The Influence of Veteran Status, Psychiatric Diagnosis, and Traumatic Brain Injury on Inadequate Sleep

Adequate sleep is essential for health, social participation, and wellbeing. We use 2010 and 2011 Behavioral Risk Factor Surveillance System data (N = 35,602) to examine differences in sleep adequacy between: non-veterans; non-combat veterans with no psychiatric diagnosis or traumatic brain injury (TBI); combat veterans with no psychiatric diagnosis or TBI; and veterans (non-combat and combat combined) with a psychiatric diagnosis and/or TBI. On average, respondents reported 9.28 days of inadequate sleep; veterans with a psychiatric diagnosis and/or TBI reported the most—12.25 days. Multivariate analyses indicated that veterans with a psychiatric diagnosis and/or TBI had significantly more days of inadequate sleep than all other groups. Findings contribute to a growing literature on the relevance of the military service–psychiatric diagnosis–TBI nexus for sleep problems by using population-representative data and non-veteran and healthy veteran comparison groups. This research underscores the importance of screening and treating veterans for sleep problems, and can be used by social workers and health professionals to advocate for increased education and research about sleep problems among veterans with mental health problems and/or TBI

Efficient exploration of unknown indoor environments using a team of mobile robots

Whenever multiple robots have to solve a common task, they need to coordinate their actions to carry out the task efficiently and to avoid interferences between individual robots. This is especially the case when considering the problem of exploring an unknown environment with a team of mobile robots. To achieve efficient terrain coverage with the sensors of the robots, one first needs to identify unknown areas in the environment. Second, one has to assign target locations to the individual robots so that they gather new and relevant information about the environment with their sensors. This assignment should lead to a distribution of the robots over the environment in a way that they avoid redundant work and do not interfere with each other by, for example, blocking their paths. In this paper, we address the problem of efficiently coordinating a large team of mobile robots. To better distribute the robots over the environment and to avoid redundant work, we take into account the type of place a potential target is located in (e.g., a corridor or a room). This knowledge allows us to improve the distribution of robots over the environment compared to approaches lacking this capability. To autonomously determine the type of a place, we apply a classifier learned using the AdaBoost algorithm. The resulting classifier takes laser range data as input and is able to classify the current location with high accuracy. We additionally use a hidden Markov model to consider the spatial dependencies between nearby locations. Our approach to incorporate the information about the type of places in the assignment process has been implemented and tested in different environments. The experiments illustrate that our system effectively distributes the robots over the environment and allows them to accomplish their mission faster compared to approaches that ignore the place labels

Size Acceptance: A Discursive Analysis of Online Blogs

This document is an Accepted Manuscript of an article published by Taylor & Francis Group in Fat Studies on 25 May 2018, available online at: https://doi.org/10.1080/21604851.2018.1473704. Under embargo until 25 May 2019.Dominant discourses of “fatness” and “fat people” have implications for physical and mental health. Although alternative discourses such as “size acceptance” exist, there has been little consideration of the ways in which these alternative arguments (and speakers) may be positioned to be heard. Using a discursive thematic analysis, the authors demonstrate that size acceptance online bloggers have created a community online that enables them to persuasively provide alternative claims to “expertise,” which positions their views as credible and legitimate alternatives to those of more established authority figures—such as health professionals. This has implications not only for the lived experience of fat people, but also for researchers by emphasizing the importance of exploring not just what is said, but how, if we are to understand how different articulated positions are to be persuasive.Peer reviewe

An Autonomous Robotic System for Mapping Abandoned Mines

We present the software architecture of a robotic system for mapping abandoned mines. The software is capable of acquiring consistent 2D maps of large mines with many cycles, represented as Markov random fields. 3D C-space maps are acquired from local 3D range scans, which are used to identify navigable paths using A* search. Our system has been deployed in three abandoned mines, two of which inaccessible to people, where it has acquired maps of unprecedented detail and accuracy

Interplay of gravitation and linear superposition of different mass eigenstates

The interplay of gravitation and the quantum-mechanical principle of linear superposition induces a new set of neutrino oscillation phases. These ensure that the flavor-oscillation clocks, inherent in the phenomenon of neutrino oscillations, redshift precisely as required by Einstein's theory of gravitation. The physical observability of these phases in the context of the solar neutrino anomaly, type-II supernovae, and certain atomic systems is briefly discussed

Partial inhibition and bilevel optimization in flux balance analysis

Motivation: Within Flux Balance Analysis, the investigation of complex subtasks, such as finding the optimal perturbation of the network or finding an optimal combination of drugs, often requires to set up a bilevel optimization problem. In order to keep the linearity and convexity of these nested optimization problems, an ON/OFF description of the effect of the perturbation (i.e. Boolean variable) is normally used. This restriction may not be realistic when one wants, for instance, to describe the partial inhibition of a reaction induced by a drug.Results: In this paper we present a formulation of the bilevel optimization which overcomes the oversimplified ON/OFF modeling while preserving the linear nature of the problem. A case study is considered: the search of the best multi-drug treatment which modulates an objective reaction and has the minimal perturbation on the whole network. The drug inhibition is described and modulated through a convex combination of a fixed number of Boolean variables. The results obtained from the application of the algorithm to the core metabolism of E.coli highlight the possibility of finding a broader spectrum of drug combinations compared to a simple ON/OFF modeling.Conclusions: The method we have presented is capable of treating partial inhibition inside a bilevel optimization, without loosing the linearity property, and with reasonable computational performances also on large metabolic networks. The more fine-graded representation of the perturbation allows to enlarge the repertoire of synergistic combination of drugs for tasks such as selective perturbation of cellular metabolism. This may encourage the use of the approach also for other cases in which a more realistic modeling is required. \ua9 2013 Facchetti and Altafini; licensee BioMed Central Ltd

MVCSLAM: Mono-Vision Corner SLAM for Autonomous Micro-Helicopters in GPS Denied Environments

We present a real-time vision navigation and ranging method (VINAR) for the purpose of Simultaneous Localization and Mapping (SLAM) using monocular vision. Our navigation strategy assumes a GPS denied unknown environment, whose indoor architecture is represented via corner based feature points obtained through a monocular camera. We experiment on a case study mission of vision based SLAM through a conventional maze of corridors in a large building with an autonomous Micro Aerial Vehicle (MAV). We propose a method for gathering useful landmarks from a monocular camera for SLAM use. We make use of the corners by exploiting the architectural features of the manmade indoors

HIV Types, Groups, Subtypes and Recombinant Forms: Errors in Replication, Selection Pressure and Quasispecies

HIV-1 is a chimpanzee virus which was transmitted to humans by several zoonotic events resulting in infection with HIV-1 groups M P, and in parallel transmission events from sooty mangabey monkey viruses leading to infections with HIV-2 groups A H. Both viruses have circulated in the human population for about 80 years. In the infected patient, HIV mutates, and by elimination of some of the viruses by the action of the immune system individual quasispecies are formed. Along with the selection of the fittest viruses, mutation and recombination after superinfection with HIV from different groups or subtypes have resulted in the diversity of their patterns of geographic distribution. Despite the high variability observed, some essential parts of the HIV genome are highly conserved. Viral diversity is further facilitated in some parts of the HIV genome by drug selection pressure and may also be enhanced by different genetic factors, including HLA in patients from different regions of the world. Viral and human genetic factors influence pathogenesis. Viral genetic factors are proteins such as Tat, Vif and Rev. Human genetic factors associated with a better clinical outcome are proteins such as APOBEC, langerin, tetherin and chemokine receptor 5 (CCR5) and HLA B27, B57, DRB1{*}1303, KIR and PARD3B. Copyright (C) 2012 S. Karger AG, Base

Spontaneous Reaction Silencing in Metabolic Optimization

Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical non-optimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.Comment: 34 pages, 6 figure