171 research outputs found
Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo
We use data from the second science run of the LIGO gravitational-wave
detectors to search for the gravitational waves from primordial black hole
(PBH) binary coalescence with component masses in the range 0.2--.
The analysis requires a signal to be found in the data from both LIGO
observatories, according to a set of coincidence criteria. No inspiral signals
were found. Assuming a spherical halo with core radius 5 kpc extending to 50
kpc containing non-spinning black holes with masses in the range 0.2--, we place an observational upper limit on the rate of PBH coalescence
of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.
Search for Standard Model Higgs Boson Production in Association with a W Boson using a Neural Network
We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 inverse fb. We select events consistent with a signature of a single charged lepton, missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to $150 GeV/c^2, respectively.We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions (pp̅ →W±H→ℓνbb̅ ) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 fb-1. We select events consistent with a signature of a single charged lepton (e±/μ±), missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to 150 GeV/c2, respectively.Peer reviewe
Multi-messenger observations of a binary neutron star merger
On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
Harnessing learning biases is essential for applying social learning in conservation
Social learning can influence how animals respond to anthropogenic changes in the environment, determining whether animals survive novel threats and exploit novel resources or produce maladaptive behaviour and contribute to human-wildlife conflict. Predicting where social learning will occur and manipulating its use are, therefore, important in conservation, but doing so is not straightforward. Learning is an inherently biased process that has been shaped by natural selection to prioritize important information and facilitate its efficient uptake. In this regard, social learning is no different from other learning processes because it too is shaped by perceptual filters, attentional biases and learning constraints that can differ between habitats, species, individuals and contexts. The biases that constrain social learning are not understood well enough to accurately predict whether or not social learning will occur in many situations, which limits the effective use of social learning in conservation practice. Nevertheless, we argue that by tapping into the biases that guide the social transmission of information, the conservation applications of social learning could be improved. We explore the conservation areas where social learning is highly relevant and link them to biases in the cues and contexts that shape social information use. The resulting synthesis highlights many promising areas for collaboration between the fields and stresses the importance of systematic reviews of the evidence surrounding social learning practices.BBSRC David Phillips Fellowship (BB/H021817/1
The effect of psychological interventions on anxiety and depression in cancer patients: results of two meta-analyses
Metagenomics of the Deep Mediterranean, a Warm Bathypelagic Habitat
BACKGROUND: Metagenomics is emerging as a powerful method to study the function and physiology of the unexplored microbial biosphere, and is causing us to re-evaluate basic precepts of microbial ecology and evolution. Most marine metagenomic analyses have been nearly exclusively devoted to photic waters. METHODOLOGY/PRINCIPAL FINDINGS: We constructed a metagenomic fosmid library from 3,000 m-deep Mediterranean plankton, which is much warmer (approximately 14 degrees C) than waters of similar depth in open oceans (approximately 2 degrees C). We analyzed the library both by phylogenetic screening based on 16S rRNA gene amplification from clone pools and by sequencing both insert extremities of ca. 5,000 fosmids. Genome recruitment strategies showed that the majority of high scoring pairs corresponded to genomes from Rhizobiales within the Alphaproteobacteria, Cenarchaeum symbiosum, Planctomycetes, Acidobacteria, Chloroflexi and Gammaproteobacteria. We have found a community structure similar to that found in the aphotic zone of the Pacific. However, the similarities were significantly higher to the mesopelagic (500-700 m deep) in the Pacific than to the single 4000 m deep sample studied at this location. Metabolic genes were mostly related to catabolism, transport and degradation of complex organic molecules, in agreement with a prevalent heterotrophic lifestyle for deep-sea microbes. However, we observed a high percentage of genes encoding dehydrogenases and, among them, cox genes, suggesting that aerobic carbon monoxide oxidation may be important in the deep ocean as an additional energy source. CONCLUSIONS/SIGNIFICANCE: The comparison of metagenomic libraries from the deep Mediterranean and the Pacific ALOHA water column showed that bathypelagic Mediterranean communities resemble more mesopelagic communities in the Pacific, and suggests that, in the absence of light, temperature is a major stratifying factor in the oceanic water column, overriding pressure at least over 4000 m deep. Several chemolithotrophic metabolic pathways could supplement organic matter degradation in this most depleted habitat
Neural Mechanisms of Human Perceptual Learning: Electrophysiological Evidence for a Two-Stage Process
Artículo de publicación ISIBackground: Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed.
Methodology/Principal Findings: We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing.This research was supported by CONICYT doctoral grant to C.M.H. and by an ECOS-Sud/CONICYT grant C08S02 and FONDECYT 1090612 grant to D.C.
and F.A
Measurement of b hadron lifetimes in exclusive decays containing a J/psi in p-pbar collisions at sqrt(s)=1.96TeV
We report on a measurement of -hadron lifetimes in the fully reconstructed
decay modes B^+ -->J/Psi K+, B^0 --> J/Psi K*, B^0 --> J/Psi Ks, and Lambda_b
--> J/Psi Lambda using data corresponding to an integrated luminosity of 4.3
, collected by the CDF II detector at the Fermilab Tevatron. The
measured lifetimes are B^+ = , B^0 = and Lambda_b = . The lifetime ratios are B^+/B^0 = and Lambda_b/B^0 = . These are the most precise determinations
of these quantities from a single experiment.Comment: revised version. accepted for PRL publicatio
Measurement of ZZ production in leptonic final states at {\surd}s of 1.96 TeV at CDF
In this paper we present a precise measurement of the total ZZ production
cross section in pp collisions at {\surd}s= 1.96 TeV, using data collected with
the CDF II detector corresponding to an integrated luminosity of approximately
6 fb-1. The result is obtained by combining separate measurements in the
four-charged (lll'l'), and two-charged-lepton and two-neutral-lepton (llvv)
decay modes of the Z. The combined measured cross section for pp {\to} ZZ is
1.64^(+0.44)_(-0.38) pb. This is the most precise measurement of the ZZ
production cross section in 1.96 TeV pp collisions to date.Comment: submitted to Phys. Rev. Let
- …
