5,229 research outputs found
Search for bâu transitions in B±â[KâϱÏ0]DK± decays
We present a study of the decays B±âDK± with D mesons reconstructed in the K+Ï-Ï0 or K-Ï+Ï0 final states, where D indicates a D0 or a DÌ
0 meson. Using a sample of 474Ă106 BBÌ
pairs collected with the BABAR detector at the PEP-II asymmetric-energy e+e- collider at SLAC, we measure the ratios R±âĄÎ(B±â[KâϱÏ0]DK±)/Î(B±â[K±ÏâÏ0]DK±). We obtain R+=(5-10+12(stat)-4+2(syst))Ă10-3 and R-=(12-10+12(stat)-5+3(syst))Ă10-3, from which we extract the upper limits at 90% probability: R+<23Ă10-3 and R-<29Ă10-3. Using these measurements, we obtain an upper limit for the ratio rB of the magnitudes of the bâu and bâc amplitudes rB<0.13 at 90% probability
Action Intentions, Predictive Processing, and Mind Reading: Turning Goalkeepers Into Penalty Killers
The key to action control is oneâs ability to adequately predict the consequences of oneâs actions. Predictive processing theories assume that forward models enable rapid âpreplayâ to assess the match between predicted and intended action effects. Here we propose the novel hypothesis that âreadingâ anotherâs action intentions requires a rich forward model of that agentâs action. Such a forward model can be obtained and enriched through learning by either practice or simulation. Based on this notion, we ran a series of studies on soccer goalkeepers and novices, who predicted the intended direction of penalties being kicked at them in a computerized penalty-reading task. In line with hypotheses, extensive practice in penalty kicking improved performance in penalty reading among goalkeepers who had extensive prior experience in penalty blocking but not in penalty kicking. A robust benefit in penalty reading did not result from practice in kinesthetic motor imagery of penalty kicking in novice participants. To test whether goalkeepers actually use such penalty-kicking imagery in penalty reading, we trained a machine-learning classifier on multivariate fMRI activity patterns to distinguish motor-imagery-related from attention-related strategies during a penalty-imagery training task. We then applied that classifier to fMRI data related to a separate penalty-reading task and showed that 2/3 of all correctly read penalty kicks were classified as engaging the motor-imagery circuit rather than merely the attention circuit. This study provides initial evidence that, in order to read our opponentâs action intention, it helps to observe their action kinematics, and use our own forward model to predict the sensory consequences of âourâ penalty kick if we were to produce these action kinematics ourselves. In sum, it takes practice as a penalty kicker to become a penalty killer
Rigorous mean-field dynamics of lattice bosons: Quenches from the Mott insulator
We provide a rigorous derivation of Gutzwiller mean-field dynamics for
lattice bosons, showing that it is exact on fully connected lattices. We apply
this formalism to quenches in the interaction parameter from the Mott insulator
to the superfluid state. Although within mean-field the Mott insulator is a
steady state, we show that a dynamical critical interaction exists, such
that for final interaction parameter the Mott insulator is
exponentially unstable towards emerging long-range superfluid order, whereas
for the Mott insulating state is stable. We discuss the implications
of this prediction for finite-dimensional systems.Comment: 6 pages, 3 figures, published versio
Large-Scale Sleep Condition Analysis Using Selfies from Social Media
Sleep condition is closely related to an individual's health. Poor sleep
conditions such as sleep disorder and sleep deprivation affect one's daily
performance, and may also cause many chronic diseases. Many efforts have been
devoted to monitoring people's sleep conditions. However, traditional
methodologies require sophisticated equipment and consume a significant amount
of time. In this paper, we attempt to develop a novel way to predict
individual's sleep condition via scrutinizing facial cues as doctors would.
Rather than measuring the sleep condition directly, we measure the
sleep-deprived fatigue which indirectly reflects the sleep condition. Our
method can predict a sleep-deprived fatigue rate based on a selfie provided by
a subject. This rate is used to indicate the sleep condition. To gain deeper
insights of human sleep conditions, we collected around 100,000 faces from
selfies posted on Twitter and Instagram, and identified their age, gender, and
race using automatic algorithms. Next, we investigated the sleep condition
distributions with respect to age, gender, and race. Our study suggests among
the age groups, fatigue percentage of the 0-20 youth and adolescent group is
the highest, implying that poor sleep condition is more prevalent in this age
group. For gender, the fatigue percentage of females is higher than that of
males, implying that more females are suffering from sleep issues than males.
Among ethnic groups, the fatigue percentage in Caucasian is the highest
followed by Asian and African American.Comment: 2017 International Conference on Social Computing,
Behavioral-Cultural Modeling, & Prediction and Behavior Representation in
Modeling and Simulation (SBP-BRiMS'17
Genetical Genomics Reveals Large Scale Genotype-By-Environment Interactions in Arabidopsis thaliana
One of the major goals of quantitative genetics is to unravel the complex interactions between molecular genetic factors and the environment. The effects of these genotype-by-environment interactions also affect and cause variation in gene expression. The regulatory loci responsible for this variation can be found by genetical genomics that involves the mapping of quantitative trait loci (QTLs) for gene expression traits also called expression-QTL (eQTLs). Most genetical genomics experiments published so far, are performed in a single environment and hence do not allow investigation of the role of genotype-by-environment interactions. Furthermore, most studies have been done in a steady state environment leading to acclimated expression patterns. However a response to the environment or change therein can be highly plastic and possibly lead to more and larger differences between genotypes. Here we present a genetical genomics study on 120 Arabidopsis thaliana, Landsberg erecta Ă Cape Verde Islands, recombinant inbred lines (RILs) in active response to the environment by treating them with 3 h of shade. The results of this experiment are compared to a previous study on seedlings of the same RILs from a steady state environment. The combination of two highly different conditions but exactly the same RILs with a fixed genetic variation showed the large role of genotype-by-environment interactions on gene expression levels. We found environment-dependent hotspots of transcript regulation. The major hotspot was confirmed by the expression profile of a near isogenic line. Our combined analysis leads us to propose CSN5A, a COP9 signalosome component, as a candidate regulator for the gene expression response to shade
Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications
This paper presents a novel pairwise constraint propagation approach by
decomposing the challenging constraint propagation problem into a set of
independent semi-supervised learning subproblems which can be solved in
quadratic time using label propagation based on k-nearest neighbor graphs.
Considering that this time cost is proportional to the number of all possible
pairwise constraints, our approach actually provides an efficient solution for
exhaustively propagating pairwise constraints throughout the entire dataset.
The resulting exhaustive set of propagated pairwise constraints are further
used to adjust the similarity matrix for constrained spectral clustering. Other
than the traditional constraint propagation on single-source data, our approach
is also extended to more challenging constraint propagation on multi-source
data where each pairwise constraint is defined over a pair of data points from
different sources. This multi-source constraint propagation has an important
application to cross-modal multimedia retrieval. Extensive results have shown
the superior performance of our approach.Comment: The short version of this paper appears as oral paper in ECCV 201
A multi-parent recombinant inbred line population of C. elegans allows identification of novel QTLs for complex life history traits
Background
The nematode Caenorhabditis elegans has been extensively used to explore the relationships between complex traits, genotypes, and environments. Complex traits can vary across different genotypes of a species, and the genetic regulators of trait variation can be mapped on the genome using quantitative trait locus (QTL) analysis of recombinant inbred lines (RILs) derived from genetically and phenotypically divergent parents. Most RILs have been derived from crossing two parents from globally distant locations. However, the genetic diversity between local C. elegans populations can be as diverse as between global populations and could thus provide means of identifying genetic variation associated with complex traits relevant on a broader scale.
Results
To investigate the effect of local genetic variation on heritable traits, we developed a new RIL population derived from 4 parental wild isolates collected from 2 closely located sites in France: Orsay and Santeuil. We crossed these 4 genetically diverse parental isolates to generate a population of 200 multi-parental RILs and used RNA-seq to obtain sequence polymorphisms identifying almost 9000 SNPs variable between the 4 genotypes with an average spacing of 11 kb, doubling the mapping resolution relative to currently available RIL panels for many loci. The SNPs were used to construct a genetic map to facilitate QTL analysis. We measured life history traits such as lifespan, stress resistance, developmental speed, and population growth in different environments, and found substantial variation for most traits. We detected multiple QTLs for most traits, including novel QTLs not found in previous QTL analysis, including those for lifespan and pathogen responses. This shows that recombining genetic variation across C. elegans populations that are in geographical close proximity provides ample variation for QTL mapping.
Conclusion
Taken together, we show that using more parents than the classical two parental genotypes to construct a RIL population facilitates the detection of QTLs and that the use of wild isolates facilitates the detection of QTLs. The use of multi-parent RIL populations can further enhance our understanding of local adaptation and life history trade-offs
Evaluating Multimedia Features and Fusion for Example-Based Event Detection
Multimedia event detection (MED) is a challenging problem because of the heterogeneous content and variable quality found in large collections of Internet videos. To study the value of multimedia features and fusion for representing and learning events from a set of example video clips, we created SESAME, a system for video SEarch with Speed and Accuracy for Multimedia Events. SESAME includes multiple bag-of-words event classifiers based on single data types: low-level visual, motion, and audio features; high-level semantic visual concepts; and automatic speech recognition. Event detection performance was evaluated for each event classifier. The performance of low-level visual and motion features was improved by the use of difference coding. The accuracy of the visual concepts was nearly as strong as that of the low-level visual features. Experiments with a number of fusion methods for combining the event detection scores from these classifiers revealed that simple fusion methods, such as arithmetic mean, perform as well as or better than other, more complex fusion methods. SESAMEâs performance in the 2012 TRECVID MED evaluation was one of the best reported
Relativistic quantum effects of Dirac particles simulated by ultracold atoms
Quantum simulation is a powerful tool to study a variety of problems in
physics, ranging from high-energy physics to condensed-matter physics. In this
article, we review the recent theoretical and experimental progress in quantum
simulation of Dirac equation with tunable parameters by using ultracold neutral
atoms trapped in optical lattices or subject to light-induced synthetic gauge
fields. The effective theories for the quasiparticles become relativistic under
certain conditions in these systems, making them ideal platforms for studying
the exotic relativistic effects. We focus on the realization of one, two, and
three dimensional Dirac equations as well as the detection of some relativistic
effects, including particularly the well-known Zitterbewegung effect and Klein
tunneling. The realization of quantum anomalous Hall effects is also briefly
discussed.Comment: 22 pages, review article in Frontiers of Physics: Proceedings on
Quantum Dynamics of Ultracold Atom
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