Audiovisual Metadata Platform Pilot Development (AMPPD), Final Project Report

This report documents the experience and findings of the Audiovisual Metadata Platform Pilot Development (AMPPD) project, which has worked to enable more efficient generation of metadata to support discovery and use of digitized and born-digital audio and moving image collections. The AMPPD project was carried out by partners Indiana University Libraries, AVP, University of Texas at Austin, and New York Public Library between 2018-2021

Two Types of Burst Firing in Gonadotrophin‐Releasing Hormone Neurones

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92106/1/j.1365-2826.2012.02313.x.pd

Improved W boson mass measurement with the D0 detector

We have measured the W boson mass using the D0 detector and a data sample of 82 pb^-1 from the Tevatron collider. This measurement used W -> e nu decays, where the electron is close to a boundary of a central electromagnetic calorimeter module. Such 'edge' electrons have not been used in any previous D0 analysis, and represent a 14% increase in the W boson sample size. For these electrons, new response and resolution parameters are determined, and revised backgrounds and underlying event energy flow measurements are made. When the current measurement is combined with previous D0 W boson mass measurements, we obtain M_W = 80.483 +/- 0.084 GeV. The 8% improvement from the previous D0 measurement is primarily due to the improved determination of the response parameters for non-edge electrons using the sample of Z bosons with non-edge and edge electrons.Comment: submitted to Phys. Rev. D; 20 pages, 18 figures, 9 table

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Epigenetic Programming by Early-Life Stress

Studies show that adverse conditions during early life can increase risks of developing mood disorders later in life. It is currently hypothesized that levels of environmental adversity in this early developmental period are able to shape the experience-dependent maturation of stress-regulating pathways leading to long-lasting alterations in stress responsivity during adulthood; a phenomenon often referred to as “early-life programming.” Research is addressing the molecular mechanisms underlying this programming by which gene–environment interactions can predispose individuals toward psychopathology. Here we review key findings from animal and clinical studies examining the effects of prenatal and postnatal environment in shaping development of the neuroendocrine regulation of stress and the role of epigenetic mechanisms in translating early-life conditions into long-lasting gene expression changes underpinning stress-related behaviors. We also review latest ideas regarding interactions between environments at different developmental stages and evidence for transgenerational effects. Understanding how prenatal and postnatal experiences can give rise to lasting epigenetic marks conferring increased vulnerability to mental disorders is a major focus of molecular psychiatry and should pave new guidelines for therapeutic interventions

Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?

It is widely accepted that humans and animals minimize energetic cost while walking. While such principles predict average behavior, they do not explain the variability observed in walking. For robust performance, walking movements must adapt at each step, not just on average. Here, we propose an analytical framework that reconciles issues of optimality, redundancy, and stochasticity. For human treadmill walking, we defined a goal function to formulate a precise mathematical definition of one possible control strategy: maintain constant speed at each stride. We recorded stride times and stride lengths from healthy subjects walking at five speeds. The specified goal function yielded a decomposition of stride-to-stride variations into new gait variables explicitly related to achieving the hypothesized strategy. Subjects exhibited greatly decreased variability for goal-relevant gait fluctuations directly related to achieving this strategy, but far greater variability for goal-irrelevant fluctuations. More importantly, humans immediately corrected goal-relevant deviations at each successive stride, while allowing goal-irrelevant deviations to persist across multiple strides. To demonstrate that this was not the only strategy people could have used to successfully accomplish the task, we created three surrogate data sets. Each tested a specific alternative hypothesis that subjects used a different strategy that made no reference to the hypothesized goal function. Humans did not adopt any of these viable alternative strategies. Finally, we developed a sequence of stochastic control models of stride-to-stride variability for walking, based on the Minimum Intervention Principle. We demonstrate that healthy humans are not precisely “optimal,” but instead consistently slightly over-correct small deviations in walking speed at each stride. Our results reveal a new governing principle for regulating stride-to-stride fluctuations in human walking that acts independently of, but in parallel with, minimizing energetic cost. Thus, humans exploit task redundancies to achieve robust control while minimizing effort and allowing potentially beneficial motor variability