966 research outputs found

    Fermi Gamma-ray Imaging of a Radio Galaxy

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    The Fermi Gamma-ray Space Telescope has detected the gamma-ray glow emanating from the giant radio lobes of the radio galaxy Centaurus A. The resolved gamma-ray image shows the lobes clearly separated from the central active source. In contrast to all other active galaxies detected so far in high-energy gamma-rays, the lobe flux constitutes a considerable portion (>1/2) of the total source emission. The gamma-ray emission from the lobes is interpreted as inverse Compton scattered relic radiation from the cosmic microwave background (CMB), with additional contribution at higher energies from the infrared-to-optical extragalactic background light (EBL). These measurements provide gamma-ray constraints on the magnetic field and particle energy content in radio galaxy lobes, and a promising method to probe the cosmic relic photon fields.Comment: 27 pages, includes Supplementary Online Material; corresponding authors: C.C. Cheung, Y. Fukazawa, J. Knodlseder, L. Stawar

    Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

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    The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health

    Stress-Induced Reinstatement of Drug Seeking: 20 Years of Progress

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    In human addicts, drug relapse and craving are often provoked by stress. Since 1995, this clinical scenario has been studied using a rat model of stress-induced reinstatement of drug seeking. Here, we first discuss the generality of stress-induced reinstatement to different drugs of abuse, different stressors, and different behavioral procedures. We also discuss neuropharmacological mechanisms, and brain areas and circuits controlling stress-induced reinstatement of drug seeking. We conclude by discussing results from translational human laboratory studies and clinical trials that were inspired by results from rat studies on stress-induced reinstatement. Our main conclusions are (1) The phenomenon of stress-induced reinstatement, first shown with an intermittent footshock stressor in rats trained to self-administer heroin, generalizes to other abused drugs, including cocaine, methamphetamine, nicotine, and alcohol, and is also observed in the conditioned place preference model in rats and mice. This phenomenon, however, is stressor specific and not all stressors induce reinstatement of drug seeking. (2) Neuropharmacological studies indicate the involvement of corticotropin-releasing factor (CRF), noradrenaline, dopamine, glutamate, kappa/dynorphin, and several other peptide and neurotransmitter systems in stress-induced reinstatement. Neuropharmacology and circuitry studies indicate the involvement of CRF and noradrenaline transmission in bed nucleus of stria terminalis and central amygdala, and dopamine, CRF, kappa/dynorphin, and glutamate transmission in other components of the mesocorticolimbic dopamine system (ventral tegmental area, medial prefrontal cortex, orbitofrontal cortex, and nucleus accumbens). (3) Translational human laboratory studies and a recent clinical trial study show the efficacy of alpha-2 adrenoceptor agonists in decreasing stress-induced drug craving and stress-induced initial heroin lapse

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Observation of Bc+ →j /ψD (∗)K (∗) decays

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    A search for the decays B+c→J/ψD(*)0K+ and B+c→J/ψD(*)+K*0 is performed with data collected at the LHCb experiment corresponding to an integrated luminosity of 3 fb−1. The decays B+c→J/ψ0K+ and B+c→J/ψD*0K+ are observed for the first time, while first evidence is reported for the B+c→JψD*+K*0 and B+c→J/ψD+K*0 decays. The branching fractions of these decays are determined relative to the B+c→J/ψπ+ decay. The B+c mass is measured, using the J/ψD0K+ final state, to be 6274.28±1.40(stat)±0.32(syst) MeV/c2. This is the most precise single measurement of the B+c mass to date

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Towards a collaborative research: A case study on linking science to farmers' perceptions and knowledge on Arabica coffee pests and diseases and its management

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    The scientific community has recognized the importance of integrating farmer's perceptions and knowledge (FPK) for the development of sustainable pest and disease management strategies. However, the knowledge gap between indigenous and scientific knowledge still contributes to misidentification of plant health constraints and poor adoption of management solutions. This is particularly the case in the context of smallholder farming in developing countries. In this paper, we present a case study on coffee production in Uganda, a sector depending mostly on smallholder farming facing a simultaneous and increasing number of socio-ecological pressures. The objectives of this study were (i) to examine and relate FPK on Arabica Coffee Pests and Diseases (CPaD) to altitude and the vegetation structure of the production systems; (ii) to contrast results with perceptions from experts and (iii) to compare results with field observations, in order to identify constraints for improving the information flow between scientists and farmers. Data were acquired by means of interviews and workshops. One hundred and fifty farmer households managing coffee either at sun exposure, under shade trees or inter-cropped with bananas and spread across an altitudinal gradient were selected. Field sampling of the two most important CPaD was conducted on a subset of 34 plots. The study revealed the following findings: (i) Perceptions on CPaD with respect to their distribution across altitudes and perceived impact are partially concordant among farmers, experts and field observations (ii) There are discrepancies among farmers and experts regarding management practices and the development of CPaD issues of the previous years. (iii) Field observations comparing CPaD in different altitudes and production systems indicate ambiguity of the role of shade trees. According to the locality-specific variability in CPaD pressure as well as in FPK, the importance of developing spatially variable and relevant CPaD control practices is proposed. (Résumé d'auteur

    Comparative Analysis of Dengue and Zika Outbreaks Reveals Differences by Setting and Virus.

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    The pacific islands of Micronesia have experienced several outbreaks of mosquito-borne diseases over the past decade. In outbreaks on small islands, the susceptible population is usually well defined, and there is no co-circulation of pathogens. Because of this, analysing such outbreaks can be useful for understanding the transmission dynamics of the pathogens involved, and particularly so for yet understudied pathogens such as Zika virus. Here, we compared three outbreaks of dengue and Zika virus in two different island settings in Micronesia, the Yap Main Islands and Fais, using a mathematical model of transmission dynamics and making full use of commonalities in disease and setting between the outbreaks. We found that the estimated reproduction numbers for Zika and dengue were similar when considered in the same setting, but that, conversely, reproduction number for the same disease can vary considerably by setting. On the Yap Main Islands, we estimated a reproduction number of 8.0-16 (95% Credible Interval (CI)) for the dengue outbreak and 4.8-14 (95% CI) for the Zika outbreak, whereas for the dengue outbreak on Fais our estimate was 28-102 (95% CI). We further found that the proportion of cases of Zika reported was smaller (95% CI 1.4%-1.9%) than that of dengue (95% CI: 47%-61%). We confirmed these results in extensive sensitivity analysis. They suggest that models for dengue transmission can be useful for estimating the predicted dynamics of Zika transmission, but care must be taken when extrapolating findings from one setting to another

    The consequences of reservoir host eradication on disease epidemiology in animal communities.

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    Non-native species have often been linked with introduction of novel pathogens that spill over into native communities, and the amplification of the prevalence of native parasites. In the case of introduced generalist pathogens, their disease epidemiology in the extant communities remains poorly understood. Here, Sphaerothecum destruens, a generalist fungal-like fish pathogen with bi-modal transmission (direct and environmental) was used to characterise the biological drivers responsible for disease emergence in temperate fish communities. A range of biotic factors relating to both the pathogen and the surrounding host communities were used in a novel susceptible-exposed-infectious-recovered (SEIR) model to test how these factors affected disease epidemiology. These included: (i) pathogen prevalence in an introduced reservoir host (Pseudorasbora parva); (ii) the impact of reservoir host eradication and its timing and (iii) the density of potential hosts in surrounding communities and their connectedness. These were modelled across 23 combinations and indicated that the spill-over of pathogen propagules via environmental transmission resulted in rapid establishment in adjacent fish communities (<1 year). Although disease dynamics were initially driven by environmental transmission in these communities, once sufficient numbers of native hosts were infected, the disease dynamics were driven by intra-species transmission. Subsequent eradication of the introduced host, irrespective of its timing (after one, two or three years), had limited impact on the long-term disease dynamics among local fish communities. These outputs reinforced the importance of rapid detection and eradication of non-native species, in particular when such species are identified as healthy reservoirs of a generalist pathogen

    Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

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