8,742 research outputs found

    Selected Papers from SDEWES 2017: The 12th Conference on Sustainable Development of Energy, Water and Environment Systems

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    EU energy policy is more and more promoting a resilient, efficient and sustainable energy system. Several agreements have been signed in the last few months that set ambitious goals in terms of energy efficiency and emission reductions and to reduce the energy consumption in buildings. These actions are expected to fulfill the goals negotiated at the Paris Agreement in 2015. The successful development of this ambitious energy policy needs to be supported by scientific knowledge: a huge effort must be made in order to develop more efficient energy conversion technologies based both on renewables and fossil fuels. Similarly, researchers are also expected to work on the integration of conventional and novel systems, also taking into account the needs for the management of the novel energy systems in terms of energy storage and devices management. Therefore, a multi-disciplinary approach is required in order to achieve these goals. To ensure that the scientists belonging to the different disciplines are aware of the scientific progress in the other research areas, specific Conferences are periodically organized. One of the most popular conferences in this area is the Sustainable Development of Energy, Water and Environment Systems (SDEWES) Series Conference. The 12th Sustainable Development of Energy, Water and Environment Systems Conference was recently held in Dubrovnik, Croatia. The present Special Issue of Energies, specifically dedicated to the 12th SDEWES Conference, is focused on five main fields: energy policy and energy efficiency in smart energy systems, polygeneration and district heating, advanced combustion techniques and fuels, biomass and building efficiency

    (E)-3-(2,6-Dichloro­benzyl­idene)indolin-2-one

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    There are two independent mol­ecules in the asymmetric unit of the title compound, C15H9Cl2NO. The dihedral angles between the oxindolyl and dichloro­phenyl rings are essentially identical for the two independent mol­ecules [63.4 (1) and 63.2 (1)°]. Dimers linked by amide–carbonyl N—H⋯O hydrogen bonds are formed from each symmetry-independent mol­ecule and the respective symmetry equivalent created by inversion

    Cooling Performance in a Dual Energy Storage Ring Cooler

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    The longitudinal and transverse emittance growth in hadron beams due to intra-beam scattering (IBS) and other heating sources deteriorate the luminosity in a collider. Hence, a strong hadron beam cooling is required to reduce and preserve the emittance. The cooling of high energy hadron beam is challenging. We propose a dual energy storage ring-based electron cooler that uses an electron beam to extract heat away from hadron beam in the cooler ring while the electron beam is cooled by synchrotron radiation damping in the high energy damping ring. In this paper, we present a design of a dual energy storage ring-based electron cooler. Finally, the cooling performance is simulated using Jefferson Lab Simulation Package for Electron Cooling (JSPEC) for proton beams at the top energy of 275 GeV for Electron-Ion Collider

    Compact Superconducting RF-Dipole Cavity Designs for Deflecting and Crabbing Applications

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    Over the years the superconducting parallel-bar design has evolved into an rf-dipole cavity with improved properties. The new rf-dipole design is considered for a number of deflecting and crabbing applications. Some of those applications are the 499 MHz rf separator system for the Jefferson Lab 12 GeV upgrade, the 400 MHz crabbing cavity system for the proposed LHC high luminosity upgrade, and the 750 MHz crabbing cavity for the medium energy electron-ion collider in Jefferson Lab. In this paper we present the optimized rf design in terms of rf performance including rf properties, higher order modes (HOM) properties, multipacting, and multipole expansion for the above mentioned applications

    Y2, Y4 receptors and obesity

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    TPM: Cloud-Based Tele PTSD Monitor Using Multi-Dimensional Information

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    An automated system that can remotely and non-intrusively screen individuals at high risk for Post-Traumatic Stress Disorder (PTSD) and monitor their progress during treatment would be desired by many Veterans Affairs (VAs) as well as other PTSD treatment and research organizations. In this paper, we present an automated, cloud-based Tele-PTSD Monitor (TPM) system based on the fusion of multiple sources of information. The TPM system can be hosted in a cloud environment and accessed through landline or cell phones, or on the Internet through a web portal or mobile application (app)

    HOM Damping Coupler Design for the 400-MHz RF Dipole Compact Crab Cavity for the LHC HiLumi Upgrade

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    Crab cavities are adapted as the baseline design for the LHC HiLumi upgrade to achieve head-on beam-beam collisions for further improvement in luminosity. A 400- MHz compact RF dipole crab cavity design was developed by a joint effort between Old Dominion University and SLAC under the support of US LARP program. This design has shown very favorable RF parameters and can fit into the available beamline spacing for both vertical and horizontal crabbing schemes. A niobium proof-of-principle cavity based on such a design has been manufactured for vertical test. In addition, there are stringent wakefield requirements that needed to be met for such a cavity in order to preserve the quality of the circulating beams. In this paper, we will discuss different damping schemes for such a compact design and present the HOM coupler designs to meet the damping requirements

    D-SPACE4Cloud: A Design Tool for Big Data Applications

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    The last years have seen a steep rise in data generation worldwide, with the development and widespread adoption of several software projects targeting the Big Data paradigm. Many companies currently engage in Big Data analytics as part of their core business activities, nonetheless there are no tools and techniques to support the design of the underlying hardware configuration backing such systems. In particular, the focus in this report is set on Cloud deployed clusters, which represent a cost-effective alternative to on premises installations. We propose a novel tool implementing a battery of optimization and prediction techniques integrated so as to efficiently assess several alternative resource configurations, in order to determine the minimum cost cluster deployment satisfying QoS constraints. Further, the experimental campaign conducted on real systems shows the validity and relevance of the proposed method

    A Voice-Based Automated System for PTSD Screening and Monitoring

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    Comprehensive evaluation of PTSD includes diagnostic interviews, self-report testing, and physiological reactivity measures. It is often difficult and costly to diagnose PTSD due to patient access and the variability in symptoms presented. Additionally, potential patients are often reluctant to seek help due to the stigma associated with the disorder. A voice-based automated system that is able to remotely screen individuals at high risk for PTSD and monitor their symptoms during treatment has the potential to make great strides in alleviating the barriers to cost effective PTSD assessment and progress monitoring. In this paper we present a voice-based automated Tele-PTSD Monitor (TPM) system currently in development, designed to remotely screen, and provide assistance to clinicians in diagnosing PTSD. The TPM system can be accessed via a Public Switched Telephone Network (PSTN) or the Internet. The acquired voice data is then sent to a secure server to invoke the PTSD Scoring Engine (PTSD-SE) where a PTSD mental health score is computed. If the score exceeds a predefined threshold, the system will notify clinicians (via email or short message service) for confirmation and/or an appropriate follow-up assessment and intervention. The TPM system requires only voice input and performs computer-based automated PTSD scoring, resulting in low cost and easy field-deployment. The concept of the TPM system was supported using a limited dataset with an average detection accuracy of up to 95.88%
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