The Conductance of a Perfect Thin Film with Diffuse Surface Scattering

The conductance of thin films with diffusive surface scattering was solved semi-classically by Fuchs and Sondheimer. However, when the intrinsic electron mean free path is very large or infinite their conductance diverges. In this letter a simple diffraction picture is presented. It yields a conductance which corresponds to a limiting mean free path. PACS: 73.50.-h, 73.50.Bk, 73.23.-b, 73.25.+i, B14

Supersoft X-rays reveal a classical nova in the M 31 globular cluster Bol 126

[Abridged] Classical novae (CNe) represent the main class of supersoft X-ray sources (SSSs) in the central region of our neighbouring galaxy M 31. Only three confirmed novae and three SSSs have been discovered in globular clusters (GCs) of any galaxy so far, of which one nova and two SSSs (including the nova) were found in M 31 GCs. To study the SSS state of CNe we carried out a high-cadence X-ray monitoring of the M 31 central area with XMM-Newton and Chandra. We analysed X-ray and optical data of a new transient X-ray source in the M 31 GC Bol 126, discovered serendipitously in Swift observations. Our optical data set was based on regular M 31 monitoring programmes from five different small telescopes. Additionally, we made use of Pan-STARRS 1 data obtained during the PAndromeda survey. Our observations reveal that the X-ray source in Bol 126 is the third SSS in an M 31 GC and can be confirmed as the second CN in the M 31 GC system. This nova is named M31N 2010-10f. Its properties in the X-ray and optical regimes agree with a massive white dwarf (M_WD >~ 1.3 M_sun) in the binary system. Incorporating the data on previously found (suspected) novae in M 31 GCs we used our high-cadence X-ray monitoring observations to estimate a tentative nova rate in the M 31 GC system of 0.05 /yr/GC. An optical estimate, based on the recent 10.5-year WeCAPP survey, gives a lower nova rate, which is compatible with the X-ray rate on the 95% confidence level. There is growing evidence that the nova rate in GCs is higher than expected from primordial binary formation and under conditions as in the field. Dynamical binary formation and/or additional accretion from the intracluster medium are possible scenarios for an increased nova rate, but observational confirmation for this enhancement has been absent, so far. Regular X-ray monitoring observations of M 31 provide a promising strategy to find these novae.Comment: 14 pages, 6 figures, 3 tables; accepted by Astronomy and Astrophysic

Electronic Structure of Three-Dimensional Superlattices Subject to Tilted Magnetic Fields

Full quantum-mechanical description of electrons moving in 3D structures with unidirectional periodic modulation subject to tilted magnetic fields requires an extensive numerical calculation. To understand magneto-oscillations in such systems it is in many cases sufficient to use the quasi-classical approach, in which the zero-magnetic-field Fermi surface is considered as a magnetic-field-independent rigid body in k-space and periods of oscillations are related to extremal cross-sections of the Fermi surface cut by planes perpendicular to the magnetic-field direction. We point out cases where the quasi-classical treatment fails and propose a simple tight-binding fully-quantum-mechanical model of the superlattice electronic structure.Comment: 8 pages, 7 figures, RevTex, submitted to Phys. Rev.

A Requirement-centric Approach to Web Service Modeling, Discovery, and Selection

Service-Oriented Computing (SOC) has gained considerable popularity for implementing Service-Based Applications (SBAs) in a flexible\ud and effective manner. The basic idea of SOC is to understand users'\ud requirements for SBAs first, and then discover and select relevant\ud services (i.e., that fit closely functional requirements) and offer\ud a high Quality of Service (QoS). Understanding users’ requirements\ud is already achieved by existing requirement engineering approaches\ud (e.g., TROPOS, KAOS, and MAP) which model SBAs in a requirement-driven\ud manner. However, discovering and selecting relevant and high QoS\ud services are still challenging tasks that require time and effort\ud due to the increasing number of available Web services. In this paper,\ud we propose a requirement-centric approach which allows: (i) modeling\ud users’ requirements for SBAs with the MAP formalism and specifying\ud required services using an Intentional Service Model (ISM); (ii)\ud discovering services by querying the Web service search engine Service-Finder\ud and using keywords extracted from the specifications provided by\ud the ISM; and(iii) selecting automatically relevant and high QoS services\ud by applying Formal Concept Analysis (FCA). We validate our approach\ud by performing experiments on an e-books application. The experimental\ud results show that our approach allows the selection of relevant and\ud high QoS services with a high accuracy (the average precision is\ud 89.41%) and efficiency (the average recall is 95.43%)

Dissemination and implementation science training needs: Insights from practitioners and researchers

INTRODUCTION: Dissemination and implementation research training has great potential to improve the impact and reach of health-related research; however, research training needs from the end user perspective are unknown. This paper identifies and prioritizes dissemination and implementation research training needs. METHODS: A diverse sample of researchers, practitioners, and policymakers was invited to participate in Concept Mapping in 2014–2015. Phase 1 (Brainstorming) gathered participants' responses to the prompt: To improve the impact of research evidence in practice and policy settings, a skill in which researchers need more training is… The resulting statement list was edited and included subsequent phases. Phase 2 (Sorting) asked participants to sort each statement into conceptual piles. In Phase 3 (Rating), participants rated the difficulty and importance of incorporating each statement into a training curriculum. A multidisciplinary team synthesized and interpreted the results in 2015–2016. RESULTS: During Brainstorming, 60 researchers and 60 practitioners/policymakers contributed 274 unique statements. Twenty-nine researchers and 16 practitioners completed sorting and rating. Nine concept clusters were identified: Communicating Research Findings, Improve Practice Partnerships, Make Research More Relevant, Strengthen Communication Skills, Develop Research Methods and Measures, Consider and Enhance Fit, Build Capacity for Research, and Understand Multilevel Context. Though researchers and practitioners had high agreement about importance (r =0.93) and difficulty (r =0.80), ratings differed for several clusters (e.g., Build Capacity for Research). CONCLUSIONS: Including researcher and practitioner perspectives in competency development for dissemination and implementation research identifies skills and capacities needed to conduct and communicate contextualized, meaningful, and relevant research

Lunar lander conceptual design

This paper is a first look at the problems of building a lunar lander to support a small lunar surface base. A series of trade studies was performed to define the lander. The initial trades concerned choosing number of stages, payload mass, parking orbit altitude, and propellant type. Other important trades and issues included plane change capability, propellant loading and maintenance location, and reusability considerations. Given a rough baseline, the systems were then reviewed. A conceptual design was then produced. The process was carried through only one iteration. Many more iterations are needed. A transportation system using reusable, aerobraked orbital transfer vehicles (OTV's) is assumed. These OTV's are assumed to be based and maintained at a low Earth orbit (LEO) space station, optimized for transportation functions. Single- and two-stage OTV stacks are considered. The OTV's make the translunar injection (TLI), lunar orbit insertion (LOI), and trans-Earth injection (TEI) burns, as well as midcourse and perigee raise maneuvers

Federating distributed clinical data for the prediction of adverse hypotensive events

The ability to predict adverse hypotensive events, where a patient's arterial blood pressure drops to abnormally low (and dangerous) levels, would be of major benefit to the fields of primary and secondary health care, and especially to the traumatic brain injury domain. A wealth of data exist in health care systems providing information on the major health indicators of patients in hospitals (blood pressure, temperature, heart rate, etc.). It is believed that if enough of these data could be drawn together and analysed in a systematic way, then a system could be built that will trigger an alarm predicting the onset of a hypotensive event over a useful time scale, e.g. half an hour in advance. In such circumstances, avoidance measures can be taken to prevent such events arising. This is the basis for the Avert-IT project (http://www.avert-it.org), a collaborative EU-funded project involving the construction of a hypotension alarm system exploiting Bayesian neural networks using techniques of data federation to bring together the relevant information for study and system development

Measuring Masculinity in Men With Chronic Disease

© The Author(s) 2019. The Masculinity in Chronic Disease Inventory (MCD-I) is a new measure of internalized masculine beliefs previously validated in the context of prostate cancer. The present study assessed the validity of the MCD-I in men with other chronic diseases to explore its potential for wider application. A cross-sectional survey of 633 men aged 47–93 years old (M = 68 years), of whom 68% reported ≥2 chronic conditions, was conducted. Measures included the MCD-I and Erectile Function. Exploratory and confirmatory factor analyses were performed followed by tests for discriminant validity. A five-factor structure was confirmed that explained 60% of the variance, with good to excellent reliabilities (α = 0.68–0.93) for the domains of Optimistic Action, Sexual Importance/Priority, Family Responsibilities, Emotional Self-Reliance, and Strength/Fitness. The MCD-I is a valid measure of internalized masculine beliefs for men with chronic disease that appears sensitive to age and to sexual health. The tailoring of health services for men can be guided by MCD-I outcomes to ensure gender-sensitized men’s health interventions

Gravitational quasinormal modes for Anti-de Sitter black holes

Quasinormal mode spectra for gravitational perturbations of black holes in four dimensional de Sitter and anti-de Sitter space are investigated. The anti-de Sitter case is relevant to the ADS-CFT correspondence in superstring theory. The ADS-CFT correspondence suggests a prefered set of boundary conditions.Comment: 12 pages, 6 figures in ReVTe

Energy Minimization in D2D-Assisted Cache-Enabled Internet of Things: A Deep Reinforcement Learning Approach

Mobile edge caching (MEC) and device-to-device (D2D) communications are two potential technologies to resolve traffic overload problems in the Internet of Things. Previous works usually investigate them separately with MEC for traffic offloading and D2D for information transmission. In this article, a joint framework consisting of MEC and cache-enabled D2D communications is proposed to minimize the energy cost of systematic traffic transmission, where file popularity and user preference are the critical criteria for small base stations (SBSs) and user devices, respectively. Under this framework, we propose a novel caching strategy, where the Markov decision process is applied to model the requesting behaviors. A novel scheme based on reinforcement learning (RL) is proposed to reveal the popularity of files as well as users' preference. In particular, a Q-learning algorithm and a deep Q-network algorithm are, respectively, applied to user devices and the SBS due to different complexities of status. To save the energy cost of systematic traffic transmission, users acquire partial traffic through D2D communications based on the cached contents and user distribution. Taking the memory limits, D2D available files, and status changing into consideration, the proposed RL algorithm enables user devices and the SBS to prefetch the optimal files while learning, which can reduce the energy cost significantly. Simulation results demonstrate the superior energy saving performance of the proposed RL-based algorithm over other existing methods under various conditions