Discovering the Higgs Through Highly-Displaced Vertices

We suggest that the Higgs could be discovered at the Tevatron or the LHC (perhaps at the LHCb detector) through decays with one or more substantially displaced vertices from the decay of new neutral particles. This signal may occur with a small but measurable branching fraction in the recently-described ``hidden valley'' models, hep-ph/0604261; weakly-coupled models with multiple scalars, including those of hep-ph/0511250, can also provide such signals, potentially with a much larger branching fraction. This decay channel may extend the Higgs mass reach for the Tevatron. Unusual combinations of b jets, lepton pairs and/or missing energy may accompany this signal.Comment: v2, minor improvements/clarifications, one added referenc

Echoes of a Hidden Valley at Hadron Colliders

We consider examples of ``hidden-valley'' models, in which a new confining gauge group is added to the standard model. Such models often arise in string constructions, and elsewhere. The resulting (electrically-neutral) bound states can have low masses and long lifetimes, and could be observed at the LHC and Tevatron. Production multiplicities are often large. Final states with heavy flavor are common; lepton pairs, displaced vertices and/or missing energy are possible. Accounting for LEP constraints, we find LHC production cross-sections typically in the 1-100 fb range, though they can be larger. It is possible the Higgs boson could be discovered at the Tevatron through rare decays to the new particles.Comment: 5 pages, 5 figures (v2: minor improvements, one added reference, no substantial changes

Clinico-Neuropathological Findings in the Oldest Old from the Georgia Centenarian Study

Background: Centenarian studies are important sources for understanding of factors that contribute to longevity and healthy aging. Clinico-neuropathological finding is a key in identifying pathology and factors contributing to age-related cognitive decline and dementia in the oldest old. Objective: To characterize the cross-sectional relationship between neuropathologies and measures of premortem cognitive performance in centenarians. Methods: Data were acquired from 49 centenarians (≥98 years) from the Georgia Centenarian Study. Cognitive assessment from the time point closest to mortality was used (\u3c1 year for all subjects) and scores for cognitive domains were established. Neuropathologies [cerebral atrophy, ventricular dilation, atherosclerosis, cerebral amyloid angiopathy (CAA), Lewy bodies, hippocampal sclerosis (HS), hippocampal TDP-43 proteinopathy, neuritic plaque (NP) and neurofibrillary tangle (NFT) counts, Braak staging, and National Institute on Aging-Reagan Institute (NIARI) criteria for the neuropathological diagnosis of Alzheimer’s disease (AD)] were compared among subjects with different ratings of dementia. Linear regression was applied to evaluate the association between cognitive domain scores and neuropathologies. Results: Wide ranges of AD-type neuropathological changes were observed in both non-demented and demented subjects. Neocortical NFT and Braak staging were related to clinical dementia rating. Neocortical NFT and NP, Braak and NIARI staging, cerebral and ventricular atrophy, HS, CAA, and TDP-43 proteinopathy were differentially associated with poor performance in multiple cognitive domains and activities of daily living. Conclusion: AD-type pathology was associated with severe dementia and poor cognition but was not the only variable that explained cognitive impairment, indicating the complexity and heterogeneity of pathophysiology of dementia in the oldest old

Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health

The article of record as published may be found at http://dx.doi.org/10.1093/sleep/zsab161Risks associated with fatigue that accumulates during work shifts have historically been managed through working time arrangements that specify fixed maximum durations of work shifts and minimum durations of time off. By themselves, such arrangements are not sufficient to curb risks to performance, safety, and health caused by misalignment between work schedules and the biological regulation of waking alertness and sleep. Science-based approaches for determining shift duration and mitigating associated risks, while addressing operational needs, require: 1) a recognition of the factors contributing to fatigue and fatigue-related risks; 2) an understanding of evidence-based countermeasures that may reduce fatigue and/or fatigue-related risks; and 3) an informed approach to selecting workplace-specific strategies for managing work hours. We propose a series of guiding principles to assist stakeholders with designing a shift duration decision-making process that effectively balances the need to meet operational demands with the need to manage fatigue-related risks.Academy of Sleep Medicine (AASM)Sleep Research Societ

Measured energy content of frequently purchased restaurant meals : multi-country cross sectional study

Funding: This work was supported in part by the US Department of Agriculture under agreement no. 58-1950-4-003 with Tufts University and a Tufts University Provost award to SBR. The study had additional funding in Brazil from FAPESP grants 2013/18520-0 and 2013/14489-1 to VS; in China from the National Science Foundation of China grant No 91431102 to JRS and International Partnership Program of Chinese Academy of Sciences grant No GJHZ1660 to JRS; in Finland from internal funding by the University of Eastern Finland to JP; in Ghana from the University of Georgia Global Research Collaborative Grant Program to AKA. The views expressed are those of the authors. The sponsors had no role in the design, undertaking, or reporting of the study.Peer reviewedPublisher PD

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

The fifteenth data release of the Sloan Digital Sky Surveys : first release of MaNGA derived quantities, data visualization tools and stellar library

Twenty years have passed since first light for the Sloan Digital SkySurvey (SDSS). Here, we release data taken by the fourth phase of SDSS(SDSS-IV) across its first three years of operation (July 2014-July2017). This is the third data release for SDSS-IV, and the fifteenth from SDSS (Data Release Fifteen; DR15). New data come from MaNGA - we release 4824 datacubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g. stellar and gas kinematics, emission line, andother maps) from the MaNGA Data Analysis Pipeline (DAP), and a new data visualisation and access tool we call "Marvin". The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials and examples of data use. While SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V(2020-2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data.Publisher PDFPeer reviewe

Objective Bayesian Estimation for the Number of Classes in a Population Using Jeffreys and Reference Priors

Estimation of the number of classes in a closed population is a problem that arises in many different subject areas. A common application occurs in animal populations where there is interest in determining the number of different species, also the diversity or species richness, of the population. In this dissertation a class of models are considered, all with the common assumption that the number of individual items from each class, contributed to the sample, is a Poisson random variable. In order to conduct objective Bayesian inference, Jeffreys and reference priors are derived from the full likelihood. The Jeffreys and reference priors are functions of the information for the model parameters. The information is calculated in part using the linear difference score for integer parameter models (Lindsay & Roeder 1987). A main accomplishment of this dissertation is deriving the form of the Jeffreys and reference priors for the number of classes. Both of the priors for the Jeffreys and reference methods factor into two independent priors, one for the parameter of interest and one for the nuisance parameters. This gives a justification for choosing these priors independent a priori, as is generally done for this problem. In this dissertation we prove that the posterior determined by these priors is proper for some low dimensional problems. With increased dimensionality, the form of the prior and posterior becomes increasingly intractable and we propose methods to deal with these difficulties. Microbial samples from the Framvaren Fjord (Behnke et al. 2006) and Lepidoptera data (Fisher et al. 1943) are used to illustrate that these priors can be used to implement a fully Bayesian procedure for the number of classes. The reference prior is comparable to maximum likelihood results, while the Jeffreys prior deviates from the frequentist estimates in models with larger numbers of parameters