135 resultados para 319-C0010A


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Power, and consequently energy, has recently attained first-class system resource status, on par with conventional metrics such as CPU time. To reduce energy consumption, many hardware- and OS-level solutions have been investigated. However, application-level information - which can provide the system with valuable insights unattainable otherwise - was only considered in a handful of cases. We introduce OpenMPE, an extension to OpenMP designed for power management. OpenMP is the de-facto standard for programming parallel shared memory systems, but does not yet provide any support for power control. Our extension exposes (i) per-region multi-objective optimization hints and (ii) application-level adaptation parameters, in order to create energy-saving opportunities for the whole system stack. We have implemented OpenMPE support in a compiler and runtime system, and empirically evaluated its performance on two architectures, mobile and desktop. Our results demonstrate the effectiveness of OpenMPE with geometric mean energy savings across 9 use cases of 15 % while maintaining full quality of service.

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In this work, an economical route based on hydrothermal and layer-by-layer (LBL) self-assembly processes has been developed to synthesize unique Al 2O3-modified LiV3O8 nanosheets, comprising a core of LiV3O8 nanosheets and a thin Al 2O3 nanolayer. The thickness of the Al2O 3 nanolayer can be tuned by altering the LBL cycles. When evaluated for their lithium-storage properties, the 1 LBL Al2O 3-modified LiV3O8 nanosheets exhibit a high discharge capacity of 191 mA h g-1 at 300 mA g-1 (1C) over 200 cycles and excellent rate capability, demonstrating that enhanced physical and/or chemical properties can be achieved through proper surface modification. © 2014 Elsevier B.V. All rights reserved.

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Long-term use of arsenic contaminated groundwater to irrigate crops, especially paddy rice (Oryza sativa L.) has resulted in elevated soil arsenic levels in Bangladesh. There is, therefore, concern regarding accumulation of arsenic in rice grown on these soils. A greenhouse pot experiment was conducted to evaluate the impact of arsenic-contaminated irrigation water on the growth and uptake of arsenic into rice grain, husk, straw and root. There were altogether 10 treatments which were a combination of five arsenate irrigation water concentrations (0-8 mg As l-1) and two soil phosphate amendments. Use of arsenate containing irrigation water reduced plant height, decreased rice yield and affected development of root growth. Arsenic concentrations in all plant parts increased with increasing arsenate concentration in irrigation water. However, arsenic concentration in rice grain did not exceed the maximum permissible limit of 1.0 mg As kg-1. Arsenic accumulation in rice straw at very high levels indicates that feeding cattle with such contaminated straw could be a direct threat for their health and also, indirectly, to human health via presumably contaminated bovine meat and milk. Phosphate application neither showed any significant difference in plant growth and development, nor in As concentrations in plant parts.

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The effects of potentially toxic metals on ectomycorrhizal (ECM) fungi and their higher plant hosts are examined in this review. Investigations at a species and community level have revealed wide inter- and intraspecific variation in sensitivity to metals. Adaptive and constitutive mechanisms of ECM tolerance are proposed and discussed in relation to proven tolerance mechanisms in bacteria, yeasts and plants. Problems with methodology and research priorities are highlighted. These include the need for a detailed understanding of the genetic basis of tolerance in the ECM symbiosis, and for studies of ECM community dynamics in polluted sites.

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this article discusses the three main strategies employed across the globe to raise the levels of women's political representation

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Over the last decade in a growing number of countries there has emerged an interest in the experiences of young people leaving state care. This has included a limited amount of cross national comparison. This paper reports the bleak descriptive picture of poor outcomes and lack of support that has emerged
but cautions that this be recognised as primarily expressing an Anglo-American descriptive empirical engagement with the issue. It then goes on to argue for using Esping-Anderson’s three types of welfare regime and the European Union policy goal of social inclusion as starting points to develop a more dynamic, systemic international picture of care leaving.

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As modern power grids move towards becoming a smart grid, there is an increasing reliance on the data that is transmitted and processed by ICT systems. This reliance introduces new digital attack vectors. Many of the proposed approaches that aim to address this problem largely focus on applying well-known ICT security solutions. However, what is needed are approaches that meet the complex concerns of the smart grid as a cyber-physical system. Furthermore, to support the automatic control loops that exist in a power grid, similarly automatic security and resilience mechanisms are needed that rely on minimal operator intervention. The research proposed in this paper aims to develop a framework that ensures resilient smart grid operation in light of successful cyber-attacks.

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As data analytics are growing in importance they are also quickly becoming one of the dominant application domains that require parallel processing. This paper investigates the applicability of OpenMP, the dominant shared-memory parallel programming model in high-performance computing, to the domain of data analytics. We contrast the performance and programmability of key data analytics benchmarks against Phoenix++, a state-of-the-art shared memory map/reduce programming system. Our study shows that OpenMP outperforms the Phoenix++ system by a large margin for several benchmarks. In other cases, however, the programming model is lacking support for this application domain.

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People in developing countries have faced multigenerational undernutrition and are currently undergoing major lifestyle changes, contributing to an epidemic of metabolic diseases, though the underlying mechanisms remain unclear. Using a Wistar rat model of undernutrition over 50 generations, we show that Undernourished rats exhibit low birth-weight, high visceral adiposity (DXA/MRI), and insulin resistance (hyperinsulinemic-euglycemic clamps), compared to age-/gender-matched control rats. Undernourished rats also have higher circulating insulin, homocysteine, endotoxin and leptin levels, lower adiponectin, vitamin B12 and folate levels, and an 8-fold increased susceptibility to Streptozotocin-induced diabetes compared to control rats. Importantly, these metabolic abnormalities are not reversed after two generations of unrestricted access to commercial chow (nutrient recuperation). Altered epigenetic signatures in insulin-2 gene promoter region of Undernourished rats are not reversed by nutrient recuperation, and may contribute to the persistent detrimental metabolic profiles in similar multigenerational undernourished human populations.

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WHIRLBOB, also known as STRIBOBr2, is an AEAD (Authenticated Encryption with Associated Data) algorithm derived from STRIBOBr1 and the Whirlpool hash algorithm. WHIRLBOB/STRIBOBr2 is a second round candidate in the CAESAR competition. As with STRIBOBr1, the reduced-size Sponge design has a strong provable security link with a standardized hash algorithm. The new design utilizes only the LPS or ρ component of Whirlpool in flexibly domain-separated BLNK Sponge mode. The number of rounds is increased from 10 to 12 as a countermeasure against Rebound Distinguishing attacks. The 8 ×8 - bit S-Box used by Whirlpool and WHIRLBOB is constructed from 4 ×4 - bit “MiniBoxes”. We report on fast constant-time Intel SSSE3 and ARM NEON SIMD WHIRLBOB implementations that keep full miniboxes in registers and access them via SIMD shuffles. This is an efficient countermeasure against AES-style cache timing side-channel attacks. Another main advantage of WHIRLBOB over STRIBOBr1 (and most other AEADs) is its greatly reduced implementation footprint on lightweight platforms. On many lower-end microcontrollers the total software footprint of π+BLNK = WHIRLBOB AEAD is less than half a kilobyte. We also report an FPGA implementation that requires 4,946 logic units for a single round of WHIRLBOB, which compares favorably to 7,972 required for Keccak / Keyak on the same target platform. The relatively small S-Box gate count also enables efficient 64-bit bitsliced straight-line implementations. We finally present some discussion and analysis on the relationships between WHIRLBOB, Whirlpool, the Russian GOST Streebog hash, and the recent draft Russian Encryption Standard Kuznyechik.

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Radiation induced bystander effects are secondary effects caused by the production of chemical signals by cells in response to radiation. We present a Bio-PEPA model which builds on previous modelling work in this field to predict: the surviving fraction of cells in response to radiation, the relative proportion of cell death caused by bystander signalling, the risk of non-lethal damage and the probability of observing bystander signalling for a given dose. This work provides the foundation for modelling bystander effects caused by biologically realistic dose distributions, with implications for cancer therapies.

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Controlled periodic illumination is a hypothesis postulated in the early 1990s for enhancing the efficiency of semiconductor photocatalytic reactions. This technique has been proposed to improve photocatalytic efficiency by the nature of photon introduction alone. Before its application in semiconductor photocatalysis, controlled periodic illumination had been investigated in other fields including photosynthesis. This paper presents a detailed review of the state of the art research undertaken on the application of controlled periodic illumination in semiconductor photocatalysis. The review briefly introduces semiconductor photocatalysis, and then presents a detailed explanation of this technique, its importance to photocatalytic efficiency, an overview of previous results of its application in significant studies and present knowledge. Results from previous as well as some of the most recent studies indicate potential applications of controlled periodic illumination in areas other than just the improvement of the efficiency of the photocatalytic process.

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This book provides a comprehensive tutorial on similarity operators. The authors systematically survey the set of similarity operators, primarily focusing on their semantics, while also touching upon mechanisms for processing them effectively.

The book starts off by providing introductory material on similarity search systems, highlighting the central role of similarity operators in such systems. This is followed by a systematic categorized overview of the variety of similarity operators that have been proposed in literature over the last two decades, including advanced operators such as RkNN, Reverse k-Ranks, Skyline k-Groups and K-N-Match. Since indexing is a core technology in the practical implementation of similarity operators, various indexing mechanisms are summarized. Finally, current research challenges are outlined, so as to enable interested readers to identify potential directions for future investigations.

In summary, this book offers a comprehensive overview of the field of similarity search operators, allowing readers to understand the area of similarity operators as it stands today, and in addition providing them with the background needed to understand recent novel approaches.

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The ability of an agent to make quick, rational decisions in an uncertain environment is paramount for its applicability in realistic settings. Markov Decision Processes (MDP) provide such a framework, but can only model uncertainty that can be expressed as probabilities. Possibilistic counterparts of MDPs allow to model imprecise beliefs, yet they cannot accurately represent probabilistic sources of uncertainty and they lack the efficient online solvers found in the probabilistic MDP community. In this paper we advance the state of the art in three important ways. Firstly, we propose the first online planner for possibilistic MDP by adapting the Monte-Carlo Tree Search (MCTS) algorithm. A key component is the development of efficient search structures to sample possibility distributions based on the DPY transformation as introduced by Dubois, Prade, and Yager. Secondly, we introduce a hybrid MDP model that allows us to express both possibilistic and probabilistic uncertainty, where the hybrid model is a proper extension of both probabilistic and possibilistic MDPs. Thirdly, we demonstrate that MCTS algorithms can readily be applied to solve such hybrid models.