presence of Recombination

PubMed Central

Wilson, Daniel J.; McVean, Gilean

2006-01-01

Models of molecular evolution that incorporate the ratio of nonsynonymous to synonymous polymorphism (dN/dS ratio) as a parameter can be used to identify sites that are under diversifying selection or functional constraint in a sample of gene sequences. However, when there has been recombination in the evolutionary history of the sequences, reconstructing a single phylogenetic tree is not appropriate, and inference based on a single tree can give misleading results. In the presence of high levels of recombination, the identification of sites experiencing diversifying selection can suffer from a false-positive rate as high as 90%. We present a model that uses a population genetics approximation to the coalescent with recombination and use reversible-jump MCMC to perform Bayesian inference on both the dN/dS ratio and the recombination rate, allowing each to vary along the sequence. We demonstrate that the method has the power to detect variation in the dN/dS ratio and the recombination rate and does not suffer from a high false-positive rate. We use the method to analyze the porB gene of Neisseria meningitidis and verify the inferences using prior sensitivity analysis and model criticism techniques. PMID:16387887

Factors associated with routine immunization coverage of children under one year old in Lao People's Democratic Republic.

PubMed

Phoummalaysith, Bounfeng; Yamamoto, Eiko; Xeuatvongsa, Anonh; Louangpradith, Viengsakhone; Keohavong, Bounxou; Saw, Yu Mon; Hamajima, Nobuyuki

2018-05-03

Routine vaccination is administered free of charge to all children under one year old in Lao People's Democratic Republic (Lao PDR) and the national goal is to achieve at least 95% coverage with all vaccines included in the national immunization program by 2025. In this study, factors related to the immunization system and characteristics of provinces and districts in Lao PDR were examined to evaluate the association with routine immunization coverage. Coverage rates for Bacillus Calmette-Guerin (BCG), Diphtheria-Tetanus-Pertussis-Hepatitis B (DTP-HepB), DTP-HepB-Hib (Haemophilus influenzae type B), polio (OPV), and measles (MCV1) vaccines from 2002 to 2014 collected through regular reporting system, were used to identify the immunization coverage trends in Lao PDR. Correlation analysis was performed using immunization coverage, characteristics of provinces or districts (population, population density, and proportion of poor villages and high-risk villages), and factors related to immunization service (including the proportions of the following: villages served by health facility levels, vaccine session types, and presence of well-functioning cold chain equipment). To determine factors associated with low coverage, provinces were categorized based on 80% of DTP-HepB-Hib3 coverage (<80% = low group; ≥80% = high group). Coverages of BCG, DTP-HepB3, OPV3 and MCV1 increased gradually from 2007 to 2014 (82.2-88.3% in 2014). However, BCG coverage showed the least improvement from 2002 to 2014. The coverage of each vaccine correlated with the coverage of the other vaccines and DTP-HepB-Hib dropout rate in provinces as well as districts. The provinces with low immunization coverage were correlated with higher proportions of poor villages. Routine immunization coverage has been improving in the last 13 years, but the national goal is not yet reached in Lao PDR. The results of this study suggest that BCG coverage and poor villages should be targeted to improve nationwide coverage. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of cloud top height and cloud coverage from satellites using the O2 A and B bands

NASA Technical Reports Server (NTRS)

Kuze, Akihiko; Chance, Kelly V.

1994-01-01

Cloud height and cloud coverage detection are important for total ozone retrieval using ultraviolet and visible scattered light. Use of the O2 A and B bands, around 761 and 687 nm, by a satellite-borne instrument of moderately high spectral resolution viewing in the nadir makes it possible to detect cloud top height and related parameters, including fractional coverage. The measured values of a satellite-borne spectrometer are convolutions of the instrument slit function and the atmospheric transmittance between cloud top and satellite. Studies here determine the optical depth between a satellite orbit and the Earth or cloud top height to high accuracy using FASCODE 3. Cloud top height and a cloud coverage parameter are determined by least squares fitting to calculated radiance ratios in the oxygen bands. A grid search method is used to search the parameter space of cloud top height and the coverage parameter to minimize an appropriate sum of squares of deviations. For this search, nonlinearity of the atmospheric transmittance (i.e., leverage based on varying amounts of saturation in the absorption spectrum) is important for distinguishing between cloud top height and fractional coverage. Using the above-mentioned method, an operational cloud detection algorithm which uses minimal computation time can be implemented.

Efficient Exact Inference With Loss Augmented Objective in Structured Learning.

PubMed

Bauer, Alexander; Nakajima, Shinichi; Muller, Klaus-Robert

2016-08-19

Structural support vector machine (SVM) is an elegant approach for building complex and accurate models with structured outputs. However, its applicability relies on the availability of efficient inference algorithms--the state-of-the-art training algorithms repeatedly perform inference to compute a subgradient or to find the most violating configuration. In this paper, we propose an exact inference algorithm for maximizing nondecomposable objectives due to special type of a high-order potential having a decomposable internal structure. As an important application, our method covers the loss augmented inference, which enables the slack and margin scaling formulations of structural SVM with a variety of dissimilarity measures, e.g., Hamming loss, precision and recall, Fβ-loss, intersection over union, and many other functions that can be efficiently computed from the contingency table. We demonstrate the advantages of our approach in natural language parsing and sequence segmentation applications.

Inferring Toxicological Responses of HepG2 Cells from ...

EPA Pesticide Factsheets

Understanding the dynamic perturbation of cell states by chemicals can aid in for predicting their adverse effects. High-content imaging (HCI) was used to measure the state of HepG2 cells over three time points (1, 24, and 72 h) in response to 976 ToxCast chemicals for 10 different concentrations (0.39-200µM). Cell state was characterized by p53 activation (p53), c-Jun activation (SK), phospho-Histone H2A.x (OS), phospho-Histone H3 (MA), alpha tubulin (Mt), mitochondrial membrane potential (MMP), mitochondrial mass (MM), cell cycle arrest (CCA), nuclear size (NS) and cell number (CN). Dynamic cell state perturbations due to each chemical concentration were utilized to infer coarse-grained dependencies between cellular functions as Boolean networks (BNs). BNs were inferred from data in two steps. First, the data for each state variable were discretized into changed/active (> 1 standard deviation), and unchanged/inactive values. Second, the discretized data were used to learn Boolean relationships between variables. In our case, a BN is a wiring diagram between nodes that represent 10 previously described observable phenotypes. Functional relationships between nodes were represented as Boolean functions. We found that inferred BN show that HepG2 cell response is chemical and concentration specific. We observed presence of both point and cycle BN attractors. In addition, there are instances where Boolean functions were not found. We believe that this may be either

Learning Time-Varying Coverage Functions

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

Learning Time-Varying Coverage Functions.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-12-08

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data.

The subglacial roughness of Antarctica: Analogs, interpretation and implications for ice thickness uncertainities

NASA Astrophysics Data System (ADS)

Young, D. A.; Grima, C.; Greenbaum, J. S.; Beem, L.; Cavitte, M. G.; Quartini, E.; Kempf, S. D.; Roberts, J. L.; Siegert, M. J.; Ritz, C.; Blankenship, D. D.

2017-12-01

Over the last twenty five years, extensive ice penetrating radar (IPR) coverage of Antarctica has been obtained, at lines spacings down to 1 km in some cases. However, many glacial processes occur at finer scales, so infering likely landscape parameters is required for a useful interpolation between lines. Profile roughness is also important for understanding the uncertainties inherent in IPR observations. Subglacial roughness has also been used to infer large scale bed rock properties and history. Similar work has been conducted on a regional basis with complilations of data from the 1970's and more recent local studies. Here we present a compilation of IPR-derived profile roughness data covering three great basins of Antarctica: the Byrd Subglacial Basin in West Antarctica, and the Wilkes Subglacial Basin and Aurora Subglacial Basins in East Antarctica; and treat these data using root mean squared deviation (RMSD). Coverage is provied by a range of IPR systems with varying vintages with differing instrument and processing parameters; we present approaches to account for the differences between these systems. We use RMSD, a tool commonly used in planetary investigations, to investigate the self-affine behaviour of the bed at kilometer scales and extract fractal parameters from the data to predict roughness and uncertainties in ice thickness measurement. Lastly, we apply a sensor model to a range of bare-earth terrestrial digital elevation models to futher understand the impact of the sensor model on the inference of subglacial topography and roughness, and to the first order analogies for the lithology of the substrate. This map of roughness, at scales between the pulse limited radar footprint and typical line spacings, provides an understanding of the distribution of Paleogene subglacial sediments, insight in to the distribution of uncertainties and a potential basal properties mask for ice sheet models. A particular goal of this map is to provide insight into required IPR coverage needs for site selection for old ice and subglacial samples for subglacial access systems like US-RAID and SUBGLACIOR.

Caititu: a tool to graphically represent peptide sequence coverage and domain distribution.

PubMed

Carvalho, Paulo C; Junqueira, Magno; Valente, Richard H; Domont, Gilberto B

2008-10-07

Here we present Caititu, an easy-to-use proteomics software to graphically represent peptide sequence coverage and domain distribution for different correlated samples (e.g. originated from 2D gel spots) relatively to the full-sequence of the known protein they are related to. Although Caititu has a broad applicability, we exemplify its usefulness in Toxinology using snake venom as a model. For example, proteolytic processing may lead to inactivation or loss of domains. Therefore, our proposed graphic representation for peptides identified by two dimensional electrophoresis followed by mass spectrometric identification of excised spots can aid in inferring what kind of processing happened to the toxins, if any. Caititu is freely available to download at: http://pcarvalho.com/things/caititu.

Proton dynamics and surface heterogeneity of silica gel with adsorbed benzene below one monolayer coverage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, E.M.; O'Reilly, D.E.; Tsangb), T.

1979-04-01

Proton and deuteron NMR relaxation times of C/sub 6/H/sub 6/, C/sub 6/D/sub 6/, and mixtures of these molecules have been measured on a superpure silica gel (SPSG) and a sample of a Matheson silica gel (MSG) both dehydrated at 600/sup 0/ C and rotational (intramolecular) and translational (intermolecular) correlation times have been computed from the relaxation time data at a statistical coverage theta=0.6. Three kinds of adsorption sites have been observed: (1) A sites, which are probably oxygen vacancies on the surface, (2) B sites which are assigned to paired hydroxyl groups on the surface, and finally (3) C sitesmore » which comprise 80% of the occupied surface and are primarily isolated hydroxyl groups. Rotational and translational motions are highly correlated for the A and B site molecules. The mean number of molecules clustered at the A and B sites are inferred from the intermolecular second moments associated with each of these sites. The surface density of the A sites is 1.1 x 10/sup 12/ cm/sup -2/ for SPSG and 3.1 x 10/sup 12/ cm/sup -2/ for MSG.« less

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

PubMed

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinical Paresthesia Atlas Illustrates Likelihood of Coverage Based on Spinal Cord Stimulator Electrode Location.

PubMed

Taghva, Alexander; Karst, Edward; Underwood, Paul

2017-08-01

Concordant paresthesia coverage is an independent predictor of pain relief following spinal cord stimulation (SCS). Using aggregate data, our objective is to produce a map of paresthesia coverage as a function of electrode location in SCS. This retrospective analysis used x-rays, SCS programming data, and paresthesia coverage maps from the EMPOWER registry of SCS implants for chronic neuropathic pain. Spinal level of dorsal column stimulation was determined by x-ray adjudication and active cathodes in patient programs. Likelihood of paresthesia coverage was determined as a function of stimulating electrode location. Segments of paresthesia coverage were grouped anatomically. Fisher's exact test was used to identify significant differences in likelihood of paresthesia coverage as a function of spinal stimulation level. In the 178 patients analyzed, the most prevalent areas of paresthesia coverage were buttocks, anterior and posterior thigh (each 98%), and low back (94%). Unwanted paresthesia at the ribs occurred in 8% of patients. There were significant differences in the likelihood of achieving paresthesia, with higher thoracic levels (T5, T6, and T7) more likely to achieve low back coverage but also more likely to introduce paresthesia felt at the ribs. Higher levels in the thoracic spine were associated with greater coverage of the buttocks, back, and thigh, and with lesser coverage of the leg and foot. This paresthesia atlas uses real-world, aggregate data to determine likelihood of paresthesia coverage as a function of stimulating electrode location. It represents an application of "big data" techniques, and a step toward achieving personalized SCS therapy tailored to the individual's chronic pain. © 2017 International Neuromodulation Society.

Bayesian Inference of High-Dimensional Dynamical Ocean Models

NASA Astrophysics Data System (ADS)

Lin, J.; Lermusiaux, P. F. J.; Lolla, S. V. T.; Gupta, A.; Haley, P. J., Jr.

2015-12-01

This presentation addresses a holistic set of challenges in high-dimension ocean Bayesian nonlinear estimation: i) predict the probability distribution functions (pdfs) of large nonlinear dynamical systems using stochastic partial differential equations (PDEs); ii) assimilate data using Bayes' law with these pdfs; iii) predict the future data that optimally reduce uncertainties; and (iv) rank the known and learn the new model formulations themselves. Overall, we allow the joint inference of the state, equations, geometry, boundary conditions and initial conditions of dynamical models. Examples are provided for time-dependent fluid and ocean flows, including cavity, double-gyre and Strait flows with jets and eddies. The Bayesian model inference, based on limited observations, is illustrated first by the estimation of obstacle shapes and positions in fluid flows. Next, the Bayesian inference of biogeochemical reaction equations and of their states and parameters is presented, illustrating how PDE-based machine learning can rigorously guide the selection and discovery of complex ecosystem models. Finally, the inference of multiscale bottom gravity current dynamics is illustrated, motivated in part by classic overflows and dense water formation sites and their relevance to climate monitoring and dynamics. This is joint work with our MSEAS group at MIT.

Model-based analyses of whole-genome data reveal a complex evolutionary history involving archaic introgression in Central African Pygmies.

PubMed

Hsieh, PingHsun; Woerner, August E; Wall, Jeffrey D; Lachance, Joseph; Tishkoff, Sarah A; Gutenkunst, Ryan N; Hammer, Michael F

2016-03-01

Comparisons of whole-genome sequences from ancient and contemporary samples have pointed to several instances of archaic admixture through interbreeding between the ancestors of modern non-Africans and now extinct hominids such as Neanderthals and Denisovans. One implication of these findings is that some adaptive features in contemporary humans may have entered the population via gene flow with archaic forms in Eurasia. Within Africa, fossil evidence suggests that anatomically modern humans (AMH) and various archaic forms coexisted for much of the last 200,000 yr; however, the absence of ancient DNA in Africa has limited our ability to make a direct comparison between archaic and modern human genomes. Here, we use statistical inference based on high coverage whole-genome data (greater than 60×) from contemporary African Pygmy hunter-gatherers as an alternative means to study the evolutionary history of the genus Homo. Using whole-genome simulations that consider demographic histories that include both isolation and gene flow with neighboring farming populations, our inference method rejects the hypothesis that the ancestors of AMH were genetically isolated in Africa, thus providing the first whole genome-level evidence of African archaic admixture. Our inferences also suggest a complex human evolutionary history in Africa, which involves at least a single admixture event from an unknown archaic population into the ancestors of AMH, likely within the last 30,000 yr. © 2016 Hsieh et al.; Published by Cold Spring Harbor Laboratory Press.

Low-coverage, whole-genome sequencing of Artocarpus camansi (Moraceae) for phylogenetic marker development and gene discovery1

PubMed Central

Gardner, Elliot M.; Johnson, Matthew G.; Ragone, Diane; Wickett, Norman J.; Zerega, Nyree J. C.

2016-01-01

Premise of the study: We used moderately low-coverage (17×) whole-genome sequencing of Artocarpus camansi (Moraceae) to develop genomic resources for Artocarpus and Moraceae. Methods and Results: A de novo assembly of Illumina short reads (251,378,536 pairs, 2 × 100 bp) accounted for 93% of the predicted genome size. Predicted coding regions were used in a three-way orthology search with published genomes of Morus notabilis and Cannabis sativa. Phylogenetic markers for Moraceae were developed from 333 inferred single-copy exons. Ninety-eight putative MADS-box genes were identified. Analysis of all predicted coding regions resulted in preliminary annotation of 49,089 genes. An analysis of synonymous substitutions for pairs of orthologs (Ks analysis) in M. notabilis and A. camansi strongly suggested a lineage-specific whole-genome duplication in Artocarpus. Conclusions: This study substantially increases the genomic resources available for Artocarpus and Moraceae and demonstrates the value of low-coverage de novo assemblies for nonmodel organisms with moderately large genomes. PMID:27437173

Can the starpatch on Xi Bootis A be explained by using tangential flows?

NASA Technical Reports Server (NTRS)

Toner, Clifford G.; Labonte, Barry J.

1991-01-01

It is demonstrated that a modification of the starpatch model of Toner and Gray (1988), using tangential flows instead of an enhanced granulation velocity dispersion within the patch, is very successful at reproducing both the observed line asymmetry and the line broadening variations observed in the G8 dwarf Xi Boo A. Areal coverage of 10 percent + or - 3 percent of the visible disk, latitude 30 deg + or - 4 deg, mean brightness 0.85 + or - 0.05 relative to the 'quiet' photosphere, mean tangential flow velocities of 8.0 + or - 1.5 km/s, and dispersions about the mean of 8/0 + or - 2.0 km/s are inferred for the patch. A feature at a latitude of about 30 deg is inferred which covers about 10 percent of the visible disk and is 10-20 percent fainter than the rest of the photosphere. It is inferred that 70-80 percent of the patch is penumbra.

Every Cloud has a Silver Lining: Synthesizing Spectra for Exoplanets with Inhomogeneous Aerosol Coverage

NASA Astrophysics Data System (ADS)

DiTomasso, Victoria; Kempton, Eliza; Rauscher, Emily; Roman, Michael

2018-01-01

In order to learn about exoplanets, we observe the light coming from their host stars. In particular, we can observe a host star while its planet is in transit. During transit, we are able to observe light from the star that has passed through the planet’s atmosphere and isolate that signal in a transmission spectrum. Previous transit observations have suggested that some hot Jupiters have aerosols in their atmospheres. We have calculated the effects that non-uniform aerosol coverage would have on the resulting transmission spectra of hot Jupiters. We used 3D atmospheric models of a planet with varying aerosol coverage to produce synthetic transmission spectra of the planet during full transit. We also produced transmission spectra from the start of transit, ingress, and the end of transit, egress, to determine if we can identify whether atmospheric aerosols are concentrated on the east or west side of the exoplanet. This will help us determine global aerosol structure, as well as indicate whether these planets are dominated by photochemically produced haze or directly condensed clouds. Using these spectra, we will test the feasibility of inferring aerosol coverage on a hot Jupiter using the Hubble Space Telescope.

Multilayer densities using a wavelet-based gravity method and their tectonic implications beneath the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xu, Chuang; Luo, Zhicai; Sun, Rong; Zhou, Hao; Wu, Yihao

2018-06-01

Determining density structure of the Tibetan Plateau is helpful in better understanding of tectonic structure and development. Seismic method, as traditional approach obtaining a large number of achievements of density structure in the Tibetan Plateau except in the centre and west, is primarily inhibited by the poor seismic station coverage. As the implementation of satellite gravity missions, gravity method is more competitive because of global homogeneous gravity coverage. In this paper, a novel wavelet-based gravity method with high computation efficiency and excellent local identification capability is developed to determine multilayer densities beneath the Tibetan Plateau. The inverted six-layer densities from 0 to 150 km depth can reveal rich tectonic structure and development of study area: (1) The densities present a clockwise pattern, nearly east-west high-low alternating pattern in the west and nearly south-north high-low alternating pattern in the east, which is almost perpendicular to surface movement direction relative to the stable Eurasia from the Global Positioning System velocity field; (2) Apparent fold structure approximately from 10 to 110 km depth can be inferred from the multilayer densities, the deformational direction of which is nearly south-north in the west and east-west in the east; (3) Possible channel flows approximately from 30 to 110 km depth can also be observed clearly during the multilayer densities. Moreover, the inverted multilayer densities are in agreement with previous studies, which verify the correctness and effectiveness of our method.

Multilayer Densities Using a Wavelet-based Gravity Method and Their Tectonic Implications beneath the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xu, Chuang; Luo, Zhicai; Sun, Rong; Zhou, Hao; Wu, Yihao

2018-03-01

Determining density structure of the Tibetan Plateau is helpful in better understanding tectonic structure and development. Seismic method, as traditional approach obtaining a large number of achievements of density structure in the Tibetan Plateau except in the center and west, is primarily inhibited by the poor seismic station coverage. As the implementation of satellite gravity missions, gravity method is more competitive because of global homogeneous gravity coverage. In this paper, a novel wavelet-based gravity method with high computation efficiency and excellent local identification capability is developed to determine multilayer densities beneath the Tibetan Plateau. The inverted 6-layer densities from 0 km to 150 km depth can reveal rich tectonic structure and development of study area: (1) The densities present a clockwise pattern, nearly east-west high-low alternating pattern in the west and nearly south-north high-low alternating pattern in the east, which is almost perpendicular to surface movement direction relative to the stable Eurasia from the Global Positioning System velocity field; (2) Apparent fold structure approximately from 10 km to 110 km depth can be inferred from the multilayer densities, the deformational direction of which is nearly south-north in the west and east-west in the east; (3) Possible channel flows approximately from 30 km to 110 km depth can be also observed clearly during the multilayer densities. Moreover, the inverted multilayer densities are in agreement with previous studies, which verify the correctness and effectiveness of our method.

A High-Resolution Aerosol Retrieval Method for Urban Areas Using MISR Data

NASA Astrophysics Data System (ADS)

Moon, T.; Wang, Y.; Liu, Y.; Yu, B.

2012-12-01

Satellite-retrieved Aerosol Optical Depth (AOD) can provide a cost-effective way to monitor particulate air pollution without using expensive ground measurement sensors. One of the current state-of-the-art AOD retrieval method is NASA's Multi-angle Imaging SpectroRadiometer (MISR) operational algorithm, which has the spatial resolution of 17.6 km x 17.6 km. While the MISR baseline scheme already leads to exciting research opportunities to study particle compositions at regional scale, its spatial resolution is too coarse for analyzing urban areas where the AOD level has stronger spatial variations. We develop a novel high-resolution AOD retrieval algorithm that still uses MISR's radiance observations but has the resolution of 4.4km x 4.4km. We achieve the high resolution AOD retrieval by implementing a hierarchical Bayesian model and Monte-Carlo Markov Chain (MCMC) inference method. Our algorithm not only improves the spatial resolution, but also extends the coverage of AOD retrieval and provides with additional composition information of aerosol components that contribute to the AOD. We validate our method using the recent NASA's DISCOVER-AQ mission data, which contains the ground measured AOD values for Washington DC and Baltimore area. The validation result shows that, compared to the operational MISR retrievals, our scheme has 41.1% more AOD retrieval coverage for the DISCOVER-AQ data points and 24.2% improvement in mean-squared error (MSE) with respect to the AERONET ground measurements.

Mapping lava morphology of the Galapagos Spreading Center at 92°W: fuzzy logic provides a classification of high-resolution bathymetry and backscatter

NASA Astrophysics Data System (ADS)

McClinton, J. T.; White, S. M.; Sinton, J. M.; Rubin, K. H.; Bowles, J. A.

2010-12-01

Differences in axial lava morphology along the Galapagos Spreading Center (GSC) can indicate variations in magma supply and emplacement dynamics due to the influence of the adjacent Galapagos hot spot. Unfortunately, the ability to discriminate fine-scale lava morphology has historically been limited to observations of the small coverage areas of towed camera surveys and submersible operations. This research presents a neuro-fuzzy approach to automated seafloor classification using spatially coincident, high-resolution bathymetry and backscatter data. The classification method implements a Sugeno-type fuzzy inference system trained by a multi-layered adaptive neural network and is capable of rapidly classifying seafloor morphology based on attributes of surface geometry and texture. The system has been applied to the 92°W segment of the western GSC in order to quantify coverage areas and distributions of pillow, lobate, and sheet lava morphology. An accuracy assessment has been performed on the classification results. The resulting classified maps provide a high-resolution view of GSC axial morphology and indicate the study area terrain is approximately 40% pillow flows, 40% lobate and sheet flows, and 10% fissured or faulted area, with about 10% of the study area unclassifiable. Fine-scale features such as eruptive fissures, tumuli, and individual pillowed lava flow fronts are also visible. Although this system has been applied to lava morphology, its design and implementation are applicable to other undersea mapping applications.

Role of Utility and Inference in the Evolution of Functional Information

PubMed Central

Sharov, Alexei A.

2009-01-01

Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are constructed within each communication system to represent reality and they evolve towards higher adaptability on a long time scale. PMID:20160960

Partitioning of ocean and land uptake of CO2 as inferred by delta C-13 measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network

NASA Technical Reports Server (NTRS)

Ciais, Philippe; Tans, Pieter P.; White, James W. C.; Trolier, Michael; Francey, Roger J.; Berry, Joe A.; Randall, David R.; Sellers, Piers J.; Collatz, James G.; Schimel, David S.

1995-01-01

Using delta C-13 measurements in atmospheric CO2 from a cooperative global air sampling network, we determined the partitioning of the net uptake of CO2 between ocean and land as a function of latitude and time. The majority of delta C-13 measurements were made at the Institute of Arctic and Alpine Research (INSTAAR) of the University of Colorado. We perform an inverse deconvolution of both CO2 and delta C-13 observations, using a two-dimensional model of atmospheric transport. Also, the discrimination against C-13 by plant photosynthesis, as a function of latitude and time, is calculated from global runs of the simple biosphere (SiB) model. Uncertainty due to the longitudinal structure of the data, which is not represented by the model, is studied through a bootstrap analysis by adding and omitting measurement sites. The resulting error estimates for our inferred sources and sinks are of the order of 1 GTC (1 GTC = 10(exp 15) gC). Such error bars do not reflect potential systematic errors arising from our estimates of the isotopic disequilibria between the atmosphere and the oceans and biosphere, which are estimated in a separate sensitivity analysis. With respect to global totals for 1992 we found that 3.2 GTC of carbon dissolved into the ocean and that 1.5 GTC were sequestered by land ecosystems. Northern hemisphere ocean gyres north of 15 deg N absorbed 2.7 GTC. The equatorial oceans between 10 deg S and 10 deg N were a net source to the atmosphere of 0.9 GTC. We obtained a sink of 1.6 GTC in southern ocean gyres south of 20 deg S, although the deconvolution is poorly constrained by sparse data coverage at high southern latitudes. The seasonal uptake of CO2 in the northern gyres appears to be correlated with a bloom of phytoplankton in surface waters. On land, northern temperate and boreal ecosystems between 35 deg N and 65 deg N were found to be a major sink of CO2 in 1992, as large as 3.5 GTC. Northern tropical ecosystems (equator-30 deg N) appear to be a net source to the source to the atmosphere of 2 GTC which could reflect biomass burning. A small sink, 0.3 GTC, was inferred for southern tropical ecosystems (30 deg S-equator).

Influence of the interfacial peptide organization on the catalysis of hydrogen evolution.

PubMed

Doneux, Th; Dorcák, V; Palecek, E

2010-01-19

The hydrogen evolution reaction is catalyzed by peptides and proteins adsorbed on electrode materials with high overpotentials for this reaction, such as mercury. The catalytic response characteristics are known to be very sensitive to the composition and structure of the investigated biomolecule, opening the way to the implementation of a label-free, reagentless electroanalytical method in protein analysis. Herein, it is shown using the model peptide Cys-Ala-Ala-Ala-Ala-Ala that the interfacial organization significantly influences the catalytic behavior. This peptide forms at the electrode two distinct films, depending on the concentration and accumulation time. The low-coverage film, composed of flat-lying molecules (area per molecule of approximately 250-290 A(2)), yields a well-defined catalytic peak at potentials around -1.75 V. The high-coverage film, made of upright-oriented peptides (area per molecule of approximately 43 A(2)), is catalytically more active and the peak is observed at potentials less negative by approximately 0.4 V. The higher activity, evidenced by constant-current chronopotentiometry and cyclic voltammetry, is attributed to an increase in the acid dissociation constant of the amino acid residues as a result of the low permittivity of the interfacial region, as inferred from impedance measurements. An analogy is made to the known differences in acidic-basic behaviors of solvent-exposed and hydrophobic domains of proteins.

Gelation And Mechanical Response of Patchy Rods

NASA Astrophysics Data System (ADS)

Kazem, Navid; Majidi, Carmel; Maloney, Craig

We perform Brownian Dynamics simulations to study the gelation of suspensions of attractive, rod-like particles. We show that details of the particle-particle interactions can dramatically affect the dynamics of gelation and the structure and mechanics of the networks that form. If the attraction between the rods is perfectly smooth along their length, they will collapse into compact bundles. If the attraction is sufficiently corrugated or patchy, over time, a rigid space spanning network forms. We study the structure and mechanical properties of the networks that form as a function of the fraction of the surface that is allowed to bind. Surprisingly, the structural and mechanical properties are non-monotonic in the surface coverage. At low coverage, there are not a sufficient number of cross-linking sites to form networks. At high coverage, rods bundle and form disconnected clusters. At intermediate coverage, robust networks form. The elastic modulus and yield stress are both non-monotonic in the surface coverage. The stiffest and strongest networks show an essentially homogeneous deformation under strain with rods re-orienting along the extensional axis. Weaker, clumpy networks at high surface coverage exhibit relatively little re-orienting with strong non-affine deformation. These results suggest design strategies for tailoring surface interactions between rods to yield rigid networks with optimal properties. National Science Foundation and the Air Force Office of Scientific Research.

Drug release through liposome pores.

PubMed

Dan, Nily

2015-02-01

Electrical, ultrasound and other types of external fields are known to induce the formation of pores in cellular and model membranes. This paper examines drug release through field induced liposome pores using Monte Carlo simulations. We find that drug release rates vary as a function of pore size and spacing, as well as the overall fraction of surface area covered by pores: The rate of release from liposomes is found to increase rapidly with pore surface coverage, approaching that of the fully ruptured liposome at fractional pore areas. For a given pore surface coverage, the pore size affects the release rate in the limit of low coverage, but not when the pores cover a relatively high fraction of the liposome surface area. On the other hand, for a given pore size and surface coverage, the distribution of pores significantly affects the release in the limit of high surface coverage: The rate of release from a liposome covered with a regularly spaced array of pores is, in this limit, higher than the release rate from (most) systems where the pores are distributed randomly on the liposome surface. In contrast, there is little effect of the pore distribution on release when the pore surface coverage is low. The simulation results are in good agreement with the predictions of detailed diffusion models. Copyright © 2014 Elsevier B.V. All rights reserved.

Topics in inference and decision-making with partial knowledge

NASA Technical Reports Server (NTRS)

Safavian, S. Rasoul; Landgrebe, David

1990-01-01

Two essential elements needed in the process of inference and decision-making are prior probabilities and likelihood functions. When both of these components are known accurately and precisely, the Bayesian approach provides a consistent and coherent solution to the problems of inference and decision-making. In many situations, however, either one or both of the above components may not be known, or at least may not be known precisely. This problem of partial knowledge about prior probabilities and likelihood functions is addressed. There are at least two ways to cope with this lack of precise knowledge: robust methods, and interval-valued methods. First, ways of modeling imprecision and indeterminacies in prior probabilities and likelihood functions are examined; then how imprecision in the above components carries over to the posterior probabilities is examined. Finally, the problem of decision making with imprecise posterior probabilities and the consequences of such actions are addressed. Application areas where the above problems may occur are in statistical pattern recognition problems, for example, the problem of classification of high-dimensional multispectral remote sensing image data.

Inhomogeneous Poisson process rate function inference from dead-time limited observations.

PubMed

Verma, Gunjan; Drost, Robert J

2017-05-01

The estimation of an inhomogeneous Poisson process (IHPP) rate function from a set of process observations is an important problem arising in optical communications and a variety of other applications. However, because of practical limitations of detector technology, one is often only able to observe a corrupted version of the original process. In this paper, we consider how inference of the rate function is affected by dead time, a period of time after the detection of an event during which a sensor is insensitive to subsequent IHPP events. We propose a flexible nonparametric Bayesian approach to infer an IHPP rate function given dead-time limited process realizations. Simulation results illustrate the effectiveness of our inference approach and suggest its ability to extend the utility of existing sensor technology by permitting more accurate inference on signals whose observations are dead-time limited. We apply our inference algorithm to experimentally collected optical communications data, demonstrating the practical utility of our approach in the context of channel modeling and validation.

Beyond the political model of reporting: nonspecific symptoms in media communication about AIDS.

PubMed

Check, W A

1987-01-01

Mass media have functioned well in transmitting much of the basic information about the AIDS epidemic; however, media coverage of AIDS has been flawed. In many ways these flaws have resulted from the limitations and conventions of traditional journalism, especially the need to appeal to a large mainstream audience and a reliance on authorities as sources and validators of information. News stories typically rely on a single articulate authority, and articles that involve conspiracy or controversy or have a high entertainment value are favored. Although coverage of politics and social issues is not distorted by these journalistic conventions, coverage of science suffers. Analysis of news coverage of AIDS shows that mass media often respond to sensationalism rather than to important scientific developments. In addition, scientific disagreements are better adjudicated by evidence than by appeals to authority. As a result, media coverage often obscures the process of scientific deliberation. Public health officials need to consider setting up a special channel of communications to clarify information about AIDS.

MO-FG-CAMPUS-TeP2-04: Optimizing for a Specified Target Coverage Probability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fredriksson, A

2016-06-15

Purpose: The purpose of this work is to develop a method for inverse planning of radiation therapy margins. When using this method the user specifies a desired target coverage probability and the system optimizes to meet the demand without any explicit specification of margins to handle setup uncertainty. Methods: The method determines which voxels to include in an optimization function promoting target coverage in order to achieve a specified target coverage probability. Voxels are selected in a way that retains the correlation between them: The target is displaced according to the setup errors and the voxels to include are selectedmore » as the union of the displaced target regions under the x% best scenarios according to some quality measure. The quality measure could depend on the dose to the considered structure alone or could depend on the dose to multiple structures in order to take into account correlation between structures. Results: A target coverage function was applied to the CTV of a prostate case with prescription 78 Gy and compared to conventional planning using a DVH function on the PTV. Planning was performed to achieve 90% probability of CTV coverage. The plan optimized using the coverage probability function had P(D98 > 77.95 Gy) = 0.97 for the CTV. The PTV plan using a constraint on minimum DVH 78 Gy at 90% had P(D98 > 77.95) = 0.44 for the CTV. To match the coverage probability optimization, the DVH volume parameter had to be increased to 97% which resulted in 0.5 Gy higher average dose to the rectum. Conclusion: Optimizing a target coverage probability is an easily used method to find a margin that achieves the desired coverage probability. It can lead to reduced OAR doses at the same coverage probability compared to planning with margins and DVH functions.« less

Spatially extensive uniform stress fields on Venus inferred from radial dike swarm geometries: The Aphrodite Terra example

NASA Technical Reports Server (NTRS)

Grosfils, Eric B.; Head, James W.

1993-01-01

The high resolution and near global coverage of Magellan radar images is facilitating attempts to systematically investigate the stresses that have deformed the venusian crust. Here we continue earlier efforts to utilize approximately 170 large, radially lineated structures interpreted as dike swarms to assess the orientation of the regional maximum horizontal compressive stress (MHCS) which existed in their vicinities during emplacement. Examination of swarms near the equator reveals a link to broad scale regional structures, such as Aphrodite Terra, across distances in excess of 1000 km, suggesting the existence of first order stress fields which affect areas of more than 10(exp 6) sq km in a uniform fashion. Focusing further upon the Aphrodite Terra region, the MHCS field in the surrounding lowlands inferred from radial swarms is oriented approximately normal to the slope of the highland topography. This stress configuration appears, at a simple level, to be incompatible with that expected during either upwelling or downwelling construction of the highlands. In addition, the relatively undeformed geometry of the radial structures within the highlands implies that these dike swarm features formed more recently than their highly deformed surroundings. We conclude that the differential stresses which existed during emplacement of the dike swarms within and adjacent to the Aphrodite Terra highlands are related to the gravitational relaxation of pre-existing topography.

Extreme-Depth Re-sequencing of Mitochondrial DNA Finds No Evidence of Paternal Transmission in Humans.

PubMed

Pyle, Angela; Hudson, Gavin; Wilson, Ian J; Coxhead, Jonathan; Smertenko, Tania; Herbert, Mary; Santibanez-Koref, Mauro; Chinnery, Patrick F

2015-05-01

Recent reports have questioned the accepted dogma that mammalian mitochondrial DNA (mtDNA) is strictly maternally inherited. In humans, the argument hinges on detecting a signature of inter-molecular recombination in mtDNA sequences sampled at the population level, inferring a paternal source for the mixed haplotypes. However, interpreting these data is fraught with difficulty, and direct experimental evidence is lacking. Using extreme-high depth mtDNA re-sequencing up to ~1.2 million-fold coverage, we find no evidence that paternal mtDNA haplotypes are transmitted to offspring in humans, thus excluding a simple dilution mechanism for uniparental transmission of mtDNA present in all healthy individuals. Our findings indicate that an active mechanism eliminates paternal mtDNA which likely acts at the molecular level.

Extreme-Depth Re-sequencing of Mitochondrial DNA Finds No Evidence of Paternal Transmission in Humans

PubMed Central

Pyle, Angela; Hudson, Gavin; Wilson, Ian J.; Coxhead, Jonathan; Smertenko, Tania; Herbert, Mary; Santibanez-Koref, Mauro; Chinnery, Patrick F.

2015-01-01

Recent reports have questioned the accepted dogma that mammalian mitochondrial DNA (mtDNA) is strictly maternally inherited. In humans, the argument hinges on detecting a signature of inter-molecular recombination in mtDNA sequences sampled at the population level, inferring a paternal source for the mixed haplotypes. However, interpreting these data is fraught with difficulty, and direct experimental evidence is lacking. Using extreme-high depth mtDNA re-sequencing up to ~1.2 million-fold coverage, we find no evidence that paternal mtDNA haplotypes are transmitted to offspring in humans, thus excluding a simple dilution mechanism for uniparental transmission of mtDNA present in all healthy individuals. Our findings indicate that an active mechanism eliminates paternal mtDNA which likely acts at the molecular level. PMID:25973765

Judicial Perceptions of Media Portrayals of Offenders with High Functioning Autistic Spectrum Disorders.

PubMed

Berryessa, Colleen M

In recent years, sensational media reporting focusing on crimes committed by those diagnosed with or thought to have High Functioning Autistic Spectrum Disorders (hfASDs) has caused societal speculation that there is a link between the disorder and violent criminality. No research exists on how and if the judiciary understands and is affected by this coverage. Therefore this study aims to examine how judges perceive and are influenced by media attention surrounding hfASDs and criminality. Semi-structured interviews were conducted with 21 California Superior Court Judges, including questions on media portrayal. Judges perceived general media portrayals of hfASDs in both positive and negative ways. However, almost all judges who had experienced media coverage surrounding hfASDs and criminality identified it as misleading and harmful to public perceptions of the disorder. These findings suggest judges are not exempt from media attention surrounding violence and hfASDs, and they recognize the potential adverse effects of this negative coverage. Although judges' report their opinions are not affected, the results demonstrate that judges are worried that the public and potentially other criminal justice actors are adversely affected and will continue to be moving forward.

Judicial Perceptions of Media Portrayals of Offenders with High Functioning Autistic Spectrum Disorders

PubMed Central

Berryessa, Colleen M.

2015-01-01

In recent years, sensational media reporting focusing on crimes committed by those diagnosed with or thought to have High Functioning Autistic Spectrum Disorders (hfASDs) has caused societal speculation that there is a link between the disorder and violent criminality. No research exists on how and if the judiciary understands and is affected by this coverage. Therefore this study aims to examine how judges perceive and are influenced by media attention surrounding hfASDs and criminality. Semi-structured interviews were conducted with 21 California Superior Court Judges, including questions on media portrayal. Judges perceived general media portrayals of hfASDs in both positive and negative ways. However, almost all judges who had experienced media coverage surrounding hfASDs and criminality identified it as misleading and harmful to public perceptions of the disorder. These findings suggest judges are not exempt from media attention surrounding violence and hfASDs, and they recognize the potential adverse effects of this negative coverage. Although judges’ report their opinions are not affected, the results demonstrate that judges are worried that the public and potentially other criminal justice actors are adversely affected and will continue to be moving forward. PMID:25722757

Surface reaction modification: The effect of structured overlayers of sulfur on the kinetics and mechanism of the decomposition of formic acid on Pt(111)

NASA Astrophysics Data System (ADS)

Abbas, N.; Madix, R. J.

The reaction of formic acid (DCOOH) on Pt(111), Pt(111)-(2×2)S and Pt(111)-(√3×√3)R30°S surfaces was examined by temperature programmed reaction spectroscopy. On the clean surface formic acid decomposed to yield primarily carbon dioxide and the hydrogenic species (H 2, HD and D 2) at low coverages. Although the formation of water and carbon monoxide via a dehydration reaction was observed at these coverages, the yield of these products was small when compared to the other products of reaction. The evolution of CO 2 at low temperature was ascribed to the decomposition of the formate intermediate. In the presence of sulfur the amount of molecularly adsorbed formic acid decreased up to a factor of three on the (√3×√3)R30°S surface, and a decline in the reactivity of over an order of magnitude was also observed. The only products formed were the hydrogenic species and carbon dioxide. The absence of carbon monoxide indicated that the dehydration pathway was blocked by sulfur. In addition to the low temperature CO 2 peak a high temperature CO 2-producing path was also evident. It was inferred from both the stoichiometry and the coincident evolution of D 2 and CO 2 in the high temperature states that these products also evolved due to the decomposition of the formate intermediate. On increasing the sulfur coverage to one-third monolayer this intermediate was further stabilized, and a predominance of the decomposition via the high temperature path was observed. Stability of the formate intermediate was attributed to inhibition of the decomposition reaction by sulfur atoms. The activation energy for formate decomposition increased from 15 kcal/gmole on the clean surface to 24.3 kcal/gmol on the (√3×√3)R30°S overlayer.

Backward renormalization-group inference of cortical dipole sources and neural connectivity efficacy

NASA Astrophysics Data System (ADS)

Amaral, Selene da Rocha; Baccalá, Luiz A.; Barbosa, Leonardo S.; Caticha, Nestor

2017-06-01

Proper neural connectivity inference has become essential for understanding cognitive processes associated with human brain function. Its efficacy is often hampered by the curse of dimensionality. In the electroencephalogram case, which is a noninvasive electrophysiological monitoring technique to record electrical activity of the brain, a possible way around this is to replace multichannel electrode information with dipole reconstructed data. We use a method based on maximum entropy and the renormalization group to infer the position of the sources, whose success hinges on transmitting information from low- to high-resolution representations of the cortex. The performance of this method compares favorably to other available source inference algorithms, which are ranked here in terms of their performance with respect to directed connectivity inference by using artificially generated dynamic data. We examine some representative scenarios comprising different numbers of dynamically connected dipoles over distinct cortical surface positions and under different sensor noise impairment levels. The overall conclusion is that inverse problem solutions do not affect the correct inference of the direction of the flow of information as long as the equivalent dipole sources are correctly found.

Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes.

PubMed

Feuermann, Marc; Gaudet, Pascale; Mi, Huaiyu; Lewis, Suzanna E; Thomas, Paul D

2016-01-01

We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.Database URL: http://amigo.geneontology.org/amigo. © The Author(s) 2016. Published by Oxford University Press.

Evaluation of some random effects methodology applicable to bird ringing data

USGS Publications Warehouse

Burnham, K.P.; White, Gary C.

2002-01-01

Existing models for ring recovery and recapture data analysis treat temporal variations in annual survival probability (S) as fixed effects. Often there is no explainable structure to the temporal variation in S1,..., Sk; random effects can then be a useful model: Si = E(S) + ??i. Here, the temporal variation in survival probability is treated as random with average value E(??2) = ??2. This random effects model can now be fit in program MARK. Resultant inferences include point and interval estimation for process variation, ??2, estimation of E(S) and var (E??(S)) where the latter includes a component for ??2 as well as the traditional component for v??ar(S??\\S??). Furthermore, the random effects model leads to shrinkage estimates, Si, as improved (in mean square error) estimators of Si compared to the MLE, S??i, from the unrestricted time-effects model. Appropriate confidence intervals based on the Si are also provided. In addition, AIC has been generalized to random effects models. This paper presents results of a Monte Carlo evaluation of inference performance under the simple random effects model. Examined by simulation, under the simple one group Cormack-Jolly-Seber (CJS) model, are issues such as bias of ??s2, confidence interval coverage on ??2, coverage and mean square error comparisons for inference about Si based on shrinkage versus maximum likelihood estimators, and performance of AIC model selection over three models: Si ??? S (no effects), Si = E(S) + ??i (random effects), and S1,..., Sk (fixed effects). For the cases simulated, the random effects methods performed well and were uniformly better than fixed effects MLE for the Si.

Independent evolution of genomic characters during major metazoan transitions.

PubMed

Simakov, Oleg; Kawashima, Takeshi

2017-07-15

Metazoan evolution encompasses a vast evolutionary time scale spanning over 600 million years. Our ability to infer ancestral metazoan characters, both morphological and functional, is limited by our understanding of the nature and evolutionary dynamics of the underlying regulatory networks. Increasing coverage of metazoan genomes enables us to identify the evolutionary changes of the relevant genomic characters such as the loss or gain of coding sequences, gene duplications, micro- and macro-synteny, and non-coding element evolution in different lineages. In this review we describe recent advances in our understanding of ancestral metazoan coding and non-coding features, as deduced from genomic comparisons. Some genomic changes such as innovations in gene and linkage content occur at different rates across metazoan clades, suggesting some level of independence among genomic characters. While their contribution to biological innovation remains largely unclear, we review recent literature about certain genomic changes that do correlate with changes to specific developmental pathways and metazoan innovations. In particular, we discuss the origins of the recently described pharyngeal cluster which is conserved across deuterostome genomes, and highlight different genomic features that have contributed to the evolution of this group. We also assess our current capacity to infer ancestral metazoan states from gene models and comparative genomics tools and elaborate on the future directions of metazoan comparative genomics relevant to evo-devo studies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Affective expressions in groups and inferences about members' relational well-being: The effects of socially engaging and disengaging emotions.

PubMed

Rothman, Naomi B; Magee, Joe C

2016-01-01

Our findings draw attention to the interpersonal communication function of a relatively unexplored dimension of emotions-the level of social engagement versus disengagement. In four experiments, regardless of valence and target group gender, observers infer greater relational well-being (more cohesiveness and less conflict) between group members from socially engaging (sadness and appreciation) versus disengaging (anger and pride) emotion expressions. Supporting our argument that social (dis)engagement is a critical dimension communicated by these emotions, we demonstrate (1) that inferences about group members' self-interest mediate the effect of socially engaging emotions on cohesiveness and (2) that the influence of socially disengaging emotion expressions on inferences of conflict is attenuated when groups have collectivistic norms (i.e., members value a high level of social engagement). Furthermore, we show an important downstream consequence of these inferences of relational well-being: Groups that seem less cohesive because of their members' proud (versus appreciative) expressions are also expected to have worse task performance.

Zn2+ and Sr2+ Adsorption at the TiO2 (110)-Electrolyte Interface: Influence of Ionic Strength, Coverage, and Anions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang,Z.; Fenter, P.; Cheng, L.

2006-01-01

The X-ray standing wave technique was used to probe the sensitivity of Zn{sup 2+} and Sr{sup 2+} ion adsorption to changes in both the adsorbed ion coverage and the background electrolyte species and concentrations at the rutile ({alpha}-TiO{sub 2}) (110)-aqueous interface. Measurements were made with various background electrolytes (NaCl, NaTr, RbCl, NaBr) at concentrations as high as 1 m. The results demonstrate that Zn{sub 2+} and Sr{sub 2+} reside primarily in the condensed layer and that the ion heights above the Ti-O surface plane are insensitive to ionic strength and the choice of background electrolyte (with <0.1 Angstroms changes overmore » the full compositional range). The lack of any specific anion coadsorption upon probing with Br{sup -}, coupled with the insensitivity of Zn{sup 2+} and Sr{sup 2+} cation heights to changes in the background electrolyte, implies that anions do not play a significant role in the adsorption of these divalent metal ions to the rutile (110) surface. Absolute ion coverage measurements for Zn{sup 2+} and Sr{sup 2+} show a maximum Stern-layer coverage of {approx}0.5 monolayer, with no significant variation in height as a function of Stern-layer coverage. These observations are discussed in the context of Gouy-Chapman-Stern models of the electrical double layer developed from macroscopic sorption and pH-titration studies of rutile powder suspensions. Direct comparison between these experimental observations and the MUltiSIte Complexation (MUSIC) model predictions of cation surface coverage as a function of ionic strength revealed good agreement between measured and predicted surface coverages with no adjustable parameters.« less

Predicted Arabidopsis Interactome Resource and Gene Set Linkage Analysis: A Transcriptomic Analysis Resource.

PubMed

Yao, Heng; Wang, Xiaoxuan; Chen, Pengcheng; Hai, Ling; Jin, Kang; Yao, Lixia; Mao, Chuanzao; Chen, Xin

2018-05-01

An advanced functional understanding of omics data is important for elucidating the design logic of physiological processes in plants and effectively controlling desired traits in plants. We present the latest versions of the Predicted Arabidopsis Interactome Resource (PAIR) and of the gene set linkage analysis (GSLA) tool, which enable the interpretation of an observed transcriptomic change (differentially expressed genes [DEGs]) in Arabidopsis ( Arabidopsis thaliana ) with respect to its functional impact for biological processes. PAIR version 5.0 integrates functional association data between genes in multiple forms and infers 335,301 putative functional interactions. GSLA relies on this high-confidence inferred functional association network to expand our perception of the functional impacts of an observed transcriptomic change. GSLA then interprets the biological significance of the observed DEGs using established biological concepts (annotation terms), describing not only the DEGs themselves but also their potential functional impacts. This unique analytical capability can help researchers gain deeper insights into their experimental results and highlight prospective directions for further investigation. We demonstrate the utility of GSLA with two case studies in which GSLA uncovered how molecular events may have caused physiological changes through their collective functional influence on biological processes. Furthermore, we showed that typical annotation-enrichment tools were unable to produce similar insights to PAIR/GSLA. The PAIR version 5.0-inferred interactome and GSLA Web tool both can be accessed at http://public.synergylab.cn/pair/. © 2018 American Society of Plant Biologists. All Rights Reserved.

Phylogenomics of plant genomes: a methodology for genome-wide searches for orthologs in plants

PubMed Central

Conte, Matthieu G; Gaillard, Sylvain; Droc, Gaetan; Perin, Christophe

2008-01-01

Background Gene ortholog identification is now a major objective for mining the increasing amount of sequence data generated by complete or partial genome sequencing projects. Comparative and functional genomics urgently need a method for ortholog detection to reduce gene function inference and to aid in the identification of conserved or divergent genetic pathways between several species. As gene functions change during evolution, reconstructing the evolutionary history of genes should be a more accurate way to differentiate orthologs from paralogs. Phylogenomics takes into account phylogenetic information from high-throughput genome annotation and is the most straightforward way to infer orthologs. However, procedures for automatic detection of orthologs are still scarce and suffer from several limitations. Results We developed a procedure for ortholog prediction between Oryza sativa and Arabidopsis thaliana. Firstly, we established an efficient method to cluster A. thaliana and O. sativa full proteomes into gene families. Then, we developed an optimized phylogenomics pipeline for ortholog inference. We validated the full procedure using test sets of orthologs and paralogs to demonstrate that our method outperforms pairwise methods for ortholog predictions. Conclusion Our procedure achieved a high level of accuracy in predicting ortholog and paralog relationships. Phylogenomic predictions for all validated gene families in both species were easily achieved and we can conclude that our methodology outperforms similarly based methods. PMID:18426584

Bayesian inference and assessment for rare-event bycatch in marine fisheries: a drift gillnet fishery case study.

PubMed

Martin, Summer L; Stohs, Stephen M; Moore, Jeffrey E

2015-03-01

Fisheries bycatch is a global threat to marine megafauna. Environmental laws require bycatch assessment for protected species, but this is difficult when bycatch is rare. Low bycatch rates, combined with low observer coverage, may lead to biased, imprecise estimates when using standard ratio estimators. Bayesian model-based approaches incorporate uncertainty, produce less volatile estimates, and enable probabilistic evaluation of estimates relative to management thresholds. Here, we demonstrate a pragmatic decision-making process that uses Bayesian model-based inferences to estimate the probability of exceeding management thresholds for bycatch in fisheries with < 100% observer coverage. Using the California drift gillnet fishery as a case study, we (1) model rates of rare-event bycatch and mortality using Bayesian Markov chain Monte Carlo estimation methods and 20 years of observer data; (2) predict unobserved counts of bycatch and mortality; (3) infer expected annual mortality; (4) determine probabilities of mortality exceeding regulatory thresholds; and (5) classify the fishery as having low, medium, or high bycatch impact using those probabilities. We focused on leatherback sea turtles (Dermochelys coriacea) and humpback whales (Megaptera novaeangliae). Candidate models included Poisson or zero-inflated Poisson likelihood, fishing effort, and a bycatch rate that varied with area, time, or regulatory regime. Regulatory regime had the strongest effect on leatherback bycatch, with the highest levels occurring prior to a regulatory change. Area had the strongest effect on humpback bycatch. Cumulative bycatch estimates for the 20-year period were 104-242 leatherbacks (52-153 deaths) and 6-50 humpbacks (0-21 deaths). The probability of exceeding a regulatory threshold under the U.S. Marine Mammal Protection Act (Potential Biological Removal, PBR) of 0.113 humpback deaths was 0.58, warranting a "medium bycatch impact" classification of the fishery. No PBR thresholds exist for leatherbacks, but the probability of exceeding an anticipated level of two deaths per year, stated as part of a U.S. Endangered Species Act assessment process, was 0.0007. The approach demonstrated here would allow managers to objectively and probabilistically classify fisheries with respect to bycatch impacts on species that have population-relevant mortality reference points, and declare with a stipulated level of certainty that bycatch did or did not exceed estimated upper bounds.

Intermediate-scale plasma irregularities in the polar ionosphere inferred from GPS radio occultation

NASA Astrophysics Data System (ADS)

Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O.; Butala, M. D.; Mannucci, A. J.

2015-02-01

We report intermediate-scale plasma irregularities in the polar ionosphere inferred from high-resolution radio occultation (RO) measurements using GPS (Global Positioning System) to CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) satellite radio links. The high inclination of CASSIOPE and the high rate of signal reception by the GPS Attitude, Positioning, and Profiling RO receiver on CASSIOPE enable a high-resolution investigation of the dynamics of the polar ionosphere with unprecedented detail. Intermediate-scale, scintillation-producing irregularities, which correspond to 1 to 40 km scales, were inferred by applying multiscale spectral analysis on the RO phase measurements. Using our multiscale spectral analysis approach and satellite data (Polar Operational Environmental Satellites and Defense Meteorological Satellite Program), we discovered that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap. We found that large length scales and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap implying that the irregularity scales and phase scintillation characteristics are a function of the solar wind and magnetospheric forcings.

The complex behavior of the Pd 7 cluster supported on TiO 2 (110) during CO oxidation: adsorbate-driven promoting effect

DOE PAGES

An, Wei; Liu, Ping

2016-09-07

When using the TiO 2(110)-supported Pd7 cluster as a model catalyst, we identified the dynamics of supported metal nanoparticles using density functional theory calculations, at the sub-nanometer scale and under reactive environments. Increasing the CO coverage can induce a structural transformation from Pd 7-3D/TiO 2(110) at low coverage to Pd 7-2D/TiO 2(110) at the saturation coverage wherein CO saturation-driven Pd7-2D/TiO 2(110) structure displays superior CO oxidation activity at the interfacial sites, which are highly active for catalyzing O 2 dissociation and CO oxidation via bifunctional synergy.

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

PubMed

Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia

2016-10-01

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

NASA Technical Reports Server (NTRS)

Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Sparse Bayesian Inference and the Temperature Structure of the Solar Corona

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren, Harry P.; Byers, Jeff M.; Crump, Nicholas A.

Measuring the temperature structure of the solar atmosphere is critical to understanding how it is heated to high temperatures. Unfortunately, the temperature of the upper atmosphere cannot be observed directly, but must be inferred from spectrally resolved observations of individual emission lines that span a wide range of temperatures. Such observations are “inverted” to determine the distribution of plasma temperatures along the line of sight. This inversion is ill posed and, in the absence of regularization, tends to produce wildly oscillatory solutions. We introduce the application of sparse Bayesian inference to the problem of inferring the temperature structure of themore » solar corona. Within a Bayesian framework a preference for solutions that utilize a minimum number of basis functions can be encoded into the prior and many ad hoc assumptions can be avoided. We demonstrate the efficacy of the Bayesian approach by considering a test library of 40 assumed temperature distributions.« less

Single board system for fuzzy inference

NASA Technical Reports Server (NTRS)

Symon, James R.; Watanabe, Hiroyuki

1991-01-01

The very large scale integration (VLSI) implementation of a fuzzy logic inference mechanism allows the use of rule-based control and decision making in demanding real-time applications. Researchers designed a full custom VLSI inference engine. The chip was fabricated using CMOS technology. The chip consists of 688,000 transistors of which 476,000 are used for RAM memory. The fuzzy logic inference engine board system incorporates the custom designed integrated circuit into a standard VMEbus environment. The Fuzzy Logic system uses Transistor-Transistor Logic (TTL) parts to provide the interface between the Fuzzy chip and a standard, double height VMEbus backplane, allowing the chip to perform application process control through the VMEbus host. High level C language functions hide details of the hardware system interface from the applications level programmer. The first version of the board was installed on a robot at Oak Ridge National Laboratory in January of 1990.

Financial burdens and barriers to care among nonelderly adults: The role of functional limitations and chronic conditions.

PubMed

Bernard, Didem; Selden, Thomas; Yeh, Susan

2016-04-01

People with functional limitations and chronic conditions account for the greatest resource use within the health care system. To examine financial burdens and barriers to care among nonelderly adults, focusing on the role of functional limitations and chronic conditions. High financial burden is defined as medical spending exceeding 20 percent of family income. Financial barriers are defined as delaying care/being unable to get care for financial reasons, and reporting that delaying care/going without was a big problem. Data are from the Medical Expenditure Panel Survey (2008-2012). Functional limitations are associated with increased prevalence of financial burdens. Among single adults, the frequency of high burdens is 20.3% for those with functional limitations, versus 7.8% for those without. Among those with functional limitations, those with 3 or more chronic conditions are twice as likely to have high burdens compared to those without chronic conditions (22.2% versus 11.1%, respectively). Similar patterns occur among persons in multi-person families whose members have functional limitations and chronic conditions. Having functional limitations and chronic conditions is also strongly associated with financial barriers to care: 40.2% among the uninsured, 21.9% among those with public coverage, and 13.6% among those with private group insurance were unable to get care. Functional limitations and chronic conditions are associated with increased prevalence of burdens and financial barriers in all insurance categories, with the exception that an association between functional limitations and the prevalence of burdens was not observed for public coverage. Published by Elsevier Inc.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Influenza Vaccination Coverage Rate according to the Pulmonary Function of Korean Adults Aged 40 Years and Over: Analysis of the Fifth Korean National Health and Nutrition Examination Survey

PubMed Central

2016-01-01

Influenza vaccination is an effective strategy to reduce morbidity and mortality, particularly for those who have decreased lung functions. This study was to identify the factors that affect vaccination coverage according to the results of pulmonary function tests depending on the age. In this cross-sectional study, data were obtained from 3,224 adults over the age of 40 who participated in the fifth National Health and Nutrition Examination Survey and underwent pulmonary function testing in 2012. To identify the factors that affect vaccination rate, logistic regression analysis was conducted after dividing the subjects into two groups based on the age of 65. Influenza vaccination coverage of the entire subjects was 45.2%, and 76.8% for those aged 65 and over. The group with abnormal pulmonary function had a higher vaccination rate than the normal group, but any pulmonary dysfunction or history of COPD did not affect the vaccination coverage in the multivariate analysis. The subjects who were 40-64 years-old had higher vaccination coverage when they were less educated or with restricted activity level, received health screenings, and had chronic diseases. Those aged 65 and over had significantly higher vaccination coverage only when they received regular health screenings. Any pulmonary dysfunction or having COPD showed no significant correlation with the vaccination coverage in the Korean adult population. PMID:27134491

An integrated open framework for thermodynamics of reactions that combines accuracy and coverage.

PubMed

Noor, Elad; Bar-Even, Arren; Flamholz, Avi; Lubling, Yaniv; Davidi, Dan; Milo, Ron

2012-08-01

The laws of thermodynamics describe a direct, quantitative relationship between metabolite concentrations and reaction directionality. Despite great efforts, thermodynamic data suffer from limited coverage, scattered accessibility and non-standard annotations. We present a framework for unifying thermodynamic data from multiple sources and demonstrate two new techniques for extrapolating the Gibbs energies of unmeasured reactions and conditions. Both methods account for changes in cellular conditions (pH, ionic strength, etc.) by using linear regression over the ΔG(○) of pseudoisomers and reactions. The Pseudoisomeric Reactant Contribution method systematically infers compound formation energies using measured K' and pK(a) data. The Pseudoisomeric Group Contribution method extends the group contribution method and achieves a high coverage of unmeasured reactions. We define a continuous index that predicts the reversibility of a reaction under a given physiological concentration range. In the characteristic physiological range 3μM-3mM, we find that roughly half of the reactions in Escherichia coli's metabolism are reversible. These new tools can increase the accuracy of thermodynamic-based models, especially in non-standard pH and ionic strengths. The reversibility index can help modelers decide which reactions are reversible in physiological conditions. Freely available on the web at: http://equilibrator.weizmann.ac.il. Website implemented in Python, MySQL, Apache and Django, with all major browsers supported. The framework is open-source (code.google.com/p/milo-lab), implemented in pure Python and tested mainly on Linux. ron.milo@weizmann.ac.il Supplementary data are available at Bioinformatics online.

An integrated open framework for thermodynamics of reactions that combines accuracy and coverage

PubMed Central

Noor, Elad; Bar-Even, Arren; Flamholz, Avi; Lubling, Yaniv; Davidi, Dan; Milo, Ron

2012-01-01

Motivation: The laws of thermodynamics describe a direct, quantitative relationship between metabolite concentrations and reaction directionality. Despite great efforts, thermodynamic data suffer from limited coverage, scattered accessibility and non-standard annotations. We present a framework for unifying thermodynamic data from multiple sources and demonstrate two new techniques for extrapolating the Gibbs energies of unmeasured reactions and conditions. Results: Both methods account for changes in cellular conditions (pH, ionic strength, etc.) by using linear regression over the ΔG○ of pseudoisomers and reactions. The Pseudoisomeric Reactant Contribution method systematically infers compound formation energies using measured K′ and pKa data. The Pseudoisomeric Group Contribution method extends the group contribution method and achieves a high coverage of unmeasured reactions. We define a continuous index that predicts the reversibility of a reaction under a given physiological concentration range. In the characteristic physiological range 3μM–3mM, we find that roughly half of the reactions in Escherichia coli's metabolism are reversible. These new tools can increase the accuracy of thermodynamic-based models, especially in non-standard pH and ionic strengths. The reversibility index can help modelers decide which reactions are reversible in physiological conditions. Availability: Freely available on the web at: http://equilibrator.weizmann.ac.il. Website implemented in Python, MySQL, Apache and Django, with all major browsers supported. The framework is open-source (code.google.com/p/milo-lab), implemented in pure Python and tested mainly on Linux. Contact: ron.milo@weizmann.ac.il Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:22645166

Estimates of Active Region Area Coverage through Simultaneous Measurements of the He i λλ 5876 and 10830 Lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andretta, Vincenzo; Covino, Elvira; Giampapa, Mark S.

2017-04-20

Simultaneous, high-quality measurements of the neutral helium triplet features at 5876 Å and 10830 Å in a sample of solar-type stars are presented. The observations were made with ESO telescopes at the La Silla Paranal Observatory under program ID 088.D-0028(A) and MPG Utility Run for Fiber Extended-range Optical Spectrograph 088.A-9029(A). The equivalent widths of these features combined with chromospheric models are utilized to infer the fractional area coverage, or filling factor, of magnetic regions outside of spots. We find that the majority of the sample is characterized by filling factors less than unity. However, discrepancies occur among the coolest K-typemore » and the warmest and most rapidly rotating F-type dwarf stars. We discuss these apparently anomalous results and find that in the case of K-type stars, they are an artifact of the application of chromospheric models best suited to the Sun than to stars with significantly lower T {sub eff}. The case of the F-type rapid rotators can be explained by the measurement uncertainties of the equivalent widths, but they may also be due to a non-magnetic heating component in their atmospheres. With the exceptions noted above, preliminary results suggest that the average heating rates in the active regions are the same from one star to the other, differing in the spatially integrated, observed level of activity due to the area coverage. Hence, differences in activity in this sample are mainly due to the filling factor of active regions.« less

Biocrusts role on nitrogen cycle and microbial communities from underlying soils in drylands

NASA Astrophysics Data System (ADS)

Anguita-Maeso, Manuel; Miralles*, Isabel; van Wesemael, Bas; Lázaro, Roberto; Ortega, Raúl; Garcia-Salcedo, José Antonio; Soriano**, Miguel

2017-04-01

Biocrusts are distributed in arid areas widely covering most of the soil surface and playing an essential role in the functioning of nitrogen cycle. The absence of biocrust coverage might affect the soil nitrogen content and the quantity and diversity of microbial communities in underlying biocrust soils. To analyse this mater, we have collected three underlying soils biocrusts samples dominated by the lichen Diploschistes diacapsis and Squamarina lentigera from Tabernas desert (southeast of Spain) at two extremes of its spatial distribution range: one with a high percentage of biocrust coverage and other with a huge degradation and low percentage of biocrust coverage in order to determine differences on the total nitrogen content and microbial communities from these underlying soils. DNA from these samples was isolated though a commercial kit and it was used as template for metagenomic analysis. We accomplished a sequencing of the amplicons V4-V5 of the 16S rRNA gene with Next-Generation Sequencing (NGS) Illumina MiSeq platform and a relative quantity of bacteria (rRNA 16S) and fungi (ITS1-5.8S) were conducted by quantitative qPCR. Total nitrogen was measured by the Kjeldahl method. Statistical analyses were based on ANOVAs, heatmap and Generalized Linear Models (GLM). The results showed 1.89E+09 bacteria per gram of soil in the high biocrust coverage position while 6.98E+08 microorganisms per gram of soil were found in the less favourable position according to the lower percentage of biocrust coverage. Similarly, 1.19E+12 was the amount of fungi per gram of soil located in the favourable position with higher biocrust coverage and 7.62E+11 was found in the unfavourable position. Furthermore, the soil under high percentage of biocrust coverage showed the greatest total nitrogen content (1.1 g kg-1) whereas the soil sampled under depressed percentage of biocrust coverage displayed the fewest quantity of total nitrogen content (0.9 g kg-1). Metagenomic and statistical analysis exhibited different bacteria communities according to underlying soils with unlike percentage of biocrust coverage. Opitutus and Adhaeribacter predominated in soil under high biocrust coverage percentage whereas Chelatococcus was found as prevalent bacteria community in soils under low biocrust coverage percentage. Our data illustrate that the percentage of biocrust coverage influence the total nitrogen content in underlying biocrust soils and also affects the amount and the variety of bacteria communities in these underlying soils. (*) Financial support by Marie Curie Intra-European Fellowship (FP7-577 PEOPLE-2013-IEF, Proposal n° 623393) and (**) by the Ministerio de Economía y Competitividad (MINECO) cofinanced with FEDER funds (project CGL2015-71709-R) is acknowledged.

Data Analysis Techniques for Physical Scientists

NASA Astrophysics Data System (ADS)

Pruneau, Claude A.

2017-10-01

Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.

Deploying digital health data to optimize influenza surveillance at national and local scales

PubMed Central

Arab, Ali; Viboud, Cécile; Grenfell, Bryan T.; Bansal, Shweta

2018-01-01

The surveillance of influenza activity is critical to early detection of epidemics and pandemics and the design of disease control strategies. Case reporting through a voluntary network of sentinel physicians is a commonly used method of passive surveillance for monitoring rates of influenza-like illness (ILI) worldwide. Despite its ubiquity, little attention has been given to the processes underlying the observation, collection, and spatial aggregation of sentinel surveillance data, and its subsequent effects on epidemiological understanding. We harnessed the high specificity of diagnosis codes in medical claims from a database that represented 2.5 billion visits from upwards of 120,000 United States healthcare providers each year. Among influenza seasons from 2002-2009 and the 2009 pandemic, we simulated limitations of sentinel surveillance systems such as low coverage and coarse spatial resolution, and performed Bayesian inference to probe the robustness of ecological inference and spatial prediction of disease burden. Our models suggest that a number of socio-environmental factors, in addition to local population interactions, state-specific health policies, as well as sampling effort may be responsible for the spatial patterns in U.S. sentinel ILI surveillance. In addition, we find that biases related to spatial aggregation were accentuated among areas with more heterogeneous disease risk, and sentinel systems designed with fixed reporting locations across seasons provided robust inference and prediction. With the growing availability of health-associated big data worldwide, our results suggest mechanisms for optimizing digital data streams to complement traditional surveillance in developed settings and enhance surveillance opportunities in developing countries. PMID:29513661

Human brain lesion-deficit inference remapped.

PubMed

Mah, Yee-Haur; Husain, Masud; Rees, Geraint; Nachev, Parashkev

2014-09-01

Our knowledge of the anatomical organization of the human brain in health and disease draws heavily on the study of patients with focal brain lesions. Historically the first method of mapping brain function, it is still potentially the most powerful, establishing the necessity of any putative neural substrate for a given function or deficit. Great inferential power, however, carries a crucial vulnerability: without stronger alternatives any consistent error cannot be easily detected. A hitherto unexamined source of such error is the structure of the high-dimensional distribution of patterns of focal damage, especially in ischaemic injury-the commonest aetiology in lesion-deficit studies-where the anatomy is naturally shaped by the architecture of the vascular tree. This distribution is so complex that analysis of lesion data sets of conventional size cannot illuminate its structure, leaving us in the dark about the presence or absence of such error. To examine this crucial question we assembled the largest known set of focal brain lesions (n = 581), derived from unselected patients with acute ischaemic injury (mean age = 62.3 years, standard deviation = 17.8, male:female ratio = 0.547), visualized with diffusion-weighted magnetic resonance imaging, and processed with validated automated lesion segmentation routines. High-dimensional analysis of this data revealed a hidden bias within the multivariate patterns of damage that will consistently distort lesion-deficit maps, displacing inferred critical regions from their true locations, in a manner opaque to replication. Quantifying the size of this mislocalization demonstrates that past lesion-deficit relationships estimated with conventional inferential methodology are likely to be significantly displaced, by a magnitude dependent on the unknown underlying lesion-deficit relationship itself. Past studies therefore cannot be retrospectively corrected, except by new knowledge that would render them redundant. Positively, we show that novel machine learning techniques employing high-dimensional inference can nonetheless accurately converge on the true locus. We conclude that current inferences about human brain function and deficits based on lesion mapping must be re-evaluated with methodology that adequately captures the high-dimensional structure of lesion data. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

NASA Astrophysics Data System (ADS)

Validi, AbdoulAhad

2014-03-01

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

Automatic Road Gap Detection Using Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

2011-09-01

Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

5 CFR 9901.202 - Coverage.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 3 2011-01-01 2011-01-01 false Coverage. 9901.202 Section 9901.202... (NSPS) Classification General § 9901.202 Coverage. (a) This subpart applies to eligible DoD employees... functional units are eligible for coverage under this subpart: (1) Employees and positions that would...

5 CFR 9901.202 - Coverage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Coverage. 9901.202 Section 9901.202... (NSPS) Classification General § 9901.202 Coverage. (a) This subpart applies to eligible DoD employees... functional units are eligible for coverage under this subpart: (1) Employees and positions that would...

Analyzing the test process using structural coverage

NASA Technical Reports Server (NTRS)

Ramsey, James; Basili, Victor R.

1985-01-01

A large, commercially developed FORTRAN program was modified to produce structural coverage metrics. The modified program was executed on a set of functionally generated acceptance tests and a large sample of operational usage cases. The resulting structural coverage metrics are combined with fault and error data to evaluate structural coverage. It was shown that in the software environment the functionally generated tests seem to be a good approximation of operational use. The relative proportions of the exercised statement subclasses change as the structural coverage of the program increases. A method was also proposed for evaluating if two sets of input data exercise a program in a similar manner. Evidence was provided that implies that in this environment, faults revealed in a procedure are independent of the number of times the procedure is executed and that it may be reasonable to use procedure coverage in software models that use statement coverage. Finally, the evidence suggests that it may be possible to use structural coverage to aid in the management of the acceptance test processed.

Joint coverage probability in a simulation study on Continuous-Time Markov Chain parameter estimation.

PubMed

Benoit, Julia S; Chan, Wenyaw; Doody, Rachelle S

2015-01-01

Parameter dependency within data sets in simulation studies is common, especially in models such as Continuous-Time Markov Chains (CTMC). Additionally, the literature lacks a comprehensive examination of estimation performance for the likelihood-based general multi-state CTMC. Among studies attempting to assess the estimation, none have accounted for dependency among parameter estimates. The purpose of this research is twofold: 1) to develop a multivariate approach for assessing accuracy and precision for simulation studies 2) to add to the literature a comprehensive examination of the estimation of a general 3-state CTMC model. Simulation studies are conducted to analyze longitudinal data with a trinomial outcome using a CTMC with and without covariates. Measures of performance including bias, component-wise coverage probabilities, and joint coverage probabilities are calculated. An application is presented using Alzheimer's disease caregiver stress levels. Comparisons of joint and component-wise parameter estimates yield conflicting inferential results in simulations from models with and without covariates. In conclusion, caution should be taken when conducting simulation studies aiming to assess performance and choice of inference should properly reflect the purpose of the simulation.

Framing Space: UK Newspaper Reporting of the Beagle 2 and Cassini-Huygens Space Missions

NASA Astrophysics Data System (ADS)

Jergovic, B.; Miller, S.

2008-05-01

Relatively little scholarly work has been done on looking at the portrayal of astronomy and space science in the media. This short article examines the UK press coverage of two space missions: the Beagle 2 mission to Mars and the Cassini-Huygens mission to Saturn and its moon Titan. In both cases, the leading scientists exerted a strong influence on what journalists reported, to the extent that some journalists appeared to be almost "embedded" in the mission. For the most part the coverage is positive in tone and the loss of the Beagle 2 spacecraft does not reflect badly on the (later) Cassini-Huygens coverage. Most journalists only covered the actual mission events and, in the case of Huygens, did not follow up to cover the peer-reviewed scientific articles that appeared later. Off-the-cuff comments made by scientists at the time of the missions were widely reported. There appears to be an appreciation by journalists and (by inference) their readership that this was science in the making, and that allowances should be made if these comments later turned out to be inaccurate.

Contrasting taxonomic stratification of microbial communities in two hypersaline meromictic lakes

PubMed Central

Andrei, Adrian-Ştefan; Robeson, Michael S; Baricz, Andreea; Coman, Cristian; Muntean, Vasile; Ionescu, Artur; Etiope, Giuseppe; Alexe, Mircea; Sicora, Cosmin Ionel; Podar, Mircea; Banciu, Horia Leonard

2015-01-01

Hypersaline meromictic lakes are extreme environments in which water stratification is associated with powerful physicochemical gradients and high salt concentrations. Furthermore, their physical stability coupled with vertical water column partitioning makes them important research model systems in microbial niche differentiation and biogeochemical cycling. Here, we compare the prokaryotic assemblages from Ursu and Fara Fund hypersaline meromictic lakes (Transylvanian Basin, Romania) in relation to their limnological factors and infer their role in elemental cycling by matching taxa to known taxon-specific biogeochemical functions. To assess the composition and structure of prokaryotic communities and the environmental factors that structure them, deep-coverage small subunit (SSU) ribosomal RNA (rDNA) amplicon sequencing, community domain-specific quantitative PCR and physicochemical analyses were performed on samples collected along depth profiles. The analyses showed that the lakes harbored multiple and diverse prokaryotic communities whose distribution mirrored the water stratification patterns. Ursu Lake was found to be dominated by Bacteria and to have a greater prokaryotic diversity than Fara Fund Lake that harbored an increased cell density and was populated mostly by Archaea within oxic strata. In spite of their contrasting diversity, the microbial populations indigenous to each lake pointed to similar physiological functions within carbon degradation and sulfate reduction. Furthermore, the taxonomy results coupled with methane detection and its stable C isotope composition indicated the presence of a yet-undescribed methanogenic group in the lakes' hypersaline monimolimnion. In addition, ultrasmall uncultivated archaeal lineages were detected in the chemocline of Fara Fund Lake, where the recently proposed Nanohaloarchaeota phylum was found to thrive. PMID:25932617

Estimation of Image Sensor Fill Factor Using a Single Arbitrary Image

PubMed Central

Wen, Wei; Khatibi, Siamak

2017-01-01

Achieving a high fill factor is a bottleneck problem for capturing high-quality images. There are hardware and software solutions to overcome this problem. In the solutions, the fill factor is known. However, this is an industrial secrecy by most image sensor manufacturers due to its direct effect on the assessment of the sensor quality. In this paper, we propose a method to estimate the fill factor of a camera sensor from an arbitrary single image. The virtual response function of the imaging process and sensor irradiance are estimated from the generation of virtual images. Then the global intensity values of the virtual images are obtained, which are the result of fusing the virtual images into a single, high dynamic range radiance map. A non-linear function is inferred from the original and global intensity values of the virtual images. The fill factor is estimated by the conditional minimum of the inferred function. The method is verified using images of two datasets. The results show that our method estimates the fill factor correctly with significant stability and accuracy from one single arbitrary image according to the low standard deviation of the estimated fill factors from each of images and for each camera. PMID:28335459

Theoretical aspects of studies of high coverage oxidation of the Cu(100) surface using low energy positrons

NASA Astrophysics Data System (ADS)

Fazleev, N. G.; Maddox, W. B.; Reed, J. A.

2011-03-01

The study of adsorption of oxygen on transition metal surface is important for the understanding of oxidation, heterogeneous catalysis, and metal corrosion. The structures formed on transition metal surfaces vary from simple adlayers of chemisorbed oxygen to more complex structures which results from diffusion of oxygen into the sub-surface regions. In this work we present the results of an ab-initio investigation of positron surface and bulk states and annihilation probabilities of surface-trapped positrons with relevant core electrons at the Cu(100) missing row reconstructed surface under conditions of high oxygen coverage. Calculations are performed for various surface and subsurface oxygen coverages ranging from 0.50 to 1.50 monolayers. Calculations are also performed for the on-surface adsorption of oxygen on the unreconstructed Cu(001) surface for coverages up to one monolayer to use for comparison. Estimates of the positron binding energy, positron work function, and annihilation characteristics reveal their sensitivity to atomic structure of the topmost layers of the surface and charge transfer. Theoretical results are compared with experimental data obtained from studies of oxidation of the Cu(100) surface using positron annihilation induced Auger electron spectroscopy.

In search of functional association from time-series microarray data based on the change trend and level of gene expression

PubMed Central

He, Feng; Zeng, An-Ping

2006-01-01

Background The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. Results In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC), includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC) method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC) based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological interactions, including 443 known protein interactions and some known cell cycle related regulatory interactions. It should be emphasized that the overlapping of gene pairs detected by the three methods is normally not very high, indicating a necessity of combining the different methods in search of functional association of genes from time-series data. For a p-value threshold of 1E-5 the percentage of process-identity and function-similarity gene pairs among the shared part of the three methods reaches 60.2% and 55.6% respectively, building a good basis for further experimental and functional study. Furthermore, the combined use of methods is important to infer more complete regulatory circuits and network as exemplified in this study. Conclusion The TC method can significantly augment the current major methods to infer functional linkages and biological network and is well suitable for exploring temporal relationships of gene expression in time-series data. PMID:16478547

Combining item response theory with multiple imputation to equate health assessment questionnaires.

PubMed

Gu, Chenyang; Gutman, Roee

2017-09-01

The assessment of patients' functional status across the continuum of care requires a common patient assessment tool. However, assessment tools that are used in various health care settings differ and cannot be easily contrasted. For example, the Functional Independence Measure (FIM) is used to evaluate the functional status of patients who stay in inpatient rehabilitation facilities, the Minimum Data Set (MDS) is collected for all patients who stay in skilled nursing facilities, and the Outcome and Assessment Information Set (OASIS) is collected if they choose home health care provided by home health agencies. All three instruments or questionnaires include functional status items, but the specific items, rating scales, and instructions for scoring different activities vary between the different settings. We consider equating different health assessment questionnaires as a missing data problem, and propose a variant of predictive mean matching method that relies on Item Response Theory (IRT) models to impute unmeasured item responses. Using real data sets, we simulated missing measurements and compared our proposed approach to existing methods for missing data imputation. We show that, for all of the estimands considered, and in most of the experimental conditions that were examined, the proposed approach provides valid inferences, and generally has better coverages, relatively smaller biases, and shorter interval estimates. The proposed method is further illustrated using a real data set. © 2016, The International Biometric Society.

ARACNe-AP: Gene Network Reverse Engineering through Adaptive Partitioning inference of Mutual Information. | Office of Cancer Genomics

Cancer.gov

The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable to deal with sample sets providing largely uneven coverage of the probability density space.

A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes

USGS Publications Warehouse

Arnett, Heather A.; Saros, Jasmine E.; Mast, M. Alisa

2012-01-01

Atmospheric deposition of reactive nitrogen (Nr) has enriched oligotrophic lakes with nitrogen (N) in many regions of the world and elicited dramatic changes in diatom community structure. The lakewater concentrations of nitrate that cause these community changes remain unclear, raising interest in the development of diatom-based transfer functions to infer nitrate. We developed a diatom calibration set using surface sediment samples from 46 high-elevation lakes across the Rocky Mountains of the western US, a region spanning an N deposition gradient from very low to moderate levels (<1 to 3.2 kg Nr ha−1 year−1 in wet deposition). Out of the fourteen measured environmental variables for these 46 lakes, ordination analysis identified that nitrate, specific conductance, total phosphorus, and hypolimnetic water temperature were related to diatom distributions. A transfer function was developed for nitrate and applied to a sedimentary diatom profile from Heart Lake in the central Rockies. The model coefficient of determination (bootstrapping validation) of 0.61 suggested potential for diatom-inferred reconstructions of lakewater nitrate concentrations over time, but a comparison of observed versus diatom-inferred nitrate values revealed the poor performance of this model at low nitrate concentrations. Resource physiology experiments revealed that nitrogen requirements of two key taxa were opposite to nitrate optima defined in the transfer function. Our data set reveals two underlying ecological constraints that impede the development of nitrate transfer functions in oligotrophic lakes: (1) even in lakes with nitrate concentrations below quantification (<1 μg L−1), diatom assemblages were already dominated by species indicative of moderate N enrichment; (2) N-limited oligotrophic lakes switch to P limitation after receiving only modest inputs of reactive N, shifting the controls on diatom species changes along the length of the nitrate gradient. These constraints suggest that quantitative inferences of nitrate from diatom assemblages will likely require experimental approaches.

5 CFR 9901.503 - Coverage.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 3 2011-01-01 2011-01-01 false Coverage. 9901.503 Section 9901.503... (NSPS) Staffing and Employment General § 9901.503 Coverage. (a) At his or her sole and exclusive... in DoD organizational and functional units are eligible for coverage under this subpart: (1...

5 CFR 9901.503 - Coverage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Coverage. 9901.503 Section 9901.503... (NSPS) Staffing and Employment General § 9901.503 Coverage. (a) At his or her sole and exclusive... in DoD organizational and functional units are eligible for coverage under this subpart: (1...

Rupture process of the September 12, 2007 Southern Sumatra earthquake from tsunami waveform inversion

NASA Astrophysics Data System (ADS)

Lorito, S.; Romano, F.; Piatanesi, A.

2007-12-01

The aim of this work is to infer the slip distribution and mean rupture velocity along the rupture zone of the 12 September 2007 Southern Sumatra, Indonesia from available tide-gauge records of the tsunami. We select waveforms from 12 stations, distributed along the west coast of Sumatra and in the whole Indian Ocean (11 GLOSS stations and 1 DART buoy). We assume the fault plane and the slip direction to be consistent with both the geometry of the subducting plate and the early focal mechanism solutions. Then we subdivide the fault plane into several subfaults (both along strike and down dip) and compute the corresponding Green's functions by numerical solution of the shallow water equations through a finite difference method. The slip distribution and rupture velocity are determined simultaneously by means of a simulated annealing technique. We compare the recorded and synthetic waveforms in the time domain, using a cost function that is a trade-off between the L1 and L2 norms. Preliminary synthetic checkerboard tests, using the station coverage and the sampling interval of the available data, indicate that the main features of the rupture process may be robustly inverted.

Causal Mediation Analysis for the Cox Proportional Hazards Model with a Smooth Baseline Hazard Estimator.

PubMed

Wang, Wei; Albert, Jeffrey M

2017-08-01

An important problem within the social, behavioral, and health sciences is how to partition an exposure effect (e.g. treatment or risk factor) among specific pathway effects and to quantify the importance of each pathway. Mediation analysis based on the potential outcomes framework is an important tool to address this problem and we consider the estimation of mediation effects for the proportional hazards model in this paper. We give precise definitions of the total effect, natural indirect effect, and natural direct effect in terms of the survival probability, hazard function, and restricted mean survival time within the standard two-stage mediation framework. To estimate the mediation effects on different scales, we propose a mediation formula approach in which simple parametric models (fractional polynomials or restricted cubic splines) are utilized to approximate the baseline log cumulative hazard function. Simulation study results demonstrate low bias of the mediation effect estimators and close-to-nominal coverage probability of the confidence intervals for a wide range of complex hazard shapes. We apply this method to the Jackson Heart Study data and conduct sensitivity analysis to assess the impact on the mediation effects inference when the no unmeasured mediator-outcome confounding assumption is violated.

Confidence intervals for a difference between lognormal means in cluster randomization trials.

PubMed

Poirier, Julia; Zou, G Y; Koval, John

2017-04-01

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

Evolution of Western Mediterranean Sea Surface Temperature between 1985 and 2005: a complementary study in situ, satellite and modelling approaches

NASA Astrophysics Data System (ADS)

Troupin, C.; Lenartz, F.; Sirjacobs, D.; Alvera-Azcárate, A.; Barth, A.; Ouberdous, M.; Beckers, J.-M.

2009-04-01

In order to evaluate the variability of the sea surface temperature (SST) in the Western Mediterranean Sea between 1985 and 2005, an integrated approach combining geostatistical tools and modelling techniques has been set up. The objectives are: underline the capability of each tool to capture characteristic phenomena, compare and assess the quality of their outputs, infer an interannual trend from the results. Diva (Data Interpolating Variationnal Analysis, Brasseur et al. (1996) Deep-Sea Res.) was applied on a collection of in situ data gathered from various sources (World Ocean Database 2005, Hydrobase2, Coriolis and MedAtlas2), from which duplicates and suspect values were removed. This provided monthly gridded fields in the region of interest. Heterogeneous time data coverage was taken into account by computing and removing the annual trend, provided by Diva detrending tool. Heterogeneous correlation length was applied through an advection constraint. Statistical technique DINEOF (Data Interpolation with Empirical Orthogonal Functions, Alvera-Azc

ASSESSING AND COMBINING RELIABILITY OF PROTEIN INTERACTION SOURCES

PubMed Central

LEACH, SONIA; GABOW, AARON; HUNTER, LAWRENCE; GOLDBERG, DEBRA S.

2008-01-01

Integrating diverse sources of interaction information to create protein networks requires strategies sensitive to differences in accuracy and coverage of each source. Previous integration approaches calculate reliabilities of protein interaction information sources based on congruity to a designated ‘gold standard.’ In this paper, we provide a comparison of the two most popular existing approaches and propose a novel alternative for assessing reliabilities which does not require a gold standard. We identify a new method for combining the resultant reliabilities and compare it against an existing method. Further, we propose an extrinsic approach to evaluation of reliability estimates, considering their influence on the downstream tasks of inferring protein function and learning regulatory networks from expression data. Results using this evaluation method show 1) our method for reliability estimation is an attractive alternative to those requiring a gold standard and 2) the new method for combining reliabilities is less sensitive to noise in reliability assignments than the similar existing technique. PMID:17990508

Systematic inference of functional phosphorylation events in yeast metabolism.

PubMed

Chen, Yu; Wang, Yonghong; Nielsen, Jens

2017-07-01

Protein phosphorylation is a post-translational modification that affects proteins by changing their structure and conformation in a rapid and reversible way, and it is an important mechanism for metabolic regulation in cells. Phosphoproteomics enables high-throughput identification of phosphorylation events on metabolic enzymes, but identifying functional phosphorylation events still requires more detailed biochemical characterization. Therefore, development of computational methods for investigating unknown functions of a large number of phosphorylation events identified by phosphoproteomics has received increased attention. We developed a mathematical framework that describes the relationship between phosphorylation level of a metabolic enzyme and the corresponding flux through the enzyme. Using this framework, it is possible to quantitatively estimate contribution of phosphorylation events to flux changes. We showed that phosphorylation regulation analysis, combined with a systematic workflow and correlation analysis, can be used for inference of functional phosphorylation events in steady and dynamic conditions, respectively. Using this analysis, we assigned functionality to phosphorylation events of 17 metabolic enzymes in the yeast Saccharomyces cerevisiae , among which 10 are novel. Phosphorylation regulation analysis cannot only be extended for inference of other functional post-translational modifications but also be a promising scaffold for multi-omics data integration in systems biology. Matlab codes for flux balance analysis in this study are available in Supplementary material. yhwang@ecust.edu.cn or nielsenj@chalmers.se. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

International Satellite Cloud Climatology Project (ISCCP) Ice Snow Product in Native (NAT) Format (ISCCP_ICESNOW_NAT)

NASA Technical Reports Server (NTRS)

Rossow, William B. (Principal Investigator)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=112 Km; Longitude_Resolution=112 Km; Temporal_Resolution=5-day].

EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes.

PubMed

Kumar, Narendra; Skolnick, Jeffrey

2012-10-15

High-quality enzyme function annotation is essential for understanding the biochemistry, metabolism and disease processes of organisms. Previously, we developed a multi-component high-precision enzyme function predictor, EFICAz(2) (enzyme function inference by a combined approach). Here, we present an updated improved version, EFICAz(2.5), that is trained on a significantly larger data set of enzyme sequences and PROSITE patterns. We also present the results of the application of EFICAz(2.5) to the enzyme reannotation of 396 genomes cataloged in the ENSEMBL database. The EFICAz(2.5) server and database is freely available with a use-friendly interface at http://cssb.biology.gatech.edu/EFICAz2.5.

Using the underlying biological organization of the Mycobacterium tuberculosis functional network for protein function prediction.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2012-07-01

Despite ever-increasing amounts of sequence and functional genomics data, there is still a deficiency of functional annotation for many newly sequenced proteins. For Mycobacterium tuberculosis (MTB), more than half of its genome is still uncharacterized, which hampers the search for new drug targets within the bacterial pathogen and limits our understanding of its pathogenicity. As for many other genomes, the annotations of proteins in the MTB proteome were generally inferred from sequence homology, which is effective but its applicability has limitations. We have carried out large-scale biological data integration to produce an MTB protein functional interaction network. Protein functional relationships were extracted from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and additional functional interactions from microarray, sequence and protein signature data. The confidence level of protein relationships in the additional functional interaction data was evaluated using a dynamic data-driven scoring system. This functional network has been used to predict functions of uncharacterized proteins using Gene Ontology (GO) terms, and the semantic similarity between these terms measured using a state-of-the-art GO similarity metric. To achieve better trade-off between improvement of quality, genomic coverage and scalability, this prediction is done by observing the key principles driving the biological organization of the functional network. This study yields a new functionally characterized MTB strain CDC1551 proteome, consisting of 3804 and 3698 proteins out of 4195 with annotations in terms of the biological process and molecular function ontologies, respectively. These data can contribute to research into the Development of effective anti-tubercular drugs with novel biological mechanisms of action. Copyright © 2011 Elsevier B.V. All rights reserved.

Marginally specified priors for non-parametric Bayesian estimation

PubMed Central

Kessler, David C.; Hoff, Peter D.; Dunson, David B.

2014-01-01

Summary Prior specification for non-parametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. A statistician is unlikely to have informed opinions about all aspects of such a parameter but will have real information about functionals of the parameter, such as the population mean or variance. The paper proposes a new framework for non-parametric Bayes inference in which the prior distribution for a possibly infinite dimensional parameter is decomposed into two parts: an informative prior on a finite set of functionals, and a non-parametric conditional prior for the parameter given the functionals. Such priors can be easily constructed from standard non-parametric prior distributions in common use and inherit the large support of the standard priors on which they are based. Additionally, posterior approximations under these informative priors can generally be made via minor adjustments to existing Markov chain approximation algorithms for standard non-parametric prior distributions. We illustrate the use of such priors in the context of multivariate density estimation using Dirichlet process mixture models, and in the modelling of high dimensional sparse contingency tables. PMID:25663813

Identification and correction of systematic error in high-throughput sequence data

PubMed Central

2011-01-01

Background A feature common to all DNA sequencing technologies is the presence of base-call errors in the sequenced reads. The implications of such errors are application specific, ranging from minor informatics nuisances to major problems affecting biological inferences. Recently developed "next-gen" sequencing technologies have greatly reduced the cost of sequencing, but have been shown to be more error prone than previous technologies. Both position specific (depending on the location in the read) and sequence specific (depending on the sequence in the read) errors have been identified in Illumina and Life Technology sequencing platforms. We describe a new type of systematic error that manifests as statistically unlikely accumulations of errors at specific genome (or transcriptome) locations. Results We characterize and describe systematic errors using overlapping paired reads from high-coverage data. We show that such errors occur in approximately 1 in 1000 base pairs, and that they are highly replicable across experiments. We identify motifs that are frequent at systematic error sites, and describe a classifier that distinguishes heterozygous sites from systematic error. Our classifier is designed to accommodate data from experiments in which the allele frequencies at heterozygous sites are not necessarily 0.5 (such as in the case of RNA-Seq), and can be used with single-end datasets. Conclusions Systematic errors can easily be mistaken for heterozygous sites in individuals, or for SNPs in population analyses. Systematic errors are particularly problematic in low coverage experiments, or in estimates of allele-specific expression from RNA-Seq data. Our characterization of systematic error has allowed us to develop a program, called SysCall, for identifying and correcting such errors. We conclude that correction of systematic errors is important to consider in the design and interpretation of high-throughput sequencing experiments. PMID:22099972

45 CFR 155.735 - Termination of coverage.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Functions: Small Business Health Options Program (SHOP) § 155.735 Termination of coverage. (a) General requirements. The SHOP must determine the timing, form, and manner in which coverage in a QHP may be terminated. (b) Termination of employer group health coverage at the request of the employer. (1) The SHOP must...

45 CFR 155.735 - Termination of coverage.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Functions: Small Business Health Options Program (SHOP) § 155.735 Termination of coverage. (a) General requirements. The SHOP must determine the timing, form, and manner in which coverage in a QHP may be terminated. (b) Termination of employer group health coverage at the request of the employer. (1) The SHOP must...

5 CFR 9901.302 - Coverage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Coverage. 9901.302 Section 9901.302... (NSPS) Pay and Pay Administration General § 9901.302 Coverage. (a) This subpart applies to eligible DoD... organizational and functional units are eligible for coverage under this subpart: (1) Employees and positions who...

5 CFR 9901.302 - Coverage.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 3 2011-01-01 2011-01-01 false Coverage. 9901.302 Section 9901.302... (NSPS) Pay and Pay Administration General § 9901.302 Coverage. (a) This subpart applies to eligible DoD... organizational and functional units are eligible for coverage under this subpart: (1) Employees and positions who...

Linear-array based full-view high-resolution photoacoustic computed tomography of whole mouse brain functions in vivo

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Pengfei; Wang, Lihong V.

2018-02-01

Photoacoustic computed tomography (PACT) is a non-invasive imaging technique offering high contrast, high resolution, and deep penetration in biological tissues. We report a photoacoustic computed tomography (PACT) system equipped with a high frequency linear array for anatomical and functional imaging of the mouse whole brain. The linear array was rotationally scanned in the coronal plane to achieve the full-view coverage. We investigated spontaneous neural activities in the deep brain by monitoring the hemodynamics and observed strong interhemispherical correlations between contralateral regions, both in the cortical layer and in the deep regions.

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

PubMed

Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D

2002-01-01

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.

Reference-dependent risk sensitivity as rational inference.

PubMed

Denrell, Jerker C

2015-07-01

Existing explanations of reference-dependent risk sensitivity attribute it to cognitive imperfections and heuristic choice processes. This article shows that behavior consistent with an S-shaped value function could be an implication of rational inferences about the expected values of alternatives. Theoretically, I demonstrate that even a risk-neutral Bayesian decision maker, who is uncertain about the reliability of observations, should use variability in observed outcomes as a predictor of low expected value for outcomes above a reference level, and as a predictor of high expected value for outcomes below a reference level. Empirically, I show that combining past outcomes using an S-shaped value function leads to accurate predictions about future values. The theory also offers a rationale for why risk sensitivity consistent with an inverse S-shaped value function should occur in experiments on decisions from experience with binary payoff distributions. (c) 2015 APA, all rights reserved).

Expression of Lithospheric Shear Zones in Rock Elasticity Tensors and in Anisotropic Receiver Functions and Inferences on the Roots of Faults and Lower Crustal Deformation

NASA Astrophysics Data System (ADS)

Schulte-Pelkum, V.; Condit, C.; Brownlee, S. J.; Mahan, K. H.; Raju, A.

2016-12-01

We investigate shear zone-related deformation fabric from field samples, its dependence on conditions during fabric formation, and its detection in situ using seismic data. We present a compilation of published rock elasticity tensors measured in the lab or calculated from middle and deep crustal samples and compare the strength and symmetry of seismic anisotropy as a function of location within a shear zone, pressure-temperature conditions during formation, and composition. Common strengths of seismic anisotropy range from a few to 10 percent. Apart from the typically considered fabric in mica, amphibole and quartz also display fabrics that induce seismic anisotropy, although the interaction between different minerals can result in destructive interference in the total measured anisotropy. The availability of full elasticity tensors enables us to predict the seismic signal from rock fabric at depth. A method particularly sensitive to anisotropy of a few percent in localized zones of strain at depth is the analysis of azimuthally dependent amplitude and polarity variations in teleseismic receiver functions. We present seismic results from California and Colorado. In California, strikes of seismically detected fabric show a strong alignment with current strike-slip motion between the Pacific and North American plates, with high signal strength near faults and from depths below the brittle-ductile transition. These results suggest that the faults have roots in the ductile crust; determining the degree of localization, i.e., the width of the fault-associated shear zones, would require an analysis with denser station coverage, which now exists in some areas. In Colorado, strikes of seismically detected fabric show a broad NW-SE to NNW-SSE alignment that may be related to Proterozoic fabric developed at high temperatures, but locally may also show isotropic dipping contrasts associated with Laramide faulting. The broad trend is punctuated with NE-SW-trending strikes parallel to exhumed and highly localized structures such as the Idaho Springs-Ralston and Black Canyon shear zones. In either case, denser seismic studies should elucidate the width of the deep seismic expression of the shear zones.

An integrative method for testing form–function linkages and reconstructed evolutionary pathways of masticatory specialization

PubMed Central

Tseng, Z. Jack; Flynn, John J.

2015-01-01

Morphology serves as a ubiquitous proxy in macroevolutionary studies to identify potential adaptive processes and patterns. Inferences of functional significance of phenotypes or their evolution are overwhelmingly based on data from living taxa. Yet, correspondence between form and function has been tested in only a few model species, and those linkages are highly complex. The lack of explicit methodologies to integrate form and function analyses within a deep-time and phylogenetic context weakens inferences of adaptive morphological evolution, by invoking but not testing form–function linkages. Here, we provide a novel approach to test mechanical properties at reconstructed ancestral nodes/taxa and the strength and direction of evolutionary pathways in feeding biomechanics, in a case study of carnivorous mammals. Using biomechanical profile comparisons that provide functional signals for the separation of feeding morphologies, we demonstrate, using experimental optimization criteria on estimation of strength and direction of functional changes on a phylogeny, that convergence in mechanical properties and degree of evolutionary optimization can be decoupled. This integrative approach is broadly applicable to other clades, by using quantitative data and model-based tests to evaluate interpretations of function from morphology and functional explanations for observed macroevolutionary pathways. PMID:25994295

Benchmarking Inverse Statistical Approaches for Protein Structure and Design with Exactly Solvable Models.

PubMed

Jacquin, Hugo; Gilson, Amy; Shakhnovich, Eugene; Cocco, Simona; Monasson, Rémi

2016-05-01

Inverse statistical approaches to determine protein structure and function from Multiple Sequence Alignments (MSA) are emerging as powerful tools in computational biology. However the underlying assumptions of the relationship between the inferred effective Potts Hamiltonian and real protein structure and energetics remain untested so far. Here we use lattice protein model (LP) to benchmark those inverse statistical approaches. We build MSA of highly stable sequences in target LP structures, and infer the effective pairwise Potts Hamiltonians from those MSA. We find that inferred Potts Hamiltonians reproduce many important aspects of 'true' LP structures and energetics. Careful analysis reveals that effective pairwise couplings in inferred Potts Hamiltonians depend not only on the energetics of the native structure but also on competing folds; in particular, the coupling values reflect both positive design (stabilization of native conformation) and negative design (destabilization of competing folds). In addition to providing detailed structural information, the inferred Potts models used as protein Hamiltonian for design of new sequences are able to generate with high probability completely new sequences with the desired folds, which is not possible using independent-site models. Those are remarkable results as the effective LP Hamiltonians used to generate MSA are not simple pairwise models due to the competition between the folds. Our findings elucidate the reasons for the success of inverse approaches to the modelling of proteins from sequence data, and their limitations.

Understanding the pseudocapacitance of RuO2 from joint density functional theory

NASA Astrophysics Data System (ADS)

Zhan, Cheng; Jiang, De-en

2016-11-01

Pseudocapacitors have been experimentally studied for many years in electric energy storage. However, first principles understanding of the pseudocapacitive behavior is still not satisfactory due to the complexity involved in modeling electrochemistry. In this paper, we applied joint density functional theory (JDFT) to simulate the pseudocapacitive behavior of RuO2, a prototypical material, in a model electrolyte. We obtained from JDFT a capacitive curve which showed a redox peak position comparable to that in the experimental cyclic voltammetry (CV) curve. We found that the experimental turning point from double-layer to pseudocapacitive charge storage at low scan rates could be explained by the hydrogen adsorption at low coverage. As the electrode voltage becomes more negative, H coverage increases and causes the surface-structure change, leading to bended -OH bonds at the on-top oxygen atoms and large capacitance. This H coverage-dependent capacitance can explain the high pseudocapacitance of hydrous RuO2. Our work here provides a first principles understanding of the pseudocapacitance for RuO2 in particular and for transition-metal oxides in general.

Using Geographic Information Systems and Spatial Analysis Methods to Assess Household Water Access and Sanitation Coverage in the SHINE Trial.

PubMed

Ntozini, Robert; Marks, Sara J; Mangwadu, Goldberg; Mbuya, Mduduzi N N; Gerema, Grace; Mutasa, Batsirai; Julian, Timothy R; Schwab, Kellogg J; Humphrey, Jean H; Zungu, Lindiwe I

2015-12-15

Access to water and sanitation are important determinants of behavioral responses to hygiene and sanitation interventions. We estimated cluster-specific water access and sanitation coverage to inform a constrained randomization technique in the SHINE trial. Technicians and engineers inspected all public access water sources to ascertain seasonality, function, and geospatial coordinates. Households and water sources were mapped using open-source geospatial software. The distance from each household to the nearest perennial, functional, protected water source was calculated, and for each cluster, the median distance and the proportion of households within <500 m and >1500 m of such a water source. Cluster-specific sanitation coverage was ascertained using a random sample of 13 households per cluster. These parameters were included as covariates in randomization to optimize balance in water and sanitation access across treatment arms at the start of the trial. The observed high variability between clusters in both parameters suggests that constraining on these factors was needed to reduce risk of bias. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America.

Generalized Bootstrap Method for Assessment of Uncertainty in Semivariogram Inference

USGS Publications Warehouse

Olea, R.A.; Pardo-Iguzquiza, E.

2011-01-01

The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap. ?? 2010 International Association for Mathematical Geosciences.

Past and present cosmic structure in the SDSS DR7 main sample

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jasche, J.; Leclercq, F.; Wandelt, B.D., E-mail: jasche@iap.fr, E-mail: florent.leclercq@polytechnique.org, E-mail: wandelt@iap.fr

2015-01-01

We present a chrono-cosmography project, aiming at the inference of the four dimensional formation history of the observed large scale structure from its origin to the present epoch. To do so, we perform a full-scale Bayesian analysis of the northern galactic cap of the Sloan Digital Sky Survey (SDSS) Data Release 7 main galaxy sample, relying on a fully probabilistic, physical model of the non-linearly evolved density field. Besides inferring initial conditions from observations, our methodology naturally and accurately reconstructs non-linear features at the present epoch, such as walls and filaments, corresponding to high-order correlation functions generated by late-time structuremore » formation. Our inference framework self-consistently accounts for typical observational systematic and statistical uncertainties such as noise, survey geometry and selection effects. We further account for luminosity dependent galaxy biases and automatic noise calibration within a fully Bayesian approach. As a result, this analysis provides highly-detailed and accurate reconstructions of the present density field on scales larger than ∼ 3 Mpc/h, constrained by SDSS observations. This approach also leads to the first quantitative inference of plausible formation histories of the dynamic large scale structure underlying the observed galaxy distribution. The results described in this work constitute the first full Bayesian non-linear analysis of the cosmic large scale structure with the demonstrated capability of uncertainty quantification. Some of these results will be made publicly available along with this work. The level of detail of inferred results and the high degree of control on observational uncertainties pave the path towards high precision chrono-cosmography, the subject of simultaneously studying the dynamics and the morphology of the inhomogeneous Universe.« less

Opto-mechanical design of a new cross dispersion unit for the CRIRES+ high resolution spectrograph for the VLT

NASA Astrophysics Data System (ADS)

Lizon, Jean Louis; Klein, Barbara; Oliva, Ernesto; Löwinger, Tom; Anglada Escude, Guillem; Baade, Dietrich; Bristow, Paul; Dorn, Reinhold J.; Follert, Roman; Grunhut, Jason; Hatzes, Artie; Heiter, Ulrike; Ives, Derek; Jung, Yves; Kerber, Florian; Lockhart, Matt; Marquart, Thomas; Origlia, Livia; Pasquini, Luca; Paufique, Jerome; Piskunov, N.; Pozna, Eszter; Reiners, Ansgar; Smette, Alain; Smoker, Jonathan; Seemann, Ulf; Stempels, Eric; Valenti, Elena

2014-07-01

CRIRES is one of the few IR (0.92-5.2 μm) high-resolution spectrographs in operation at the VLT since 2006. Despite good performance it suffers a limitation that significantly hampers its ability: a small spectral coverage per exposure. The CRIRES upgrade (CRIRES+) proposes to transform CRIRES into a cross-dispersed spectrograph while maintaining the high resolution (100000) and increasing the wavelength coverage by a factor 10 compared to the current capabilities. A major part of the upgrade is the exchange of the actual cryogenic pre-disperser module by a new cross disperser unit. In addition to a completely new optical design, a number of important changes are required on key components and functions like the slit unit and detectors units. We will outline the design of these new units fitting inside a predefined and restricted space. The mechanical design of the new functions including a description and analysis will be presented. Finally we will present the strategy for the implementation of the changes.

Intermediate scale plasma density irregularities in the polar ionosphere inferred from radio occultation

NASA Astrophysics Data System (ADS)

Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O. P.; Butala, M.; Mannucci, A. J.

2014-12-01

In this research, we report intermediate scale plasma density irregularities in the high-latitude ionosphere inferred from high-resolution radio occultation (RO) measurements in the CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) - GPS (Global Positioning System) satellites radio link. The high inclination of the CASSIOPE satellite and high rate of signal receptionby the occultation antenna of the GPS Attitude, Positioning and Profiling (GAP) instrument on the Enhanced Polar Outflow Probe platform on CASSIOPE enable a high temporal and spatial resolution investigation of the dynamics of the polar ionosphere, magnetosphere-ionospherecoupling, solar wind effects, etc. with unprecedented details compared to that possible in the past. We have carried out high spatial resolution analysis in altitude and geomagnetic latitude of scintillation-producing plasma density irregularities in the polar ionosphere. Intermediate scale, scintillation-producing plasma density irregularities, which corresponds to 2 to 40 km spatial scales were inferred by applying multi-scale spectral analysis on the RO phase delay measurements. Using our multi-scale spectral analysis approach and Polar Operational Environmental Satellites (POES) and Defense Meteorological Satellite Program (DMSP) observations, we infer that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap regions. In specific terms, we found that large length scales and and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap region. Hence, the irregularity scales and phase scintillation characteristics are a function of the solar wind and the magnetospheric forcing. Multi-scale analysis may become a powerful diagnostic tool for characterizing how the ionosphere is dynamically driven by these factors.

An Agent-Based Model of School Closing in Under-Vacccinated Communities During Measles Outbreaks.

PubMed

Getz, Wayne M; Carlson, Colin; Dougherty, Eric; Porco Francis, Travis C; Salter, Richard

2016-04-01

The winter 2014-15 measles outbreak in the US represents a significant crisis in the emergence of a functionally extirpated pathogen. Conclusively linking this outbreak to decreases in the measles/mumps/rubella (MMR) vaccination rate (driven by anti-vaccine sentiment) is critical to motivating MMR vaccination. We used the NOVA modeling platform to build a stochastic, spatially-structured, individual-based SEIR model of outbreaks, under the assumption that R 0 ≈ 7 for measles. We show this implies that herd immunity requires vaccination coverage of greater than approximately 85%. We used a network structured version of our NOVA model that involved two communities, one at the relatively low coverage of 85% coverage and one at the higher coverage of 95%, both of which had 400-student schools embedded, as well as students occasionally visiting superspreading sites (e.g. high-density theme parks, cinemas, etc.). These two vaccination coverage levels are within the range of values occurring across California counties. Transmission rates at schools and superspreading sites were arbitrarily set to respectively 5 and 15 times background community rates. Simulations of our model demonstrate that a 'send unvaccinated students home' policy in low coverage counties is extremely effective at shutting down outbreaks of measles.

An Agent-Based Model of School Closing in Under-Vacccinated Communities During Measles Outbreaks

PubMed Central

Getz, Wayne M.; Carlson, Colin; Dougherty, Eric; Porco, Travis C.; Salter, Richard

2016-01-01

The winter 2014–15 measles outbreak in the US represents a significant crisis in the emergence of a functionally extirpated pathogen. Conclusively linking this outbreak to decreases in the measles/mumps/rubella (MMR) vaccination rate (driven by anti-vaccine sentiment) is critical to motivating MMR vaccination. We used the NOVA modeling platform to build a stochastic, spatially-structured, individual-based SEIR model of outbreaks, under the assumption that R0 ≈ 7 for measles. We show this implies that herd immunity requires vaccination coverage of greater than approximately 85%. We used a network structured version of our NOVA model that involved two communities, one at the relatively low coverage of 85% coverage and one at the higher coverage of 95%, both of which had 400-student schools embedded, as well as students occasionally visiting superspreading sites (e.g. high-density theme parks, cinemas, etc.). These two vaccination coverage levels are within the range of values occurring across California counties. Transmission rates at schools and superspreading sites were arbitrarily set to respectively 5 and 15 times background community rates. Simulations of our model demonstrate that a ‘send unvaccinated students home’ policy in low coverage counties is extremely effective at shutting down outbreaks of measles. PMID:27668297

On the Accuracy of Language Trees

PubMed Central

Pompei, Simone; Loreto, Vittorio; Tria, Francesca

2011-01-01

Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical, phonological, syntactic) features or characters for many different languages: a set of parallel corpora whose compilation represents a paramount achievement in linguistics. From this perspective the reconstruction of language trees is an example of inverse problems: starting from present, incomplete and often noisy, information, one aims at inferring the most likely past evolutionary history. A fundamental issue in inverse problems is the evaluation of the inference made. A standard way of dealing with this question is to generate data with artificial models in order to have full access to the evolutionary process one is going to infer. This procedure presents an intrinsic limitation: when dealing with real data sets, one typically does not know which model of evolution is the most suitable for them. A possible way out is to compare algorithmic inference with expert classifications. This is the point of view we take here by conducting a thorough survey of the accuracy of reconstruction methods as compared with the Ethnologue expert classifications. We focus in particular on state-of-the-art distance-based methods for phylogeny reconstruction using worldwide linguistic databases. In order to assess the accuracy of the inferred trees we introduce and characterize two generalizations of standard definitions of distances between trees. Based on these scores we quantify the relative performances of the distance-based algorithms considered. Further we quantify how the completeness and the coverage of the available databases affect the accuracy of the reconstruction. Finally we draw some conclusions about where the accuracy of the reconstructions in historical linguistics stands and about the leading directions to improve it. PMID:21674034

Colorimetric Detection of Small Molecules in Complex Matrixes via Target-Mediated Growth of Aptamer-Functionalized Gold Nanoparticles.

PubMed

Soh, Jun Hui; Lin, Yiyang; Rana, Subinoy; Ying, Jackie Y; Stevens, Molly M

2015-08-04

A versatile and sensitive colorimetric assay that allows the rapid detection of small-molecule targets using the naked eye is demonstrated. The working principle of the assay integrates aptamer-target recognition and the aptamer-controlled growth of gold nanoparticles (Au NPs). Aptamer-target interactions modulate the amount of aptamer strands adsorbed on the surface of aptamer-functionalized Au NPs via desorption of the aptamer strands when target molecules bind with the aptamer. Depending on the resulting aptamer coverage, Au NPs grow into morphologically varied nanostructures, which give rise to different colored solutions. Au NPs with low aptamer coverage grow into spherical NPs, which produce red-colored solutions, whereas Au NPs with high aptamer coverage grow into branched NPs, which produce blue-colored solutions. We achieved visible colorimetric response and nanomolar detection limits for the detection of ochratoxin A (1 nM) in red wine samples, as well as cocaine (1 nM) and 17β-estradiol (0.2 nM) in spiked synthetic urine and saliva, respectively. The detection limits were well within clinically and physiologically relevant ranges, and below the maximum food safety limits. The assay is highly sensitive, specific, and able to detect an array of analytes rapidly without requiring sophisticated equipment, making it relevant for many applications, such as high-throughput drug and clinical screening, food sampling, and diagnostics. Furthermore, the assay is easily adapted as a chip-based platform for rapid and portable target detection.

A flow-pulse adsorption-microcalorimetry system for studies of adsorption processes on powder catalysts

NASA Astrophysics Data System (ADS)

You, Rui; Li, Zhaorui; Zeng, Hongyu; Huang, Weixin

2018-06-01

A pulse chemisorption system combining a Tian-Calvet microcalorimeter (Setaram Sensys EVO 600) and an automated chemisorption apparatus (Micromeritics Autochem II 2920) was established to accurately measure differential adsorption heats of gas molecules' chemisorption on solid surfaces in a flow-pulse mode. Owing to high sensitivity and high degree of automation in a wide range of temperatures from -100 to 600 °C, this coupled system can present adsorption heats as a function of adsorption temperature and adsorbate coverage. The functions of this system were demonstrated by successful measurements of CO adsorption heats on Pd surfaces at various temperatures and also at different CO coverages by varying the CO concentration in the pulse dose. Key parameters, including adsorption amounts, integral adsorption heats, and differential adsorption heats of CO adsorption on a Pd/CeO2 catalyst, were acquired. Our adsorption-microcalorimetry system provides a powerful technique for the investigation of adsorption processes on powder catalysts.

The Orbit of the Gamma-Ray Binary 1FGL J1018.6−5856

DOE Office of Scientific and Technical Information (OSTI.GOV)

Monageng, I. M.; McBride, V. A.; Kniazev, A. Y.

2017-09-20

Gamma-ray binaries are a small subclass of the high mass X-ray binary population that exhibit emission across the whole electromagnetic spectrum. We present the radial velocities of 1FGL J1018.6−5856 based on the observations obtained with the Southern African Large Telescope. We combine our measurements with those published in the literature to get a broad phase coverage. The mass function obtained supports a neutron star compact object, although a black hole mass is possible for the very low inclination angles. The improved phase coverage allows constraints to be placed on the orbital eccentricity ( e = 0.31 ± 0.16), which agreesmore » with the estimates from the high-energy data.« less

Less is More: Membrane Protein Digestion Beyond Urea–Trypsin Solution for Next-level Proteomics*

PubMed Central

Zhang, Xi

2015-01-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea–trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting—not destroying—structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. PMID:26081834

Standardised Benchmarking in the Quest for Orthologs

PubMed Central

Altenhoff, Adrian M.; Boeckmann, Brigitte; Capella-Gutierrez, Salvador; Dalquen, Daniel A.; DeLuca, Todd; Forslund, Kristoffer; Huerta-Cepas, Jaime; Linard, Benjamin; Pereira, Cécile; Pryszcz, Leszek P.; Schreiber, Fabian; Sousa da Silva, Alan; Szklarczyk, Damian; Train, Clément-Marie; Bork, Peer; Lecompte, Odile; von Mering, Christian; Xenarios, Ioannis; Sjölander, Kimmen; Juhl Jensen, Lars; Martin, Maria J.; Muffato, Matthieu; Gabaldón, Toni; Lewis, Suzanna E.; Thomas, Paul D.; Sonnhammer, Erik; Dessimoz, Christophe

2016-01-01

The identification of evolutionarily related genes across different species—orthologs in particular—forms the backbone of many comparative, evolutionary, and functional genomic analyses. Achieving high accuracy in orthology inference is thus essential. Yet the true evolutionary history of genes, required to ascertain orthology, is generally unknown. Furthermore, orthologs are used for very different applications across different phyla, with different requirements in terms of the precision-recall trade-off. As a result, assessing the performance of orthology inference methods remains difficult for both users and method developers. Here, we present a community effort to establish standards in orthology benchmarking and facilitate orthology benchmarking through an automated web-based service (http://orthology.benchmarkservice.org). Using this new service, we characterise the performance of 15 well-established orthology inference methods and resources on a battery of 20 different benchmarks. Standardised benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimal requirement for new tools and resources, and guides the development of more accurate orthology inference methods. PMID:27043882

Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes

NASA Astrophysics Data System (ADS)

Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.

2013-12-01

Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.

Roughening of Pt nanoparticles induced by surface-oxide formation.

PubMed

Zhu, Tianwei; Hensen, Emiel J M; van Santen, Rutger A; Tian, Na; Sun, Shi-Gang; Kaghazchi, Payam; Jacob, Timo

2013-02-21

Using density functional theory (DFT) and thermodynamic considerations we studied the equilibrium shape of Pt nanoparticles (NPs) under electrochemical conditions. We found that at very high oxygen coverage, obtained at high electrode potentials, the experimentally-observed tetrahexahedral (THH) NPs consist of high-index (520) faces. Since high-index surfaces often show higher (electro-)chemical activity in comparison to their close-packed counterparts, the THH NPs can be promising candidates for various (electro-)catalytic applications.

Maize - GO annotation methods, evaluation, and review (Maize-GAMER)

USDA-ARS?s Scientific Manuscript database

Making a genome sequence accessible and useful involves three basic steps: genome assembly, structural annotation, and functional annotation. The quality of data generated at each step influences the accuracy of inferences that can be made, with high-quality analyses produce better datasets resultin...

Positive selection on sociobiological traits in invasive fire ants.

PubMed

Privman, Eyal; Cohen, Pnina; Cohanim, Amir B; Riba-Grognuz, Oksana; Shoemaker, DeWayne; Keller, Laurent

2018-06-19

The fire ant Solenopsis invicta and its close relatives are highly invasive. Enhanced social cooperation may facilitate invasiveness in these and other invasive ant species. We investigated whether invasiveness in Solenopsis fire ants was accompanied by positive selection on sociobiological traits by applying a phylogenomics approach to infer ancient selection, and a population genomics approach to infer recent and ongoing selection in both native and introduced S. invicta populations. A combination of whole-genome sequencing of 40 haploid males and reduced-representation genomic sequencing of 112 diploid workers identified 1,758,116 and 169,682 polymorphic markers, respectively. The resulting high-resolution maps of genomic polymorphism provide high inference power to test for positive selection. Our analyses provide evidence of positive selection on putative ion channel genes, which are implicated in neurological functions, and on vitellogenin, which is a key regulator of development and caste determination. Furthermore, molecular functions implicated in pheromonal signaling have experienced recent positive selection. Genes with signatures of positive selection were significantly more often those over-expressed in workers compared with queens and males, suggesting that worker traits are under stronger selection than queen and male traits. These results provide insights into selection pressures and ongoing adaptation in an invasive social insect and support the hypothesis that sociobiological traits are under more positive selection than traits related to non-social traits in such invasive species. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Interoceptive inference: From computational neuroscience to clinic.

PubMed

Owens, Andrew P; Allen, Micah; Ondobaka, Sasha; Friston, Karl J

2018-04-22

The central and autonomic nervous systems can be defined by their anatomical, functional and neurochemical characteristics, but neither functions in isolation. For example, fundamental components of autonomically mediated homeostatic processes are afferent interoceptive signals reporting the internal state of the body and efferent signals acting on interoceptive feedback assimilated by the brain. Recent predictive coding (interoceptive inference) models formulate interoception in terms of embodied predictive processes that support emotion and selfhood. We propose interoception may serve as a way to investigate holistic nervous system function and dysfunction in disorders of brain, body and behaviour. We appeal to predictive coding and (active) interoceptive inference, to describe the homeostatic functions of the central and autonomic nervous systems. We do so by (i) reviewing the active inference formulation of interoceptive and autonomic function, (ii) survey clinical applications of this formulation and (iii) describe how it offers an integrative approach to human physiology; particularly, interactions between the central and peripheral nervous systems in health and disease. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Pragmatic inferences in high-functioning adults with autism and Asperger syndrome.

PubMed

Pijnacker, Judith; Hagoort, Peter; Buitelaar, Jan; Teunisse, Jan-Pieter; Geurts, Bart

2009-04-01

Although people with autism spectrum disorders (ASD) often have severe problems with pragmatic aspects of language, little is known about their pragmatic reasoning. We carried out a behavioral study on high-functioning adults with autistic disorder (n = 11) and Asperger syndrome (n = 17) and matched controls (n = 28) to investigate whether they are capable of deriving scalar implicatures, which are generally considered to be pragmatic inferences. Participants were presented with underinformative sentences like "Some sparrows are birds". This sentence is logically true, but pragmatically inappropriate if the scalar implicature "Not all sparrows are birds" is derived. The present findings indicate that the combined ASD group was just as likely as controls to derive scalar implicatures, yet there was a difference between participants with autistic disorder and Asperger syndrome, suggesting a potential differentiation between these disorders in pragmatic reasoning. Moreover, our results suggest that verbal intelligence is a constraint for task performance in autistic disorder but not in Asperger syndrome.

Bacterial growth laws reflect the evolutionary importance of energy efficiency.

PubMed

Maitra, Arijit; Dill, Ken A

2015-01-13

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell's fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.

Inferring network structure from cascades.

PubMed

Ghonge, Sushrut; Vural, Dervis Can

2017-07-01

Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the activation probability of a node is a generic function of its degree and the number of its active neighbors. We report high success rates for synthetic and real networks, for several different cascade models.

Inferring network structure from cascades

NASA Astrophysics Data System (ADS)

Ghonge, Sushrut; Vural, Dervis Can

2017-07-01

Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the activation probability of a node is a generic function of its degree and the number of its active neighbors. We report high success rates for synthetic and real networks, for several different cascade models.

Inferring Boolean network states from partial information

PubMed Central

2013-01-01

Networks of molecular interactions regulate key processes in living cells. Therefore, understanding their functionality is a high priority in advancing biological knowledge. Boolean networks are often used to describe cellular networks mathematically and are fitted to experimental datasets. The fitting often results in ambiguities since the interpretation of the measurements is not straightforward and since the data contain noise. In order to facilitate a more reliable mapping between datasets and Boolean networks, we develop an algorithm that infers network trajectories from a dataset distorted by noise. We analyze our algorithm theoretically and demonstrate its accuracy using simulation and microarray expression data. PMID:24006954

De novo inference of protein function from coarse-grained dynamics.

PubMed

Bhadra, Pratiti; Pal, Debnath

2014-10-01

Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 µs coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all. © 2014 Wiley Periodicals, Inc.

Validity of smoke alarm self-report measures and reasons for over-reporting.

PubMed

Stepnitz, Rebecca; Shields, Wendy; McDonald, Eileen; Gielen, Andrea

2012-10-01

Many residential fire deaths occur in homes with no or non-functioning smoke alarms (SAs). Self-reported SA coverage is high, but studies have found varying validity for self-report measures. The authors aim to: (1) determine over-reporting of coverage, (2) describe socio-demographic correlates of over-reporting and (3) report reasons for over-reporting. The authors surveyed 603 households in a large, urban area about fire safety behaviours and then tested all SAs in the home. 23 participants who over-reported their SA coverage were telephoned and asked about why they had misreported. Full coverage was reported in 70% of households but observed in only 41%, with a low positive predictive value (54.2%) for the self-report measure. Most over-reporters assumed alarms were working because they were mounted or did not think a working alarm in a basement or attic was needed to be fully protected. If alarms cannot be tested, researchers or those counselling residents on fire safety should carefully probe self-reported coverage. Our findings support efforts to equip more homes with hard-wired or 10 year lithium battery alarms to reduce the need for user maintenance.

Periodic domain boundary ordering in a dense molecular adlayer: Sub-saturation carbon monoxide on Pd(111)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Pan; Liu, Shizhong; Hong, Sung -Young

Here, we describe a previously unreported ordered phase of carbon monoxide adsorbed on the (111) facet of single crystal palladium at near-saturation coverage. The adlayer superstructure is identified from low energy electron diffraction to be c(16×2) with respect to the underlying Pd(111) surface net. The ideal coverage is determined to be 0.6875 ML, approximately 92% of the 0.75–ML saturation coverage. Density functional theory calculations support a model for the molecular packing characterized by strips of locally-saturated (2×2) regions, with the CO bound near high-symmetry surface sites, separated by antiphase domain boundaries. The structure exists in a narrow coverage range andmore » is prepared by heating the saturated adlayer to desorb a small fraction of the CO. Comparison of the c(16×2) domain-boundary structure with structural motifs at lower coverages suggests that between 0.6 and 0.6875 ML the adlayer order may be more strongly influenced by interadsorbate repulsion than by adsorption-site-specific interactions. The system is an example of the structural complexity that results from the compromise between adsorbate–substrate and adsorbate–adsorbate interactions.« less

Periodic domain boundary ordering in a dense molecular adlayer: Sub-saturation carbon monoxide on Pd(111)

DOE PAGES

Xu, Pan; Liu, Shizhong; Hong, Sung -Young; ...

2016-12-31

Here, we describe a previously unreported ordered phase of carbon monoxide adsorbed on the (111) facet of single crystal palladium at near-saturation coverage. The adlayer superstructure is identified from low energy electron diffraction to be c(16×2) with respect to the underlying Pd(111) surface net. The ideal coverage is determined to be 0.6875 ML, approximately 92% of the 0.75–ML saturation coverage. Density functional theory calculations support a model for the molecular packing characterized by strips of locally-saturated (2×2) regions, with the CO bound near high-symmetry surface sites, separated by antiphase domain boundaries. The structure exists in a narrow coverage range andmore » is prepared by heating the saturated adlayer to desorb a small fraction of the CO. Comparison of the c(16×2) domain-boundary structure with structural motifs at lower coverages suggests that between 0.6 and 0.6875 ML the adlayer order may be more strongly influenced by interadsorbate repulsion than by adsorption-site-specific interactions. The system is an example of the structural complexity that results from the compromise between adsorbate–substrate and adsorbate–adsorbate interactions.« less

Maize GO annotation—methods, evaluation, and review (maize-GAMER)

USDA-ARS?s Scientific Manuscript database

We created a new high-coverage, robust, and reproducible functional annotation of maize protein-coding genes based on Gene Ontology (GO) term assignments. Whereas the existing Phytozome and Gramene maize GO annotation sets only cover 41% and 56% of maize protein-coding genes, respectively, this stu...

Economic grand rounds: the price is right? Changes in the quantity of services used and prices paid in response to parity.

PubMed

Goldman, Howard H; Barry, Colleen L; Normand, Sharon-Lise T; Azzone, Vanessa; Busch, Alisa B; Huskamp, Haiden A

2012-02-01

The impact of parity coverage on the quantity of behavioral health services used by enrollees and on the prices of these services was examined in a set of Federal Employees Health Benefit (FEHB) Program plans. After parity implementation, the quantity of services used in the FEHB plans declined in five service categories, compared with plans that did not have parity coverage. The decline was significant for all service types except inpatient care. Because a previous study of the FEHB Program found that total spending on behavioral health services did not increase after parity implementation, it can be inferred that average prices must have increased over the period. The finding of a decline in service use and increase in prices provides an empirical window on what might be expected after implementation of the federal parity law and the parity requirement under the health care reform law.

A recent bottleneck of Y chromosome diversity coincides with a global change in culture

PubMed Central

Saag, Lauri; Vicente, Mário; Sayres, Melissa A. Wilson; Järve, Mari; Talas, Ulvi Gerst; Rootsi, Siiri; Ilumäe, Anne-Mai; Mägi, Reedik; Mitt, Mario; Pagani, Luca; Puurand, Tarmo; Faltyskova, Zuzana; Clemente, Florian; Cardona, Alexia; Metspalu, Ene; Sahakyan, Hovhannes; Yunusbayev, Bayazit; Hudjashov, Georgi; DeGiorgio, Michael; Loogväli, Eva-Liis; Eichstaedt, Christina; Eelmets, Mikk; Chaubey, Gyaneshwer; Tambets, Kristiina; Litvinov, Sergei; Mormina, Maru; Xue, Yali; Ayub, Qasim; Zoraqi, Grigor; Korneliussen, Thorfinn Sand; Akhatova, Farida; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Ricaut, François-Xavier; Kusuma, Pradiptajati; Razafindrazaka, Harilanto; Pierron, Denis; Cox, Murray P.; Sultana, Gazi Nurun Nahar; Willerslev, Rane; Muller, Craig; Westaway, Michael; Lambert, David; Skaro, Vedrana; Kovačevic´, Lejla; Turdikulova, Shahlo; Dalimova, Dilbar; Khusainova, Rita; Trofimova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Lichman, Daria V.; Isakova, Jainagul; Pocheshkhova, Elvira; Sabitov, Zhaxylyk; Barashkov, Nikolay A.; Nymadawa, Pagbajabyn; Mihailov, Evelin; Seng, Joseph Wee Tien; Evseeva, Irina; Migliano, Andrea Bamberg; Abdullah, Syafiq; Andriadze, George; Primorac, Dragan; Atramentova, Lubov; Utevska, Olga; Yepiskoposyan, Levon; Marjanovic´, Damir; Kushniarevich, Alena; Behar, Doron M.; Gilissen, Christian; Vissers, Lisenka; Veltman, Joris A.; Balanovska, Elena; Derenko, Miroslava; Malyarchuk, Boris; Metspalu, Andres; Fedorova, Sardana; Eriksson, Anders; Manica, Andrea; Mendez, Fernando L.; Karafet, Tatiana M.; Veeramah, Krishna R.; Bradman, Neil; Hammer, Michael F.; Osipova, Ludmila P.; Balanovsky, Oleg; Khusnutdinova, Elza K.; Johnsen, Knut; Remm, Maido; Thomas, Mark G.; Tyler-Smith, Chris; Underhill, Peter A.; Willerslev, Eske; Nielsen, Rasmus; Metspalu, Mait; Villems, Richard

2015-01-01

It is commonly thought that human genetic diversity in non-African populations was shaped primarily by an out-of-Africa dispersal 50–100 thousand yr ago (kya). Here, we present a study of 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Applying ancient DNA calibration, we date the Y-chromosomal most recent common ancestor (MRCA) in Africa at 254 (95% CI 192–307) kya and detect a cluster of major non-African founder haplogroups in a narrow time interval at 47–52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck. In contrast to demographic reconstructions based on mtDNA, we infer a second strong bottleneck in Y-chromosome lineages dating to the last 10 ky. We hypothesize that this bottleneck is caused by cultural changes affecting variance of reproductive success among males. PMID:25770088

A genomic history of Aboriginal Australia.

PubMed

Malaspinas, Anna-Sapfo; Westaway, Michael C; Muller, Craig; Sousa, Vitor C; Lao, Oscar; Alves, Isabel; Bergström, Anders; Athanasiadis, Georgios; Cheng, Jade Y; Crawford, Jacob E; Heupink, Tim H; Macholdt, Enrico; Peischl, Stephan; Rasmussen, Simon; Schiffels, Stephan; Subramanian, Sankar; Wright, Joanne L; Albrechtsen, Anders; Barbieri, Chiara; Dupanloup, Isabelle; Eriksson, Anders; Margaryan, Ashot; Moltke, Ida; Pugach, Irina; Korneliussen, Thorfinn S; Levkivskyi, Ivan P; Moreno-Mayar, J Víctor; Ni, Shengyu; Racimo, Fernando; Sikora, Martin; Xue, Yali; Aghakhanian, Farhang A; Brucato, Nicolas; Brunak, Søren; Campos, Paula F; Clark, Warren; Ellingvåg, Sturla; Fourmile, Gudjugudju; Gerbault, Pascale; Injie, Darren; Koki, George; Leavesley, Matthew; Logan, Betty; Lynch, Aubrey; Matisoo-Smith, Elizabeth A; McAllister, Peter J; Mentzer, Alexander J; Metspalu, Mait; Migliano, Andrea B; Murgha, Les; Phipps, Maude E; Pomat, William; Reynolds, Doc; Ricaut, Francois-Xavier; Siba, Peter; Thomas, Mark G; Wales, Thomas; Wall, Colleen Ma'run; Oppenheimer, Stephen J; Tyler-Smith, Chris; Durbin, Richard; Dortch, Joe; Manica, Andrea; Schierup, Mikkel H; Foley, Robert A; Lahr, Marta Mirazón; Bowern, Claire; Wall, Jeffrey D; Mailund, Thomas; Stoneking, Mark; Nielsen, Rasmus; Sandhu, Manjinder S; Excoffier, Laurent; Lambert, David M; Willerslev, Eske

2016-10-13

The population history of Aboriginal Australians remains largely uncharacterized. Here we generate high-coverage genomes for 83 Aboriginal Australians (speakers of Pama-Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal Australian ancestors diversified 25-40 thousand years ago (kya), suggesting pre-Holocene population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all of the studied Aboriginal Australians descend from a single founding population that differentiated ~10-32 kya. We infer a population expansion in northeast Australia during the Holocene epoch (past 10,000 years) associated with limited gene flow from this region to the rest of Australia, consistent with the spread of the Pama-Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51-72 kya, following a single out-of-Africa dispersal, and subsequently admixed with archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.

Impact of Sampling Schemes on Demographic Inference: An Empirical Study in Two Species with Different Mating Systems and Demographic Histories

PubMed Central

St. Onge, K. R.; Palmé, A. E.; Wright, S. I.; Lascoux, M.

2012-01-01

Most species have at least some level of genetic structure. Recent simulation studies have shown that it is important to consider population structure when sampling individuals to infer past population history. The relevance of the results of these computer simulations for empirical studies, however, remains unclear. In the present study, we use DNA sequence datasets collected from two closely related species with very different histories, the selfing species Capsella rubella and its outcrossing relative C. grandiflora, to assess the impact of different sampling strategies on summary statistics and the inference of historical demography. Sampling strategy did not strongly influence the mean values of Tajima’s D in either species, but it had some impact on the variance. The general conclusions about demographic history were comparable across sampling schemes even when resampled data were analyzed with approximate Bayesian computation (ABC). We used simulations to explore the effects of sampling scheme under different demographic models. We conclude that when sequences from modest numbers of loci (<60) are analyzed, the sampling strategy is generally of limited importance. The same is true under intermediate or high levels of gene flow (4Nm > 2–10) in models in which global expansion is combined with either local expansion or hierarchical population structure. Although we observe a less severe effect of sampling than predicted under some earlier simulation models, our results should not be seen as an encouragement to neglect this issue. In general, a good coverage of the natural range, both within and between populations, will be needed to obtain a reliable reconstruction of a species’s demographic history, and in fact, the effect of sampling scheme on polymorphism patterns may itself provide important information about demographic history. PMID:22870403

Inference of Epidemiological Dynamics Based on Simulated Phylogenies Using Birth-Death and Coalescent Models

PubMed Central

Boskova, Veronika; Bonhoeffer, Sebastian; Stadler, Tanja

2014-01-01

Quantifying epidemiological dynamics is crucial for understanding and forecasting the spread of an epidemic. The coalescent and the birth-death model are used interchangeably to infer epidemiological parameters from the genealogical relationships of the pathogen population under study, which in turn are inferred from the pathogen genetic sequencing data. To compare the performance of these widely applied models, we performed a simulation study. We simulated phylogenetic trees under the constant rate birth-death model and the coalescent model with a deterministic exponentially growing infected population. For each tree, we re-estimated the epidemiological parameters using both a birth-death and a coalescent based method, implemented as an MCMC procedure in BEAST v2.0. In our analyses that estimate the growth rate of an epidemic based on simulated birth-death trees, the point estimates such as the maximum a posteriori/maximum likelihood estimates are not very different. However, the estimates of uncertainty are very different. The birth-death model had a higher coverage than the coalescent model, i.e. contained the true value in the highest posterior density (HPD) interval more often (2–13% vs. 31–75% error). The coverage of the coalescent decreases with decreasing basic reproductive ratio and increasing sampling probability of infecteds. We hypothesize that the biases in the coalescent are due to the assumption of deterministic rather than stochastic population size changes. Both methods performed reasonably well when analyzing trees simulated under the coalescent. The methods can also identify other key epidemiological parameters as long as one of the parameters is fixed to its true value. In summary, when using genetic data to estimate epidemic dynamics, our results suggest that the birth-death method will be less sensitive to population fluctuations of early outbreaks than the coalescent method that assumes a deterministic exponentially growing infected population. PMID:25375100

Quantifying uncertainty in soot volume fraction estimates using Bayesian inference of auto-correlated laser-induced incandescence measurements

NASA Astrophysics Data System (ADS)

Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.

2016-01-01

Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.

Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals.

PubMed

Taylor, Jeremy F; Whitacre, Lynsey K; Hoff, Jesse L; Tizioto, Polyana C; Kim, JaeWoo; Decker, Jared E; Schnabel, Robert D

2016-08-17

Decreasing sequencing costs and development of new protocols for characterizing global methylation, gene expression patterns and regulatory regions have stimulated the generation of large livestock datasets. Here, we discuss experiences in the analysis of whole-genome and transcriptome sequence data. We analyzed whole-genome sequence (WGS) data from 132 individuals from five canid species (Canis familiaris, C. latrans, C. dingo, C. aureus and C. lupus) and 61 breeds, three bison (Bison bison), 64 water buffalo (Bubalus bubalis) and 297 bovines from 17 breeds. By individual, data vary in extent of reference genome depth of coverage from 4.9X to 64.0X. We have also analyzed RNA-seq data for 580 samples representing 159 Bos taurus and Rattus norvegicus animals and 98 tissues. By aligning reads to a reference assembly and calling variants, we assessed effects of average depth of coverage on the actual coverage and on the number of called variants. We examined the identity of unmapped reads by assembling them and querying produced contigs against the non-redundant nucleic acids database. By imputing high-density single nucleotide polymorphism data on 4010 US registered Angus animals to WGS using Run4 of the 1000 Bull Genomes Project and assessing the accuracy of imputation, we identified misassembled reference sequence regions. We estimate that a 24X depth of coverage is required to achieve 99.5 % coverage of the reference assembly and identify 95 % of the variants within an individual's genome. Genomes sequenced to low average coverage (e.g., <10X) may fail to cover 10 % of the reference genome and identify <75 % of variants. About 10 % of genomic DNA or transcriptome sequence reads fail to align to the reference assembly. These reads include loci missing from the reference assembly and misassembled genes and interesting symbionts, commensal and pathogenic organisms. Assembly errors and a lack of annotation of functional elements significantly limit the utility of the current draft livestock reference assemblies. The Functional Annotation of Animal Genomes initiative seeks to annotate functional elements, while a 70X Pac-Bio assembly for cow is underway and may result in a significantly improved reference assembly.

Estimating Premium Sensitivity for Children's Public Health Insurance Coverage: Selection but No Death Spiral

PubMed Central

Marton, James; Ketsche, Patricia G; Snyder, Angela; Adams, E Kathleen; Zhou, Mei

2015-01-01

Objective To estimate the effect of premium increases on the probability that near-poor and moderate-income children disenroll from public coverage. Data Sources Enrollment, eligibility, and claims data for Georgia's PeachCare for Kids™ (CHIP) program for multiple years. Study Design We exploited policy-induced variation in premiums generated by cross-sectional differences and changes over time in enrollee age, family size, and income to estimate the duration of enrollment as a function of the effective (per child) premium. We classify children as being of low, medium, or high illness severity. Principal Findings A dollar increase in the per-child premium is associated with a slight increase in a typical child's monthly probability of exiting coverage from 7.70 to 7.83 percent. Children with low illness severity have a significantly higher monthly baseline probability of exiting than children with medium or high illness severity, but the enrollment response to premium increases is similar across all three groups. Conclusions Success in achieving coverage gains through public programs is tempered by persistent problems in maintaining enrollment, which is modestly affected by premium increases. Retention is subject to adverse selection problems, but premium increases do not appear to significantly magnify the selection problem in this case. PMID:25130764

High depth, whole-genome sequencing of cholera isolates from Haiti and the Dominican Republic.

PubMed

Sealfon, Rachel; Gire, Stephen; Ellis, Crystal; Calderwood, Stephen; Qadri, Firdausi; Hensley, Lisa; Kellis, Manolis; Ryan, Edward T; LaRocque, Regina C; Harris, Jason B; Sabeti, Pardis C

2012-09-11

Whole-genome sequencing is an important tool for understanding microbial evolution and identifying the emergence of functionally important variants over the course of epidemics. In October 2010, a severe cholera epidemic began in Haiti, with additional cases identified in the neighboring Dominican Republic. We used whole-genome approaches to sequence four Vibrio cholerae isolates from Haiti and the Dominican Republic and three additional V. cholerae isolates to a high depth of coverage (>2000x); four of the seven isolates were previously sequenced. Using these sequence data, we examined the effect of depth of coverage and sequencing platform on genome assembly and identification of sequence variants. We found that 50x coverage is sufficient to construct a whole-genome assembly and to accurately call most variants from 100 base pair paired-end sequencing reads. Phylogenetic analysis between the newly sequenced and thirty-three previously sequenced V. cholerae isolates indicates that the Haitian and Dominican Republic isolates are closest to strains from South Asia. The Haitian and Dominican Republic isolates form a tight cluster, with only four variants unique to individual isolates. These variants are located in the CTX region, the SXT region, and the core genome. Of the 126 mutations identified that separate the Haiti-Dominican Republic cluster from the V. cholerae reference strain (N16961), 73 are non-synonymous changes, and a number of these changes cluster in specific genes and pathways. Sequence variant analyses of V. cholerae isolates, including multiple isolates from the Haitian outbreak, identify coverage-specific and technology-specific effects on variant detection, and provide insight into genomic change and functional evolution during an epidemic.

Cognitive Inference Device for Activity Supervision in the Elderly

PubMed Central

2014-01-01

Human activity, life span, and quality of life are enhanced by innovations in science and technology. Aging individual needs to take advantage of these developments to lead a self-regulated life. However, maintaining a self-regulated life at old age involves a high degree of risk, and the elderly often fail at this goal. Thus, the objective of our study is to investigate the feasibility of implementing a cognitive inference device (CI-device) for effective activity supervision in the elderly. To frame the CI-device, we propose a device design framework along with an inference algorithm and implement the designs through an artificial neural model with different configurations, mapping the CI-device's functions to minimise the device's prediction error. An analysis and discussion are then provided to validate the feasibility of CI-device implementation for activity supervision in the elderly. PMID:25405211

Impact of coverage on the reliability of a fault tolerant computer

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1975-01-01

A mathematical reliability model is established for a reconfigurable fault tolerant avionic computer system utilizing state-of-the-art computers. System reliability is studied in light of the coverage probabilities associated with the first and second independent hardware failures. Coverage models are presented as a function of detection, isolation, and recovery probabilities. Upper and lower bonds are established for the coverage probabilities and the method for computing values for the coverage probabilities is investigated. Further, an architectural variation is proposed which is shown to enhance coverage.

CA1 subfield contributions to memory integration and inference

PubMed Central

Schlichting, Margaret L.; Zeithamova, Dagmar; Preston, Alison R.

2014-01-01

The ability to combine information acquired at different times to make novel inferences is a powerful function of episodic memory. One perspective suggests that by retrieving related knowledge during new experiences, existing memories can be linked to the new, overlapping information as it is encoded. The resulting memory traces would thus incorporate content across event boundaries, representing important relationships among items encountered during separate experiences. While prior work suggests that the hippocampus is involved in linking memories experienced at different times, the involvement of specific subfields in this process remains unknown. Using both univariate and multivariate analyses of high-resolution functional magnetic resonance imaging (fMRI) data, we localized this specialized encoding mechanism to human CA1. Specifically, right CA1 responses during encoding of events that overlapped with prior experience predicted subsequent success on a test requiring inferences about the relationships among events. Furthermore, we employed neural pattern similarity analysis to show that patterns of activation evoked during overlapping event encoding were later reinstated in CA1 during successful inference. The reinstatement of CA1 patterns during inference was specific to those trials that were performed quickly and accurately, consistent with the notion that linking memories during learning facilitates novel judgments. These analyses provide converging evidence that CA1 plays a unique role in encoding overlapping events and highlight the dynamic interactions between hippocampal-mediated encoding and retrieval processes. More broadly, our data reflect the adaptive nature of episodic memories, in which representations are derived across events in anticipation of future judgments. PMID:24888442

Bayesian inference of galaxy formation from the K-band luminosity function of galaxies: tensions between theory and observation

NASA Astrophysics Data System (ADS)

Lu, Yu; Mo, H. J.; Katz, Neal; Weinberg, Martin D.

2012-04-01

We conduct Bayesian model inferences from the observed K-band luminosity function of galaxies in the local Universe, using the semi-analytic model (SAM) of galaxy formation introduced in Lu et al. The prior distributions for the 14 free parameters include a large range of possible models. We find that some of the free parameters, e.g. the characteristic scales for quenching star formation in both high-mass and low-mass haloes, are already tightly constrained by the single data set. The posterior distribution includes the model parameters adopted in other SAMs. By marginalizing over the posterior distribution, we make predictions that include the full inferential uncertainties for the colour-magnitude relation, the Tully-Fisher relation, the conditional stellar mass function of galaxies in haloes of different masses, the H I mass function, the redshift evolution of the stellar mass function of galaxies and the global star formation history. Using posterior predictive checking with the available observational results, we find that the model family (i) predicts a Tully-Fisher relation that is curved; (ii) significantly overpredicts the satellite fraction; (iii) vastly overpredicts the H I mass function; (iv) predicts high-z stellar mass functions that have too many low-mass galaxies and too few high-mass ones and (v) predicts a redshift evolution of the stellar mass density and the star formation history that are in moderate disagreement. These results suggest that some important processes are still missing in the current model family, and we discuss a number of possible solutions to solve the discrepancies, such as interactions between galaxies and dark matter haloes, tidal stripping, the bimodal accretion of gas, preheating and a redshift-dependent initial mass function.

Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments

NASA Astrophysics Data System (ADS)

Atwal, Gurinder S.; Kinney, Justin B.

2016-03-01

A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.

Quantifying the Impact of Spectral Coverage on the Retrieval of Molecular Abundances from Exoplanet Transmission Spectra

NASA Astrophysics Data System (ADS)

Chapman, John W.; Zellem, Robert T.; Line, Michael R.; Vasisht, Gautam; Bryden, Geoff; Willacy, Karen; Iyer, Aishwarya R.; Bean, Jacob; Cowan, Nicolas B.; Fortney, Jonathan J.; Griffith, Caitlin A.; Kataria, Tiffany; Kempton, Eliza M.-R.; Kreidberg, Laura; Moses, Julianne I.; Stevenson, Kevin B.; Swain, Mark R.

2017-10-01

Using forward models for representative exoplanet atmospheres and a radiometric instrument model, we generated synthetic observational data to explore how well the major C- and O-bearing chemical species (CO, CO2, CH4, and H2O), important for determining atmospheric opacity and radiation balance, can be constrained by transit measurements as a function of spectral wavelength coverage. This work features simulations for a notional transit spectroscopy mission and compares two cases for instrument spectral coverage (wavelength coverage from 0.5-2.5 μm and 0.5-5 μm). The simulation is conducted on a grid with a range of stellar magnitudes and incorporates a full retrieval of atmospheric model parameters. We consider a range of planets from sub-Neptunes to hot Jupiters and include both low and high mean molecular weight atmospheres. We find that including the 2.5-5 μm wavelength range provides a significant improvement in the degree of constraint on the retrieved molecular abundances: up to ˜3 orders of magnitude for a low mean molecular weight atmosphere (μ = 2.3) and up to a factor of ˜6 for a high mean molecular weight atmosphere (μ = 28). These decreased uncertainties imply that broad spectral coverage between the visible and the mid-infrared is an important tool for understanding the chemistry and composition of exoplanet atmospheres. This analysis suggests that the James Webb Space Telescope’s (JWST) Near-Infrared Spectrograph (NIRSpec) 0.6-5 μm prism spectroscopy mode, or similar wavelength coverage with possible future missions, will be an important resource for exoplanet atmospheric characterization.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Functional Inference of Complex Anatomical Tendinous Networks at a Macroscopic Scale via Sparse Experimentation

PubMed Central

Saxena, Anupam; Lipson, Hod; Valero-Cuevas, Francisco J.

2012-01-01

In systems and computational biology, much effort is devoted to functional identification of systems and networks at the molecular-or cellular scale. However, similarly important networks exist at anatomical scales such as the tendon network of human fingers: the complex array of collagen fibers that transmits and distributes muscle forces to finger joints. This network is critical to the versatility of the human hand, and its function has been debated since at least the 16th century. Here, we experimentally infer the structure (both topology and parameter values) of this network through sparse interrogation with force inputs. A population of models representing this structure co-evolves in simulation with a population of informative future force inputs via the predator-prey estimation-exploration algorithm. Model fitness depends on their ability to explain experimental data, while the fitness of future force inputs depends on causing maximal functional discrepancy among current models. We validate our approach by inferring two known synthetic Latex networks, and one anatomical tendon network harvested from a cadaver's middle finger. We find that functionally similar but structurally diverse models can exist within a narrow range of the training set and cross-validation errors. For the Latex networks, models with low training set error [<4%] and resembling the known network have the smallest cross-validation errors [∼5%]. The low training set [<4%] and cross validation [<7.2%] errors for models for the cadaveric specimen demonstrate what, to our knowledge, is the first experimental inference of the functional structure of complex anatomical networks. This work expands current bioinformatics inference approaches by demonstrating that sparse, yet informative interrogation of biological specimens holds significant computational advantages in accurate and efficient inference over random testing, or assuming model topology and only inferring parameters values. These findings also hold clues to both our evolutionary history and the development of versatile machines. PMID:23144601

Functional inference of complex anatomical tendinous networks at a macroscopic scale via sparse experimentation.

PubMed

Saxena, Anupam; Lipson, Hod; Valero-Cuevas, Francisco J

2012-01-01

In systems and computational biology, much effort is devoted to functional identification of systems and networks at the molecular-or cellular scale. However, similarly important networks exist at anatomical scales such as the tendon network of human fingers: the complex array of collagen fibers that transmits and distributes muscle forces to finger joints. This network is critical to the versatility of the human hand, and its function has been debated since at least the 16(th) century. Here, we experimentally infer the structure (both topology and parameter values) of this network through sparse interrogation with force inputs. A population of models representing this structure co-evolves in simulation with a population of informative future force inputs via the predator-prey estimation-exploration algorithm. Model fitness depends on their ability to explain experimental data, while the fitness of future force inputs depends on causing maximal functional discrepancy among current models. We validate our approach by inferring two known synthetic Latex networks, and one anatomical tendon network harvested from a cadaver's middle finger. We find that functionally similar but structurally diverse models can exist within a narrow range of the training set and cross-validation errors. For the Latex networks, models with low training set error [<4%] and resembling the known network have the smallest cross-validation errors [∼5%]. The low training set [<4%] and cross validation [<7.2%] errors for models for the cadaveric specimen demonstrate what, to our knowledge, is the first experimental inference of the functional structure of complex anatomical networks. This work expands current bioinformatics inference approaches by demonstrating that sparse, yet informative interrogation of biological specimens holds significant computational advantages in accurate and efficient inference over random testing, or assuming model topology and only inferring parameters values. These findings also hold clues to both our evolutionary history and the development of versatile machines.

A Total Ozone Dependent Ozone Profile Climatology Based on Ozone-Sondes and Aura MLS Data

NASA Astrophysics Data System (ADS)

Labow, G. J.; McPeters, R. D.; Ziemke, J. R.

2014-12-01

A new total ozone-based ozone profile climatology has been created for use in satellite and/or ground based ozone retrievals. This climatology was formed by combining data from the Microwave Limb Sounder (MLS) with data from balloon sondes and binned by zone and total ozone. Because profile shape varies with total column ozone, this climatology better captures the ozone variations than the previously used seasonal climatologies, especially near the tropopause. This is significantly different than ozone climatologies used in the past as there is no time component. The MLS instrument on Aura has excellent latitude coverage and measures ozone profiles daily from the upper troposphere to the lower mesosphere at ~3.5 km resolution. Almost a million individual MLS ozone measurements are merged with data from over 55,000 ozonesondes which are then binned as a function of total ozone. The climatology consists of average ozone profiles as a function of total ozone for six 30 degree latitude bands covering altitudes from 0-75 km (in Z* pressure altitude coordinates). This new climatology better represents the profile shape as a function of total ozone than previous climatologies and shows some remarkable and somewhat unexpected correlations between total ozone and ozone in the lower altitudes, particularly in the lower and middle troposphere. These data can also be used to infer biases and errors in either the MLS retrievals or ozone sondes.

Statistical analysis of fNIRS data: a comprehensive review.

PubMed

Tak, Sungho; Ye, Jong Chul

2014-01-15

Functional near-infrared spectroscopy (fNIRS) is a non-invasive method to measure brain activities using the changes of optical absorption in the brain through the intact skull. fNIRS has many advantages over other neuroimaging modalities such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), or magnetoencephalography (MEG), since it can directly measure blood oxygenation level changes related to neural activation with high temporal resolution. However, fNIRS signals are highly corrupted by measurement noises and physiology-based systemic interference. Careful statistical analyses are therefore required to extract neuronal activity-related signals from fNIRS data. In this paper, we provide an extensive review of historical developments of statistical analyses of fNIRS signal, which include motion artifact correction, short source-detector separation correction, principal component analysis (PCA)/independent component analysis (ICA), false discovery rate (FDR), serially-correlated errors, as well as inference techniques such as the standard t-test, F-test, analysis of variance (ANOVA), and statistical parameter mapping (SPM) framework. In addition, to provide a unified view of various existing inference techniques, we explain a linear mixed effect model with restricted maximum likelihood (ReML) variance estimation, and show that most of the existing inference methods for fNIRS analysis can be derived as special cases. Some of the open issues in statistical analysis are also described. Copyright © 2013 Elsevier Inc. All rights reserved.

A knowledge representation view on biomedical structure and function.

PubMed Central

Schulz, Stefan; Hahn, Udo

2002-01-01

In biomedical ontologies, structural and functional considerations are of outstanding importance, and concepts which belong to these two categories are highly interdependent. At the representational level both axes must be clearly kept separate in order to support disciplined ontology engineering. Furthermore, the biaxial organization of physical structure (both by a taxonomic and partonomic order) entails intricate patterns of inference. We here propose a layered encoding of taxonomic, partonomic and functional aspects of biomedical concepts using description logics. PMID:12463912

Approximate Bayesian computation in large-scale structure: constraining the galaxy-halo connection

NASA Astrophysics Data System (ADS)

Hahn, ChangHoon; Vakili, Mohammadjavad; Walsh, Kilian; Hearin, Andrew P.; Hogg, David W.; Campbell, Duncan

2017-08-01

Standard approaches to Bayesian parameter inference in large-scale structure assume a Gaussian functional form (chi-squared form) for the likelihood. This assumption, in detail, cannot be correct. Likelihood free inferences such as approximate Bayesian computation (ABC) relax these restrictions and make inference possible without making any assumptions on the likelihood. Instead ABC relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter haloes with galaxies. Using specific implementation of ABC supplemented with population Monte Carlo importance sampling, a generative forward model using HOD and a distance metric based on galaxy number density, two-point correlation function and galaxy group multiplicity function, we constrain the HOD parameters of mock observation generated from selected 'true' HOD parameters. The parameter constraints we obtain from ABC are consistent with the 'true' HOD parameters, demonstrating that ABC can be reliably used for parameter inference in LSS. Furthermore, we compare our ABC constraints to constraints we obtain using a pseudo-likelihood function of Gaussian form with MCMC and find consistent HOD parameter constraints. Ultimately, our results suggest that ABC can and should be applied in parameter inference for LSS analyses.

OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.

Surface states and annihilation characteristics of positrons trapped at the oxidized Cu(100) surface

NASA Astrophysics Data System (ADS)

Fazleev, N. G.; Weiss, A. H.

2013-06-01

In this work we present the results of theoretical studies of positron surface and bulk states and annihilation probabilities of surface-trapped positrons with relevant core electrons at the oxidized Cu(100) surface under conditions of high oxygen coverage. Oxidation of the Cu(100) surface has been studied by performing an ab-initio investigation of the stability and electronic structure of the Cu(100) missing row reconstructed surface at various on-surface and subsurface oxygen coverages ranging from 0.5 to 1.5 monolayers using density functional theory (DFT). All studied structures have been found to be energetically more favorable as compared to structures formed by purely on-surface oxygen adsorption. The observed decrease in the positron work function when oxygen atoms occupy on-surface and subsurface sites has been attributed to a significant charge redistribution within the first two layers, buckling effects within each layer and an interlayer expansion. The computed positron binding energy, positron surface state wave function, and annihilation probabilities of the surface trapped positrons with relevant core electrons demonstrate their sensitivity to oxygen coverage, atomic structure of the topmost layers of surfaces, and charge transfer effects. Theoretical results are compared with experimental data obtained from studies of oxidation of the Cu(100) surface using positron annihilation induced Auger electron spectroscopy (PAES). The results presented provide an explanation for the changes observed in the probability of annihilation of surface trapped positrons with Cu 3p core-level electrons as a function of annealing temperature.

Characterizing Arctic sea ice topography and atmospheric form drag using high-resolution IceBridge data

NASA Astrophysics Data System (ADS)

Petty, A.; Tsamados, M.; Kurtz, N. T.; Farrell, S. L.; Newman, T.; Harbeck, J.; Feltham, D. L.; Richter-Menge, J.

2015-12-01

Here we present a detailed analysis of Arctic sea ice topography using high resolution, three-dimensional surface elevation data from the NASA Operation IceBridge Airborne Topographic Mapper (ATM) laser altimeter. We derive novel ice topography statistics from 2009-2014 across both first-year and multiyear ice regimes - including the height, area coverage, orientation and spacing of distinct surface features. The sea ice topography exhibits strong spatial variability, including increased surface feature (e.g. pressure ridge) height and area coverage within the multi-year ice regions. The ice topography also shows a strong coastal dependency, with the feature height and area coverage increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. The ice topography data have also been used to explicitly calculate atmospheric drag coefficients over Arctic sea ice; utilizing existing relationships regarding ridge geometry and their impact on form drag. The results are being used to calibrate the recent drag parameterization scheme included in the sea ice model CICE.

On imputing function to structure from the behavioural effects of brain lesions.

PubMed

Young, M P; Hilgetag, C C; Scannell, J W

2000-01-29

What is the link, if any, between the patterns of connections in the brain and the behavioural effects of localized brain lesions? We explored this question in four related ways. First, we investigated the distribution of activity decrements that followed simulated damage to elements of the thalamocortical network, using integrative mechanisms that have recently been used to successfully relate connection data to information on the spread of activation, and to account simultaneously for a variety of lesion effects. Second, we examined the consequences of the patterns of decrement seen in the simulation for each type of inference that has been employed to impute function to structure on the basis of the effects of brain lesions. Every variety of conventional inference, including double dissociation, readily misattributed function to structure. Third, we tried to derive a more reliable framework of inference for imputing function to structure, by clarifying concepts of function, and exploring a more formal framework, in which knowledge of connectivity is necessary but insufficient, based on concepts capable of mathematical specification. Fourth, we applied this framework to inferences about function relating to a simple network that reproduces intact, lesioned and paradoxically restored orientating behaviour. Lesion effects could be used to recover detailed and reliable information on which structures contributed to particular functions in this simple network. Finally, we explored how the effects of brain lesions and this formal approach could be used in conjunction with information from multiple neuroscience methodologies to develop a practical and reliable approach to inferring the functional roles of brain structures.

Displaying contextual information reduces the costs of imperfect decision automation in rapid retasking of ISR assets.

PubMed

Rovira, Ericka; Cross, Austin; Leitch, Evan; Bonaceto, Craig

2014-09-01

The impact of a decision support tool designed to embed contextual mission factors was investigated. Contextual information may enable operators to infer the appropriateness of data underlying the automation's algorithm. Research has shown the costs of imperfect automation are more detrimental than perfectly reliable automation when operators are provided with decision support tools. Operators may trust and rely on the automation more appropriately if they understand the automation's algorithm. The need to develop decision support tools that are understandable to the operator provides the rationale for the current experiment. A total of 17 participants performed a simulated rapid retasking of intelligence, surveillance, and reconnaissance (ISR) assets task with manual, decision automation, or contextual decision automation differing in two levels of task demand: low or high. Automation reliability was set at 80%, resulting in participants experiencing a mixture of reliable and automation failure trials. Dependent variables included ISR coverage and response time of replanning routes. Reliable automation significantly improved ISR coverage when compared with manual performance. Although performance suffered under imperfect automation, contextual decision automation helped to reduce some of the decrements in performance. Contextual information helps overcome the costs of imperfect decision automation. Designers may mitigate some of the performance decrements experienced with imperfect automation by providing operators with interfaces that display contextual information, that is, the state of factors that affect the reliability of the automation's recommendation.

Bowen emission from Aquila X-1: evidence for multiple components and constraint on the accretion disc vertical structure

NASA Astrophysics Data System (ADS)

Jiménez-Ibarra, F.; Muñoz-Darias, T.; Wang, L.; Casares, J.; Mata Sánchez, D.; Steeghs, D.; Armas Padilla, M.; Charles, P. A.

2018-03-01

We present a detailed spectroscopic study of the optical counterpart of the neutron star X-ray transient Aquila X-1 during its 2011, 2013 and 2016 outbursts. We use 65 intermediate resolution GTC-10.4 m spectra with the aim of detecting irradiation-induced Bowen blend emission from the donor star. While Gaussian fitting does not yield conclusive results, our full phase coverage allows us to exploit Doppler mapping techniques to independently constrain the donor star radial velocity. By using the component N III 4640.64/4641.84 Å, we measure Kem = 102 ± 6 km s-1. This highly significant detection (≳13σ) is fully compatible with the true companion star radial velocity obtained from near-infrared spectroscopy during quiescence. Combining these two velocities we determine, for the first time, the accretion disc opening angle and its associated error from direct spectroscopic measurements and detailed modelling, obtaining α = 15.5 ^{+ 2.5}_{-5} deg. This value is consistent with theoretical work if significant X-ray irradiation is taken into account and is important in the light of recent observations of GX339-4, where discrepant results were obtained between the donor's intrinsic radial velocity and the Bowen-inferred value. We also discuss the limitations of the Bowen technique when complete phase coverage is not available.

On land-use modeling: A treatise of satellite imagery data and misclassification error

NASA Astrophysics Data System (ADS)

Sandler, Austin M.

Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

The September 25, 2003 Tokachi-Oki Mw 8.3 Earthquake: Rupture Process From Joint Inversion of Tsunami Waveform, GPS, and Pressure Gages Data

NASA Astrophysics Data System (ADS)

Romano, F.; Lorito, S.; Piatanesi, A.; Antonioli, A.; George, D. L.; Hirata, K.

2008-12-01

We infer the slip distribution along the rupture zone of the September 25, 2003 Hokkaido Region (Japan) from tide-gages records of the tsunami, pressure gages, and GPS measured static coseismic displacements. According to USGS, this one has been the largest earthquake in 2003. We select waveforms from 16 stations, distributed along the east coast of the Hokkaido Region and the north-east coast of the Tohoku Region. Furthermore we select more than 100 GPS stations positioned on these regions and 2 high-precision pressure gages positioned in open sea near the epicenter; indeed the seafloor measurement of the water pressure is an innovative geodetic observation because the displacement of the seafloor is directly proportional to water pressure increase. We assume the fault plane to be consistent with the geometry of the subducting plate and the slip direction with the focal mechanism solutions and previous inversions of teleseismic body waves. We subdivide the fault plane into several subfaults (both along strike and down dip) and we compute the corresponding Green's function for the coseismic displacement considering a 3D Earth's model implemented in a Finite-Element code. As for the tsunami Green's function we use the shallow water equations and a bathymetric dataset with 10 arcsec of spatial resolution. The slip distribution is determined by means of a simulated annealing technique. Synthetic checkerboard tests, using the station coverage of the available data, indicate that the main features of the rupture process may be robustly inverted with a minimum subfault area of 30x30 km. We compare our results with those obtained by previous inversions of teleseismic, GPS and tsunami data.

DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Costa, Michelle N.; Stevens, S.L.

A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks thatmore » are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a predictive model of transcriptional expression levels.« less

45 CFR 155.1040 - Transparency in coverage.

Code of Federal Regulations, 2014 CFR

2014-10-01

....1040 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS... Functions: Certification of Qualified Health Plans § 155.1040 Transparency in coverage. (a) General requirement. The Exchange must collect information relating to coverage transparency as described in § 156.220...

45 CFR 155.1040 - Transparency in coverage.

Code of Federal Regulations, 2013 CFR

2013-10-01

....1040 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS... Functions: Certification of Qualified Health Plans § 155.1040 Transparency in coverage. (a) General requirement. The Exchange must collect information relating to coverage transparency as described in § 156.220...

Adult Attachment Affects Neural Response to Preference-Inferring in Ambiguous Scenarios: Evidence From an fMRI Study

PubMed Central

Zhang, Xing; Ran, Guangming; Xu, Wenjian; Ma, Yuanxiao; Chen, Xu

2018-01-01

Humans are highly social animals, and the ability to cater to the preferences of other individuals is encouraged by society. Preference-inferring is an important aspect of the theory of mind (TOM). Many previous studies have shown that attachment style is closely related to TOM ability. However, little is known about the effects of adult attachment style on preferences inferring under different levels of certainty. Here, we investigated how adult attachment style affects neural activity underlying preferences inferred under different levels of certainty by using functional magnetic resonance imaging (fMRI). The fMRI results demonstrated that adult attachment influenced the activation of anterior insula (AI) and inferior parietal lobule (IPL) in response to ambiguous preference-inferring. More specifically, in the ambiguous preference condition, the avoidant attached groups exhibited a significantly enhanced activation than secure and anxious attached groups in left IPL; the anxious attached groups exhibited a significantly reduced activation secure attached group in left IPL. In addition, the anxious attached groups exhibited a significantly reduced activation than secure and avoidant attached groups in left AI. These results were also further confirmed by the subsequent PPI analysis. The results from current study suggest that, under ambiguous situations, the avoidant attached individuals show lower sensitivity to the preference of other individuals and need to invest more cognitive resources for preference-reasoning; while compared with avoidant attached group, the anxious attached individuals express high tolerance for uncertainty and a higher ToM proficiency. Results from the current study imply that differences in preference-inferring under ambiguous conditions associated with different levels of individual attachment may explain the differences in interpersonal interaction. PMID:29559932

The positive relationships between plant coverage, species richness, and aboveground biomass are ubiquitous across plant growth forms in semi-steppe rangelands.

PubMed

Sanaei, Anvar; Ali, Arshad; Chahouki, Mohammad Ali Zare

2018-01-01

The positive relationships between biodiversity and aboveground biomass are important for biodiversity conservation and greater ecosystem functioning and services that humans depend on. However, the interaction effects of plant coverage and biodiversity on aboveground biomass across plant growth forms (shrubs, forbs and grasses) in natural rangelands are poorly studied. Here, we hypothesized that, while accounting for environmental factors and disturbance intensities, the positive relationships between plant coverage, biodiversity, and aboveground biomass are ubiquitous across plant growth forms in natural rangelands. We applied structural equation models (SEMs) using data from 735 quadrats across 35 study sites in semi-steppe rangelands in Iran. The combination of plant coverage and species richness rather than Shannon's diversity or species diversity (a latent variable of species richness and evenness) substantially enhance aboveground biomass across plant growth forms. In all selected SEMs, plant coverage had a strong positive direct effect on aboveground biomass (β = 0.72 for shrubs, 0.84 for forbs and 0.80 for grasses), followed by a positive effect of species richness (β = 0.26 for shrubs, 0.05 for forbs and 0.09 for grasses), and topographic factors. Disturbance intensity had a negative effect on plant coverage, whereas it had a variable effect on species richness across plant growth forms. Plant coverage had a strong positive total effect on aboveground biomass (β = 0.84 for shrubs, 0.88 for forbs, and 0.85 for grasses), followed by a positive effect of species richness, and a negative effect of disturbance intensity across plant growth forms. Our results shed light on the management of rangelands that is high plant coverage can significantly improve species richness and aboveground biomass across plant growth forms. We also found that high disturbance intensity due to heavy grazing has a strong negative effect on plant coverage rather than species richness in semi-steppe rangelands. This study suggests that proper grazing systems (e.g. rotational system) based on carrying capacity and stocking rate of a rangeland may be helpful for biodiversity conservation, better grazing of livestock, improvement of plant coverage and enhancement of aboveground biomass. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inference of neuronal network spike dynamics and topology from calcium imaging data

PubMed Central

Lütcke, Henry; Gerhard, Felipe; Zenke, Friedemann; Gerstner, Wulfram; Helmchen, Fritjof

2013-01-01

Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP) occurrence (“spike trains”) from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR) and acquisition rate affect spike inference and whether additional information about network structure can be extracted. Here we present a simulation framework for quantitatively assessing how well spike dynamics and network topology can be inferred from noisy calcium imaging data. For simulated AP-evoked calcium transients in neocortical pyramidal cells, we analyzed the quality of spike inference as a function of SNR and data acquisition rate using a recently introduced peeling algorithm. Given experimentally attainable values of SNR and acquisition rate, neural spike trains could be reconstructed accurately and with up to millisecond precision. We then applied statistical neuronal network models to explore how remaining uncertainties in spike inference affect estimates of network connectivity and topological features of network organization. We define the experimental conditions suitable for inferring whether the network has a scale-free structure and determine how well hub neurons can be identified. Our findings provide a benchmark for future calcium imaging studies that aim to reliably infer neuronal network properties. PMID:24399936

Phylogeny of haemosporidian blood parasites revealed by a multi-gene approach.

PubMed

Borner, Janus; Pick, Christian; Thiede, Jenny; Kolawole, Olatunji Matthew; Kingsley, Manchang Tanyi; Schulze, Jana; Cottontail, Veronika M; Wellinghausen, Nele; Schmidt-Chanasit, Jonas; Bruchhaus, Iris; Burmester, Thorsten

2016-01-01

The apicomplexan order Haemosporida is a clade of unicellular blood parasites that infect a variety of reptilian, avian and mammalian hosts. Among them are the agents of human malaria, parasites of the genus Plasmodium, which pose a major threat to human health. Illuminating the evolutionary history of Haemosporida may help us in understanding their enormous biological diversity, as well as tracing the multiple host switches and associated acquisitions of novel life-history traits. However, the deep-level phylogenetic relationships among major haemosporidian clades have remained enigmatic because the datasets employed in phylogenetic analyses were severely limited in either gene coverage or taxon sampling. Using a PCR-based approach that employs a novel set of primers, we sequenced fragments of 21 nuclear genes from seven haemosporidian parasites of the genera Leucocytozoon, Haemoproteus, Parahaemoproteus, Polychromophilus and Plasmodium. After addition of genomic data from 25 apicomplexan species, the unreduced alignment comprised 20,580 bp from 32 species. Phylogenetic analyses were performed based on nucleotide, codon and amino acid data employing Bayesian inference, maximum likelihood and maximum parsimony. All analyses resulted in highly congruent topologies. We found consistent support for a basal position of Leucocytozoon within Haemosporida. In contrast to all previous studies, we recovered a sister group relationship between the genera Polychromophilus and Plasmodium. Within Plasmodium, the sauropsid and mammal-infecting lineages were recovered as sister clades. Support for these relationships was high in nearly all trees, revealing a novel phylogeny of Haemosporida, which is robust to the choice of the outgroup and the method of tree inference. Copyright © 2015 Elsevier Inc. All rights reserved.

Ecological restoration and its effects on a regional climate: the source region of the Yellow River, China.

PubMed

Li, Zhouyuan; Liu, Xuehua; Niu, Tianlin; Kejia, De; Zhou, Qingping; Ma, Tianxiao; Gao, Yunyang

2015-05-19

The source region of the Yellow River, China, experienced degradation during the 1980s and 1990s, but effective ecological restoration projects have restored the alpine grassland ecosystem. The local government has taken action to restore the grassland area since 1996. Remote sensing monitoring results show an initial restoration of this alpine grassland ecosystem with the structural transformation of land cover from 2000 to 2009 as low- and high-coverage grassland recovered. From 2000 to 2009, the low-coverage grassland area expanded by over 25% and the bare soil area decreased by approximately 15%. To examine the relationship between ecological structure and function, surface temperature (Ts) and evapotranspiration (ET) levels were estimated to study the dynamics of the hydro-heat pattern. The results show a turning point in approximately the year 2000 from a declining ET to a rising ET, eventually reaching the 1990 level of approximately 1.5 cm/day. We conclude that grassland coverage expansion has improved the regional hydrologic cycle as a consequence of ecological restoration. Thus, we suggest that long-term restoration and monitoring efforts would help maintain the climatic adjustment functions of this alpine grassland ecosystem.

Parallel Proximity Detection for Computer Simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)

1997-01-01

The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are includes by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

Parallel Proximity Detection for Computer Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)

1998-01-01

The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are included by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

Theory of Mind disruption and recruitment of the right hemisphere during narrative comprehension in autism

PubMed Central

Mason, Robert A.; Williams, Diane L.; Kana, Rajesh K.; Minshew, Nancy; Just, Marcel Adam

2008-01-01

The intersection of Theory of Mind (ToM) processing and complex narrative comprehension in high functioning autism was examined by comparing cortical activation during the reading of passages that required inferences based on either intentions, emotional states, or physical causality. Right hemisphere activation was substantially greater for all sentences in the autism group than in a matched control group suggesting decreased LH capacity in autism resulting in a spillover of processing to RH homologs. Moreover, the ToM network was disrupted. The autism group showed similar activation for all inference types in the right temporo-parietal component of the ToM network whereas the control participants selectively activated this network only when appropriate. The autism group had lower functional connectivity within the ToM network and also between the ToM and a left hemisphere language network. Furthermore, the within-network functional connectivity in autism was correlated with the size of the anterior portion of the corpus callosum. PMID:17869314

Theory of Mind disruption and recruitment of the right hemisphere during narrative comprehension in autism.

PubMed

Mason, Robert A; Williams, Diane L; Kana, Rajesh K; Minshew, Nancy; Just, Marcel Adam

2008-01-15

The intersection of Theory of Mind (ToM) processing and complex narrative comprehension in high functioning autism was examined by comparing cortical activation during the reading of passages that required inferences based on either intentions, emotional states, or physical causality. Right hemisphere activation was substantially greater for all sentences in the autism group than in a matched control group suggesting decreased LH capacity in autism resulting in a spillover of processing to RH homologs. Moreover, the ToM network was disrupted. The autism group showed similar activation for all inference types in the right temporo-parietal component of the ToM network whereas the control participants selectively activated this network only when appropriate. The autism group had lower functional connectivity within the ToM network and also between the ToM and a left hemisphere language network. Furthermore, the within-network functional connectivity in autism was correlated with the size of the anterior portion of the corpus callosum.

Nonparametric Bayesian inference for mean residual life functions in survival analysis.

PubMed

Poynor, Valerie; Kottas, Athanasios

2018-01-19

Modeling and inference for survival analysis problems typically revolves around different functions related to the survival distribution. Here, we focus on the mean residual life (MRL) function, which provides the expected remaining lifetime given that a subject has survived (i.e. is event-free) up to a particular time. This function is of direct interest in reliability, medical, and actuarial fields. In addition to its practical interpretation, the MRL function characterizes the survival distribution. We develop general Bayesian nonparametric inference for MRL functions built from a Dirichlet process mixture model for the associated survival distribution. The resulting model for the MRL function admits a representation as a mixture of the kernel MRL functions with time-dependent mixture weights. This model structure allows for a wide range of shapes for the MRL function. Particular emphasis is placed on the selection of the mixture kernel, taken to be a gamma distribution, to obtain desirable properties for the MRL function arising from the mixture model. The inference method is illustrated with a data set of two experimental groups and a data set involving right censoring. The supplementary material available at Biostatistics online provides further results on empirical performance of the model, using simulated data examples. © The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Less is More: Membrane Protein Digestion Beyond Urea-Trypsin Solution for Next-level Proteomics.

PubMed

Zhang, Xi

2015-09-01

The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea-trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting-not destroying-structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Supernova Cosmology Inference with Probabilistic Photometric Redshifts (SCIPPR)

NASA Astrophysics Data System (ADS)

Peters, Christina; Malz, Alex; Hlozek, Renée

2018-01-01

The Bayesian Estimation Applied to Multiple Species (BEAMS) framework employs probabilistic supernova type classifications to do photometric SN cosmology. This work extends BEAMS to replace high-confidence spectroscopic redshifts with photometric redshift probability density functions, a capability that will be essential in the era the Large Synoptic Survey Telescope and other next-generation photometric surveys where it will not be possible to perform spectroscopic follow up on every SN. We present the Supernova Cosmology Inference with Probabilistic Photometric Redshifts (SCIPPR) Bayesian hierarchical model for constraining the cosmological parameters from photometric lightcurves and host galaxy photometry, which includes selection effects and is extensible to uncertainty in the redshift-dependent supernova type proportions. We create a pair of realistic mock catalogs of joint posteriors over supernova type, redshift, and distance modulus informed by photometric supernova lightcurves and over redshift from simulated host galaxy photometry. We perform inference under our model to obtain a joint posterior probability distribution over the cosmological parameters and compare our results with other methods, namely: a spectroscopic subset, a subset of high probability photometrically classified supernovae, and reducing the photometric redshift probability to a single measurement and error bar.

Novel Computational Approaches to Drug Discovery

NASA Astrophysics Data System (ADS)

Skolnick, Jeffrey; Brylinski, Michal

2010-01-01

New approaches to protein functional inference based on protein structure and evolution are described. First, FINDSITE, a threading based approach to protein function prediction, is summarized. Then, the results of large scale benchmarking of ligand binding site prediction, ligand screening, including applications to HIV protease, and GO molecular functional inference are presented. A key advantage of FINDSITE is its ability to use low resolution, predicted structures as well as high resolution experimental structures. Then, an extension of FINDSITE to ligand screening in GPCRs using predicted GPCR structures, FINDSITE/QDOCKX, is presented. This is a particularly difficult case as there are few experimentally solved GPCR structures. Thus, we first train on a subset of known binding ligands for a set of GPCRs; this is then followed by benchmarking against a large ligand library. For the virtual ligand screening of a number of Dopamine receptors, encouraging results are seen, with significant enrichment in identified ligands over those found in the training set. Thus, FINDSITE and its extensions represent a powerful approach to the successful prediction of a variety of molecular functions.

High Awareness but Low Coverage of a Locally Produced Fortified Complementary Food in Abidjan, Côte d'Ivoire: Findings from a Cross-Sectional Survey.

PubMed

Leyvraz, Magali; Rohner, Fabian; Konan, Amoin G; Esso, Lasme J C E; Woodruff, Bradley A; Norte, Augusto; Adiko, Adiko F; Bonfoh, Bassirou; Aaron, Grant J

2016-01-01

Poor complementary feeding practices among infants and young children in Côte d'Ivoire are major contributing factors to the country's high burden of malnutrition. As part of a broad effort to address this issue, an affordable, nutritious, and locally produced fortified complementary food product was launched in the Côte d'Ivoire in 2011. The objective of the current research was to assess various levels of coverage of the program and to identify coverage barriers. A cross-sectional household survey was conducted among caregivers of children less than 2-years of age living in Abidjan, Côte d'Ivoire. Four measures of coverage were assessed: "message coverage" (i.e., has the caregiver ever heard of the product?), "contact coverage" (i.e., has the caregiver ever fed the child the product?), "partial coverage" (i.e., has the caregiver fed the child the product in the previous month?), and "effective coverage" (i.e., has the caregiver fed the child the product in the previous 7 days?). A total of 1,113 caregivers with children between 0 and 23 months of age were interviewed. Results showed high message coverage (85.0%), moderate contact coverage (37.8%), and poor partial and effective coverages (8.8% and 4.6%, respectively). Product awareness was lower among caregivers from poorer households, but partial and effective coverages were comparable in both poor and non-poor groups. Infant and young child feeding (IYCF) practices were generally poor and did not appear to have improved since previous assessments. In conclusion, the results from the present study indicate that availability on the market and high awareness among the target population is not sufficient to achieve high and effective coverage. With market-based delivery models, significant efforts are needed to improve demand. Moreover, given the high prevalence of malnutrition and poor IYCF practices, additional modes of delivering IYCF interventions and improving IYCF practices should be considered.

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

DOE PAGES

Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; ...

2015-06-01

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond thosemore » of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.« less

Boosting Bayesian parameter inference of stochastic differential equation models with methods from statistical physics

NASA Astrophysics Data System (ADS)

Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

2016-04-01

Measured time-series of both precipitation and runoff are known to exhibit highly non-trivial statistical properties. For making reliable probabilistic predictions in hydrology, it is therefore desirable to have stochastic models with output distributions that share these properties. When parameters of such models have to be inferred from data, we also need to quantify the associated parametric uncertainty. For non-trivial stochastic models, however, this latter step is typically very demanding, both conceptually and numerically, and always never done in hydrology. Here, we demonstrate that methods developed in statistical physics make a large class of stochastic differential equation (SDE) models amenable to a full-fledged Bayesian parameter inference. For concreteness we demonstrate these methods by means of a simple yet non-trivial toy SDE model. We consider a natural catchment that can be described by a linear reservoir, at the scale of observation. All the neglected processes are assumed to happen at much shorter time-scales and are therefore modeled with a Gaussian white noise term, the standard deviation of which is assumed to scale linearly with the system state (water volume in the catchment). Even for constant input, the outputs of this simple non-linear SDE model show a wealth of desirable statistical properties, such as fat-tailed distributions and long-range correlations. Standard algorithms for Bayesian inference fail, for models of this kind, because their likelihood functions are extremely high-dimensional intractable integrals over all possible model realizations. The use of Kalman filters is illegitimate due to the non-linearity of the model. Particle filters could be used but become increasingly inefficient with growing number of data points. Hamiltonian Monte Carlo algorithms allow us to translate this inference problem to the problem of simulating the dynamics of a statistical mechanics system and give us access to most sophisticated methods that have been developed in the statistical physics community over the last few decades. We demonstrate that such methods, along with automated differentiation algorithms, allow us to perform a full-fledged Bayesian inference, for a large class of SDE models, in a highly efficient and largely automatized manner. Furthermore, our algorithm is highly parallelizable. For our toy model, discretized with a few hundred points, a full Bayesian inference can be performed in a matter of seconds on a standard PC.

Cost-Effectiveness of Providing Full Drug Coverage to Increase Medication Adherence in Post–Myocardial Infarction Medicare Beneficiaries

PubMed Central

Choudhry, Niteesh K.; Patrick, Amanda R.; Antman, Elliott M.; Avorn, Jerry; Shrank, William H.

2009-01-01

Background Effective therapies for the secondary prevention of coronary heart disease–related events are significantly underused, and attempts to improve adherence have often yielded disappointing results. Elimination of patient out-of-pocket costs may be an effective strategy to enhance medication use. We sought to estimate the incremental cost-effectiveness of providing full coverage for aspirin, β-blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and statins (combination pharmacotherapy) to individuals enrolled in the Medicare drug benefit program after acute myocardial infarction. Methods and Results We created a Markov cost-effectiveness model to estimate the incremental cost-effectiveness of providing Medicare beneficiaries with full coverage for combination pharmacotherapy compared with current coverage under the Medicare Part D program. Our analysis was conducted from the societal perspective and considered a lifetime time horizon. In a sensitivity analysis, we repeated our analysis from the perspective of Medicare. In the model, post–myocardial infarction Medicare beneficiaries who received usual prescription drug coverage under the Part D program lived an average of 8.21 quality-adjusted life-years after their initial event, incurring coronary heart disease–related medical costs of $114 000. Those who received prescription drug coverage without deductibles or copayments lived an average of 8.56 quality-adjusted life-years and incurred $111 600 in coronary heart disease–related costs. Compared with current prescription drug coverage, full coverage for post–myocardial infarction secondary prevention therapies would result in greater functional life expectancy (0.35 quality-adjusted life-year) and less resource use ($2500). From the perspective of Medicare, full drug coverage was highly cost-effective ($7182/quality-adjusted life-year) but not cost saving. Conclusions Our analysis suggests that providing full coverage for combination therapy to post–myocardial infarction Medicare beneficiaries would save both lives and money from the societal perspective. PMID:18285564

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

Space-Time Data fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Braverman, Amy; Nguyen, H.; Cressie, N.

2011-01-01

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

Sexual selection targets cetacean pelvic bones

PubMed Central

Dines, J. P.; Otárola-Castillo, E.; Ralph, P.; Alas, J.; Daley, T.; Smith, A. D.; Dean, M. D.

2014-01-01

Male genitalia evolve rapidly, probably as a result of sexual selection. Whether this pattern extends to the internal infrastructure that influences genital movements remains unknown. Cetaceans (whales and dolphins) offer a unique opportunity to test this hypothesis: since evolving from land-dwelling ancestors, they lost external hind limbs and evolved a highly reduced pelvis which seems to serve no other function except to anchor muscles that maneuver the penis. Here we create a novel morphometric pipeline to analyze the size and shape evolution of pelvic bones from 130 individuals (29 species) in the context of inferred mating system. We present two main findings: 1) males from species with relatively intense sexual selection (inferred by relative testes size) have evolved relatively large penises and pelvic bones compared to their body size, and 2) pelvic bone shape diverges more quickly in species pairs that have diverged in inferred mating system. Neither pattern was observed in the anterior-most pair of vertebral ribs, which served as a negative control. This study provides evidence that sexual selection can affect internal anatomy that controls male genitalia. These important functions may explain why cetacean pelvic bones have not been lost through evolutionary time. PMID:25186496

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

Discrimination of Human Forearm Motions on the Basis of Myoelectric Signals by Using Adaptive Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Kiso, Atsushi; Seki, Hirokazu

This paper describes a method for discriminating of the human forearm motions based on the myoelectric signals using an adaptive fuzzy inference system. In conventional studies, the neural network is often used to estimate motion intention by the myoelectric signals and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signals. This study designs the membership function and the fuzzy rules using the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. In addition, the characteristics of the myoelectric potential gradually change as a result of the muscle fatigue. Therefore, the motion discrimination should be performed by taking muscle fatigue into consideration. This study proposes a method to redesign the fuzzy inference system such that dynamic change of the myoelectric potential because of the muscle fatigue will be taken into account. Some experiments carried out using a myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.

Defining functional DNA elements in the human genome

PubMed Central

Kellis, Manolis; Wold, Barbara; Snyder, Michael P.; Bernstein, Bradley E.; Kundaje, Anshul; Marinov, Georgi K.; Ward, Lucas D.; Birney, Ewan; Crawford, Gregory E.; Dekker, Job; Dunham, Ian; Elnitski, Laura L.; Farnham, Peggy J.; Feingold, Elise A.; Gerstein, Mark; Giddings, Morgan C.; Gilbert, David M.; Gingeras, Thomas R.; Green, Eric D.; Guigo, Roderic; Hubbard, Tim; Kent, Jim; Lieb, Jason D.; Myers, Richard M.; Pazin, Michael J.; Ren, Bing; Stamatoyannopoulos, John A.; Weng, Zhiping; White, Kevin P.; Hardison, Ross C.

2014-01-01

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease. PMID:24753594

C-Span in the American Government Classroom.

ERIC Educational Resources Information Center

National Cable Satellite Corp., Washington, DC.

Encouraging educators' use of live and unedited television coverage of the functions of government, this publication contains seven lessons for the high school social studies curriculum. The C-Span has no time or space constraints and broadcasts all events in their entirety; unedited lessons teach concepts and objectives and the emphasis is on the…

Ocean surface partitioning strategies using ocean colour remote Sensing: A review

NASA Astrophysics Data System (ADS)

Krug, Lilian Anne; Platt, Trevor; Sathyendranath, Shubha; Barbosa, Ana B.

2017-06-01

The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological responses. The delineation of these functional units, each with unique, homogeneous properties and underlying ecosystem structure and dynamics, can be defined as ocean surface partitioning. The main purposes and applications of ocean partitioning include the evaluation of particular marine environments; generation of more accurate satellite ocean colour products; assimilation of data into biogeochemical and climate models; and establishment of ecosystem-based management practices. This paper reviews the diverse approaches implemented for ocean surface partition into functional units, using ocean colour remote sensing (OCRS) data, including their purposes, criteria, methods and scales. OCRS offers a synoptic, high spatial-temporal resolution, multi-decadal coverage of bio-optical properties, relevant to the applications and value of ocean surface partitioning. In combination with other biotic and/or abiotic data, OCRS-derived data (e.g., chlorophyll-a, optical properties) provide a broad and varied source of information that can be analysed using different delineation methods derived from subjective, expert-based to unsupervised learning approaches (e.g., cluster, fuzzy and empirical orthogonal function analyses). Partition schemes are applied at global to mesoscale spatial coverage, with static (time-invariant) or dynamic (time-varying) representations. A case study, the highly heterogeneous area off SW Iberian Peninsula (NE Atlantic), illustrates how the selection of spatial coverage and temporal representation affects the discrimination of distinct environmental drivers of phytoplankton variability. Advances in operational oceanography and in the subject area of satellite ocean colour, including development of new sensors, algorithms and products, are among the potential benefits from extended use, scope and applications of ocean surface partitioning using OCRS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Tony Y.; Wechsler, Risa H.; Devaraj, Kiruthika

Intensity mapping, which images a single spectral line from unresolved galaxies across cosmological volumes, is a promising technique for probing the early universe. Here we present predictions for the intensity map and power spectrum of the CO(1–0) line from galaxies atmore » $$z\\sim 2.4$$–2.8, based on a parameterized model for the galaxy–halo connection, and demonstrate the extent to which properties of high-redshift galaxies can be directly inferred from such observations. We find that our fiducial prediction should be detectable by a realistic experiment. Motivated by significant modeling uncertainties, we demonstrate the effect on the power spectrum of varying each parameter in our model. Using simulated observations, we infer constraints on our model parameter space with an MCMC procedure, and show corresponding constraints on the $${L}_{\\mathrm{IR}}$$–$${L}_{\\mathrm{CO}}$$ relation and the CO luminosity function. These constraints would be complementary to current high-redshift galaxy observations, which can detect the brightest galaxies but not complete samples from the faint end of the luminosity function. Furthermore, by probing these populations in aggregate, CO intensity mapping could be a valuable tool for probing molecular gas and its relation to star formation in high-redshift galaxies.« less

Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

PubMed Central

Liu, Ning; Cui, Xu; Bryant, Daniel M.; Glover, Gary H.; Reiss, Allan L.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research. PMID:25798327

Observations of GEO Debris with the Magellan 6.5-m Telescopes

NASA Technical Reports Server (NTRS)

Seitzer, Patrick; Burkhardt, Andrew; Cardonna, Tommaso; Lederer, Susan M.; Cowardin, Heather; Barker, Edwin S.; Abercromby, Kira J.

2012-01-01

Optical observations of geosynchronous orbit (GEO) debris are important to address two questions: 1. What is the distribution function of objects at GEO as a function of brightness? With some assumptions, this can be used to infer a size distribution. 2. Can we determine what the likely composition of individual GEO debris pieces is from studies of the spectral reflectance of these objects? In this paper we report on optical observations with the 6.5-m Magellan telescopes at Las Campanas Observatory in Chile that attempt to answer both questions. Imaging observations over a 0.5 degree diameter field-of-view have detected a significant population of optically faint debris candidates with R > 19th magnitude, corresponding to a size smaller than 20 cm assuming an albedo of 0.175. Many of these objects show brightness variations larger than a factor of 2, suggesting either irregular shapes or albedo variations or both. The object detection rate (per square degree per hour) shows an increase over the rate measured in the 0.6-m MODEST observations, implying an increase in the population at optically fainter levels. Assuming that the albedo distribution is the same for both samples, this corresponds to an increase in the population of smaller size debris. To study the second issue, calibrated reflectance spectroscopy has been obtained of a sample of GEO and near GEO objects with orbits in the public U.S. Space Surveillance Network catalog. With a 6.5-m telescope, the exposures times are short (30 seconds or less), and provide simultaneous wavelength coverage from 4500 to 8000 Angstroms. If the observed objects are tumbling, then simultaneous coverage and short exposure times are essential for a realistic assessment of the object fs spectral signature. We will compare the calibrated spectra with lab-based measurements of simple spacecraft surfaces composed of a single material.

Theoretical study of cathode surfaces and high-temperature superconductors

NASA Technical Reports Server (NTRS)

Mueller, Wolfgang

1994-01-01

The surface-dipole properties of model cathode surfaces have been investigated with relativistic scattered-wave cluster calculations. Work-function/coverage curves have been derived from these data by employing the depolarization model of interacting surface dipoles. Accurate values have been obtained for the minimum work functions of several low-work-function surfaces. In the series BaO on bcc W, hcp Os, and fcc Pt, BaO/Os shows a lower and BaO/Pt a higher work function than BaO/W, which is attributed to the different substrate crystal structures involved. Results are also presented on the electronic structure of the high-temperature superconductor YBa2Cu3O7, which has been investigated with fully relativistic calculations for the first time.

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Routine Vaccination Coverage in Northern Nigeria: Results from 40 District-Level Cluster Surveys, 2014-2015

PubMed Central

Ogbuanu, Ikechukwu U.; Adegoke, Oluwasegun J.; Scobie, Heather M.; Uba, Belinda V.; Wannemuehler, Kathleen A.; Ruiz, Alicia; Elmousaad, Hashim; Ohuabunwo, Chima J.; Mustafa, Mahmud; Nguku, Patrick; Waziri, Ndadilnasiya Endie; Vertefeuille, John F.

2016-01-01

Background Despite recent success towards controlling poliovirus transmission, Nigeria has struggled to achieve uniformly high routine vaccination coverage. A lack of reliable vaccination coverage data at the operational level makes it challenging to target program improvement. To reliably estimate vaccination coverage, we conducted district-level vaccine coverage surveys using a pre-existing infrastructure of polio technical staff in northern Nigeria. Methods Household-level cluster surveys were conducted in 40 polio high risk districts of Nigeria during 2014–2015. Global positioning system technology and intensive supervision by a pool of qualified technical staff were used to ensure high survey quality. Vaccination status of children aged 12–23 months was documented based on vaccination card or caretaker’s recall. District-level coverage estimates were calculated using survey methods. Results Data from 7,815 children across 40 districts were analyzed. District-level coverage with the third dose of diphtheria-pertussis-tetanus vaccine (DPT3) ranged widely from 1–63%, with all districts having DPT3 coverage below the target of 80%. Median coverage across all districts for each of eight vaccine doses (1 Bacille Calmette-Guérin dose, 3 DPT doses, 3 oral poliovirus vaccine doses, and 1 measles vaccine dose) was <50%. DPT3 coverage by survey was substantially lower (range: 28%–139%) than the 2013 administrative coverage reported among children aged <12 months. Common reported reasons for non-vaccination included lack of knowledge about vaccines and vaccination services (50%) and factors related to access to routine immunization services (15%). Conclusions Survey results highlighted vaccine coverage gaps that were systematically underestimated by administrative reporting across 40 polio high risk districts in northern Nigeria. Given the limitations of administrative coverage data, our approach to conducting quality district-level coverage surveys and providing data to assess and remediate issues contributing to poor vaccination coverage could serve as an example in countries with sub-optimal vaccination coverage, similar to Nigeria. PMID:27936077

Routine Vaccination Coverage in Northern Nigeria: Results from 40 District-Level Cluster Surveys, 2014-2015.

PubMed

Gunnala, Rajni; Ogbuanu, Ikechukwu U; Adegoke, Oluwasegun J; Scobie, Heather M; Uba, Belinda V; Wannemuehler, Kathleen A; Ruiz, Alicia; Elmousaad, Hashim; Ohuabunwo, Chima J; Mustafa, Mahmud; Nguku, Patrick; Waziri, Ndadilnasiya Endie; Vertefeuille, John F

2016-01-01

Despite recent success towards controlling poliovirus transmission, Nigeria has struggled to achieve uniformly high routine vaccination coverage. A lack of reliable vaccination coverage data at the operational level makes it challenging to target program improvement. To reliably estimate vaccination coverage, we conducted district-level vaccine coverage surveys using a pre-existing infrastructure of polio technical staff in northern Nigeria. Household-level cluster surveys were conducted in 40 polio high risk districts of Nigeria during 2014-2015. Global positioning system technology and intensive supervision by a pool of qualified technical staff were used to ensure high survey quality. Vaccination status of children aged 12-23 months was documented based on vaccination card or caretaker's recall. District-level coverage estimates were calculated using survey methods. Data from 7,815 children across 40 districts were analyzed. District-level coverage with the third dose of diphtheria-pertussis-tetanus vaccine (DPT3) ranged widely from 1-63%, with all districts having DPT3 coverage below the target of 80%. Median coverage across all districts for each of eight vaccine doses (1 Bacille Calmette-Guérin dose, 3 DPT doses, 3 oral poliovirus vaccine doses, and 1 measles vaccine dose) was <50%. DPT3 coverage by survey was substantially lower (range: 28%-139%) than the 2013 administrative coverage reported among children aged <12 months. Common reported reasons for non-vaccination included lack of knowledge about vaccines and vaccination services (50%) and factors related to access to routine immunization services (15%). Survey results highlighted vaccine coverage gaps that were systematically underestimated by administrative reporting across 40 polio high risk districts in northern Nigeria. Given the limitations of administrative coverage data, our approach to conducting quality district-level coverage surveys and providing data to assess and remediate issues contributing to poor vaccination coverage could serve as an example in countries with sub-optimal vaccination coverage, similar to Nigeria.

An improved rainfall disaggregation technique for GCMs

NASA Astrophysics Data System (ADS)

Onof, C.; Mackay, N. G.; Oh, L.; Wheater, H. S.

1998-08-01

Meteorological models represent rainfall as a mean value for a grid square so that when the latter is large, a disaggregation scheme is required to represent the spatial variability of rainfall. In general circulation models (GCMs) this is based on an assumption of exponentiality of rainfall intensities and a fixed value of areal rainfall coverage, dependent on rainfall type. This paper examines these two assumptions on the basis of U.K. and U.S. radar data. Firstly, the coverage of an area is strongly dependent on its size, and this dependence exhibits a scaling law over a range of sizes. Secondly, the coverage is, of course, dependent on the resolution at which it is measured, although this dependence is weak at high resolutions. Thirdly, the time series of rainfall coverages has a long-tailed autocorrelation function which is comparable to that of the mean areal rainfalls. It is therefore possible to reproduce much of the temporal dependence of coverages by using a regression of the log of the mean rainfall on the log of the coverage. The exponential assumption is satisfactory in many cases but not able to reproduce some of the long-tailed dependence of some intensity distributions. Gamma and lognormal distributions provide a better fit in these cases, but they have their shortcomings and require a second parameter. An improved disaggregation scheme for GCMs is proposed which incorporates the previous findings to allow the coverage to be obtained for any area and any mean rainfall intensity. The parameters required are given and some of their seasonal behavior is analyzed.

Indexing the Environmental Quality Performance Based on A Fuzzy Inference Approach

NASA Astrophysics Data System (ADS)

Iswari, Lizda

2018-03-01

Environmental performance strongly deals with the quality of human life. In Indonesia, this performance is quantified through Environmental Quality Index (EQI) which consists of three indicators, i.e. river quality index, air quality index, and coverage of land cover. The current of this instrument data processing was done by averaging and weighting each index to represent the EQI at the provincial level. However, we found EQI interpretations that may contain some uncertainties and have a range of circumstances possibly less appropriate if processed under a common statistical approach. In this research, we aim to manage the indicators of EQI with a more intuitive computation technique and make some inferences related to the environmental performance in 33 provinces in Indonesia. Research was conducted in three stages of Mamdani Fuzzy Inference System (MAFIS), i.e. fuzzification, data inference, and defuzzification. Data input consists of 10 environmental parameters and the output is an index of Environmental Quality Performance (EQP). Research was applied to the environmental condition data set in 2015 and quantified the results into the scale of 0 to 100, i.e. 10 provinces at good performance with the EQP above 80 dominated by provinces in eastern part of Indonesia, 22 provinces with the EQP between 80 to 50, and one province in Java Island with the EQP below 20. This research shows that environmental quality performance can be quantified without eliminating the natures of the data set and simultaneously is able to show the environment behavior along with its spatial pattern distribution.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

Inferring a Child's Level of Self-esteem from a Knowledge of Other Personality Factors.

ERIC Educational Resources Information Center

Kawash, George F.; Clewes, Janet L.

1986-01-01

Correlation and regression analysis confirmed that there is a high degree of shared variance between Coopersmith's Self-Esteem Inventory (SEI) and the Children's Personality Questionnaire (CPQ), suggesting that self-esteem may be more integrated within an individual's total personality functioning than has been discussed in the literature.…

Single-stage Reconstruction of Elbow Flexion Associated with Massive Soft-Tissue Defect Using the Latissimus Dorsi Muscle Bipolar Rotational Transfer

PubMed Central

Cuéllar, Vanessa G.; Ghiassi, Alidad; Sharpe, Frances

2016-01-01

Introduction: In the upper extremity, the latissimus dorsi muscle can be used as an ipsilateral rotational muscle flap for soft-tissue coverage or functional reconstruction of arm and elbow. Patients who have both major soft-tissue loss and functional deficits can be successfully treated with a single-stage functional latissimus dorsi rotational muscle transfer that provides simultaneous soft-tissue coverage and functional reconstruction. Methods: Our data base was queried for all patients undergoing a rotational latissimus dorsi muscle transfer for simultaneous soft-tissue coverage and functional reconstruction of elbow flexion. Four patients were identified. A chart review documented the mechanism of injury, associated injuries, soft-tissue defect size, number of surgical procedures, length of follow-up, last elbow range of motion, and flexion strength. Results: Four patients with loss of elbow flexion due to traumatic loss of the anterior compartment muscles and the overlying soft tissue underwent simultaneous soft-tissue coverage and elbow flexorplasty using the ipsilateral latissimus dorsi as a bipolar muscle rotational tissue transfer. All flaps survived and had a recovery of Medical Research Council Grade 4/5 elbow flexion strength. No additional procedures were required for elbow flexion. The surgical technique is described and supplemented with surgical technique video and patient outcome. Conclusions: This patient series augments the data provided in other series supporting the safety and efficacy of this procedure which provides both soft-tissue coverage and functional restoration of elbow flexion as a single-stage procedure in the setting of massive traumatic soft-tissue loss of the arm. PMID:27757363

Single-stage Reconstruction of Elbow Flexion Associated with Massive Soft-Tissue Defect Using the Latissimus Dorsi Muscle Bipolar Rotational Transfer.

PubMed

Stevanovic, Milan V; Cuéllar, Vanessa G; Ghiassi, Alidad; Sharpe, Frances

2016-09-01

In the upper extremity, the latissimus dorsi muscle can be used as an ipsilateral rotational muscle flap for soft-tissue coverage or functional reconstruction of arm and elbow. Patients who have both major soft-tissue loss and functional deficits can be successfully treated with a single-stage functional latissimus dorsi rotational muscle transfer that provides simultaneous soft-tissue coverage and functional reconstruction. Our data base was queried for all patients undergoing a rotational latissimus dorsi muscle transfer for simultaneous soft-tissue coverage and functional reconstruction of elbow flexion. Four patients were identified. A chart review documented the mechanism of injury, associated injuries, soft-tissue defect size, number of surgical procedures, length of follow-up, last elbow range of motion, and flexion strength. Four patients with loss of elbow flexion due to traumatic loss of the anterior compartment muscles and the overlying soft tissue underwent simultaneous soft-tissue coverage and elbow flexorplasty using the ipsilateral latissimus dorsi as a bipolar muscle rotational tissue transfer. All flaps survived and had a recovery of Medical Research Council Grade 4/5 elbow flexion strength. No additional procedures were required for elbow flexion. The surgical technique is described and supplemented with surgical technique video and patient outcome. This patient series augments the data provided in other series supporting the safety and efficacy of this procedure which provides both soft-tissue coverage and functional restoration of elbow flexion as a single-stage procedure in the setting of massive traumatic soft-tissue loss of the arm.

When is an image a health claim? A false-recollection method to detect implicit inferences about products' health benefits.

PubMed

Klepacz, Naomi A; Nash, Robert A; Egan, M Bernadette; Hodgkins, Charo E; Raats, Monique M

2016-08-01

Images on food and dietary supplement packaging might lead people to infer (appropriately or inappropriately) certain health benefits of those products. Research on this issue largely involves direct questions, which could (a) elicit inferences that would not be made unprompted, and (b) fail to capture inferences made implicitly. Using a novel memory-based method, in the present research, we explored whether packaging imagery elicits health inferences without prompting, and the extent to which these inferences are made implicitly. In 3 experiments, participants saw fictional product packages accompanied by written claims. Some packages contained an image that implied a health-related function (e.g., a brain), and some contained no image. Participants studied these packages and claims, and subsequently their memory for seen and unseen claims were tested. When a health image was featured on a package, participants often subsequently recognized health claims that-despite being implied by the image-were not truly presented. In Experiment 2, these recognition errors persisted despite an explicit warning against treating the images as informative. In Experiment 3, these findings were replicated in a large consumer sample from 5 European countries, and with a cued-recall test. These findings confirm that images can act as health claims, by leading people to infer health benefits without prompting. These inferences appear often to be implicit, and could therefore be highly pervasive. The data underscore the importance of regulating imagery on product packaging; memory-based methods represent innovative ways to measure how leading (or misleading) specific images can be. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Efficient inference for genetic association studies with multiple outcomes.

PubMed

Ruffieux, Helene; Davison, Anthony C; Hager, Jorg; Irincheeva, Irina

2017-10-01

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modeling are either too simplistic to be powerful or are impracticable for computational reasons. Inspired by Richardson and others (2010, Bayesian Statistics 9), we consider a sparse multivariate regression model that allows simultaneous selection of predictors and associated responses. As Markov chain Monte Carlo (MCMC) inference on such models can be prohibitively slow when the number of genetic variants exceeds a few thousand, we propose a variational inference approach which produces posterior information very close to that of MCMC inference, at a much reduced computational cost. Extensive numerical experiments show that our approach outperforms popular variable selection methods and tailored Bayesian procedures, dealing within hours with problems involving hundreds of thousands of genetic variants and tens to hundreds of clinical or molecular outcomes. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

PubMed Central

Zhao, Jiangsan; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A.; Nakhforoosh, Alireza

2017-01-01

Abstract Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. PMID:28168270

Robust functional regression model for marginal mean and subject-specific inferences.

PubMed

Cao, Chunzheng; Shi, Jian Qing; Lee, Youngjo

2017-01-01

We introduce flexible robust functional regression models, using various heavy-tailed processes, including a Student t-process. We propose efficient algorithms in estimating parameters for the marginal mean inferences and in predicting conditional means as well as interpolation and extrapolation for the subject-specific inferences. We develop bootstrap prediction intervals (PIs) for conditional mean curves. Numerical studies show that the proposed model provides a robust approach against data contamination or distribution misspecification, and the proposed PIs maintain the nominal confidence levels. A real data application is presented as an illustrative example.

Holocene evolution of aquatic bioactivity and terrestrial erosion inferred from Skorarvatn, Vestfirðir, Iceland: Where is the Little Ice Age?

NASA Astrophysics Data System (ADS)

Harning, D.; Geirsdottir, A.; Miller, G. H.

2016-12-01

Icelandic lake sediment is well suited to provide high-resolution, well-dated continuous archives of North Atlantic climate variability. We provide new insight into the Holocene climate evolution of Vestfirðir, NW Iceland, from a 10.3 ka multi-proxy lake sediment record from non-glacial lake Skorarvatn. Age control is derived from a combination of tephrochronology and 14C-dated macrofossils. Sediment samples were analyzed for both physical (MS, density) and biological (TC, TN, δ13C, δ15N, C/N, BSi) climate proxies, providing a sub-centennial record of aquatic bioactivity and terrestrial landscape stability, and hence, summer temperature. The lake basin was ice free by at least 10.3 ka yet the waning Icelandic Ice Sheet persisted in the catchment until 9.3 ka. The local Holocene Thermal Maximum (HTM), inferred from maximum aquatic bioactivity, spans 8.9 to 7.2 ka but was interrupted by significant cooling at 8.2 ka. In accordance with other Icelandic climate records documenting progressively cooler summers following the HTM, our record reveals reduced aquatic productivity and elevated terrestrial erosion toward the present. Superimposed on this 1st order trend are abrupt episodes of cooling, inferred from low aquatic bioactivity and/or enhanced landscape instability, at 6.4, 4.2, 3, 2.5 and 1.5 ka. Surprisingly, there is no clear indication of the Little Ice Age (LIA) in our record despite evidence for the local ice cap, Drangajökull, attaining maximum areal coverage at this time. Persistently low temperatures inferred from reduced aquatic productivity plateau at 2 ka whereas increasing terrestrial erosion ceases at 1 ka. Lack of a catchment erosion signal during the LIA may be the result of depleted catchment soils and/or perennially frozen ground preventing the mobilization of soil and vegetation. With the exception of the LIA, Skorarvatn's qualitative summer temperature record corresponds closely to summer sea surface temperature and sea ice records on the North Iceland Shelf, supporting previous evidence that the North Atlantic imparts a significant impact of the state of Iceland's terrestrial climate.

78 FR 7348 - Patient Protection and Affordable Care Act; Exchange Functions: Eligibility for Exemptions...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-01

... se and those that may apply for recognition are neither group health insurance coverage nor.... 156.602) c. Requirements for Recognition as Minimum Essential Coverage for Coverage Not Otherwise... recognition that they meet the standards under section 5000A(d)(2)(B) of the Code. We also received...

EEG functional connectivity is partially predicted by underlying white matter connectivity

PubMed Central

Chu, CJ; Tanaka, N; Diaz, J; Edlow, BL; Wu, O; Hämäläinen, M; Stufflebeam, S; Cash, SS; Kramer, MA.

2015-01-01

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales. PMID:25534110

Phytozome Comparative Plant Genomics Portal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodstein, David; Batra, Sajeev; Carlson, Joseph

2014-09-09

The Dept. of Energy Joint Genome Institute is a genomics user facility supporting DOE mission science in the areas of Bioenergy, Carbon Cycling, and Biogeochemistry. The Plant Program at the JGI applies genomic, analytical, computational and informatics platforms and methods to: 1. Understand and accelerate the improvement (domestication) of bioenergy crops 2. Characterize and moderate plant response to climate change 3. Use comparative genomics to identify constrained elements and infer gene function 4. Build high quality genomic resource platforms of JGI Plant Flagship genomes for functional and experimental work 5. Expand functional genomic resources for Plant Flagship genomes

Forward Inferences: From Activation to Long-Term Memory.

ERIC Educational Resources Information Center

Klin, Celia M.; Murray, John D.; Levine, William H.; Guzman, Alexandria E.

1999-01-01

Investigates the extent to which forward inferences are activated and encoded during reading, as well as their prevalence and their time course. Finds that inferences were encoded and retained in working memory in both high- and low-predictability conditions, and that high-predictability forward inferences were encoded into long-term memory.…

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Obesity as a risk factor for developing functional limitation among older adults: A conditional inference tree analysis

USDA-ARS?s Scientific Manuscript database

Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to con...

Narrative comprehension in 4-7-year-old children with autism: testing the Weak Central Coherence account.

PubMed

Nuske, Heather Joy; Bavin, Edith L

2011-01-01

Despite somewhat spared structural language development in high-functioning autism, communicative comprehension deficits persist. Comprehension involves the integration of meaning: global processing is required. The Weak Central Coherence theory suggests that individuals with autism are biased to process information locally. This cognitive style may impair comprehension, particularly if inferencing is required. However, task performance may be facilitated by this cognitive style if local processing is required. The current study was designed to examine the extent to which the 'weak central coherence' cognitive style affects comprehension and inferential processing of spoken narratives. The children with autism were expected to perform comparatively poorer on inferences relating to event scripts and comparatively better on inferences requiring deductive reasoning. Fourteen high-functioning children with autism were recruited from databases of various autism organizations (mean age = 6:7, 13 males, one female) and were matched on a receptive vocabulary and a picture-completion task with 14 typically developing children recruited from a local childcare centre (mean age = 4:10, seven males, seven females). The children were read short stories and asked questions about the stories. Results indicated that the children with autism were less able to make inferences based on event scripts, but the groups did not differ significantly on inferences requiring deductive logical reasoning. Despite similar group performance on questions relating to the main idea of the stories, only for the typically developing group was good performance on extracting the main idea of the narratives significantly correlated with performance on all other comprehension tasks. Findings provide some support for the Weak Central Coherence theory and demonstrate that young children with autism do not spontaneously integrate information in order to make script inferences, as do typically developing children. These findings may help to explain communicative problems of young children with autism and can be applied to intervention programme development. More research on the link between a 'weak central coherence' cognitive style and communicative comprehension in autism will be valuable in understanding the comprehension deficits associated with autism. © 2010 Royal College of Speech & Language Therapists.

Gaussian copula as a likelihood function for environmental models

NASA Astrophysics Data System (ADS)

Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.

2017-12-01

Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an interesting departure from the usage of fully parametric distributions as likelihood functions - and they could help us to better capture the statistical properties of errors and make more reliable predictions.

Using ecosystem engineers as tools in habitat restoration and rewilding: beaver and wetlands.

PubMed

Law, Alan; Gaywood, Martin J; Jones, Kevin C; Ramsay, Paul; Willby, Nigel J

2017-12-15

Potential for habitat restoration is increasingly used as an argument for reintroducing ecosystem engineers. Beaver have well known effects on hydromorphology through dam construction, but their scope to restore wetland biodiversity in areas degraded by agriculture is largely inferred. Our study presents the first formal monitoring of a planned beaver-assisted restoration, focussing on changes in vegetation over 12years within an agriculturally-degraded fen following beaver release, based on repeated sampling of fixed plots. Effects are compared to ungrazed exclosures which allowed the wider influence of waterlogging to be separated from disturbance through tree felling and herbivory. After 12years of beaver presence mean plant species richness had increased on average by 46% per plot, whilst the cumulative number of species recorded increased on average by 148%. Heterogeneity, measured by dissimilarity of plot composition, increased on average by 71%. Plants associated with high moisture and light conditions increased significantly in coverage, whereas species indicative of high nitrogen decreased. Areas exposed to both grazing and waterlogging generally showed the most pronounced change in composition, with effects of grazing seemingly additive, but secondary, to those of waterlogging. Our study illustrates that a well-known ecosystem engineer, the beaver, can with time transform agricultural land into a comparatively species-rich and heterogeneous wetland environment, thus meeting common restoration objectives. This offers a passive but innovative solution to the problems of wetland habitat loss that complements the value of beavers for water or sediment storage and flow attenuation. The role of larger herbivores has been significantly overlooked in our understanding of freshwater ecosystem function; the use of such species may yet emerge as the missing ingredient in successful restoration. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Spots and activity of solar-type stars from Kepler observations

NASA Astrophysics Data System (ADS)

Savanov, I. S.; Dmitrienko, E. S.

2017-05-01

The spot coverages S for 2846 solar-type stars with effective temperatures from 5700 K to 5800 K and gravities from 4.4 to 4.5 have been measured. An analysis based on the MAST catalog, which presents photometric measurements obtained with the Kepler Space Telescope during Q9 is presented. The existence of two groups of solar-type stars, with S values between 0.001 and 0.007 and with S > 0.007, is inferred. The second group (active stars) contains 279 stars (about 10% of the total number of stars analyzed). The mean S parameter for the entire sample is 0.004, comparable to the mean spot coverage of the Sun. In general, the dependence of S on the rotation period for solar-type stars has characteristics similar to those found earlier for stars with exoplanets. For the vast majority of the stars in the sample, the activity is constant, and independent of age. The activity of the small number of active stars with S > 0.007 decreases with age. The age variations of the chromospheric activity index R'HK are compared to variations of the spot coverage S. The relations analyzed have common characteristic features. It is likely that both the spot activity level and the chromospheric activity level abruptly decrease for stars older than 4 billion yrs.

Bi-functional ion exchangers for enhanced performance of dye-sensitized solar cells.

PubMed

Kong, Eui-Hyun; Chang, Yong-June; Lim, Jongchul; Kim, Back-Hyun; Lee, Jung-Hoon; Kwon, Do-Kyun; Park, Taiho; Jang, Hyun Myung

2013-07-28

Ion exchange using aerosol OT (AOT) offers dye adsorption twice as fast as known methods. Moreover, it suppresses the dye-agglomeration that may cause insufficient dye-coverage on the photoelectrode surface. Consequently, its dual function of fast dye-loading and higher dye-coverage significantly improves the power conversion efficiency of dye-sensitized solar cells.

Image-Data Compression Using Edge-Optimizing Algorithm for WFA Inference.

ERIC Educational Resources Information Center

Culik, Karel II; Kari, Jarkko

1994-01-01

Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

Classification of Microarray Data Using Kernel Fuzzy Inference System

PubMed Central

Kumar Rath, Santanu

2014-01-01

The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function. PMID:27433543

Stellar Populations in the Central 0.5 pc of the Galaxy. I. A New Method for Constructing Luminosity Functions and Surface-density Profiles

NASA Astrophysics Data System (ADS)

Do, T.; Lu, J. R.; Ghez, A. M.; Morris, M. R.; Yelda, S.; Martinez, G. D.; Wright, S. A.; Matthews, K.

2013-02-01

We present new high angular resolution near-infrared spectroscopic observations of the nuclear star cluster surrounding the Milky Way's central supermassive black hole. Using the integral-field spectrograph OSIRIS on Keck II behind the laser-guide-star adaptive optics system, this spectroscopic survey enables us to separate early-type (young, 4-6 Myr) and late-type (old, >1 Gyr) stars with a completeness of 50% down to K' = 15.5 mag, which corresponds to ~10 M ⊙ for the early-type stars. This work increases the radial extent of reported OSIRIS/Keck measurements by more than a factor of three from 4'' to 14'' (0.16 to 0.56 pc), along the projected disk of young stars. For our analysis, we implement a new method of completeness correction using a combination of star-planting simulations and Bayesian inference. We assign probabilities for the spectral type of every source detected in deep imaging down to K' = 15.5 mag using information from spectra, simulations, number counts, and the distribution of stars. The inferred radial surface-density profiles, Σ(R)vpropR -Γ, for the young stars and late-type giants are consistent with earlier results (Γearly = 0.93 ± 0.09, Γlate = 0.16 ± 0.07). The late-type surface-density profile is approximately flat out to the edge of the survey. While the late-type stellar luminosity function is consistent with the Galactic bulge, the completeness-corrected luminosity function of the early-type stars has significantly more young stars at faint magnitudes compared with previous surveys with similar depth. This luminosity function indicates that the corresponding mass function of the young stars is likely less top-heavy than that inferred from previous surveys.

DESCARTES' RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA.

PubMed

Bhaskar, Anand; Song, Yun S

2014-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the "folded" SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes' rule of signs for polynomials to the Laplace transform of piecewise continuous functions.

DESCARTES’ RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA1

PubMed Central

Bhaskar, Anand; Song, Yun S.

2016-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the “folded” SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes’ rule of signs for polynomials to the Laplace transform of piecewise continuous functions. PMID:28018011

Ancestry estimation and control of population stratification for sequence-based association studies.

PubMed

Wang, Chaolong; Zhan, Xiaowei; Bragg-Gresham, Jennifer; Kang, Hyun Min; Stambolian, Dwight; Chew, Emily Y; Branham, Kari E; Heckenlively, John; Fulton, Robert; Wilson, Richard K; Mardis, Elaine R; Lin, Xihong; Swaroop, Anand; Zöllner, Sebastian; Abecasis, Gonçalo R

2014-04-01

Estimating individual ancestry is important in genetic association studies where population structure leads to false positive signals, although assigning ancestry remains challenging with targeted sequence data. We propose a new method for the accurate estimation of individual genetic ancestry, based on direct analysis of off-target sequence reads, and implement our method in the publicly available LASER software. We validate the method using simulated and empirical data and show that the method can accurately infer worldwide continental ancestry when used with sequencing data sets with whole-genome shotgun coverage as low as 0.001×. For estimates of fine-scale ancestry within Europe, the method performs well with coverage of 0.1×. On an even finer scale, the method improves discrimination between exome-sequenced study participants originating from different provinces within Finland. Finally, we show that our method can be used to improve case-control matching in genetic association studies and to reduce the risk of spurious findings due to population structure.

Causal discovery and inference: concepts and recent methodological advances.

PubMed

Spirtes, Peter; Zhang, Kun

This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.

Permutation-based inference for the AUC: A unified approach for continuous and discontinuous data.

PubMed

Pauly, Markus; Asendorf, Thomas; Konietschke, Frank

2016-11-01

We investigate rank-based studentized permutation methods for the nonparametric Behrens-Fisher problem, that is, inference methods for the area under the ROC curve. We hereby prove that the studentized permutation distribution of the Brunner-Munzel rank statistic is asymptotically standard normal, even under the alternative. Thus, incidentally providing the hitherto missing theoretical foundation for the Neubert and Brunner studentized permutation test. In particular, we do not only show its consistency, but also that confidence intervals for the underlying treatment effects can be computed by inverting this permutation test. In addition, we derive permutation-based range-preserving confidence intervals. Extensive simulation studies show that the permutation-based confidence intervals appear to maintain the preassigned coverage probability quite accurately (even for rather small sample sizes). For a convenient application of the proposed methods, a freely available software package for the statistical software R has been developed. A real data example illustrates the application. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lithium-functionalized germanene: A promising media for CO2 capture

NASA Astrophysics Data System (ADS)

Mehdi Aghaei, S.; Monshi, M. M.; Torres, I.; Banakermani, M.; Calizo, I.

2018-02-01

Density functional theory (DFT) is employed to investigate the interactions of CO2 gas molecules with pristine and lithium-functionalized germanene. It is discovered that although a single CO2 molecule is weakly physisorbed on pristine germanene, a significant improvement on its adsorption energy is found by utilizing Li-functionalized germanene as the adsorbent. Excitingly, the moderate adsorption energy at high CO2 coverage secures an easy release step. Moreover, the structure of Li-functionalized germanene can be fully recovered after removal of CO2 gas molecules. Our results suggest that Li-functionalized germanene show promise for CO2 sensing and capture with a storage capacity of 12.57 mol/kg.

A QoS-guaranteed coverage precedence routing algorithm for wireless sensor networks.

PubMed

Jiang, Joe-Air; Lin, Tzu-Shiang; Chuang, Cheng-Long; Chen, Chia-Pang; Sun, Chin-Hong; Juang, Jehn-Yih; Lin, Jiun-Chuan; Liang, Wei-Wen

2011-01-01

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

Linking high parity and maternal and child mortality: what is the impact of lower health services coverage among higher order births?

PubMed

Sonneveldt, Emily; DeCormier Plosky, Willyanne; Stover, John

2013-01-01

A number of data sets show that high parity births are associated with higher child mortality than low parity births. The reasons for this relationship are not clear. In this paper we investigate whether high parity is associated with lower coverage of key health interventions that might lead to increased mortality. We used DHS data from 10 high fertility countries to examine the relationship between parity and coverage for 8 child health intervention and 9 maternal health interventions. We also used the LiST model to estimate the effect on maternal and child mortality of the lower coverage associated with high parity births. Our results show a significant relationship between coverage of maternal and child health services and birth order, even when controlling for poverty. The association between coverage and parity for maternal health interventions was more consistently significant across countries all countries, while for child health interventions there were fewer overall significant relationships and more variation both between and within countries. The differences in coverage between children of parity 3 and those of parity 6 are large enough to account for a 12% difference in the under-five mortality rate and a 22% difference in maternal mortality ratio in the countries studied. This study shows that coverage of key health interventions is lower for high parity children and the pattern is consistent across countries. This could be a partial explanation for the higher mortality rates associated with high parity. Actions to address this gap could help reduce the higher mortality experienced by high parity birth.

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three models to examine the reliability of estimates. Simulation results show that the models with estimated parameters using continuous fitness functions have better robustness properties than those using the corresponding discrete fitness functions. The inference studies and robustness analysis suggest that the proposed continuous optimization criteria are effective and robust for estimating unknown parameters in mathematical models.

Functionalized NbS2 as cathode for Li- and Na-ion batteries

NASA Astrophysics Data System (ADS)

Zhu, Jiajie; Alshareef, Husam N.; Schwingenschlögl, Udo

2017-07-01

Cathodes of Li- and Na-ion batteries usually have capacities <200 mAh/g, significantly less than the anodes. Two-dimensional materials can overcome this limitation but suffer from low voltages. In this context, we investigate NbS2 functionalized by O, F, and Cl as a cathode material by first-principles calculations, considering both the conversion and intercalation mechanisms. NbS2O2 shows a higher voltage than NbS2 for both Li and Na, but the voltage decreases drastically for increasing ion coverage. Even higher voltages and favorable dependences on the ion coverage are achieved by F and Cl functionalization. We obtain NbS2F2 and NbS2Cl2 energy densities of 1223 mW h/g and 823 mW h/g for lithiation and 1086 mW h/g and 835 mW h/g for sodiation, respectively. These values are higher than those for most state-of-the-art cathode materials ( ˜600 mW h/g). In addition, low diffusion barriers enable high cycling rates.

Postsynthetic Functionalization of Mg-MOF-74 with Tetraethylenepentamine: Structural Characterization and Enhanced CO2 Adsorption.

PubMed

Su, Xiao; Bromberg, Lev; Martis, Vladimir; Simeon, Fritz; Huq, Ashfia; Hatton, T Alan

2017-03-29

Postsynthetic functionalization of magnesium 2,5-dihydroxyterephthalate (Mg-MOF-74) with tetraethylenepentamine (TEPA) resulted in improved CO 2 adsorption performance under dry and humid conditions. XPS, elemental analysis, and neutron powder diffraction studies indicated that TEPA was incorporated throughout the MOF particle, although it coordinated preferentially with the unsaturated metal sites located in the immediate proximity to the surface. Neutron and X-ray powder diffraction analyses showed that the MOF structure was preserved after amine incorporation, with slight changes in the lattice parameters. The adsorption capacity of the functionalized amino-Mg-MOF-74 (TEPA-MOF) for CO 2 was as high as 26.9 wt % versus 23.4 wt % for the original MOF due to the extra binding sites provided by the multiunit amines. The degree of functionalization with the amines was found to be important in enhancing CO 2 adsorption, as the optimal surface coverage improved performance and stability under both pure CO 2 and CO 2 /H 2 O coadsorption, and with partially saturated surface coverage, optimal CO 2 capacity could be achieved under both wet and dry conditions by a synergistic binding of CO 2 to the amines as well as metal centers.

FPGA Acceleration of the phylogenetic likelihood function for Bayesian MCMC inference methods.

PubMed

Zierke, Stephanie; Bakos, Jason D

2010-04-12

Likelihood (ML)-based phylogenetic inference has become a popular method for estimating the evolutionary relationships among species based on genomic sequence data. This method is used in applications such as RAxML, GARLI, MrBayes, PAML, and PAUP. The Phylogenetic Likelihood Function (PLF) is an important kernel computation for this method. The PLF consists of a loop with no conditional behavior or dependencies between iterations. As such it contains a high potential for exploiting parallelism using micro-architectural techniques. In this paper, we describe a technique for mapping the PLF and supporting logic onto a Field Programmable Gate Array (FPGA)-based co-processor. By leveraging the FPGA's on-chip DSP modules and the high-bandwidth local memory attached to the FPGA, the resultant co-processor can accelerate ML-based methods and outperform state-of-the-art multi-core processors. We use the MrBayes 3 tool as a framework for designing our co-processor. For large datasets, we estimate that our accelerated MrBayes, if run on a current-generation FPGA, achieves a 10x speedup relative to software running on a state-of-the-art server-class microprocessor. The FPGA-based implementation achieves its performance by deeply pipelining the likelihood computations, performing multiple floating-point operations in parallel, and through a natural log approximation that is chosen specifically to leverage a deeply pipelined custom architecture. Heterogeneous computing, which combines general-purpose processors with special-purpose co-processors such as FPGAs and GPUs, is a promising approach for high-performance phylogeny inference as shown by the growing body of literature in this field. FPGAs in particular are well-suited for this task because of their low power consumption as compared to many-core processors and Graphics Processor Units (GPUs).

Reasoning on the Basis of Fantasy Content: Two Studies with High-Functioning Autistic Adolescents

ERIC Educational Resources Information Center

Morsanyi, Kinga; Handley, Simon J.

2012-01-01

Reasoning about problems with empirically false content can be hard, as the inferences that people draw are heavily influenced by their background knowledge. However, presenting empirically false premises in a fantasy context helps children and adolescents to disregard their beliefs, and to reason on the basis of the premises. The aim of the…

The role of place-exchange, dislocations and substrate symmetry in nickel/gold(111) heteroepitaxy

NASA Astrophysics Data System (ADS)

Cullen, William Grady

1999-12-01

The epitaxial growth of Ni on Au(111) in ultrahigh vacuum was investigated using scanning tunneling microscopy (STM) and Auger electron spectroscopy (AES). Films in the coverage range 0--2 monolayers were studied. The goals were to investigate the influence of the substrate reconstruction on the morphology of the growing film and also the possibility of intermixing between Ni and Au. Deposition of Ni at room temperature led to the growth of two-dimensional islands which nucleate at the point dislocations of the Au(111) herringbone reconstruction, as found in previous studies. Anisotropic growth features were identified and shown to result from basic symmetry properties of the Au(111) reconstruction. In addition, significant internal structure was observed within the islands, indicating that the islands are of mixed composition, and that the overlayer is not pseudomorphic. Two-dimensional island ripening was observed after deposition of Ni at room temperature, followed by moderate annealing. Results of STM and AES experiments indicate that the mass transport during ripening is due to mobile Au atoms which have detached from the original islands. Deposition at high temperature was shown to result in the formation of large epitaxial Au islands due to Ni-Au place exchange and subsequent collision-mediated nucleation of Au atoms. Island size distributions were analyzed for comparison with scaling theories, and data collapse onto a common curve was observed at different coverages and temperatures. Based on the scaling analysis, a critical nucleus of i = 2 was inferred. The annealing and high-temperature deposition experiments demonstrated that a Ni monolayer is metastable at the Au(111) surface, i.e. Au tends to segregate and cover the Ni.

Developmental Changes in Children's Inductive Inferences for Biological Concepts: Implications for the Development of Essentialist Beliefs

ERIC Educational Resources Information Center

Farrar, M. Jeffrey; Boyer-Pennington, Michelle

2011-01-01

We examined developmental changes in children's inductive inferences about biological concepts as a function of knowledge of properties and concepts. Specifically, 4- to 5-year-olds and 9- to 10-year-olds were taught either familiar or unfamiliar internal, external, or functional properties about known and unknown target animals. Children were…

Specificity of Emotion Inferences as a Function of Emotional Contextual Support

ERIC Educational Resources Information Center

Gillioz, Christelle; Gygax, Pascal M.

2017-01-01

Research on emotion inferences has shown that readers include a representation of the main character's emotional state in their mental representations of the text. We examined the specificity of emotion representations as a function of the emotion content of short narratives, in terms of the quantity and quality of emotion components included in…

Structural and electronic properties of AlN(0001) surface under partial N coverage as determined by ab initio approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strak, Pawel; Sakowski, Konrad; Kempisty, Pawel

2015-09-07

Properties of bare and nitrogen-covered Al-terminated AlN(0001) surface were determined using density functional theory (DFT) calculations. At a low nitrogen coverage, the Fermi level is pinned by Al broken bond states located below conduction band minimum. Adsorption of nitrogen is dissociative with an energy gain of 6.05 eV/molecule at a H3 site creating an overlap with states of three neighboring Al surface atoms. During this adsorption, electrons are transferred from Al broken bond to topmost N adatom states. Accompanying charge transfer depends on the Fermi level. In accordance with electron counting rule (ECR), the DFT results confirm the Fermi levelmore » is not pinned at the critical value of nitrogen coverage θ{sub N}(1) = 1/4 monolayer (ML), but it is shifted from an Al-broken bond state to Np{sub z} state. The equilibrium thermodynamic potential of nitrogen in vapor depends drastically on the Fermi level pinning being shifted by about 4 eV for an ECR state at 1/4 ML coverage. For coverage above 1/4 ML, adsorption is molecular with an energy gain of 1.5 eV at a skewed on-top position above an Al surface atom. Electronic states of the admolecule are occupied as in the free molecule, no electron transfer occurs and adsorption of a N{sub 2} molecule does not depend on the Fermi level. The equilibrium pressure of molecular nitrogen above an AlN(0001) surface depends critically on the Fermi level position, being very low and very high for low and high coverage, respectively. From this fact, one can conclude that at typical growth conditions, the Fermi level is not pinned, and the adsorption and incorporation of impurities depend on the position of Fermi level in the bulk.« less

Petrophysical Properties of Twenty Drill Cores from the Los Azufres, Mexico, Geothermal Field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iglesias, E.R.; Contreras L., E.; Garcia G., A.

1987-01-20

For this study we selected 20 drill cores covering a wide range of depths (400-3000 m), from 15 wells, that provide a reasonable coverage of the field. Only andesite, the largely predominant rock type in the field, was included in this sample. We measured bulk density, grain (solids) density, effective porosity and (matrix) permeability on a considerable number of specimens taken from the cores; and inferred the corresponding total porosity and fraction of interconnected total porosity. We characterized the statistical distributions of the measured and inferred variables. The distributions of bulk density and grain density resulted approximately normal; the distributionsmore » of effective porosity, total porosity and fraction of total porosity turned out to be bimodal; the permeability distribution resulted highly skewed towards very small (1 mdarcy) values, though values as high as 400 mdarcies were measured. We also characterized the internal inhomogeneity of the cores by means of the ratio (standard deviation/mean) corresponding to the bulk density in each core (in average there are 9 specimens per core). The cores were found to present clearly discernible inhomogeneity; this quantitative characterization will help design new experimental work and interpret currently available and forthcoming results. We also found statistically significant linear correlations between total density and density of solids, effective porosity and total density, total porosity and total density, fraction of interconnected total porosity and the inverse of the effective porosity, total porosity and effective porosity; bulk density and total porosity also correlate with elevation. These results provide the first sizable and statistically detailed database available on petrophysical properties of the Los Azufres andesites. 1 tab., 16 figs., 4 refs.« less

Comprehensive smoke alarm coverage in lower economic status homes: alarm presence, functionality, and placement.

PubMed

Sidman, Elanor A; Grossman, David C; Mueller, Beth A

2011-08-01

The objectives of this study are to estimate smoke alarm coverage and adherence with national guidelines in low- to mid-value owner-occupied residences, and to identify resident demographic, behavioral, and building characteristics and other fire and burn safety practices associated with smoke alarm utilization. Baseline visits were conducted with 779 households in King County, Washington, for a randomized trial of smoke alarm functionality. Presence, functionality, features, and location of pre-existing smoke alarms were ascertained by staff observation and testing. Household and building descriptors were collected using questionnaires. Households were classified by presence of smoke alarms, functional alarms, and functional and properly mounted alarms placed in hallways and on each floor but not in recommended avoidance locations. Smoke alarms were present in 89%, and functional units in 78%, of households. Only 6-38% met all assessed functionality and placement recommendations. Homes frequently lacked alarms in any bedrooms or on each floor. Building age, but not renovation status, was associated with all dimensions of smoke alarm coverage; post-1980 constructions were 1.7 times more likely to comply with placement recommendations than were pre-1941 homes (95% CI: 1.1-2.6). Respondent education and race/ethnicity, children <5 years, residency duration, number of floors, wood stoves and fireplaces, number of smoke alarms, recency of smoke alarm testing, carbon monoxide monitors, and fire ladders displayed varying relationships with alarm presence, functionality, and placement. Strategies for maintaining smoke alarms in functional condition and improving compliance with placement recommendations are necessary to achieve universal coverage, and will benefit the majority of households.

Reconstructing temperatures from lake sediments in northern Europe: what do the biological proxies really tell us?

NASA Astrophysics Data System (ADS)

Cunningham, Laura; Holmes, Naomi; Bigler, Christian; Dadal, Anna; Bergman, Jonas; Eriksson, Lars; Brooks, Stephen; Langdon, Pete; Caseldine, Chris

2010-05-01

Over the past two decades considerable effort has been devoted to quantitatively reconstructing temperatures from biological proxies preserved in lake sediments, via transfer functions. Such transfer functions typically consist of modern sediment samples, collected over a broad environmental gradient. Correlations between the biological communities and environmental parameters observed over these broad gradients are assumed to be equally valid temporally. The predictive ability of such spatially based transfer functions has traditionally been assessed by comparisons of measured and inferred temperatures within the calibration sets, with little validation against historical data. Although statistical techniques such as bootstrapping may improve error estimation, this approach remains partly a circular argument. This raises the question of how reliable such reconstructions are for inferring past changes in temperature? In order to address this question, we used transfer functions to reconstruct July temperatures from diatoms and chironomids from several locations across northern Europe. The transfer functions used showed good internal calibration statistics (r2 = 0.66 - 0.91). The diatom and chironomid inferred July air temperatures were compared to local observational records. As the sediment records were non-annual, all data were first smoothed using a 15 yr moving average filter. None of the five biologically-inferred temperature records were correlated with the local meteorological records. Furthermore, diatom inferred temperatures did not agree with chironomid inferred temperatures from the same cores from the same sites. In an attempt to understand this poor performance the biological proxy data was compressed using principal component analysis (PCA), and the PCA axes compared to the local meteorological data. These analyses clearly demonstrated that July temperatures were not correlated with the biological data at these locations. Some correlations were observed between the biological proxies and autumn and spring temperatures, although this varied slightly between sites and proxies. For example, chironomid data from Iceland was most strongly correlated with temperatures in February, March and April whilst in northern Sweden, the chironomid data was most strongly correlated with temperatures in March, April and May. It is suggested that the biological data at these sites may be responding to changes in the length of the ice-free period or hydrological regimes (including snow melt), rather than temperature per se. Our findings demonstrate the need to validate inferred temperatures against local meteorological data. Where such validation cannot be undertaken, inferred temperature reconstructions should be treated cautiously.

Formic Acid Dissociative Adsorption on NiO(111): Energetics and Structure of Adsorbed Formate

DOE PAGES

Zhao, Wei; Doyle, Andrew D.; Morgan, Sawyer E.; ...

2017-11-21

Here, the dissociative adsorption of carboxylic acids on oxide surfaces is important for understanding adsorbed carboxylates, which are important as intermediates in catalytic reactions, for the organo-functionalization of oxide surfaces, and in many other aspects of oxide surface chemistry. We present here the first direct experimental measurement of the heat of dissociative adsorption of any carboxylic acid on any single-crystal oxide surface. The enthalpy of the dissociative adsorption of formic acid, the simplest carboxylic acid, to produce adsorbed formate and hydrogen (as a surface hydroxyl) on a (2 × 2)-NiO(111) surface is measured by single crystal adsorption calorimetry. The differentialmore » heat of adsorption decreases with formic acid coverage from 202 to 99 kJ/mol at saturation (0.25 ML). The structure of the adsorbed products is clarified by density functional theory (DFT) calculations, which provide energies in reasonable agreement with the calorimetry. These calculations show that formic acid readily dissociates on both the oxygen and Ni terminations of the octapolar NiO(111) surfaces, donating its acid H to a surface lattice oxygen, while HCOO adsorbs preferentially with bridging-type geometry near the M-O 3/O-M 3 sites. The calculated energetics at low coverages agrees well with experimental data, while larger differences are observed at high coverage (0.25 ML). The large decrease in experimental heat of adsorption with coverage can be brought into agreement with the DFT energies if we assume that both types of octapolar surface terminations (O- and Ni-) are present on the starting surface.« less

Formic Acid Dissociative Adsorption on NiO(111): Energetics and Structure of Adsorbed Formate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Wei; Doyle, Andrew D.; Morgan, Sawyer E.

Here, the dissociative adsorption of carboxylic acids on oxide surfaces is important for understanding adsorbed carboxylates, which are important as intermediates in catalytic reactions, for the organo-functionalization of oxide surfaces, and in many other aspects of oxide surface chemistry. We present here the first direct experimental measurement of the heat of dissociative adsorption of any carboxylic acid on any single-crystal oxide surface. The enthalpy of the dissociative adsorption of formic acid, the simplest carboxylic acid, to produce adsorbed formate and hydrogen (as a surface hydroxyl) on a (2 × 2)-NiO(111) surface is measured by single crystal adsorption calorimetry. The differentialmore » heat of adsorption decreases with formic acid coverage from 202 to 99 kJ/mol at saturation (0.25 ML). The structure of the adsorbed products is clarified by density functional theory (DFT) calculations, which provide energies in reasonable agreement with the calorimetry. These calculations show that formic acid readily dissociates on both the oxygen and Ni terminations of the octapolar NiO(111) surfaces, donating its acid H to a surface lattice oxygen, while HCOO adsorbs preferentially with bridging-type geometry near the M-O 3/O-M 3 sites. The calculated energetics at low coverages agrees well with experimental data, while larger differences are observed at high coverage (0.25 ML). The large decrease in experimental heat of adsorption with coverage can be brought into agreement with the DFT energies if we assume that both types of octapolar surface terminations (O- and Ni-) are present on the starting surface.« less

Using conventional F-statistics to study unconventional sex-chromosome differentiation.

PubMed

Rodrigues, Nicolas; Dufresnes, Christophe

2017-01-01

Species with undifferentiated sex chromosomes emerge as key organisms to understand the astonishing diversity of sex-determination systems. Whereas new genomic methods are widening opportunities to study these systems, the difficulty to separately characterize their X and Y homologous chromosomes poses limitations. Here we demonstrate that two simple F -statistics calculated from sex-linked genotypes, namely the genetic distance ( F st ) between sexes and the inbreeding coefficient ( F is ) in the heterogametic sex, can be used as reliable proxies to compare sex-chromosome differentiation between populations. We correlated these metrics using published microsatellite data from two frog species ( Hyla arborea and Rana temporaria ), and show that they intimately relate to the overall amount of X-Y differentiation in populations. However, the fits for individual loci appear highly variable, suggesting that a dense genetic coverage will be needed for inferring fine-scale patterns of differentiation along sex-chromosomes. The applications of these F -statistics, which implies little sampling requirement, significantly facilitate population analyses of sex-chromosomes.

HIV Treatment as Prevention: Natural Experiments Highlight Limits of Antiretroviral Treatment as HIV Prevention

PubMed Central

Wilson, David P.

2012-01-01

There is growing enthusiasm for increasing coverage of antiretroviral treatment among HIV-infected people for the purposes of preventing ongoing transmission. Treatment as prevention will face a number of barriers when implemented in real world populations, which will likely lead to the effectiveness of this strategy being lower than proposed by optimistic modelling scenarios or ideal clinical trial settings. Some settings, as part of their prevention and treatment strategies, have already attained rates of HIV testing and use of antiretroviral therapy—with high levels of viral suppression—that many countries would aspire to as targets for a treatment-as-prevention strategy. This review examines a number of these “natural experiments”, namely, British Columbia, San Francisco, France, and Australia, to provide commentary on whether treatment as prevention has worked in real world populations. This review suggests that the population-level impact of this strategy is likely to be considerably less than as inferred from ideal conditions. PMID:22807656

Tracing the influence of land-use change on water quality and coral reefs using a Bayesian model.

PubMed

Brown, Christopher J; Jupiter, Stacy D; Albert, Simon; Klein, Carissa J; Mangubhai, Sangeeta; Maina, Joseph M; Mumby, Peter; Olley, Jon; Stewart-Koster, Ben; Tulloch, Vivitskaia; Wenger, Amelia

2017-07-06

Coastal ecosystems can be degraded by poor water quality. Tracing the causes of poor water quality back to land-use change is necessary to target catchment management for coastal zone management. However, existing models for tracing the sources of pollution require extensive data-sets which are not available for many of the world's coral reef regions that may have severe water quality issues. Here we develop a hierarchical Bayesian model that uses freely available satellite data to infer the connection between land-uses in catchments and water clarity in coastal oceans. We apply the model to estimate the influence of land-use change on water clarity in Fiji. We tested the model's predictions against underwater surveys, finding that predictions of poor water quality are consistent with observations of high siltation and low coverage of sediment-sensitive coral genera. The model thus provides a means to link land-use change to declines in coastal water quality.

A recent bottleneck of Y chromosome diversity coincides with a global change in culture.

PubMed

Karmin, Monika; Saag, Lauri; Vicente, Mário; Wilson Sayres, Melissa A; Järve, Mari; Talas, Ulvi Gerst; Rootsi, Siiri; Ilumäe, Anne-Mai; Mägi, Reedik; Mitt, Mario; Pagani, Luca; Puurand, Tarmo; Faltyskova, Zuzana; Clemente, Florian; Cardona, Alexia; Metspalu, Ene; Sahakyan, Hovhannes; Yunusbayev, Bayazit; Hudjashov, Georgi; DeGiorgio, Michael; Loogväli, Eva-Liis; Eichstaedt, Christina; Eelmets, Mikk; Chaubey, Gyaneshwer; Tambets, Kristiina; Litvinov, Sergei; Mormina, Maru; Xue, Yali; Ayub, Qasim; Zoraqi, Grigor; Korneliussen, Thorfinn Sand; Akhatova, Farida; Lachance, Joseph; Tishkoff, Sarah; Momynaliev, Kuvat; Ricaut, François-Xavier; Kusuma, Pradiptajati; Razafindrazaka, Harilanto; Pierron, Denis; Cox, Murray P; Sultana, Gazi Nurun Nahar; Willerslev, Rane; Muller, Craig; Westaway, Michael; Lambert, David; Skaro, Vedrana; Kovačevic, Lejla; Turdikulova, Shahlo; Dalimova, Dilbar; Khusainova, Rita; Trofimova, Natalya; Akhmetova, Vita; Khidiyatova, Irina; Lichman, Daria V; Isakova, Jainagul; Pocheshkhova, Elvira; Sabitov, Zhaxylyk; Barashkov, Nikolay A; Nymadawa, Pagbajabyn; Mihailov, Evelin; Seng, Joseph Wee Tien; Evseeva, Irina; Migliano, Andrea Bamberg; Abdullah, Syafiq; Andriadze, George; Primorac, Dragan; Atramentova, Lubov; Utevska, Olga; Yepiskoposyan, Levon; Marjanovic, Damir; Kushniarevich, Alena; Behar, Doron M; Gilissen, Christian; Vissers, Lisenka; Veltman, Joris A; Balanovska, Elena; Derenko, Miroslava; Malyarchuk, Boris; Metspalu, Andres; Fedorova, Sardana; Eriksson, Anders; Manica, Andrea; Mendez, Fernando L; Karafet, Tatiana M; Veeramah, Krishna R; Bradman, Neil; Hammer, Michael F; Osipova, Ludmila P; Balanovsky, Oleg; Khusnutdinova, Elza K; Johnsen, Knut; Remm, Maido; Thomas, Mark G; Tyler-Smith, Chris; Underhill, Peter A; Willerslev, Eske; Nielsen, Rasmus; Metspalu, Mait; Villems, Richard; Kivisild, Toomas

2015-04-01

It is commonly thought that human genetic diversity in non-African populations was shaped primarily by an out-of-Africa dispersal 50-100 thousand yr ago (kya). Here, we present a study of 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Applying ancient DNA calibration, we date the Y-chromosomal most recent common ancestor (MRCA) in Africa at 254 (95% CI 192-307) kya and detect a cluster of major non-African founder haplogroups in a narrow time interval at 47-52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck. In contrast to demographic reconstructions based on mtDNA, we infer a second strong bottleneck in Y-chromosome lineages dating to the last 10 ky. We hypothesize that this bottleneck is caused by cultural changes affecting variance of reproductive success among males. © 2015 Karmin et al.; Published by Cold Spring Harbor Laboratory Press.

Constraining Dust Hazes at the L/T Transition via Variability

NASA Astrophysics Data System (ADS)

Radigan, Jacqueline; Apai, Daniel; Yang, Hao; Hiranaka, Kay; Cruz, Kelle; Buenzli, Esther; Marley, Mark

2014-12-01

The T2 dwarf SIMP 1629+03 is a variable L/T transition dwarf, with a normal near-infrared spectrum. However, it is remarkable in that the wavelength dependence of its variability differs markedly from that of other L/T transition brown dwarfs. In particular, the absence of a water absorption feature in its variability spectrum indicates that a patchy, high-altitude haze, rather than a deeper cloud layer is responsible for the observed variations. We propose to obtain Spitzer+HST observations of SIMP1629+02 over two consecutive rotations periods in order to simultaneously map it?s spectral variability across 1-5 um. The wide wavelength coverage will provide a suitable lever-arm for constraining the particle size distribution in the haze. A truly flat spectrum across this wavelength range would indicate large particle sizes in comparison to those inferred for red L-dwarf hazes, and would therefore provide direct evidence of grain growth with decreasing effective temperature and/or a grain-size dependence on surface gravity in brown dwarf atmospheres.

High throughput mutagenesis for identification of residues regulating human prostacyclin (hIP) receptor expression and function.

PubMed

Bill, Anke; Rosethorne, Elizabeth M; Kent, Toby C; Fawcett, Lindsay; Burchell, Lynn; van Diepen, Michiel T; Marelli, Anthony; Batalov, Sergey; Miraglia, Loren; Orth, Anthony P; Renaud, Nicole A; Charlton, Steven J; Gosling, Martin; Gaither, L Alex; Groot-Kormelink, Paul J

2014-01-01

The human prostacyclin receptor (hIP receptor) is a seven-transmembrane G protein-coupled receptor (GPCR) that plays a critical role in vascular smooth muscle relaxation and platelet aggregation. hIP receptor dysfunction has been implicated in numerous cardiovascular abnormalities, including myocardial infarction, hypertension, thrombosis and atherosclerosis. Genomic sequencing has discovered several genetic variations in the PTGIR gene coding for hIP receptor, however, its structure-function relationship has not been sufficiently explored. Here we set out to investigate the applicability of high throughput random mutagenesis to study the structure-function relationship of hIP receptor. While chemical mutagenesis was not suitable to generate a mutagenesis library with sufficient coverage, our data demonstrate error-prone PCR (epPCR) mediated mutagenesis as a valuable method for the unbiased screening of residues regulating hIP receptor function and expression. Here we describe the generation and functional characterization of an epPCR derived mutagenesis library compromising >4000 mutants of the hIP receptor. We introduce next generation sequencing as a useful tool to validate the quality of mutagenesis libraries by providing information about the coverage, mutation rate and mutational bias. We identified 18 mutants of the hIP receptor that were expressed at the cell surface, but demonstrated impaired receptor function. A total of 38 non-synonymous mutations were identified within the coding region of the hIP receptor, mapping to 36 distinct residues, including several mutations previously reported to affect the signaling of the hIP receptor. Thus, our data demonstrates epPCR mediated random mutagenesis as a valuable and practical method to study the structure-function relationship of GPCRs.

High Throughput Mutagenesis for Identification of Residues Regulating Human Prostacyclin (hIP) Receptor Expression and Function

PubMed Central

Kent, Toby C.; Fawcett, Lindsay; Burchell, Lynn; van Diepen, Michiel T.; Marelli, Anthony; Batalov, Sergey; Miraglia, Loren; Orth, Anthony P.; Renaud, Nicole A.; Charlton, Steven J.; Gosling, Martin; Gaither, L. Alex; Groot-Kormelink, Paul J.

2014-01-01

The human prostacyclin receptor (hIP receptor) is a seven-transmembrane G protein-coupled receptor (GPCR) that plays a critical role in vascular smooth muscle relaxation and platelet aggregation. hIP receptor dysfunction has been implicated in numerous cardiovascular abnormalities, including myocardial infarction, hypertension, thrombosis and atherosclerosis. Genomic sequencing has discovered several genetic variations in the PTGIR gene coding for hIP receptor, however, its structure-function relationship has not been sufficiently explored. Here we set out to investigate the applicability of high throughput random mutagenesis to study the structure-function relationship of hIP receptor. While chemical mutagenesis was not suitable to generate a mutagenesis library with sufficient coverage, our data demonstrate error-prone PCR (epPCR) mediated mutagenesis as a valuable method for the unbiased screening of residues regulating hIP receptor function and expression. Here we describe the generation and functional characterization of an epPCR derived mutagenesis library compromising >4000 mutants of the hIP receptor. We introduce next generation sequencing as a useful tool to validate the quality of mutagenesis libraries by providing information about the coverage, mutation rate and mutational bias. We identified 18 mutants of the hIP receptor that were expressed at the cell surface, but demonstrated impaired receptor function. A total of 38 non-synonymous mutations were identified within the coding region of the hIP receptor, mapping to 36 distinct residues, including several mutations previously reported to affect the signaling of the hIP receptor. Thus, our data demonstrates epPCR mediated random mutagenesis as a valuable and practical method to study the structure-function relationship of GPCRs. PMID:24886841

Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

PubMed

Knapp, Bettina; Kaderali, Lars

2013-01-01

Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

Bayesian functional integral method for inferring continuous data from discrete measurements.

PubMed

Heuett, William J; Miller, Bernard V; Racette, Susan B; Holloszy, John O; Chow, Carson C; Periwal, Vipul

2012-02-08

Inference of the insulin secretion rate (ISR) from C-peptide measurements as a quantification of pancreatic β-cell function is clinically important in diseases related to reduced insulin sensitivity and insulin action. ISR derived from C-peptide concentration is an example of nonparametric Bayesian model selection where a proposed ISR time-course is considered to be a "model". An inferred value of inaccessible continuous variables from discrete observable data is often problematic in biology and medicine, because it is a priori unclear how robust the inference is to the deletion of data points, and a closely related question, how much smoothness or continuity the data actually support. Predictions weighted by the posterior distribution can be cast as functional integrals as used in statistical field theory. Functional integrals are generally difficult to evaluate, especially for nonanalytic constraints such as positivity of the estimated parameters. We propose a computationally tractable method that uses the exact solution of an associated likelihood function as a prior probability distribution for a Markov-chain Monte Carlo evaluation of the posterior for the full model. As a concrete application of our method, we calculate the ISR from actual clinical C-peptide measurements in human subjects with varying degrees of insulin sensitivity. Our method demonstrates the feasibility of functional integral Bayesian model selection as a practical method for such data-driven inference, allowing the data to determine the smoothing timescale and the width of the prior probability distribution on the space of models. In particular, our model comparison method determines the discrete time-step for interpolation of the unobservable continuous variable that is supported by the data. Attempts to go to finer discrete time-steps lead to less likely models. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Inferring Higher Functional Information for RIKEN Mouse Full-Length cDNA Clones With FACTS

PubMed Central

Nagashima, Takeshi; Silva, Diego G.; Petrovsky, Nikolai; Socha, Luis A.; Suzuki, Harukazu; Saito, Rintaro; Kasukawa, Takeya; Kurochkin, Igor V.; Konagaya, Akihiko; Schönbach, Christian

2003-01-01

FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence Sources) is a semiautomated knowledge discovery and annotation system that integrates molecular function information derived from sequence analysis results (sequence inferred) with functional information extracted from text. Text-inferred information was extracted from keyword-based retrievals of MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN mouse cDNA FANTOM2 clone annotations were informative for text searches. MEDLINE queries yielded molecular interaction-containing sentences for 23.1% of the clones. When disease MeSH and GO terms were matched with retrieved abstracts, 22.7% of clones were associated with potential diseases, and 32.5% with GO identifiers. A significant number (23.5%) of disease MeSH-associated clones were also found to have a hereditary disease association (OMIM Morbidmap). Inferred neoplastic and nervous system disease represented 49.6% and 36.0% of disease MeSH-associated clones, respectively. A comparison of sequence-based GO assignments with informative text-based GO assignments revealed that for 78.2% of clones, identical GO assignments were provided for that clone by either method, whereas for 21.8% of clones, the assignments differed. In contrast, for OMIM assignments, only 28.5% of clones had identical sequence-based and text-based OMIM assignments. Sequence, sentence, and term-based functional associations are included in the FACTS database (http://facts.gsc.riken.go.jp/), which permits results to be annotated and explored through web-accessible keyword and sequence search interfaces. The FACTS database will be a critical tool for investigating the functional complexity of the mouse transcriptome, cDNA-inferred interactome (molecular interactions), and pathome (pathologies). PMID:12819151

Context recognition for a hyperintensional inference machine

NASA Astrophysics Data System (ADS)

Duží, Marie; Fait, Michal; Menšík, Marek

2017-07-01

The goal of this paper is to introduce the algorithm of context recognition in the functional programming language TIL-Script, which is a necessary condition for the implementation of the TIL-Script inference machine. The TIL-Script language is an operationally isomorphic syntactic variant of Tichý's Transparent Intensional Logic (TIL). From the formal point of view, TIL is a hyperintensional, partial, typed λ-calculus with procedural semantics. Hyperintensional, because TIL λ-terms denote procedures (defined as TIL constructions) producing set-theoretic functions rather than the functions themselves; partial, because TIL is a logic of partial functions; and typed, because all the entities of TIL ontology, including constructions, receive a type within a ramified hierarchy of types. These features make it possible to distinguish three levels of abstraction at which TIL constructions operate. At the highest hyperintensional level the object to operate on is a construction (though a higher-order construction is needed to present this lower-order construction as an object of predication). At the middle intensional level the object to operate on is the function presented, or constructed, by a construction, while at the lowest extensional level the object to operate on is the value (if any) of the presented function. Thus a necessary condition for the development of an inference machine for the TIL-Script language is recognizing a context in which a construction occurs, namely extensional, intensional and hyperintensional context, in order to determine the type of an argument at which a given inference rule can be properly applied. As a result, our logic does not flout logical rules of extensional logic, which makes it possible to develop a hyperintensional inference machine for the TIL-Script language.

The role of mirroring and mentalizing networks in mediating action intentions in autism.

PubMed

Libero, Lauren E; Maximo, Jose O; Deshpande, Hrishikesh D; Klinger, Laura G; Klinger, Mark R; Kana, Rajesh K

2014-01-01

The ability to interpret agents' intent from their actions is a vital skill in successful social interaction. However, individuals with autism spectrum disorders (ASD) have been found to have difficulty in attributing intentions to others. The present study investigated the neural mechanisms of inferring intentions from actions in individuals with ASD. Functional magnetic resonance imaging (fMRI) data were acquired from 21 high-functioning young adults with ASD and 22 typically developing (TD) control participants, while making judgments about the means (how an action is performed) and intention (why an action is performed) of a model's actions. Across both groups of participants, the middle and superior temporal cortex, extending to temporoparietal junction, and posterior cingulate cortex, responded significantly to inferring the intent of an action, while inferior parietal lobule and occipital cortices were active for judgments about the means of an action. Participants with ASD had significantly reduced activation in calcarine sulcus and significantly increased activation in left inferior frontal gyrus, compared to TD peers, while attending to the intentions of actions. Also, ASD participants had weaker functional connectivity between frontal and posterior temporal regions while processing intentions. These results suggest that processing actions and intentions may not be mutually exclusive, with reliance on mirroring and mentalizing mechanisms mediating action understanding. Overall, inferring information about others' actions involves activation of the mirror neuron system and theory-of-mind regions, and this activation (and the synchrony between activated brain regions) appears altered in young adults with ASD.

Inference comprehension in text reading: Performance of individuals with right- versus left-hemisphere lesions and the influence of cognitive functions.

PubMed

Silagi, Marcela Lima; Radanovic, Marcia; Conforto, Adriana Bastos; Mendonça, Lucia Iracema Zanotto; Mansur, Leticia Lessa

2018-01-01

Right-hemisphere lesions (RHL) may impair inference comprehension. However, comparative studies between left-hemisphere lesions (LHL) and RHL are rare, especially regarding reading comprehension. Moreover, further knowledge of the influence of cognition on inferential processing in this task is needed. To compare the performance of patients with RHL and LHL on an inference reading comprehension task. We also aimed to analyze the effects of lesion site and to verify correlations between cognitive functions and performance on the task. Seventy-five subjects were equally divided into the groups RHL, LHL, and control group (CG). The Implicit Management Test was used to evaluate inference comprehension. In this test, subjects read short written passages and subsequently answer five types of questions (explicit, logical, distractor, pragmatic, and other), which require different types of inferential reasoning. The cognitive functional domains of attention, memory, executive functions, language, and visuospatial abilities were assessed using the Cognitive Linguistic Quick Test (CLQT). The LHL and RHL groups presented difficulties in inferential comprehension in comparison with the CG. However, the RHL group presented lower scores than the LHL group on logical, pragmatic and other questions. A covariance analysis did not show any effect of lesion site within the hemispheres. Overall, all cognitive domains were correlated with all the types of questions from the inference test (especially logical, pragmatic, and other). Attention and visuospatial abilities affected the scores of both the RHL and LHL groups, and only memory influenced the performance of the RHL group. Lesions in either hemisphere may cause difficulties in making inferences during reading. However, processing more complex inferences was more difficult for patients with RHL than for those with LHL, which suggests that the right hemisphere plays an important role in tasks with higher comprehension demands. Cognition influences inferential processing during reading in brain-injured subjects.

Application of AUVs in the Exploration for and Characterization of Arc Volcano Seafloor Hydrothermal Systems

NASA Astrophysics Data System (ADS)

de Ronde, C. E. J.; Walker, S. L.; Caratori Tontini, F.; Baker, E. T.; Embley, R. W.; Yoerger, D.

2014-12-01

The application of Autonomous Underwater Vehicles (AUVs) in the search for, and characterization of, seafloor hydrothermal systems associated with arc volcanoes has provided important information at a scale relevant to the study of these systems. That is, 1-2 m resolution bathymetric mapping of the seafloor, when combined with high-resolution magnetic and water column measurements, enables the discharge of hydrothermal vent fluids to be coupled with geological and structural features, and inferred upflow zones. Optimum altitude for the AUVs is ~70 m ensuring high resolution coverage of the area, maximum exposure to hydrothermal venting, and efficency of survey. The Brothers caldera and Clark cone volcanoes of the Kermadec arc have been surveyed by ABE and Sentry. At Brothers, bathymetric mapping shows complex features on the caldera walls including embayment's, ridges extending orthogonal to the walls and the location of a dominant ring fault. Water column measurements made by light scattering, temperature, ORP and pH sensors confirmed the location of the known vent fields on the NW caldera wall and atop the two cones, and discovered a new field on the West caldera wall. Evidence for diffuse discharge was also seen on the rim of the NW caldera wall; conversely, there was little evidence for discharge over an inferred ancient vent site on the SE caldera wall. Magnetic measurements show a strong correlation between the boundaries of vent fields determined by water column measurements and observed from manned submersible and towed camera surveys, and donut-shaped zones of magnetic 'lows' that are focused along ring faults. A magnetic low was also observed to cover the SE caldera site. Similar surveys over the NW edifice of Clark volcano also show a strong correlation between active hydrothermal venting and magnetic lows. Here, the survey revealed a pattern resembling Swiss cheese of magnetic lows, indicating more widespread permeability. Moreover, the magnetic survey showed evidence for a highly magnetized ring structure ~350 m below the volcano summit considered to represent a buried (by continued growth of the cone) caldera rim. Zones of magnetic lows located inside the inferred caldera that are not associated with present-day venting are consistent with an earlier stage of hydrothermal activity.

Nanoparticle layer deposition for highly controlled multilayer formation based on high- coverage monolayers of nanoparticles

PubMed Central

Liu, Yue; Williams, Mackenzie G.; Miller, Timothy J.; Teplyakov, Andrew V.

2015-01-01

This paper establishes a strategy for chemical deposition of functionalized nanoparticles onto solid substrates in a layer-by-layer process based on self-limiting surface chemical reactions leading to complete monolayer formation within the multilayer system without any additional intermediate layers – nanoparticle layer deposition (NPLD). This approach is fundamentally different from previously established traditional layer-by-layer deposition techniques and is conceptually more similar to well-known atomic and molecular – layer deposition processes. The NPLD approach uses efficient chemical functionalization of the solid substrate material and complementary functionalization of nanoparticles to produce a nearly 100% coverage of these nanoparticles with the use of “click chemistry”. Following this initial deposition, a second complete monolayer of nanoparticles is deposited using a copper-catalyzed “click reaction” with the azide-terminated silica nanoparticles of a different size. This layer-by-layer growth is demonstrated to produce stable covalently-bound multilayers of nearly perfect structure over macroscopic solid substrates. The formation of stable covalent bonds is confirmed spectroscopically and the stability of the multilayers produced is tested by sonication in a variety of common solvents. The 1-, 2- and 3-layer structures are interrogated by electron microscopy and atomic force microscopy and the thickness of the multilayers formed is fully consistent with that expected for highly efficient monolayer formation with each cycle of growth. This approach can be extended to include a variety of materials deposited in a predesigned sequence on different substrates with a highly conformal filling. PMID:26726273

GFam: a platform for automatic annotation of gene families.

PubMed

Sasidharan, Rajkumar; Nepusz, Tamás; Swarbreck, David; Huala, Eva; Paccanaro, Alberto

2012-10-01

We have developed GFam, a platform for automatic annotation of gene/protein families. GFam provides a framework for genome initiatives and model organism resources to build domain-based families, derive meaningful functional labels and offers a seamless approach to propagate functional annotation across periodic genome updates. GFam is a hybrid approach that uses a greedy algorithm to chain component domains from InterPro annotation provided by its 12 member resources followed by a sequence-based connected component analysis of un-annotated sequence regions to derive consensus domain architecture for each sequence and subsequently generate families based on common architectures. Our integrated approach increases sequence coverage by 7.2 percentage points and residue coverage by 14.6 percentage points higher than the coverage relative to the best single-constituent database within InterPro for the proteome of Arabidopsis. The true power of GFam lies in maximizing annotation provided by the different InterPro data sources that offer resource-specific coverage for different regions of a sequence. GFam's capability to capture higher sequence and residue coverage can be useful for genome annotation, comparative genomics and functional studies. GFam is a general-purpose software and can be used for any collection of protein sequences. The software is open source and can be obtained from http://www.paccanarolab.org/software/gfam/.

MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics.

PubMed

Helaers, Raphaël; Milinkovitch, Michel C

2010-07-15

The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at http://www.metapiga.org.

MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics

PubMed Central

2010-01-01

Background The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Results Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. Conclusions The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at http://www.metapiga.org. PMID:20633263

Unified Theory of Inference for Text Understanding

DTIC Science & Technology

1986-11-25

Technical Report S. L. Graham Principal Investigator (4151 642-2059 DTIC ^ELECTE APR 2 21987 D "The views and conclusions contained in this document...obtain X? Function - Infer P will use X for its normal purpose, if it has one. Intervention - How could C keep P from obtaining X? Knowledge Propagation...likelihood is low otherwise, likelihood is moderate otherwise, does X have a normal function ? if so, does P do actions like this function ? if so

Neural system prediction and identification challenge.

PubMed

Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

2013-01-01

Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

Neural system prediction and identification challenge

PubMed Central

Vlachos, Ioannis; Zaytsev, Yury V.; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

2013-01-01

Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered. PMID:24399966

Oxygen chemisorption on copper (110)

NASA Astrophysics Data System (ADS)

Mundenar, J. M.; Baddorf, A. P.; Plummer, E. W.; Sneddon, L. G.; Didio, R. A.; Zehner, D. M.

1987-09-01

High resolution electron energy loss spectroscopy (EELS) and angle-resolved ultra-violet photoelectron spectroscopy (UPS) have been used: (1) to study a surface phonon of Cu(110) as a function of oxygen coverage, (2) to identify oxygen adsorption site(s) in the p(2×1)O, c(6×2)O, and disordered oxygen overlayer (formed by O 2 exposure at 100 K), and (3) to determine whether molecular adsorption or dissociation of O 2 followed by atomic adsorption occurs after oxygen exposure at 100 K. With EELS, a continuous shift in energy of the surface phonon as a function of oxygen exposure at 300 K is observed. Our EELS data for the p(2×1)O overlayer support previous reports of a single long-bridge adsorption site, while indicating two sites are populated in the c(6×2)O overlayer: a long-bridge site and a four-coordinated site. The long-bridge site is populated at all coverages while the four-coordinated sites is occupied only after high exposures (≥2×10 4 L) at room temperature, or after exposures >2 L at low temperature (100 K). For both conditions the oxygen coverages are greater than 0.5 monolayer. Also, EELS and complementary UPS data clearly show that oxygen adsorbs dissociatively on Cu(110) after O 2 exposure at 100 K. At this temperature, LEED results indicate that the oxygen atoms are adsorbed without long-range order; however, local adsorption sites, which are similar to those in the c(6×2)O surface, are observed.

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS

PubMed Central

Kuai, Moshen; Cheng, Gang; Li, Yong

2018-01-01

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively. PMID:29510569

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS.

PubMed

Kuai, Moshen; Cheng, Gang; Pang, Yusong; Li, Yong

2018-03-05

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively.

Connecting CO intensity mapping to molecular gas and star formation in the epoch of galaxy assembly

DOE PAGES

Li, Tony Y.; Wechsler, Risa H.; Devaraj, Kiruthika; ...

2016-01-29

Intensity mapping, which images a single spectral line from unresolved galaxies across cosmological volumes, is a promising technique for probing the early universe. Here we present predictions for the intensity map and power spectrum of the CO(1–0) line from galaxies atmore » $$z\\sim 2.4$$–2.8, based on a parameterized model for the galaxy–halo connection, and demonstrate the extent to which properties of high-redshift galaxies can be directly inferred from such observations. We find that our fiducial prediction should be detectable by a realistic experiment. Motivated by significant modeling uncertainties, we demonstrate the effect on the power spectrum of varying each parameter in our model. Using simulated observations, we infer constraints on our model parameter space with an MCMC procedure, and show corresponding constraints on the $${L}_{\\mathrm{IR}}$$–$${L}_{\\mathrm{CO}}$$ relation and the CO luminosity function. These constraints would be complementary to current high-redshift galaxy observations, which can detect the brightest galaxies but not complete samples from the faint end of the luminosity function. Furthermore, by probing these populations in aggregate, CO intensity mapping could be a valuable tool for probing molecular gas and its relation to star formation in high-redshift galaxies.« less

Fibrinogen adsorption mechanisms at the gold substrate revealed by QCM-D measurements and RSA modeling.

PubMed

Kubiak, Katarzyna; Adamczyk, Zbigniew; Cieśla, Michał

2016-03-01

Adsorption kinetics of fibrinogen at a gold substrate at various pHs was thoroughly studied using the QCM-D method. The experimental were interpreted in terms of theoretical calculations performed according to the random sequential adsorption model (RSA). In this way, the hydration functions and water factors of fibrinogen monolayers were quantitatively evaluated at various pHs. It was revealed that for the lower range of fibrinogen coverage the hydration function were considerably lower than previously obtained for the silica sensor [33]. The lower hydration of fibrinogen monolayers on the gold sensor was attributed to its higher roughness. However, for higher fibrinogen coverage the hydration functions for both sensors became identical exhibiting an universal behavior. By using the hydration functions, the fibrinogen adsorption/desorption runs derived from QCM-D measurements were converted to the Γd vs. the time relationships. This allowed to precisely determine the maximum coverage that varied between 1.6mgm(-2) at pH 3.5 and 4.5mgm(-2) at pH 7.4 (for ionic strength of 0.15M). These results agree with theoretical eRSA modeling and previous experimental data derived by using ellipsometry, OWLS and TIRF. Various fibrinogen adsorption mechanisms were revealed by exploiting the maximum coverage data. These results allow one to develop a method for preparing fibrinogen monolayers of well-controlled coverage and molecule orientation. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrating evolutionary and functional approaches to infer adaptation at specific loci.

PubMed

Storz, Jay F; Wheat, Christopher W

2010-09-01

Inferences about adaptation at specific loci are often exclusively based on the static analysis of DNA sequence variation. Ideally,population-genetic evidence for positive selection serves as a stepping-off point for experimental studies to elucidate the functional significance of the putatively adaptive variation. We argue that inferences about adaptation at specific loci are best achieved by integrating the indirect, retrospective insights provided by population-genetic analyses with the more direct, mechanistic insights provided by functional experiments. Integrative studies of adaptive genetic variation may sometimes be motivated by experimental insights into molecular function, which then provide the impetus to perform population genetic tests to evaluate whether the functional variation is of adaptive significance. In other cases, studies may be initiated by genome scans of DNA variation to identify candidate loci for recent adaptation. Results of such analyses can then motivate experimental efforts to test whether the identified candidate loci do in fact contribute to functional variation in some fitness-related phenotype. Functional studies can provide corroborative evidence for positive selection at particular loci, and can potentially reveal specific molecular mechanisms of adaptation.

FFPred 2.0: Improved Homology-Independent Prediction of Gene Ontology Terms for Eukaryotic Protein Sequences

PubMed Central

Minneci, Federico; Piovesan, Damiano; Cozzetto, Domenico; Jones, David T.

2013-01-01

To understand fully cell behaviour, biologists are making progress towards cataloguing the functional elements in the human genome and characterising their roles across a variety of tissues and conditions. Yet, functional information – either experimentally validated or computationally inferred by similarity – remains completely missing for approximately 30% of human proteins. FFPred was initially developed to bridge this gap by targeting sequences with distant or no homologues of known function and by exploiting clear patterns of intrinsic disorder associated with particular molecular activities and biological processes. Here, we present an updated and improved version, which builds on larger datasets of protein sequences and annotations, and uses updated component feature predictors as well as revised training procedures. FFPred 2.0 includes support vector regression models for the prediction of 442 Gene Ontology (GO) terms, which largely expand the coverage of the ontology and of the biological process category in particular. The GO term list mainly revolves around macromolecular interactions and their role in regulatory, signalling, developmental and metabolic processes. Benchmarking experiments on newly annotated proteins show that FFPred 2.0 provides more accurate functional assignments than its predecessor and the ProtFun server do; also, its assignments can complement information obtained using BLAST-based transfer of annotations, improving especially prediction in the biological process category. Furthermore, FFPred 2.0 can be used to annotate proteins belonging to several eukaryotic organisms with a limited decrease in prediction quality. We illustrate all these points through the use of both precision-recall plots and of the COGIC scores, which we recently proposed as an alternative numerical evaluation measure of function prediction accuracy. PMID:23717476

Modeling the state dependent impulse control for computer virus propagation under media coverage

NASA Astrophysics Data System (ADS)

Liang, Xiyin; Pei, Yongzhen; Lv, Yunfei

2018-02-01

A state dependent impulsive control model is proposed to model the spread of computer virus incorporating media coverage. By the successor function, the sufficient conditions for the existence and uniqueness of order-1 periodic solution are presented first. Secondly, for two classes of periodic solutions, the geometric property of successor function and the analogue of the Poincaré criterion are employed to obtain the stability results. These results show that the number of the infective computers is under the threshold all the time. Finally, the theoretic and numerical analysis show that media coverage can delay the spread of computer virus.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

PubMed

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A; Nakhforoosh, Alireza

2017-02-01

Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Diverse Effects, Complex Causes: Children Use Information about Machines' Functional Diversity to Infer Internal Complexity

ERIC Educational Resources Information Center

Ahl, Richard E.; Keil, Frank C.

2017-01-01

Four studies explored the abilities of 80 adults and 180 children (4-9 years), from predominantly middle-class families in the Northeastern United States, to use information about machines' observable functional capacities to infer their internal, "hidden" mechanistic complexity. Children as young as 4 and 5 years old used machines'…

Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

PubMed Central

Sun, Junfeng; Li, Zhijun; Tong, Shanbao

2012-01-01

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470

Bundled automobile insurance coverage and accidents.

PubMed

Li, Chu-Shiu; Liu, Chwen-Chi; Peng, Sheng-Chang

2013-01-01

This paper investigates the characteristics of automobile accidents by taking into account two types of automobile insurance coverage: comprehensive vehicle physical damage insurance and voluntary third-party liability insurance. By using a unique data set in the Taiwanese automobile insurance market, we explore the bundled automobile insurance coverage and the occurrence of claims. It is shown that vehicle physical damage insurance is the major automobile coverage and affects the decision to purchase voluntary liability insurance coverage as a complement. Moreover, policyholders with high vehicle physical damage insurance coverage have a significantly higher probability of filing vehicle damage claims, and if they additionally purchase low voluntary liability insurance coverage, their accident claims probability is higher than those who purchase high voluntary liability insurance coverage. Our empirical results reveal that additional automobile insurance coverage information can capture more driver characteristics and driving behaviors to provide useful information for insurers' underwriting policies and to help analyze the occurrence of automobile accidents. Copyright © 2012 Elsevier Ltd. All rights reserved.

Type Ia supernova Hubble residuals and host-galaxy properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, A. G.; Aldering, G.; Aragon, C.

2014-03-20

Kim et al. introduced a new methodology for determining peak-brightness absolute magnitudes of type Ia supernovae from multi-band light curves. We examine the relation between their parameterization of light curves and Hubble residuals, based on photometry synthesized from the Nearby Supernova Factory spectrophotometric time series, with global host-galaxy properties. The K13 Hubble residual step with host mass is 0.013 ± 0.031 mag for a supernova subsample with data coverage corresponding to the K13 training; at <<1σ, the step is not significant and lower than previous measurements. Relaxing the data coverage requirement of the Hubble residual step with the host massmore » is 0.045 ± 0.026 mag for the larger sample; a calculation using the modes of the distributions, less sensitive to outliers, yields a step of 0.019 mag. The analysis of this article uses K13 inferred luminosities, as distinguished from previous works that use magnitude corrections as a function of SALT2 color and stretch parameters: steps at >2σ significance are found in SALT2 Hubble residuals in samples split by the values of their K13 x(1) and x(2) light-curve parameters. x(1) affects the light-curve width and color around peak (similar to the Δm {sub 15} and stretch parameters), and x(2) affects colors, the near-UV light-curve width, and the light-curve decline 20-30 days after peak brightness. The novel light-curve analysis, increased parameter set, and magnitude corrections of K13 may be capturing features of SN Ia diversity arising from progenitor stellar evolution.« less

Direct visualization of atomically precise nitrogen-doped graphene nanoribbons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yi; Zhang, Yanfang; Li, Geng

2014-07-14

We have fabricated atomically precise nitrogen-doped chevron-type graphene nanoribbons by using the on-surface synthesis technique combined with the nitrogen substitution of the precursors. Scanning tunneling microscopy and spectroscopy indicate that the well-defined nanoribbons tend to align with the neighbors side-by-side with a band gap of 1.02 eV, which is in good agreement with the density functional theory calculation result. The influence of the high precursor coverage on the quality of the nanoribbons is also studied. We find that graphene nanoribbons with sufficient aspect ratios can only be fabricated at sub-monolayer precursor coverage. This work provides a way to construct atomically precisemore » nitrogen-doped graphene nanoribbons.« less

Chemically modified electrodes by nucleophilic substitution of chlorosilylated platinum oxide surfaces

NASA Astrophysics Data System (ADS)

Chen, Chun-Hsien; Hutchison, James H.; Postlethwaite, Timothy A.; Richardson, John N.; Murray, R. W.

1994-07-01

Chlorosilylated platinum oxide electrode surfaces can be generated by reaction of SiCl4 vapor with an electrochemically prepared monolayer of platinum oxide. A variety of nucleophilic agents (such as alcohols, amines, thiols, and Grignard reagents) can be used to displace chloride and thereby functionalize the metal surface. Electroactive surfaces prepared with ferrocene methanol as the nucleophile show that derivatization by small molecules can achieve coverages on the order of a full monolayer. Surfaces modified with long-chain alkyl groups efficiently block electrode reactions of redox probes dissolved in the contacting solution, but other electrochemical (double layer capacitance and surface coverage) and contact angle measurements suggest that these molecule films are not highly ordered, self-assembled monolayers.

State contraceptive coverage laws: creative responses to questions of "conscience".

PubMed

Dailard, C

1999-08-01

The Federal Employees Health Benefits Program (FEHBP) guaranteed contraceptive coverage for employees of the federal government. However, opponents of the FEHBP contraceptive coverage questioned the viability of the conscience clause. Supporters of the contraceptive coverage pressed for the narrowest exemption, one that only permit religious plans that clearly states religious objection to contraception. There are six of the nine states that have enacted contraceptive coverage laws aimed at the private sector. The statutes included a provision of conscience clause. The private sector disagrees to the plan since almost all of the employees¿ work for employers who only offer one plan. The scope of exemption for employers was an issue in five states that have enacted the contraceptive coverage. In Hawaii and California, it was exemplified that if employers are exempted from the contraceptive coverage based on religious grounds, an employee will be entitled to purchase coverage directly from the plan. There are still questions on how an insurer, who objects based on religious grounds to a plan with contraceptive coverage, can function in a marketplace where such coverage is provided by most private sector employers.

Medicine, Media, and Celebrities: News Coverage of Breast Cancer, 1960-1995.

ERIC Educational Resources Information Center

Corbett, Julia B.; Mori, Motomi

1999-01-01

Contributes to scholarship on the role of mass media in breast cancer coverage. Finds extremely high, significant correlations between numbers of medical-journal articles and newspaper, magazine, and TV coverage; a two-way concurrent relationship between breast cancer funding and media coverage, and between breast cancer incidence and TV coverage;…

A Bayesian account of ‘hysteria’

PubMed Central

Adams, Rick A.; Brown, Harriet; Pareés, Isabel; Friston, Karl J.

2012-01-01

This article provides a neurobiological account of symptoms that have been called ‘hysterical’, ‘psychogenic’ or ‘medically unexplained’, which we will call functional motor and sensory symptoms. We use a neurobiologically informed model of hierarchical Bayesian inference in the brain to explain functional motor and sensory symptoms in terms of perception and action arising from inference based on prior beliefs and sensory information. This explanation exploits the key balance between prior beliefs and sensory evidence that is mediated by (body focused) attention, symptom expectations, physical and emotional experiences and beliefs about illness. Crucially, this furnishes an explanation at three different levels: (i) underlying neuromodulatory (synaptic) mechanisms; (ii) cognitive and experiential processes (attention and attribution of agency); and (iii) formal computations that underlie perceptual inference (representation of uncertainty or precision). Our explanation involves primary and secondary failures of inference; the primary failure is the (autonomous) emergence of a percept or belief that is held with undue certainty (precision) following top-down attentional modulation of synaptic gain. This belief can constitute a sensory percept (or its absence) or induce movement (or its absence). The secondary failure of inference is when the ensuing percept (and any somatosensory consequences) is falsely inferred to be a symptom to explain why its content was not predicted by the source of attentional modulation. This account accommodates several fundamental observations about functional motor and sensory symptoms, including: (i) their induction and maintenance by attention; (ii) their modification by expectation, prior experience and cultural beliefs and (iii) their involuntary and symptomatic nature. PMID:22641838

Statistical inference on censored data for targeted clinical trials under enrichment design.

PubMed

Chen, Chen-Fang; Lin, Jr-Rung; Liu, Jen-Pei

2013-01-01

For the traditional clinical trials, inclusion and exclusion criteria are usually based on some clinical endpoints; the genetic or genomic variability of the trial participants are not totally utilized in the criteria. After completion of the human genome project, the disease targets at the molecular level can be identified and can be utilized for the treatment of diseases. However, the accuracy of diagnostic devices for identification of such molecular targets is usually not perfect. Some of the patients enrolled in targeted clinical trials with a positive result for the molecular target might not have the specific molecular targets. As a result, the treatment effect may be underestimated in the patient population truly with the molecular target. To resolve this issue, under the exponential distribution, we develop inferential procedures for the treatment effects of the targeted drug based on the censored endpoints in the patients truly with the molecular targets. Under an enrichment design, we propose using the expectation-maximization algorithm in conjunction with the bootstrap technique to incorporate the inaccuracy of the diagnostic device for detection of the molecular targets on the inference of the treatment effects. A simulation study was conducted to empirically investigate the performance of the proposed methods. Simulation results demonstrate that under the exponential distribution, the proposed estimator is nearly unbiased with adequate precision, and the confidence interval can provide adequate coverage probability. In addition, the proposed testing procedure can adequately control the size with sufficient power. On the other hand, when the proportional hazard assumption is violated, additional simulation studies show that the type I error rate is not controlled at the nominal level and is an increasing function of the positive predictive value. A numerical example illustrates the proposed procedures. Copyright © 2013 John Wiley & Sons, Ltd.

Seismic Study of the Subsurface Structure and Dynamics of the Solar Interior from High Spatial Resolution Observations

NASA Technical Reports Server (NTRS)

Korzennik, Sylvain G.

1997-01-01

We have carried out the data reduction and analysis of Mt. Wilson 60' solar tower high spatial resolution observations. The reduction of the 100-day-long summer of 1990 observation campaign in terms of rotational splittings was completed leading to an excess of 600,000 splittings. The analysis of these splittings lead to a new inference of the solar internal rotation rate as a function of depth and latitude.

CowPI: A Rumen Microbiome Focussed Version of the PICRUSt Functional Inference Software.

PubMed

Wilkinson, Toby J; Huws, Sharon A; Edwards, Joan E; Kingston-Smith, Alison H; Siu-Ting, Karen; Hughes, Martin; Rubino, Francesco; Friedersdorff, Maximillian; Creevey, Christopher J

2018-01-01

Metataxonomic 16S rDNA based studies are a commonplace and useful tool in the research of the microbiome, but they do not provide the full investigative power of metagenomics and metatranscriptomics for revealing the functional potential of microbial communities. However, the use of metagenomic and metatranscriptomic technologies is hindered by high costs and skills barrier necessary to generate and interpret the data. To address this, a tool for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was developed for inferring the functional potential of an observed microbiome profile, based on 16S data. This allows functional inferences to be made from metataxonomic 16S rDNA studies with little extra work or cost, but its accuracy relies on the availability of completely sequenced genomes of representative organisms from the community being investigated. The rumen microbiome is an example of a community traditionally underrepresented in genome and sequence databases, but recent efforts by projects such as the Global Rumen Census and Hungate 1000 have resulted in a wide sampling of 16S rDNA profiles and almost 500 fully sequenced microbial genomes from this environment. Using this information, we have developed "CowPI," a focused version of the PICRUSt tool provided for use by the wider scientific community in the study of the rumen microbiome. We evaluated the accuracy of CowPI and PICRUSt using two 16S datasets from the rumen microbiome: one generated from rDNA and the other from rRNA where corresponding metagenomic and metatranscriptomic data was also available. We show that the functional profiles predicted by CowPI better match estimates for both the meta-genomic and transcriptomic datasets than PICRUSt, and capture the higher degree of genetic variation and larger pangenomes of rumen organisms. Nonetheless, whilst being closer in terms of predictive power for the rumen microbiome, there were differences when compared to both the metagenomic and metatranscriptome data and so we recommend, where possible, functional inferences from 16S data should not replace metagenomic and metatranscriptomic approaches. The tool can be accessed at http://www.cowpi.org and is provided to the wider scientific community for use in the study of the rumen microbiome.

A Search for Water in a Super-Earth Atmosphere: High-resolution Optical Spectroscopy of 55Cancri e

DOE Office of Scientific and Technical Information (OSTI.GOV)

Esteves, Lisa J.; De Mooij, Ernst J. W.; Watson, Chris

We present the analysis of high-resolution optical spectra of four transits of 55Cnc e, a low-density super-Earth that orbits a nearby Sun-like star in under 18 hr. The inferred bulk density of the planet implies a substantial envelope, which, according to mass–radius relationships, could be either a low-mass extended or a high-mass compact atmosphere. Our observations investigate the latter scenario, with water as the dominant species. We take advantage of the Doppler cross-correlation technique, high-spectral resolution, and the large wavelength coverage of our observations to search for the signature of thousands of optical water absorption lines. Using our observations with HDSmore » on the Subaru telescope and ESPaDOnS on the Canada–France–Hawaii Telescope, we are able to place a 3 σ lower limit of 10 g mol{sup −1} on the mean-molecular weight of 55Cnc e’s water-rich (volume mixing ratio >10%), optically thin atmosphere, which corresponds to an atmospheric scale-height of ∼80 km. Our study marks the first high-spectral resolution search for water in a super-Earth atmosphere, and demonstrates that it is possible to recover known water-vapor absorption signals in a nearby super-Earth atmosphere, using high-resolution transit spectroscopy with current ground-based instruments.« less

A genome-wide scan for signatures of directional selection in domesticated pigs.

PubMed

Moon, Sunjin; Kim, Tae-Hun; Lee, Kyung-Tai; Kwak, Woori; Lee, Taeheon; Lee, Si-Woo; Kim, Myung-Jick; Cho, Kyuho; Kim, Namshin; Chung, Won-Hyong; Sung, Samsun; Park, Taesung; Cho, Seoae; Groenen, Martien Am; Nielsen, Rasmus; Kim, Yuseob; Kim, Heebal

2015-02-25

Animal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication. Whole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an F ST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness. We show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.

Progress in Childhood Vaccination Data in Immunization Information Systems - United States, 2013-2016.

PubMed

Murthy, Neil; Rodgers, Loren; Pabst, Laura; Fiebelkorn, Amy Parker; Ng, Terence

2017-11-03

In 2016, 55 jurisdictions in 49 states and six cities in the United States* used immunization information systems (IISs) to collect and manage immunization data and support vaccination providers and immunization programs. To monitor progress toward achieving IIS program goals, CDC surveys jurisdictions through an annual self-administered IIS Annual Report (IISAR). Data from the 2013-2016 IISARs were analyzed to assess progress made in four priority areas: 1) data completeness, 2) bidirectional exchange of data with electronic health record systems, 3) clinical decision support for immunizations, and 4) ability to generate childhood vaccination coverage estimates. IIS participation among children aged 4 months through 5 years increased from 90% in 2013 to 94% in 2016, and 33 jurisdictions reported ≥95% of children aged 4 months through 5 years participating in their IIS in 2016. Bidirectional messaging capacity in IISs increased from 25 jurisdictions in 2013 to 37 in 2016. In 2016, nearly all jurisdictions (52 of 55) could provide automated provider-level coverage reports, and 32 jurisdictions reported that their IISs could send vaccine forecasts to providers via Health Level 7 (HL7) messaging, up from 17 in 2013. Incremental progress was made in each area since 2013, but continued effort is needed to implement these critical functionalities among all IISs. Success in these priority areas, as defined by the IIS Functional Standards (1), bolsters clinicians' and public health practitioners' ability to attain high vaccination coverage in pediatric populations, and prepares IISs to develop more advanced functionalities to support state/local immunization services. Success in these priority areas also supports the achievement of federal immunization objectives, including the use of IISs as supplemental sampling frames for vaccination coverage surveys like the National Immunization Survey (NIS)-Child, reducing data collection costs, and supporting increased precision of state-level estimates.

Spatial variation in armouring in a channel with high sediment supply

Treesearch

T. E. Lisle; M. A. Madej

1992-01-01

Abstract - Recent advances in our understanding of the origin and function of armouring in gravel-bed rivers have not addressed the role of non-uniformity and unsteadiness of flow. These flow attributes have important influences on both the surface and subsurface bed material size distributions which are observed at low flow, from which we commonly make inferences...

The epiphytic microbiota of the globally widespread macroalga Cladophora glomerata (Chlorophyta, Cladophorales).

PubMed

Zulkifly, Shahrizim; Hanshew, Alissa; Young, Erica B; Lee, Philip; Graham, Melissa E; Graham, Michael E; Piotrowski, Michael; Graham, Linda E

2012-09-01

The filamentous chlorophyte Cladophora produces abundant nearshore populations in marine and freshwaters worldwide, often dominating periphyton communities and producing nuisance growths under eutrophic conditions. High surface area and environmental persistence foster such high functional and taxonomic diversity of epiphytic microfauna and microalgae that Cladophora has been labeled an ecological engineer. We tested the hypotheses that (1) Cladophora supports a structurally and functionally diverse epiphytic prokaryotic microbiota that influences materials cycling and (2) mutualistic host-microbe interactions occur. Because previous molecular sequencing-based analyses of the microbiota of C. glomerata found as western Lake Michigan beach drift had identified pathogenic associates such as Escherichia coli, we also asked if actively growing lentic C. glomerata harbors known pathogens. We used 16S rRNA gene amplicon pyrosequencing to examine the microbiota of C. glomerata of Lake Mendota, Dane, Wisconsin, United States, during the growing season of 2011, at the genus- or species-level to infer functional phenotypes. We used correlative scanning electron and fluorescence microscopy to describe major prokaryotic morphotypes. We found microscopic evidence for diverse bacterial morphotypes, and molecular evidence for ca. 100 distinct sequence types classifiable to genus at the 80% confidence level or species at the 96-97% level within nine bacterial phyla, but not E. coli or related human pathogens. We inferred that bacterial epiphytes of lentic C. glomerata have diverse functions in materials cycling, with traits that indicate the occurrence of mutualistic interactions with the algal host.

Thermal effects on electronic properties of CO/Pt(111) in water.

PubMed

Duan, Sai; Xu, Xin; Luo, Yi; Hermansson, Kersti; Tian, Zhong-Qun

2013-08-28

Structure and adsorption energy of carbon monoxide molecules adsorbed on the Pt(111) surfaces with various CO coverages in water as well as work function of the whole systems at room temperature of 298 K were studied by means of a hybrid method that combines classical molecular dynamics and density functional theory. We found that when the coverage of CO is around half monolayer, i.e. 50%, there is no obvious peak of the oxygen density profile appearing in the first water layer. This result reveals that, in this case, the external force applied to water molecules from the CO/Pt(111) surface almost vanishes as a result of the competitive adsorption between CO and water molecules on the Pt(111) surface. This coverage is also the critical point of the wetting/non-wetting conditions for the CO/Pt(111) surface. Averaged work function and adsorption energy from current simulations are consistent with those of previous studies, which show that thermal average is required for direct comparisons between theoretical predictions and experimental measurements. Meanwhile, the statistical behaviors of work function and adsorption energy at room temperature have also been calculated. The standard errors of the calculated work function for the water-CO/Pt(111) interfaces are around 0.6 eV at all CO coverages, while the standard error decreases from 1.29 to 0.05 eV as the CO coverage increases from 4% to 100% for the calculated adsorption energy. Moreover, the critical points for these electronic properties are the same as those for the wetting/non-wetting conditions. These findings provide a better understanding about the interfacial structure under specific adsorption conditions, which can have important applications on the structure of electric double layers and therefore offer a useful perspective for the design of the electrochemical catalysts.

Social networks help to infer causality in the tumor microenvironment.

PubMed

Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis

2016-03-15

Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.

Influenza vaccination coverage among US children from 2004/2005 to 2015/2016.

PubMed

Tian, Changwei; Wang, Hua; Wang, Wenming; Luo, Xiaoming

2018-05-15

Quantify the influenza vaccine coverage is essential to identify emerging concerns and to immunization programs for targeting interventions. Data from National Health Interview Survey were used to estimate receipt of at least one dose of influenza vaccination among children 6 months to 17 years of age. Influenza vaccination coverage increased from 16.70% during 2004/2005 to 49.43% during 2015/2016 (3.18% per year, P < 0.001); however, the coverage increased slightly after 2010/2011. Children at high risk of influenza complications had higher influenza vaccination coverage than non at-risk children. Boys and girls had similar coverage each year. While the coverage increased from 2004/2005 to 2015/2016 for all age groups, the coverage decreased with age each year (-0.64 to -1.58% per age group). There was a higher and rapid increase of coverage in Northeast than Midwest, South and West. American Indian or Alaskan Native and Asian showed higher coverage than other race groups (White, Black/African American, Multiple race). Multivariable analysis showed that high-risk status and region had the greatest associations with levels of vaccine coverage. Although the influenza vaccination coverage among children had increased remarkably since 2004/2005, establishing more effective immunization programs are warranted to achieve the Healthy People 2020 target.

Influence of different cusp coverage methods for the extension of ceramic inlays on marginal integrity and enamel crack formation in vitro.

PubMed

Krifka, Stephanie; Stangl, Martin; Wiesbauer, Sarah; Hiller, Karl-Anton; Schmalz, Gottfried; Federlin, Marianne

2009-09-01

No information is available to date about cusp design of thin (1.0 mm) non-functional cusps and its influence upon (1) marginal integrity of ceramic inlays (CI) and partial ceramic crowns (PCC) and (2) crack formation of dental tissues. The aim of this in vitro study was to investigate the effect of cusp coverage of thin non-functional cusps on marginal integrity and enamel crack formation. CI and PCC preparations were performed on extracted human molars. Non-functional cusps were adjusted to 1.0-mm wall thickness and 1.0-mm wall thickness with horizontal reduction of about 2.0 mm. Ceramic restorations (Vita Mark II, Cerec3 System) were adhesively luted with Excite/Variolink II. The specimens were exposed to thermocycling and central mechanical loading. Marginal integrity was assessed by evaluating dye penetration after thermal cycling and mechanical loading. Enamel cracks were documented under a reflective-light microscope. The data were statistically analysed with the Mann-Whitney U test, the Fishers exact test (alpha = 0.05) and the error rates method. PCC with horizontal reduction of non-functional cusps showed statistically significant less microleakage than PCC without such a cusp coverage. Preparation designs with horizontal reduction of non-functional cusps showed a tendency to less enamel crack formation than preparation designs without cusp coverage. Thin non-functional cusp walls of adhesively bonded restorations should be completely covered or reduced to avoid enamel cracks and marginal deficiency.

INFERRING THE ECCENTRICITY DISTRIBUTION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogg, David W.; Bovy, Jo; Myers, Adam D., E-mail: david.hogg@nyu.ed

2010-12-20

Standard maximum-likelihood estimators for binary-star and exoplanet eccentricities are biased high, in the sense that the estimated eccentricity tends to be larger than the true eccentricity. As with most non-trivial observables, a simple histogram of estimated eccentricities is not a good estimate of the true eccentricity distribution. Here, we develop and test a hierarchical probabilistic method for performing the relevant meta-analysis, that is, inferring the true eccentricity distribution, taking as input the likelihood functions for the individual star eccentricities, or samplings of the posterior probability distributions for the eccentricities (under a given, uninformative prior). The method is a simple implementationmore » of a hierarchical Bayesian model; it can also be seen as a kind of heteroscedastic deconvolution. It can be applied to any quantity measured with finite precision-other orbital parameters, or indeed any astronomical measurements of any kind, including magnitudes, distances, or photometric redshifts-so long as the measurements have been communicated as a likelihood function or a posterior sampling.« less

Using Corpus Linguistics to Examine the Extrapolation Inference in the Validity Argument for a High-Stakes Speaking Assessment

ERIC Educational Resources Information Center

LaFlair, Geoffrey T.; Staples, Shelley

2017-01-01

Investigations of the validity of a number of high-stakes language assessments are conducted using an argument-based approach, which requires evidence for inferences that are critical to score interpretation (Chapelle, Enright, & Jamieson, 2008b; Kane, 2013). The current study investigates the extrapolation inference for a high-stakes test of…

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Coevolutionary modeling of protein sequences: Predicting structure, function, and mutational landscapes

NASA Astrophysics Data System (ADS)

Weigt, Martin

Over the last years, biological research has been revolutionized by experimental high-throughput techniques, in particular by next-generation sequencing technology. Unprecedented amounts of data are accumulating, and there is a growing request for computational methods unveiling the information hidden in raw data, thereby increasing our understanding of complex biological systems. Statistical-physics models based on the maximum-entropy principle have, in the last few years, played an important role in this context. To give a specific example, proteins and many non-coding RNA show a remarkable degree of structural and functional conservation in the course of evolution, despite a large variability in amino acid sequences. We have developed a statistical-mechanics inspired inference approach - called Direct-Coupling Analysis - to link this sequence variability (easy to observe in sequence alignments, which are available in public sequence databases) to bio-molecular structure and function. In my presentation I will show, how this methodology can be used (i) to infer contacts between residues and thus to guide tertiary and quaternary protein structure prediction and RNA structure prediction, (ii) to discriminate interacting from non-interacting protein families, and thus to infer conserved protein-protein interaction networks, and (iii) to reconstruct mutational landscapes and thus to predict the phenotypic effect of mutations. References [1] M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon and M. Weigt ''Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1'', Mol. Biol. Evol. (2015), doi: 10.1093/molbev/msv211 [2] E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt ''Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction'', Nucleic Acids Research (2015), doi: 10.1093/nar/gkv932 [3] F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C. Sander, R. Zecchina, J.N. Onuchic, T. Hwa, M. Weigt, ''Direct-coupling analysis of residue co-evolution captures native contacts across many protein families'', Proc. Natl. Acad. Sci. 108, E1293-E1301 (2011).

Lidar Data Products and Applications Enabled by Conical Scanning

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K.; Miller, David O.; Wilkerson, Thomas D.; Lee, Sang-Woo

2004-01-01

Several new data products and applications for elastic backscatter lidar are achieved using simple conical scanning. Atmospheric boundary layer spatial and temporal structure is revealed with resolution not possible with static pointing lidars. Cloud fractional coverage as a function of altitude is possible with high temporal resolution. Wind profiles are retrieved from the cloud and aerosol structure motions revealed by scanning. New holographic technology will soon allow quasi-conical scanning and push-broom lidar imaging without mechanical scanning, high resolution, on the order of seconds.

Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T

PubMed Central

Yun, Seong Dae

2017-01-01

The relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods. PMID:28945780

Wisdom of crowds for robust gene network inference

PubMed Central

Marbach, Daniel; Costello, James C.; Küffner, Robert; Vega, Nicci; Prill, Robert J.; Camacho, Diogo M.; Allison, Kyle R.; Kellis, Manolis; Collins, James J.; Stolovitzky, Gustavo

2012-01-01

Reconstructing gene regulatory networks from high-throughput data is a long-standing problem. Through the DREAM project (Dialogue on Reverse Engineering Assessment and Methods), we performed a comprehensive blind assessment of over thirty network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae, and in silico microarray data. We characterize performance, data requirements, and inherent biases of different inference approaches offering guidelines for both algorithm application and development. We observe that no single inference method performs optimally across all datasets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse datasets. Thereby, we construct high-confidence networks for E. coli and S. aureus, each comprising ~1700 transcriptional interactions at an estimated precision of 50%. We experimentally test 53 novel interactions in E. coli, of which 23 were supported (43%). Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks. PMID:22796662

Incomplete aneurysm coverage after patent foramen ovale closure in patients with huge atrial septal aneurysm: effects on left atrial functional remodeling.

PubMed

Rigatelli, Gianluca; Ronco, Federico; Cardaioli, Paolo; Dell'avvocata, Fabio; Braggion, Gabriele; Giordan, Massimo; Aggio, Silvio

2010-08-01

Large devices are often implanted to treat patent foramen ovale (PFO) and atrial septal aneurysm (ASA) with increase risk of erosion and thrombosis. Our study is aimed to assess the impact on left atrium functional remodeling and clinical outcomes of partial coverage of the approach using moderately small Amplatzer ASD Cribriform Occluder in patients with large PFO and ASA. We prospectively enrolled 30 consecutive patients with previous stroke (mean age 36 +/- 9.5 years, 19 females), significant PFO, and large ASA referred to our center for catheter-based PFO closure. Left atrium (LA) passive and active emptying, LA conduit function, and LA ejection fraction were computed before and after 6 months from the procedure by echocardiography. The preclosure values were compared to values of a normal healthy population of sex and heart rate matched 30 patients. Preclosure values demonstrated significantly greater reservoir function as well as passive and active emptying, with significantly reduced conduit function and LA ejection fraction, when compared normal healthy subjects. All patients underwent successful transcatheter closure (25 mm device in 15 patients, 30 mm device in 6 patients, mean ratio device/diameter of the interatrial septum = 0.74). Incomplete ASA coverage in both orthogonal views was observed in 21 patients. Compared to patients with complete coverage, there were no differences in LA functional parameters and occlusion rates. This study confirmed that large ASAs are associated with LA dysfunction. The use of relatively small Amplatzer ASD Cribriform Occluder devices is probably effective enough to promote functional remodeling of the left atrium.

Hemispheric processing of predictive inferences during reading: The influence of negatively emotional valenced stimuli.

PubMed

Virtue, Sandra; Schutzenhofer, Michael; Tomkins, Blaine

2017-07-01

Although a left hemisphere advantage is usually evident during language processing, the right hemisphere is highly involved during the processing of weakly constrained inferences. However, currently little is known about how the emotional valence of environmental stimuli influences the hemispheric processing of these inferences. In the current study, participants read texts promoting either strongly or weakly constrained predictive inferences and performed a lexical decision task to inference-related targets presented to the left visual field-right hemisphere or the right visual field-left hemisphere. While reading these texts, participants either listened to dissonant music (i.e., the music condition) or did not listen to music (i.e., the no music condition). In the no music condition, the left hemisphere showed an advantage for strongly constrained inferences compared to weakly constrained inferences, whereas the right hemisphere showed high facilitation for both strongly and weakly constrained inferences. In the music condition, both hemispheres showed greater facilitation for strongly constrained inferences than for weakly constrained inferences. These results suggest that negatively valenced stimuli (such as dissonant music) selectively influences the right hemisphere's processing of weakly constrained inferences during reading.

Comparative analysis of gut microbiota associated with body mass index in a large Korean cohort.

PubMed

Yun, Yeojun; Kim, Han-Na; Kim, Song E; Heo, Seong Gu; Chang, Yoosoo; Ryu, Seungho; Shin, Hocheol; Kim, Hyung-Lae

2017-07-04

Gut microbiota plays an important role in the harvesting, storage, and expenditure of energy obtained from one's diet. Our cross-sectional study aimed to identify differences in gut microbiota according to body mass index (BMI) in a Korean population. 16S rRNA gene sequence data from 1463 subjects were categorized by BMI into normal, overweight, and obese groups. Fecal microbiotas were compared to determine differences in diversity and functional inference analysis related with BMI. The correlation between genus-level microbiota and BMI was tested using zero-inflated Gaussian mixture models, with or without covariate adjustment of nutrient intake. We confirmed differences between 16Sr RNA gene sequencing data of each BMI group, with decreasing diversity in the obese compared with the normal group. According to analysis of inferred metagenomic functional content using PICRUSt algorithm, a highly significant discrepancy in metabolism and immune functions (P < 0.0001) was predicted in the obese group. Differential taxonomic components in each BMI group were greatly affected by nutrient adjustment, whereas signature bacteria were not influenced by nutrients in the obese compared with the overweight group. We found highly significant statistical differences between normal, overweight and obese groups using a large sample size with or without diet confounding factors. Our informative dataset sheds light on the epidemiological study on population microbiome.

Inferring evolution of gene duplicates using probabilistic models and nonparametric belief propagation.

PubMed

Zeng, Jia; Hannenhalli, Sridhar

2013-01-01

Gene duplication, followed by functional evolution of duplicate genes, is a primary engine of evolutionary innovation. In turn, gene expression evolution is a critical component of overall functional evolution of paralogs. Inferring evolutionary history of gene expression among paralogs is therefore a problem of considerable interest. It also represents significant challenges. The standard approaches of evolutionary reconstruction assume that at an internal node of the duplication tree, the two duplicates evolve independently. However, because of various selection pressures functional evolution of the two paralogs may be coupled. The coupling of paralog evolution corresponds to three major fates of gene duplicates: subfunctionalization (SF), conserved function (CF) or neofunctionalization (NF). Quantitative analysis of these fates is of great interest and clearly influences evolutionary inference of expression. These two interrelated problems of inferring gene expression and evolutionary fates of gene duplicates have not been studied together previously and motivate the present study. Here we propose a novel probabilistic framework and algorithm to simultaneously infer (i) ancestral gene expression and (ii) the likely fate (SF, NF, CF) at each duplication event during the evolution of gene family. Using tissue-specific gene expression data, we develop a nonparametric belief propagation (NBP) algorithm to predict the ancestral expression level as a proxy for function, and describe a novel probabilistic model that relates the predicted and known expression levels to the possible evolutionary fates. We validate our model using simulation and then apply it to a genome-wide set of gene duplicates in human. Our results suggest that SF tends to be more frequent at the earlier stage of gene family expansion, while NF occurs more frequently later on.

Diversity of Prdm9 Zinc Finger Array in Wild Mice Unravels New Facets of the Evolutionary Turnover of this Coding Minisatellite

PubMed Central

Buard, Jérôme; Rivals, Eric; Dunoyer de Segonzac, Denis; Garres, Charlotte; Caminade, Pierre; de Massy, Bernard; Boursot, Pierre

2014-01-01

In humans and mice, meiotic recombination events cluster into narrow hotspots whose genomic positions are defined by the PRDM9 protein via its DNA binding domain constituted of an array of zinc fingers (ZnFs). High polymorphism and rapid divergence of the Prdm9 gene ZnF domain appear to involve positive selection at DNA-recognition amino-acid positions, but the nature of the underlying evolutionary pressures remains a puzzle. Here we explore the variability of the Prdm9 ZnF array in wild mice, and uncovered a high allelic diversity of both ZnF copy number and identity with the caracterization of 113 alleles. We analyze features of the diversity of ZnF identity which is mostly due to non-synonymous changes at codons −1, 3 and 6 of each ZnF, corresponding to amino-acids involved in DNA binding. Using methods adapted to the minisatellite structure of the ZnF array, we infer a phylogenetic tree of these alleles. We find the sister species Mus spicilegus and M. macedonicus as well as the three house mouse (Mus musculus) subspecies to be polyphyletic. However some sublineages have expanded independently in Mus musculus musculus and M. m. domesticus, the latter further showing phylogeographic substructure. Compared to random genomic regions and non-coding minisatellites, none of these patterns appears exceptional. In silico prediction of DNA binding sites for each allele, overlap of their alignments to the genome and relative coverage of the different families of interspersed repeated elements suggest a large diversity between PRDM9 variants with a potential for highly divergent distributions of recombination events in the genome with little correlation to evolutionary distance. By compiling PRDM9 ZnF protein sequences in Primates, Muridae and Equids, we find different diversity patterns among the three amino-acids most critical for the DNA-recognition function, suggesting different diversification timescales. PMID:24454780

Towards Semantic Web Services on Large, Multi-Dimensional Coverages

NASA Astrophysics Data System (ADS)

Baumann, P.

2009-04-01

Observed and simulated data in the Earth Sciences often come as coverages, the general term for space-time varying phenomena as set forth by standardization bodies like the Open GeoSpatial Consortium (OGC) and ISO. Among such data are 1-d time series, 2-D surface data, 3-D surface data time series as well as x/y/z geophysical and oceanographic data, and 4-D metocean simulation results. With increasing dimensionality the data sizes grow exponentially, up to Petabyte object sizes. Open standards for exploiting coverage archives over the Web are available to a varying extent. The OGC Web Coverage Service (WCS) standard defines basic extraction operations: spatio-temporal and band subsetting, scaling, reprojection, and data format encoding of the result - a simple interoperable interface for coverage access. More processing functionality is available with products like Matlab, Grid-type interfaces, and the OGC Web Processing Service (WPS). However, these often lack properties known as advantageous from databases: declarativeness (describe results rather than the algorithms), safe in evaluation (no request can keep a server busy infinitely), and optimizable (enable the server to rearrange the request so as to produce the same result faster). WPS defines a geo-enabled SOAP interface for remote procedure calls. This allows to webify any program, but does not allow for semantic interoperability: a function is identified only by its function name and parameters while the semantics is encoded in the (only human readable) title and abstract. Hence, another desirable property is missing, namely an explicit semantics which allows for machine-machine communication and reasoning a la Semantic Web. The OGC Web Coverage Processing Service (WCPS) language, which has been adopted as an international standard by OGC in December 2008, defines a flexible interface for the navigation, extraction, and ad-hoc analysis of large, multi-dimensional raster coverages. It is abstract in that it does not anticipate any particular protocol. One such protocol is given by the OGC Web Coverage Service (WCS) Processing Extension standard which ties WCPS into WCS. Another protocol which makes WCPS an OGC Web Processing Service (WPS) Profile is under preparation. Thereby, WCPS bridges WCS and WPS. The conceptual model of WCPS relies on the coverage model of WCS, which in turn is based on ISO 19123. WCS currently addresses raster-type coverages where a coverage is seen as a function mapping points from a spatio-temporal extent (its domain) into values of some cell type (its range). A retrievable coverage has an identifier associated, further the CRSs supported and, for each range field (aka band, channel), the interpolation methods applicable. The WCPS language offers access to one or several such coverages via a functional, side-effect free language. The following example, which derives the NDVI (Normalized Difference Vegetation Index) from given coverages C1, C2, and C3 within the regions identified by the binary mask R, illustrates the language concept: for c in ( C1, C2, C3 ), r in ( R ) return encode( (char) (c.nir - c.red) / (c.nir + c.red), H˜DF-EOS\\~ ) The result is a list of three HDF-EOS encoded images containing masked NDVI values. Note that the same request can operate on coverages of any dimensionality. The expressive power of WCPS includes statistics, image, and signal processing up to recursion, to maintain safe evaluation. As both syntax and semantics of any WCPS expression is well known the language is Semantic Web ready: clients can construct WCPS requests on the fly, servers can optimize such requests (this has been investigated extensively with the rasdaman raster database system) and automatically distribute them for processing in a WCPS-enabled computing cloud. The WCPS Reference Implementation is being finalized now that the standard is stable; it will be released in open source once ready. Among the future tasks is to extend WCPS to general meshes, in synchronization with the WCS standard. In this talk WCPS is presented in the context of OGC standardization. The author is co-chair of OGC's WCS Working Group (WG) and Coverages WG.

Mechanical properties of highly defective graphene: from brittle rupture to ductile fracture.

PubMed

Xu, Lanqing; Wei, Ning; Zheng, Yongping

2013-12-20

Defects are generally believed to deteriorate the superlative performance of graphene-based devices but may also be useful when carefully engineered to tailor the local properties and achieve new functionalities. Central to most defect-associated applications is the defect coverage and arrangement. In this work, we investigate, by molecular dynamics simulations, the mechanical properties and fracture dynamics of graphene sheets with randomly distributed vacancies or Stone-Wales defects under tensile deformations over a wide defect coverage range. With defects presented, an sp-sp(2) bonding network and an sp-sp(2)-sp(3) bonding network are observed in vacancy-defected and Stone-Wales-defected graphene, respectively. The ultimate strength degrades gradually with increasing defect coverage and saturates in the high-ratio regime, whereas the fracture strain presents an unusual descending-saturating-improving trend. In the dense vacancy defect situation, the fracture becomes more plastic and super-ductility is observed. Further fracture dynamics analysis reveals that the crack trapping by sp-sp(2) and sp-sp(2)-sp(3) rings and the crack-tip blunting account for the ductile fracture, whereas geometric rearrangement on the entire sheet for vacancy defects and geometric rearrangement on the specific defect sites for Stone-Wales defects account for their distinctive rules of the evolution of the fracture strain.

High vaccination coverage is associated with low epidemic level of seasonal influenza in elementary schools: an observational study in Matsumoto City, Japan.

PubMed

Uchida, Mitsuo; Kaneko, Minoru; Hidaka, Yoshihiko; Yamamoto, Hiroshi; Honda, Takayuki; Takeuchi, Shouhei; Saito, Masaya; Kawa, Shigeyuki

2018-03-13

Influenza virus transmission may be prevented by infection control measures, including vaccination, wearing a mask, gargling with water, and hand washing. It is unclear, however, whether these measures affect influenza epidemics in school settings. A prospective epidemiological survey in all public elementary schools in Matsumoto City, Japan, during the 2014/2015 season evaluated the number of diagnosed patients in each school and calculated the reproduction number of schoolchildren. At the end of the prospective survey, a cross-sectional survey evaluated the implementation of infection control measures in these schools. Both results were combined and associations among infection control measures including vaccination, mask wearing, hand washing, water gargling, and epidemic level were evaluated. Of the 13,217 schoolchildren in 29 schools, 2548 were diagnosed with seasonal influenza. A significant negative association was observed between vaccination coverage and reproduction number at each school, but not between other infection control measures and the reproduction number. A regression curve with exponential function was most predictive. At 0% vaccination, the reproduction number was estimated to be 1.39. These findings provide evidence that high vaccination coverage was associated with reduced epidemic levels in schools and suggest the need for increased vaccination of schoolchildren.

The chemical composition of cirrus forming aerosol: Lessons from the MACPEX field study

NASA Astrophysics Data System (ADS)

Cziczo, D. J.; Froyd, K. D.; Murphy, D. M.

2012-12-01

Cirrus clouds are an important factor in the Earth's climate system. These clouds exert a large radiative forcing due to their extensive global coverage and high altitude despite minimal physical and optical thickness. During the Mid-latitude Aerosol and Cloud Properties EXperiment (MACPEX) we measured chemical and physical properties of the aerosols on which cirrus ice crystals formed in situ and in real time using a laser ablation single particle mass spectrometry technique deployed aboard the NASA WB-57 research aircraft. Ice residual particles were also collected for off-line laboratory investigation including electron microscopy. Flights spanned from the Gulf of Mexico to the mid-latitudes over the United States. In most cases heterogeneous freezing was the inferred mechanism of cloud formation and aerosol composition had a significant impact on the nucleation of the ice phase. Mineral dust and some metallic particles were highly enhanced in the ice phase when compared to their abundance outside of cloud. Particles such as soot and biological material, previously suggested as ice nuclei, were not found either due to an inability to nucleate ice or low abundance. Atmospheric implications of these measurements and more advanced future analyses will be discussed.

Direct evidence for EMIC wave scattering of relativistic electrons in space

NASA Astrophysics Data System (ADS)

Zhang, X.-J.; Li, W.; Ma, Q.; Thorne, R. M.; Angelopoulos, V.; Bortnik, J.; Chen, L.; Kletzing, C. A.; Kurth, W. S.; Hospodarsky, G. B.; Baker, D. N.; Reeves, G. D.; Spence, H. E.; Blake, J. B.; Fennell, J. F.

2016-07-01

Electromagnetic ion cyclotron (EMIC) waves have been proposed to cause efficient losses of highly relativistic (>1 MeV) electrons via gyroresonant interactions. Simultaneous observations of EMIC waves and equatorial electron pitch angle distributions, which can be used to directly quantify the EMIC wave scattering effect, are still very limited, however. In the present study, we evaluate the effect of EMIC waves on pitch angle scattering of ultrarelativistic (>1 MeV) electrons during the main phase of a geomagnetic storm, when intense EMIC wave activity was observed in situ (in the plasma plume region with high plasma density) on both Van Allen Probes. EMIC waves captured by Time History of Events and Macroscale Interactions during Substorms (THEMIS) probes and on the ground across the Canadian Array for Real-time Investigations of Magnetic Activity (CARISMA) are also used to infer their magnetic local time (MLT) coverage. From the observed EMIC wave spectra and local plasma parameters, we compute wave diffusion rates and model the evolution of electron pitch angle distributions. By comparing model results with local observations of pitch angle distributions, we show direct, quantitative evidence of EMIC wave-driven relativistic electron losses in the Earth's outer radiation belt.

Kinetically controlled indium surface coverage effects on PAMBE-growth of InN/GaN(0001) quantum well structures

NASA Astrophysics Data System (ADS)

Li, Chen; Maidaniuk, Yurii; Kuchuk, Andrian V.; Shetty, Satish; Ghosh, Pijush; White, Thomas P.; Morgan, Timothy Al.; Hu, Xian; Wu, Yang; Ware, Morgan E.; Mazur, Yuriy I.; Salamo, Gregory J.

2018-05-01

We report the effects of nitrogen (N) plasma and indium (In) flux on the In adatom adsorption/desorption kinetics on a GaN(0001) surface at the relatively high plasma-assisted molecular beam epitaxy-growth temperature of 680 °C. We experimentally demonstrate that under an active N flux, the (√{3 }×√{3 })R 30 ° surface reconstruction containing In and N quickly appears and the dynamically stable In adlayers sitting on this surface exhibit a continuous change from 0 to 2 MLs as a function of In flux. Compared to the bare GaN 1 ×1 surface which is stable during In exposure without an active N flux, we observed a much faster desorption for the bottom In adlayer and the absence of an In flux window corresponding to an In coverage of 1 ML. Moreover, when the In coverage exceeds 2 MLs, the desorption rates become identical for both surfaces. Finally, the importance of In surface coverage before GaN capping was shown by growing a series of InN/GaN multiple quantum well samples. The photoluminescence data show that a consistent quantum well structure is only formed if the surface is covered by excess In droplets before GaN capping.

High efficiency multishot interleaved spiral-in/out: acquisition for high-resolution BOLD fMRI.

PubMed

Jung, Youngkyoo; Samsonov, Alexey A; Liu, Thomas T; Buracas, Giedrius T

2013-08-01

Growing demand for high spatial resolution blood oxygenation level dependent (BOLD) functional magnetic resonance imaging faces a challenge of the spatial resolution versus coverage or temporal resolution tradeoff, which can be addressed by methods that afford increased acquisition efficiency. Spiral acquisition trajectories have been shown to be superior to currently prevalent echo-planar imaging in terms of acquisition efficiency, and high spatial resolution can be achieved by employing multiple-shot spiral acquisition. The interleaved spiral in/out trajectory is preferred over spiral-in due to increased BOLD signal contrast-to-noise ratio (CNR) and higher acquisition efficiency than that of spiral-out or noninterleaved spiral in/out trajectories (Law & Glover. Magn Reson Med 2009; 62:829-834.), but to date applicability of the multishot interleaved spiral in/out for high spatial resolution imaging has not been studied. Herein we propose multishot interleaved spiral in/out acquisition and investigate its applicability for high spatial resolution BOLD functional magnetic resonance imaging. Images reconstructed from interleaved spiral-in and -out trajectories possess artifacts caused by differences in T2 decay, off-resonance, and k-space errors associated with the two trajectories. We analyze the associated errors and demonstrate that application of conjugate phase reconstruction and spectral filtering can substantially mitigate these image artifacts. After applying these processing steps, the multishot interleaved spiral in/out pulse sequence yields high BOLD CNR images at in-plane resolution below 1 × 1 mm while preserving acceptable temporal resolution (4 s) and brain coverage (15 slices of 2 mm thickness). Moreover, this method yields sufficient BOLD CNR at 1.5 mm isotropic resolution for detection of activation in hippocampus associated with cognitive tasks (Stern memory task). The multishot interleaved spiral in/out acquisition is a promising technique for high spatial resolution BOLD functional magnetic resonance imaging applications. © 2012 Wiley Periodicals, Inc.

Adsorption and Structure of Chiral Epoxides on Pd(111): Propylene Oxide and Glycidol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahapatra, Mausumi; Tysoe, Wilfred T.

Here, the adsorption of enantiopure versus racemic propylene oxide (PO) on Pd(111) is studied by temperature-programmed desorption (TPD) to explore possible differences in their saturation coverage. It is found that that the saturation coverage of enantiopure PO on Pd(111) is identical to that of racemic PO, in contrast to results on Pt(111) where significant coverage differences were found. The surface structures of enantiopure PO on Pd(111) were characterized by scanning tunneling microscopy (STM), which shows the formation of linear chains and hexagonal structures proposed to be due to freely rotating PO, in contrast to the relatively disordered PO overlayers foundmore » on Pt(111). STM experiments were carried out for enantiopure glycidol, which contains the same epoxy ring as PO, but where the methyl group of propylene oxide is replaced by a -CH 2OH group to provide a hydrogen-bonding sites. Glycidol STM images show the formation of completely different surface structures; at low coverages, glycidol forms pseudohexagonal structures which assemble from glycidol dimers, while at high coverages the surface shows extensive hydrogen-bonded networks. Density functional theory (DFT) calculations were carried out to model the enantiopure PO linear chain and the glycidol dimers that are observed by STM. Similar calculations were carried out for racemic PO and glycidol structures. The calculated interaction energies for the enantiopure and the racemic pairs reveal that there is no difference for homochiral versus heterochiral structures for both PO and glycidol on Pd(111).« less

Adsorption and Structure of Chiral Epoxides on Pd(111): Propylene Oxide and Glycidol

DOE PAGES

Mahapatra, Mausumi; Tysoe, Wilfred T.

2018-01-03

Here, the adsorption of enantiopure versus racemic propylene oxide (PO) on Pd(111) is studied by temperature-programmed desorption (TPD) to explore possible differences in their saturation coverage. It is found that that the saturation coverage of enantiopure PO on Pd(111) is identical to that of racemic PO, in contrast to results on Pt(111) where significant coverage differences were found. The surface structures of enantiopure PO on Pd(111) were characterized by scanning tunneling microscopy (STM), which shows the formation of linear chains and hexagonal structures proposed to be due to freely rotating PO, in contrast to the relatively disordered PO overlayers foundmore » on Pt(111). STM experiments were carried out for enantiopure glycidol, which contains the same epoxy ring as PO, but where the methyl group of propylene oxide is replaced by a -CH 2OH group to provide a hydrogen-bonding sites. Glycidol STM images show the formation of completely different surface structures; at low coverages, glycidol forms pseudohexagonal structures which assemble from glycidol dimers, while at high coverages the surface shows extensive hydrogen-bonded networks. Density functional theory (DFT) calculations were carried out to model the enantiopure PO linear chain and the glycidol dimers that are observed by STM. Similar calculations were carried out for racemic PO and glycidol structures. The calculated interaction energies for the enantiopure and the racemic pairs reveal that there is no difference for homochiral versus heterochiral structures for both PO and glycidol on Pd(111).« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bachan, John

Chisel is a new open-source hardware construction language developed at UC Berkeley that supports advanced hardware design using highly parameterized generators and layered domain-specific hardware languages. Chisel is embedded in the Scala programming language, which raises the level of hardware design abstraction by providing concepts including object orientation, functional programming, parameterized types, and type inference. From the same source, Chisel can generate a high-speed C++-based cycle-accurate software simulator, or low-level Verilog designed to pass on to standard ASIC or FPGA tools for synthesis and place and route.

Amount of newspaper coverage of high school athletics for boys and girls on sports page and newspaper circulation.

PubMed

Pedersen, Paul M; Whisenant, Warren A

2002-02-01

This study analyzed the amount of coverage for high school athletics in 43 newspapers with small circulation by devoting 40% of their interscholastic athletics coverage to girls in athletics, printed significantly more articles about girls' athletics than did the newspapers with medium (33%) or large (32%) circulation. Therefore, the smaller the newspaper circulation, the more equitable the coverage of athletics for girls and boys. This finding was consistent with some prior work but not all.

Ventromedial Prefrontal Cortex Is Necessary for Normal Associative Inference and Memory Integration.

PubMed

Spalding, Kelsey N; Schlichting, Margaret L; Zeithamova, Dagmar; Preston, Alison R; Tranel, Daniel; Duff, Melissa C; Warren, David E

2018-04-11

The ability to flexibly combine existing knowledge in response to novel circumstances is highly adaptive. However, the neural correlates of flexible associative inference are not well characterized. Laboratory tests of associative inference have measured memory for overlapping pairs of studied items (e.g., AB, BC) and for nonstudied pairs with common associates (i.e., AC). Findings from functional neuroimaging and neuropsychology suggest the ventromedial prefrontal cortex (vmPFC) may be necessary for associative inference. Here, we used a neuropsychological approach to test the necessity of vmPFC for successful memory-guided associative inference in humans using an overlapping pairs associative memory task. We predicted that individuals with focal vmPFC damage ( n = 5; 3F, 2M) would show impaired inferential memory but intact non-inferential memory. Performance was compared with normal comparison participants ( n = 10; 6F, 4M). Participants studied pairs of visually presented objects including overlapping pairs (AB, BC) and nonoverlapping pairs (XY). Participants later completed a three-alternative forced-choice recognition task for studied pairs (AB, BC, XY) and inference pairs (AC). As predicted, the vmPFC group had intact memory for studied pairs but significantly impaired memory for inferential pairs. These results are consistent with the perspective that the vmPFC is necessary for memory-guided associative inference, indicating that the vmPFC is critical for adaptive abilities that require application of existing knowledge to novel circumstances. Additionally, vmPFC damage was associated with unexpectedly reduced memory for AB pairs post-inference, which could potentially reflect retroactive interference. Together, these results reinforce an emerging understanding of a role for the vmPFC in brain networks supporting associative memory processes. SIGNIFICANCE STATEMENT We live in a constantly changing environment, so the ability to adapt our knowledge to support understanding of new circumstances is essential. One important adaptive ability is associative inference which allows us to extract shared features from distinct experiences and relate them. For example, if we see a woman holding a baby, and later see a man holding the same baby, then we might infer that the two adults are a couple. Despite the importance of associative inference, the brain systems necessary for this ability are not known. Here, we report that damage to human ventromedial prefrontal cortex (vmPFC) disproportionately impairs associative inference. Our findings show the necessity of the vmPFC for normal associative inference and memory integration. Copyright © 2018 the authors 0270-6474/18/383767-09$15.00/0.

Uncertainty in regional temperatures inferred from sparse global observations: Application to a probabilistic classification of El Niño

NASA Astrophysics Data System (ADS)

Ilyas, Maryam; Brierley, Christopher M.; Guillas, Serge

2017-09-01

Instrumental records showing increases in surface temperature are some of the robust and iconic evidence of climate change. But how much should we trust regional temperature estimates interpolated from sparse observations? Here we quantify the uncertainty in the instrumental record by applying multiresolution lattice kriging, a recently developed interpolation technique that leverages the multiple spatial scales of temperature anomalies. The probability of monthly anomalies across the globe is represented by an ensemble, based on HadCRUT4 and accounting for observational and coverage uncertainties. To demonstrate the potential of these new data, we investigate the area-averaged temperature anomalies over the Niño 3.4 region in the equatorial Pacific. Having developed a definition of the El Niño-Southern Oscillation (ENSO) able to cope with probability distribution functions, we classify the ENSO state for each year since 1851. We find that for many years it is ambiguous as to whether there was an El Niño or not from the Niño 3.4 region alone. These years are mainly before 1920, but also just after World War II.

Probing exoplanet clouds with optical phase curves.

PubMed

Muñoz, Antonio García; Isaak, Kate G

2015-11-03

Kepler-7b is to date the only exoplanet for which clouds have been inferred from the optical phase curve--from visible-wavelength whole-disk brightness measurements as a function of orbital phase. Added to this, the fact that the phase curve appears dominated by reflected starlight makes this close-in giant planet a unique study case. Here we investigate the information on coverage and optical properties of the planet clouds contained in the measured phase curve. We generate cloud maps of Kepler-7b and use a multiple-scattering approach to create synthetic phase curves, thus connecting postulated clouds with measurements. We show that optical phase curves can help constrain the composition and size of the cloud particles. Indeed, model fitting for Kepler-7b requires poorly absorbing particles that scatter with low-to-moderate anisotropic efficiency, conclusions consistent with condensates of silicates, perovskite, and silica of submicron radii. We also show that we are limited in our ability to pin down the extent and location of the clouds. These considerations are relevant to the interpretation of optical phase curves with general circulation models. Finally, we estimate that the spherical albedo of Kepler-7b over the Kepler passband is in the range 0.4-0.5.

Reaction of hydrogen with Ag(111): binding states, minimum energy paths, and kinetics.

PubMed

Montoya, Alejandro; Schlunke, Anna; Haynes, Brian S

2006-08-31

The interaction of atomic and molecular hydrogen with the Ag(111) surface is studied using periodic density functional total-energy calculations. This paper focuses on the site preference for adsorption, ordered structures, and energy barriers for H diffusion and H recombination. Chemisorbed H atoms are unstable with respect to the H(2) molecule in all adsorption sites below monolayer coverage. The three-hollow sites are energetically the most favorable for H chemisorption. The binding energy of H to the surface decreases slightly up to one monolayer, suggesting a small repulsive H-H interaction on nonadjacent sites. Subsurface and vacancy sites are energetically less favorable for H adsorption than on-top sites. Recombination of chemisorbed H atoms leads to the formation of gas-phase H(2) with no molecular chemisorbed state. Recombination is an exothermic process and occurs on the bridge site with a pronounced energy barrier. This energy barrier is significantly higher than that inferred from experimental temperature-programmed desorption (TPD) studies. However, there is significant permeability of H atoms through the recombination energy barrier at low temperatures, thus increasing the rate constant for H(2) desorption due to quantum tunneling effects, and improving the agreement between experiment and theory.

Seeing it my way: a case of a selective deficit in inhibiting self-perspective.

PubMed

Samson, Dana; Apperly, Ian A; Kathirgamanathan, Umalini; Humphreys, Glyn W

2005-05-01

Little is known about the functional and neural architecture of social reasoning, one major obstacle being that we crucially lack the relevant tools to test potentially different social reasoning components. In the case of belief reasoning, previous studies have tried to separate the processes involved in belief reasoning per se from those involved in the processing of the high incidental demands such as the working memory demands of typical belief tasks. In this study, we developed new belief tasks in order to disentangle, for the first time, two perspective taking components involved in belief reasoning: (i) the ability to inhibit one's own perspective (self-perspective inhibition); and (ii) the ability to infer someone else's perspective as such (other-perspective taking). The two tasks had similar demands in other-perspective taking as they both required the participant to infer that a character has a false belief about an object's location. However, the tasks varied in the self-perspective inhibition demands. In the task with the lowest self-perspective inhibition demands, at the time the participant had to infer the character's false belief, he or she had no idea what the new object's location was. In contrast, in the task with the highest self-perspective inhibition demands, at the time the participant had to infer the character's false belief, he or she knew where the object was actually located (and this knowledge had thus to be inhibited). The two tasks were presented to a stroke patient, WBA, with right prefrontal and temporal damage. WBA performed well in the low-inhibition false-belief task but showed striking difficulty in the task placing high self-perspective inhibition demands, showing a selective deficit in inhibiting self-perspective. WBA also made egocentric errors in other social and visual perspective taking tasks, indicating a difficulty with belief attribution extending to the attribution of emotions, desires and visual experiences to other people. The case of WBA, together with the recent report of three patients impaired in belief reasoning even when self-perspective inhibition demands were reduced, provide the first neuropsychological evidence that the inhibition of one's own point of view and the ability to infer someone else's point of view rely on distinct neural and functional processes.

TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions.

PubMed

Heinrich, Mattias P; Blendowski, Max; Oktay, Ozan

2018-05-30

Deep convolutional neural networks (DCNN) are currently ubiquitous in medical imaging. While their versatility and high-quality results for common image analysis tasks including segmentation, localisation and prediction is astonishing, the large representational power comes at the cost of highly demanding computational effort. This limits their practical applications for image-guided interventions and diagnostic (point-of-care) support using mobile devices without graphics processing units (GPU). We propose a new scheme that approximates both trainable weights and neural activations in deep networks by ternary values and tackles the open question of backpropagation when dealing with non-differentiable functions. Our solution enables the removal of the expensive floating-point matrix multiplications throughout any convolutional neural network and replaces them by energy- and time-preserving binary operators and population counts. We evaluate our approach for the segmentation of the pancreas in CT. Here, our ternary approximation within a fully convolutional network leads to more than 90% memory reductions and high accuracy (without any post-processing) with a Dice overlap of 71.0% that comes close to the one obtained when using networks with high-precision weights and activations. We further provide a concept for sub-second inference without GPUs and demonstrate significant improvements in comparison with binary quantisation and without our proposed ternary hyperbolic tangent continuation. We present a key enabling technique for highly efficient DCNN inference without GPUs that will help to bring the advances of deep learning to practical clinical applications. It has also great promise for improving accuracies in large-scale medical data retrieval.

Two- and Three-Year-Olds Infer and Reason about Design Intentions in Order to Categorize Broken Objects

ERIC Educational Resources Information Center

Nelson, Deborah G. Kemler; Holt, Morghan B.; Egan, Louisa Chan

2004-01-01

In naming artifacts, do young children infer and reason about the intended functions of the objects? Participants between the ages of 2 and 4 years were shown two kinds of objects derived from familiar categories. One kind was damaged so as to undermine its usual function. The other kind was also dysfunctional, but made so by adding features that…

Effects of observation heights and atmospheric wave evolution in sunspot seismology: a study using HMI and AIA (1600 A and 1700 A) data

NASA Astrophysics Data System (ADS)

Rajaguru, S. P.; Couvidaa, S.

2011-10-01

In achieving a high cadence and whole Sun coverage required of them, Doppler imagers such as HMI/SDO and MDI/SOHO necessarily forgo certain intricacies associated with magnetic and velocity field interactions, which require high (spectral) resolution spectropolarimetry for their accurate measurements with straightforward derivation of physical quantities (or observables). Magnetic field modified wave evolution, due to much reduced acoustic cut-off frequencies, in inclined field regions is one such situation. We first show, using a high cadence imaging spectropolarimetric observations made with IBIS instrument at NSO/Sac Peak, that significant contributions to seismically measured travel times arise from the line formation layers. We then present a comparative study of time-distance helioseismic measurements made over three sunspot regions using HMI and AIA (1600 A and 1700 A) data, which provide oscillation signals from three different heights. We bring out clear signals of height dependent wave phases and hence height dependent travel times. We further show that such signatures, from their differing contributions in one way travel times (in- or out-going wave travel times), could explain a significant part of the discrepancies between time-distance and other local helioseismic measurements and inferences.

45 CFR 155.1040 - Transparency in coverage.

Code of Federal Regulations, 2012 CFR

2012-10-01

....1040 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS EXCHANGE ESTABLISHMENT STANDARDS AND OTHER RELATED STANDARDS UNDER THE AFFORDABLE CARE ACT Exchange Functions: Certification of Qualified Health Plans § 155.1040 Transparency in coverage. (a) General...

The role of fMRI in cognitive neuroscience: where do we stand?

PubMed

Poldrack, Russell A

2008-04-01

Functional magnetic resonance imaging (fMRI) has quickly become the most prominent tool in cognitive neuroscience. In this article, I outline some of the limits on the kinds of inferences that can be supported by fMRI, focusing particularly on reverse inference, in which the engagement of specific mental processes is inferred from patterns of brain activation. Although this form of inference is weak, newly developed methods from the field of machine learning offer the potential to formalize and strengthen reverse inferences. I conclude by discussing the increasing presence of fMRI results in the popular media and the ethical implications of the increasing predictive power of fMRI.

Novel Cyclosilazane-Type Silicon Precursor and Two-Step Plasma for Plasma-Enhanced Atomic Layer Deposition of Silicon Nitride.

PubMed

Park, Jae-Min; Jang, Se Jin; Lee, Sang-Ick; Lee, Won-Jun

2018-03-14

We designed cyclosilazane-type silicon precursors and proposed a three-step plasma-enhanced atomic layer deposition (PEALD) process to prepare silicon nitride films with high quality and excellent step coverage. The cyclosilazane-type precursor, 1,3-di-isopropylamino-2,4-dimethylcyclosilazane (CSN-2), has a closed ring structure for good thermal stability and high reactivity. CSN-2 showed thermal stability up to 450 °C and a sufficient vapor pressure of 4 Torr at 60 °C. The energy for the chemisorption of CSN-2 on the undercoordinated silicon nitride surface as calculated by density functional theory method was -7.38 eV. The PEALD process window was between 200 and 500 °C, with a growth rate of 0.43 Å/cycle. The best film quality was obtained at 500 °C, with hydrogen impurity of ∼7 atom %, oxygen impurity less than 2 atom %, low wet etching rate, and excellent step coverage of ∼95%. At 300 °C and lower temperatures, the wet etching rate was high especially at the lower sidewall of the trench pattern. We introduced the three-step PEALD process to improve the film quality and the step coverage on the lower sidewall. The sequence of the three-step PEALD process consists of the CSN-2 feeding step, the NH 3 /N 2 plasma step, and the N 2 plasma step. The H radicals in NH 3 /N 2 plasma efficiently remove the ligands from the precursor, and the N 2 plasma after the NH 3 plasma removes the surface hydrogen atoms to activate the adsorption of the precursor. The films deposited at 300 °C using the novel precursor and the three-step PEALD process showed a significantly improved step coverage of ∼95% and an excellent wet etching resistance at the lower sidewall, which is only twice as high as that of the blanket film prepared by low-pressure chemical vapor deposition.

Survey Of High Speed Test Techniques

NASA Astrophysics Data System (ADS)

Gheewala, Tushar

1988-02-01

The emerging technologies for the characterization and production testing of high-speed devices and integrated circuits are reviewed. The continuing progress in the field of semiconductor technologies will, in the near future, demand test techniques to test 10ps to lOOps gate delays, 10 GHz to 100 GHz analog functions and 10,000 to 100,000 gates on a single chip. Clearly, no single test technique would provide a cost-effective answer to all the above demands. A divide-and-conquer approach based on a judicial selection of parametric, functional and high-speed tests will be required. In addition, design-for-test methods need to be pursued which will include on-chip test electronics as well as circuit techniques that minimize the circuit performance sensitivity to allowable process variations. The electron and laser beam based test technologies look very promising and may provide the much needed solutions to not only the high-speed test problem but also to the need for high levels of fault coverage during functional testing.

Deducing Electron Properties from Hard X-Ray Observations

NASA Technical Reports Server (NTRS)

Kontar, E. P.; Brown, J. C.; Emslie, A. G.; Hajdas, W.; Holman, G. D.; Hurford, G. J.; Kasparova, J.; Mallik, P. C. V.; Massone, A. M.; McConnell, M. L.;

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

PubMed

Andrews, Tallulah; Meader, Stephen; Vulto-van Silfhout, Anneke; Taylor, Avigail; Steinberg, Julia; Hehir-Kwa, Jayne; Pfundt, Rolph; de Leeuw, Nicole; de Vries, Bert B A; Webber, Caleb

2015-03-01

Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Impaired self-agency inferences in schizophrenia: The role of cognitive capacity and causal reasoning style.

PubMed

Prikken, M; van der Weiden, A; Kahn, R S; Aarts, H; van Haren, N E M

2018-01-01

The sense of self-agency, i.e., experiencing oneself as the cause of one's own actions, is impaired in patients with schizophrenia. Normally, inferences of self-agency are enhanced when actual outcomes match with pre-activated outcome information, where this pre-activation can result from explicitly set goals (i.e., goal-based route) or implicitly primed outcome information (i.e., prime-based route). Previous research suggests that patients show specific impairments in the prime-based route, implicating that they do not rely on matches between implicitly available outcome information and actual action-outcomes when inferring self-agency. The question remains: Why? Here, we examine whether neurocognitive functioning and self-serving bias (SSB) may explain abnormalities in patients' agency inferences. Thirty-six patients and 36 healthy controls performed a commonly used agency inference task to measure goal- and prime-based self-agency inferences. Neurocognitive functioning was assessed with the Brief Assessment of Cognition in Schizophrenia (BACS) and the SSB was assessed with the Internal Personal and Situational Attributions Questionnaire. Results showed a substantial smaller effect of primed outcome information on agency experiences in patients compared with healthy controls. Whereas patients and controls differed on BACS and marginally on SSB scores, these differences were not related to patients' impairments in prime-based agency inferences. Patients showed impairments in prime-based agency inferences, thereby replicating previous studies. This finding could not be explained by cognitive dysfunction or SSB. Results are discussed in the context of the recent surge to understand and examine deficits in agency experiences in schizophrenia. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Time-varying coupling functions: Dynamical inference and cause of synchronization transitions

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav

2017-02-01

Interactions in nature can be described by their coupling strength, direction of coupling, and coupling function. The coupling strength and directionality are relatively well understood and studied, at least for two interacting systems; however, there can be a complexity in the interactions uniquely dependent on the coupling functions. Such a special case is studied here: synchronization transition occurs only due to the time variability of the coupling functions, while the net coupling strength is constant throughout the observation time. To motivate the investigation, an example is used to present an analysis of cross-frequency coupling functions between delta and alpha brain waves extracted from the electroencephalography recording of a healthy human subject in a free-running resting state. The results indicate that time-varying coupling functions are a reality for biological interactions. A model of phase oscillators is used to demonstrate and detect the synchronization transition caused by the varying coupling functions during an invariant coupling strength. The ability to detect this phenomenon is discussed with the method of dynamical Bayesian inference, which was able to infer the time-varying coupling functions. The form of the coupling function acts as an additional dimension for the interactions, and it should be taken into account when detecting biological or other interactions from data.

Inference of a Nonlinear Stochastic Model of the Cardiorespiratory Interaction

NASA Astrophysics Data System (ADS)

Smelyanskiy, V. N.; Luchinsky, D. G.; Stefanovska, A.; McClintock, P. V.

2005-03-01

We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.

Identification of mutated driver pathways in cancer using a multi-objective optimization model.

PubMed

Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

2016-05-01

New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.

ISRNA: an integrative online toolkit for short reads from high-throughput sequencing data.

PubMed

Luo, Guan-Zheng; Yang, Wei; Ma, Ying-Ke; Wang, Xiu-Jie

2014-02-01

Integrative Short Reads NAvigator (ISRNA) is an online toolkit for analyzing high-throughput small RNA sequencing data. Besides the high-speed genome mapping function, ISRNA provides statistics for genomic location, length distribution and nucleotide composition bias analysis of sequence reads. Number of reads mapped to known microRNAs and other classes of short non-coding RNAs, coverage of short reads on genes, expression abundance of sequence reads as well as some other analysis functions are also supported. The versatile search functions enable users to select sequence reads according to their sub-sequences, expression abundance, genomic location, relationship to genes, etc. A specialized genome browser is integrated to visualize the genomic distribution of short reads. ISRNA also supports management and comparison among multiple datasets. ISRNA is implemented in Java/C++/Perl/MySQL and can be freely accessed at http://omicslab.genetics.ac.cn/ISRNA/.

Phylogenomics from Whole Genome Sequences Using aTRAM.

PubMed

Allen, Julie M; Boyd, Bret; Nguyen, Nam-Phuong; Vachaspati, Pranjal; Warnow, Tandy; Huang, Daisie I; Grady, Patrick G S; Bell, Kayce C; Cronk, Quentin C B; Mugisha, Lawrence; Pittendrigh, Barry R; Leonardi, M Soledad; Reed, David L; Johnson, Kevin P

2017-09-01

Novel sequencing technologies are rapidly expanding the size of data sets that can be applied to phylogenetic studies. Currently the most commonly used phylogenomic approaches involve some form of genome reduction. While these approaches make assembling phylogenomic data sets more economical for organisms with large genomes, they reduce the genomic coverage and thereby the long-term utility of the data. Currently, for organisms with moderate to small genomes ($<$1000 Mbp) it is feasible to sequence the entire genome at modest coverage ($10-30\\times$). Computational challenges for handling these large data sets can be alleviated by assembling targeted reads, rather than assembling the entire genome, to produce a phylogenomic data matrix. Here we demonstrate the use of automated Target Restricted Assembly Method (aTRAM) to assemble 1107 single-copy ortholog genes from whole genome sequencing of sucking lice (Anoplura) and out-groups. We developed a pipeline to extract exon sequences from the aTRAM assemblies by annotating them with respect to the original target protein. We aligned these protein sequences with the inferred amino acids and then performed phylogenetic analyses on both the concatenated matrix of genes and on each gene separately in a coalescent analysis. Finally, we tested the limits of successful assembly in aTRAM by assembling 100 genes from close- to distantly related taxa at high to low levels of coverage.Both the concatenated analysis and the coalescent-based analysis produced the same tree topology, which was consistent with previously published results and resolved weakly supported nodes. These results demonstrate that this approach is successful at developing phylogenomic data sets from raw genome sequencing reads. Further, we found that with coverages above $5-10\\times$, aTRAM was successful at assembling 80-90% of the contigs for both close and distantly related taxa. As sequencing costs continue to decline, we expect full genome sequencing will become more feasible for a wider array of organisms, and aTRAM will enable mining of these genomic data sets for an extensive variety of applications, including phylogenomics. [aTRAM; gene assembly; genome sequencing; phylogenomics.]. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

EGRINs (Environmental Gene Regulatory Influence Networks) in Rice That Function in the Response to Water Deficit, High Temperature, and Agricultural Environments[OPEN

PubMed Central

Hafemeister, Christoph; Nicotra, Adrienne B.; Jagadish, S.V. Krishna; Bonneau, Richard; Purugganan, Michael

2016-01-01

Environmental gene regulatory influence networks (EGRINs) coordinate the timing and rate of gene expression in response to environmental signals. EGRINs encompass many layers of regulation, which culminate in changes in accumulated transcript levels. Here, we inferred EGRINs for the response of five tropical Asian rice (Oryza sativa) cultivars to high temperatures, water deficit, and agricultural field conditions by systematically integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and the occurrence of known cis-regulatory elements. First, we identified 5447 putative target genes for 445 transcription factors (TFs) by connecting TFs with genes harboring known cis-regulatory motifs in nucleosome-free regions proximal to their transcriptional start sites. We then used network component analysis to estimate the regulatory activity for each TF based on the expression of its putative target genes. Finally, we inferred an EGRIN using the estimated transcription factor activity (TFA) as the regulator. The EGRINs include regulatory interactions between 4052 target genes regulated by 113 TFs. We resolved distinct regulatory roles for members of the heat shock factor family, including a putative regulatory connection between abiotic stress and the circadian clock. TFA estimation using network component analysis is an effective way of incorporating multiple genome-scale measurements into network inference. PMID:27655842

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods and Challenges

PubMed Central

Zhou, Weiqiang; Sherwood, Ben; Ji, Hongkai

2017-01-01

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data. PMID:28076869

Improved orthologous databases to ease protozoan targets inference.

PubMed

Kotowski, Nelson; Jardim, Rodrigo; Dávila, Alberto M R

2015-09-29

Homology inference helps on identifying similarities, as well as differences among organisms, which provides a better insight on how closely related one might be to another. In addition, comparative genomics pipelines are widely adopted tools designed using different bioinformatics applications and algorithms. In this article, we propose a methodology to build improved orthologous databases with the potential to aid on protozoan target identification, one of the many tasks which benefit from comparative genomics tools. Our analyses are based on OrthoSearch, a comparative genomics pipeline originally designed to infer orthologs through protein-profile comparison, supported by an HMM, reciprocal best hits based approach. Our methodology allows OrthoSearch to confront two orthologous databases and to generate an improved new one. Such can be later used to infer potential protozoan targets through a similarity analysis against the human genome. The protein sequences of Cryptosporidium hominis, Entamoeba histolytica and Leishmania infantum genomes were comparatively analyzed against three orthologous databases: (i) EggNOG KOG, (ii) ProtozoaDB and (iii) Kegg Orthology (KO). That allowed us to create two new orthologous databases, "KO + EggNOG KOG" and "KO + EggNOG KOG + ProtozoaDB", with 16,938 and 27,701 orthologous groups, respectively. Such new orthologous databases were used for a regular OrthoSearch run. By confronting "KO + EggNOG KOG" and "KO + EggNOG KOG + ProtozoaDB" databases and protozoan species we were able to detect the following total of orthologous groups and coverage (relation between the inferred orthologous groups and the species total number of proteins): Cryptosporidium hominis: 1,821 (11 %) and 3,254 (12 %); Entamoeba histolytica: 2,245 (13 %) and 5,305 (19 %); Leishmania infantum: 2,702 (16 %) and 4,760 (17 %). Using our HMM-based methodology and the largest created orthologous database, it was possible to infer 13 orthologous groups which represent potential protozoan targets; these were found because of our distant homology approach. We also provide the number of species-specific, pair-to-pair and core groups from such analyses, depicted in Venn diagrams. The orthologous databases generated by our HMM-based methodology provide a broader dataset, with larger amounts of orthologous groups when compared to the original databases used as input. Those may be used for several homology inference analyses, annotation tasks and protozoan targets identification.

Transcriptional network inference from functional similarity and expression data: a global supervised approach.

PubMed

Ambroise, Jérôme; Robert, Annie; Macq, Benoit; Gala, Jean-Luc

2012-01-06

An important challenge in system biology is the inference of biological networks from postgenomic data. Among these biological networks, a gene transcriptional regulatory network focuses on interactions existing between transcription factors (TFs) and and their corresponding target genes. A large number of reverse engineering algorithms were proposed to infer such networks from gene expression profiles, but most current methods have relatively low predictive performances. In this paper, we introduce the novel TNIFSED method (Transcriptional Network Inference from Functional Similarity and Expression Data), that infers a transcriptional network from the integration of correlations and partial correlations of gene expression profiles and gene functional similarities through a supervised classifier. In the current work, TNIFSED was applied to predict the transcriptional network in Escherichia coli and in Saccharomyces cerevisiae, using datasets of 445 and 170 affymetrix arrays, respectively. Using the area under the curve of the receiver operating characteristics and the F-measure as indicators, we showed the predictive performance of TNIFSED to be better than unsupervised state-of-the-art methods. TNIFSED performed slightly worse than the supervised SIRENE algorithm for the target genes identification of the TF having a wide range of yet identified target genes but better for TF having only few identified target genes. Our results indicate that TNIFSED is complementary to the SIRENE algorithm, and particularly suitable to discover target genes of "orphan" TFs.

Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota.

PubMed

Raguideau, Sébastien; Plancade, Sandra; Pons, Nicolas; Leclerc, Marion; Laroche, Béatrice

2016-12-01

Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in the gut or in other ecosystems.

Functional neuroanatomy of intuitive physical inference

PubMed Central

Mikhael, John G.; Tenenbaum, Joshua B.; Kanwisher, Nancy

2016-01-01

To engage with the world—to understand the scene in front of us, plan actions, and predict what will happen next—we must have an intuitive grasp of the world’s physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events—a “physics engine” in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general “multiple demand” system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action. PMID:27503892

Functional neuroanatomy of intuitive physical inference.

PubMed

Fischer, Jason; Mikhael, John G; Tenenbaum, Joshua B; Kanwisher, Nancy

2016-08-23

To engage with the world-to understand the scene in front of us, plan actions, and predict what will happen next-we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events-a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action.

Functional phylogenomics analysis of bacteria and archaea using consistent genome annotation with UniFam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk

2014-10-09

To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accuratemore » comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.« less

Explicit-Duration Hidden Markov Model Inference of UP-DOWN States from Continuous Signals

PubMed Central

McFarland, James M.; Hahn, Thomas T. G.; Mehta, Mayank R.

2011-01-01

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics. PMID:21738730

Fostering Social Cognition through an Imitation- and Synchronization-Based Dance/Movement Intervention in Adults with Autism Spectrum Disorder: A Controlled Proof-of-Concept Study.

PubMed

Koehne, Svenja; Behrends, Andrea; Fairhurst, Merle T; Dziobek, Isabel

2016-01-01

Since social cognition is impaired in individuals with autism spectrum disorder (ASD), this study aimed at establishing the efficacy of a newly developed imitation- and synchronization-based dance/movement intervention (SI-DMI) in fostering emotion inference and empathic feelings (emotional reaction to feelings of others) in adults with high-functioning ASD. Fifty-five adults with ASD (IQ ≥85) who were blinded to the aim of the study were assigned to receive either 10 weeks of a dance/movement intervention focusing on interpersonal movement imitation and synchronization (SI-DMI, n = 27) or a control movement intervention (CMI, n = 24) focusing on individual motor coordination (2 participants from each group declined before baseline testing). The primary outcome measure was the objective Multifaceted Empathy Test targeting emotion inference and empathic feelings. Secondary outcomes were scores on the self-rated Interpersonal Reactivity Index. The well-established automatic imitation task and synchronization finger-tapping task were used to quantify effects on imitation and synchronization functions, complemented by the more naturalistic Assessment of Spontaneous Interaction in Movement. Intention-to-treat analyses revealed that from baseline to 3 months, patients treated with SI-DMI showed a significantly larger improvement in emotion inference (d = 0.58), but not empathic feelings, than those treated with CMI (d = -0.04). On the close generalization level, SI-DMI increased synchronization skills and imitation tendencies, as well as whole-body imitation/synchronization and movement reciprocity/dialogue, compared to CMI. SI-DMI can be successful in promoting emotion inference in adults with ASD and warrants further investigation. © 2015 S. Karger AG, Basel.

NONPARAMETRIC MANOVA APPROACHES FOR NON-NORMAL MULTIVARIATE OUTCOMES WITH MISSING VALUES

PubMed Central

He, Fanyin; Mazumdar, Sati; Tang, Gong; Bhatia, Triptish; Anderson, Stewart J.; Dew, Mary Amanda; Krafty, Robert; Nimgaonkar, Vishwajit; Deshpande, Smita; Hall, Martica; Reynolds, Charles F.

2017-01-01

Between-group comparisons often entail many correlated response variables. The multivariate linear model, with its assumption of multivariate normality, is the accepted standard tool for these tests. When this assumption is violated, the nonparametric multivariate Kruskal-Wallis (MKW) test is frequently used. However, this test requires complete cases with no missing values in response variables. Deletion of cases with missing values likely leads to inefficient statistical inference. Here we extend the MKW test to retain information from partially-observed cases. Results of simulated studies and analysis of real data show that the proposed method provides adequate coverage and superior power to complete-case analyses. PMID:29416225

CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA.

PubMed

Kang, Shuli; Li, Qingjiao; Chen, Quan; Zhou, Yonggang; Park, Stacy; Lee, Gina; Grimes, Brandon; Krysan, Kostyantyn; Yu, Min; Wang, Wei; Alber, Frank; Sun, Fengzhu; Dubinett, Steven M; Li, Wenyuan; Zhou, Xianghong Jasmine

2017-03-24

We propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. CancerLocator outperforms two established multi-class classification methods on simulations and real data, even with the low proportion of tumor-derived DNA in the cell-free DNA scenarios. CancerLocator also achieves promising results on patient plasma samples with low DNA methylation sequencing coverage.

Hierarchical Scaffolding With Bambus

PubMed Central

Pop, Mihai; Kosack, Daniel S.; Salzberg, Steven L.

2004-01-01

The output of a genome assembler generally comprises a collection of contiguous DNA sequences (contigs) whose relative placement along the genome is not defined. A procedure called scaffolding is commonly used to order and orient these contigs using paired read information. This ordering of contigs is an essential step when finishing and analyzing the data from a whole-genome shotgun project. Most recent assemblers include a scaffolding module; however, users have little control over the scaffolding algorithm or the information produced. We thus developed a general-purpose scaffolder, called Bambus, which affords users significant flexibility in controlling the scaffolding parameters. Bambus was used recently to scaffold the low-coverage draft dog genome data. Most significantly, Bambus enables the use of linking data other than that inferred from mate-pair information. For example, the sequence of a completed genome can be used to guide the scaffolding of a related organism. We present several applications of Bambus: support for finishing, comparative genomics, analysis of the haplotype structure of genomes, and scaffolding of a mammalian genome at low coverage. Bambus is available as an open-source package from our Web site. PMID:14707177

Hierarchical scaffolding with Bambus.

PubMed

Pop, Mihai; Kosack, Daniel S; Salzberg, Steven L

2004-01-01

The output of a genome assembler generally comprises a collection of contiguous DNA sequences (contigs) whose relative placement along the genome is not defined. A procedure called scaffolding is commonly used to order and orient these contigs using paired read information. This ordering of contigs is an essential step when finishing and analyzing the data from a whole-genome shotgun project. Most recent assemblers include a scaffolding module; however, users have little control over the scaffolding algorithm or the information produced. We thus developed a general-purpose scaffolder, called Bambus, which affords users significant flexibility in controlling the scaffolding parameters. Bambus was used recently to scaffold the low-coverage draft dog genome data. Most significantly, Bambus enables the use of linking data other than that inferred from mate-pair information. For example, the sequence of a completed genome can be used to guide the scaffolding of a related organism. We present several applications of Bambus: support for finishing, comparative genomics, analysis of the haplotype structure of genomes, and scaffolding of a mammalian genome at low coverage. Bambus is available as an open-source package from our Web site.

Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

PubMed

Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

2017-01-01

Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial autocorrelation in an SDM context and, by taking account of random effects, produce outputs that can better elucidate the role of covariates in predicting species occurrence. Given that it is often unclear what the drivers are behind data clumping in an empirical occurrence dataset, or indeed how geographically restricted these data are, spatially-explicit Bayesian SDMs may be the better choice when modelling the spatial distribution of target species.

GENIUS: web server to predict local gene networks and key genes for biological functions.

PubMed

Puelma, Tomas; Araus, Viviana; Canales, Javier; Vidal, Elena A; Cabello, Juan M; Soto, Alvaro; Gutiérrez, Rodrigo A

2017-03-01

GENIUS is a user-friendly web server that uses a novel machine learning algorithm to infer functional gene networks focused on specific genes and experimental conditions that are relevant to biological functions of interest. These functions may have different levels of complexity, from specific biological processes to complex traits that involve several interacting processes. GENIUS also enriches the network with new genes related to the biological function of interest, with accuracies comparable to highly discriminative Support Vector Machine methods. GENIUS currently supports eight model organisms and is freely available for public use at http://networks.bio.puc.cl/genius . genius.psbl@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods

NASA Technical Reports Server (NTRS)

Erickson, Gary E.

2010-01-01

Response surface methodology was used to estimate the longitudinal stage separation aerodynamic characteristics of a generic, bimese, winged multi-stage launch vehicle configuration at supersonic speeds in the NASA LaRC Unitary Plan Wind Tunnel. The Mach 3 staging was dominated by shock wave interactions between the orbiter and booster vehicles throughout the relative spatial locations of interest. The inference space was partitioned into several contiguous regions within which the separation aerodynamics were presumed to be well-behaved and estimable using central composite designs capable of fitting full second-order response functions. The underlying aerodynamic response surfaces of the booster vehicle in belly-to-belly proximity to the orbiter vehicle were estimated using piecewise-continuous lower-order polynomial functions. The quality of fit and prediction capabilities of the empirical models were assessed in detail, and the issue of subspace boundary discontinuities was addressed. Augmenting the central composite designs to full third-order using computer-generated D-optimality criteria was evaluated. The usefulness of central composite designs, the subspace sizing, and the practicality of fitting lower-order response functions over a partitioned inference space dominated by highly nonlinear and possibly discontinuous shock-induced aerodynamics are discussed.

45 CFR 155.430 - Termination of coverage.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS EXCHANGE ESTABLISHMENT STANDARDS AND OTHER RELATED STANDARDS UNDER THE AFFORDABLE CARE ACT Exchange Functions in the Individual Market: Enrollment in Qualified Health Plans § 155.430 Termination of coverage...

45 CFR 155.430 - Termination of coverage.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS EXCHANGE ESTABLISHMENT STANDARDS AND OTHER RELATED STANDARDS UNDER THE AFFORDABLE CARE ACT Exchange Functions in the Individual Market: Enrollment in Qualified Health Plans § 155.430 Termination of coverage...

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.