Treating Homeless Opioid Dependent Patients with Buprenorphine in an Office-Based Setting

CONTEXT Although office-based opioid treatment with buprenorphine (OBOT-B) has been successfully implemented in primary care settings in the US, its use has not been reported in homeless patients. OBJECTIVE To characterize the feasibility of OBOT-B in homeless relative to housed patients. DESIGN A retrospective record review examining treatment failure, drug use, utilization of substance abuse treatment services, and intensity of clinical support by a nurse care manager (NCM) among homeless and housed patients in an OBOT-B program between August 2003 and October 2004. Treatment failure was defined as elopement before completing medication induction, discharge after medication induction due to ongoing drug use with concurrent nonadherence with intensified treatment, or discharge due to disruptive behavior. RESULTS Of 44 homeless and 41 housed patients enrolled over 12 months, homeless patients were more likely to be older, nonwhite, unemployed, infected with HIV and hepatitis C, and report a psychiatric illness. Homeless patients had fewer social supports and more chronic substance abuse histories with a 3- to 6-fold greater number of years of drug use, number of detoxification attempts and percentage with a history of methadone maintenance treatment. The proportion of subjects with treatment failure for the homeless (21%) and housed (22%) did not differ (P=.94). At 12 months, both groups had similar proportions with illicit opioid use [Odds ratio (OR), 0.9 (95% CI, 0.5–1.7) P=.8], utilization of counseling (homeless, 46%; housed, 49%; P=.95), and participation in mutual-help groups (homeless, 25%; housed, 29%; P=.96). At 12 months, 36% of the homeless group was no longer homeless. During the first month of treatment, homeless patients required more clinical support from the NCM than housed patients. CONCLUSIONS Despite homeless opioid dependent patients' social instability, greater comorbidities, and more chronic drug use, office-based opioid treatment with buprenorphine was effectively implemented in this population comparable to outcomes in housed patients with respect to treatment failure, illicit opioid use, and utilization of substance abuse treatment

Sr0.9_{0.9}K0.1_{0.1}Zn1.8_{1.8}Mn0.2_{0.2}As2_{2}: a ferromagnetic semiconductor with colossal magnetoresistance

A bulk diluted magnetic semiconductor (Sr,K)(Zn,Mn)$_{2}$As$_{2}$ was synthesized with decoupled charge and spin doping. It has a hexagonal CaAl$_{2}$Si$_{2}$-type structure with the (Zn,Mn)$_{2}$As$_{2}$ layer forming a honeycomb-like network. Magnetization measurements show that the sample undergoes a ferromagnetic transition with a Curie temperature of 12 K and \revision{magnetic moment reaches about 1.5 $\mu_{B}$/Mn under $\mu_0H$ = 5 T and $T$ = 2 K}. Surprisingly, a colossal negative magnetoresistance, defined as $[\rho(H)-\rho(0)]/\rho(0)$, up to $-$38\% under a low field of $\mu_0H$ = 0.1 T and to $-$99.8\% under $\mu_0H$ = 5 T, was observed at $T$ = 2 K. The colossal magnetoresistance can be explained based on the Anderson localization theory.Comment: Accepted for publication in EP

Assessing the effect of beard hair lengths on face masks used as personal protective equipment during the COVID-19 pandemic

Background Globally, a large percentage of men keep a beard at least occasionally. Workplace regulations prohibit beards with N95 respirators, but there is little information on the effect of beards with face masks worn by the public for protection against SARS-CoV-2. Methods and findings We examined the fitted filtration efficiency (FFE) of five commonly worn protective face masks as a function of beard length following the US Occupational Safety and Health Administration Quantitative Fit Test: N95 (respirator), KF94 and KN95, surgical/procedure, and cloth masks. A comparison using N95 respirators was carried out in shaven and bearded men. A detailed examination was conducted for beard lengths between 0 and 10 mm (0.5 mm increments). The effect of an exercise band covering the beard on FFE was also tested. Although N95 respirators showed considerable variability among bearded men, they had the highest FFE for beard lengths up to 10 mm. KF94 and KN95 masks lost up to 40% of their FFE. Procedure and cotton masks had poor performance even on bare skin (10–30% FFE) that did not change appreciably with beard length. Marked performance improvements were observed with an exercise band worn over the beard. Conclusions Though variable, N95 respirators offer the best respiratory protection for bearded men. While KF94 and KN95 FFE is compromised considerably by increasing beard length, they proved better options than procedure and cotton face masks. A simple exercise band improves FFE for face masks commonly used by bearded men during the COVID-19 pandemic

Filtration Efficiency of Hospital Face Mask Alternatives Available for Use during the COVID-19 Pandemic

Importance: Procuring respiratory protection for clinicians and other health care workers has become a major challenge of the coronavirus disease 2019 (COVID-19) pandemic and has resulted in nonstandard practices such as the use of expired respirators and various decontamination processes to prolong the useful life of respirators in health care settings. In addition, imported, non-National Institute for Occupational Safety and Health (NIOSH)-approved respirators have been donated or acquired by hospitals as a potential replacement for limited NIOSH-approved N95 respirators. Objective: To assess fitted filtration efficiencies (FFEs) for face mask alternatives used during the COVID-19 pandemic. Design, Setting, and Participants: For this quality-improvement study conducted between April and June 2020, we used the Occupational Safety and Health Administration's Quantitative Fit Testing Protocol for Filtering Facepiece Respirators in a laboratory atmosphere supplemented with sodium chloride particles to assess the FFEs of a variety of respirators worn by a male volunteer and female volunteer. Main Outcomes and Measures: The FFEs of respirators commonly worn by clinicians and other health care workers and available respirator alternatives during the COVID-19 pandemic. Results: Of the 29 different fitted face mask alternatives tested on 1 man and 1 woman, expired N95 respirators with intact elastic straps and respirators subjected to ethylene oxide and hydrogen peroxide sterilization had unchanged FFE (>95%). The performance of N95 respirators in the wrong size had slightly decreased performance (90%-95% FFE). All of the respirators not listed as approved in this evaluation (n = 6) failed to achieve 95% FFE. Neither of the 2 imported respirators authorized for use by the Centers for Disease Control and Prevention that were not NIOSH-approved tested in this study achieved 95% FFE, and the more effective of the 2 functioned at approximately 80% FFE. Surgical and procedural face masks had filtering performance that was lower relative to that of N95 respirators (98.5% overall FFE), with procedural face masks secured with elastic ear loops showing the lowest efficiency (38.1% overall FFE). Conclusions and Relevance: This quality-improvement study evaluating 29 face mask alternatives for use by clinicians interacting with patients during the COVID-19 pandemic found that expired N95 respirators and sterilized, used N95 respirators can be used when new N95 respirators are not available. Other alternatives may provide less effective filtration

NASA: Neural Articulated Shape Approximation

Efficient representation of articulated objects such as human bodies is an important problem in computer vision and graphics. To efficiently simulate deformation, existing approaches represent 3D objects using polygonal meshes and deform them using skinning techniques. This paper introduces neural articulated shape approximation (NASA), an alternative framework that enables efficient representation of articulated deformable objects using neural indicator functions that are conditioned on pose. Occupancy testing using NASA is straightforward, circumventing the complexity of meshes and the issue of water-tightness. We demonstrate the effectiveness of NASA for 3D tracking applications, and discuss other potential extensions.Comment: ECCV 202

A well-separated pairs decomposition algorithm for k-d trees implemented on multi-core architectures

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.Variations of k-d trees represent a fundamental data structure used in Computational Geometry with numerous applications in science. For example particle track tting in the software of the LHC experiments, and in simulations of N-body systems in the study of dynamics of interacting galaxies, particle beam physics, and molecular dynamics in biochemistry. The many-body tree methods devised by Barnes and Hutt in the 1980s and the Fast Multipole Method introduced in 1987 by Greengard and Rokhlin use variants of k-d trees to reduce the computation time upper bounds to O(n log n) and even O(n) from O(n2). We present an algorithm that uses the principle of well-separated pairs decomposition to always produce compressed trees in O(n log n) work. We present and evaluate parallel implementations for the algorithm that can take advantage of multi-core architectures.The Science and Technology Facilities Council, UK

Sampling-based Algorithms for Optimal Motion Planning

During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics Researc