148 resultados para Lenclos, Ninon de, 1620-1705


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This paper presents a scalable, statistical ‘black-box’ model for predicting the performance of parallel programs on multi-core non-uniform memory access (NUMA) systems. We derive a model with low overhead, by reducing data collection and model training time. The model can accurately predict the behaviour of parallel applications in response to changes in their concurrency, thread layout on NUMA nodes, and core voltage and frequency. We present a framework that applies the model to achieve significant energy and energy-delay-square (ED2) savings (9% and 25%, respectively) along with performance improvement (10% mean) on an actual 16-core NUMA system running realistic application workloads. Our prediction model proves substantially more accurate than previous efforts.

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TBX2 is an oncogenic transcription factor known to drive breast cancer proliferation. We have identified the cysteine protease inhibitor Cystatin 6 (CST6) as a consistently repressed TBX2 target gene, co-repressed through a mechanism involving Early Growth Response 1 (EGR1). Exogenous expression of CST6 in TBX2-expressing breast cancer cells resulted in significant apoptosis whilst non-tumorigenic breast cells remained unaffected. CST6 is an important tumor suppressor in multiple tissues, acting as a dual protease inhibitor of both papain-like cathepsins and asparaginyl endopeptidases (AEPs) such as Legumain (LGMN). Mutation of the CST6 LGMN-inhibitory domain completely abrogated its ability to induce apoptosis in TBX2-expressing breast cancer cells, whilst mutation of the cathepsin-inhibitory domain or treatment with a pan-cathepsin inhibitor had no effect, suggesting that LGMN is the key oncogenic driver enzyme. LGMN activity assays confirmed the observed growth inhibitory effects were consistent with CST6 inhibition of LGMN. Knockdown of LGMN and the only other known AEP enzyme (GPI8) by siRNA confirmed that LGMN was the enzyme responsible for maintaining breast cancer proliferation. CST6 did not require secretion or glycosylation to elicit its cell killing effects, suggesting an intracellular mode of action. Finally, we show that TBX2 and CST6 displayed reciprocal expression in a cohort of primary breast cancers with increased TBX2 expression associating with increased metastases. We have also noted that tumors with altered TBX2/CST6 expression show poor overall survival. This novel TBX2-CST6-LGMN signaling pathway, therefore, represents an exciting opportunity for the development of novel therapies to target TBX2 driven breast cancers.

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Background: This study assessed the association between adolescent ecstasy use and depressive symptoms in adolescence. Methods: The Belfast Youth Development Study surveyed a cohort annually from age 11 to 16 years. Gender, Strengths and Difficulties Questionnaire emotional subscale, living arrangements, parental affluence, parent and peer attachment, tobacco, alcohol, cannabis and ecstasy use were investigated as predictors of Short Mood and Feelings Questionnaire (SMFQ) outcome. Results: Of 5371 respondents, 301 (5.6%) had an SMFQ > 15, and 1620 (30.2) had missing data for SMFQ. Around 8% of the cohort had used ecstasy by the end of follow-up. Of the non-drug users, ∼2% showed symptoms of depression, compared with 6% of those who had used alcohol, 6% of cannabis users, 6% of ecstasy users and 7% of frequent ecstasy users. Without adjustment, ecstasy users showed around a 4-fold increased odds of depressive symptoms compared with non-drug users [odds ratio (OR) = 0.26; 95% confidence interval (CI) = 0.10, 0.68]. Further adjustment for living arrangements, peer and parental attachment attenuated the association to under a 3-fold increase (OR = 0.37; 95% CI = 0.15, 0.94). There were no differences by frequency of use. Conclusions: Ecstasy use during adolescence may be associated with poorer mental health; however, this association can be explained by the confounding social influence of family dynamics. These findings could be used to aid effective evidence-based drug policies, which concentrate criminal justice and public health resources on reducing harm.

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This paper investigated the influence of three micro electrodischarge milling process parameters, which were feed rate, capacitance, and voltage. The response variables were average surface roughness (R a ), maximum peak-to-valley roughness height (R y ), tool wear ratio (TWR), and material removal rate (MRR). Statistical models of these output responses were developed using three-level full factorial design of experiment. The developed models were used for multiple-response optimization by desirability function approach to obtain minimum R a , R y , TWR, and maximum MRR. Maximum desirability was found to be 88%. The optimized values of R a , R y , TWR, and MRR were 0.04, 0.34 μm, 0.044, and 0.08 mg min−1, respectively for 4.79 μm s−1 feed rate, 0.1 nF capacitance, and 80 V voltage. Optimized machining parameters were used in verification experiments, where the responses were found very close to the predicted values.

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In this paper, we examine a novel approach to network security against passive eavesdroppers in a ray-tracing model and implement it on a hardware platform. By configuring antenna array beam patterns to transmit the data to specific regions, it is possible to create defined regions of coverage for targeted users. By adapting the antenna configuration according to the intended user’s channel state information, this allows the vulnerability of the physical regions to eavesdropping to be reduced. We present the application of our concept to 802.11n networks where an antenna array is employed at the access point. A range of antenna array configurations are examined by simulation and then realized using the Wireless Open-Access Research Platform(WARP)

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Heterogeneous computing technologies, such as multi-core CPUs, GPUs and FPGAs can provide significant performance improvements. However, developing applications for these technologies often results in coupling applications to specific devices, typically through the use of proprietary tools. This paper presents SHEPARD, a compile time and run-time framework that decouples application development from the target platform and enables run-time allocation of tasks to heterogeneous computing devices. Through the use of special annotated functions, called managed tasks, SHEPARD approximates a task's performance on available devices, and coupled with the approximation of current device demand, decides which device can satisfy the task with the lowest overall execution time. Experiments using a task parallel application, based on an in-memory database, demonstrate the opportunity for automatic run-time task allocation to achieve speed-up over a static allocation to a single specific device. © 2014 IEEE.

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Plasma etch is a key process in modern semiconductor manufacturing facilities as it offers process simplification and yet greater dimensional tolerances compared to wet chemical etch technology. The main challenge of operating plasma etchers is to maintain a consistent etch rate spatially and temporally for a given wafer and for successive wafers processed in the same etch tool. Etch rate measurements require expensive metrology steps and therefore in general only limited sampling is performed. Furthermore, the results of measurements are not accessible in real-time, limiting the options for run-to-run control. This paper investigates a Virtual Metrology (VM) enabled Dynamic Sampling (DS) methodology as an alternative paradigm for balancing the need to reduce costly metrology with the need to measure more frequently and in a timely fashion to enable wafer-to-wafer control. Using a Gaussian Process Regression (GPR) VM model for etch rate estimation of a plasma etch process, the proposed dynamic sampling methodology is demonstrated and evaluated for a number of different predictive dynamic sampling rules. © 2013 IEEE.

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We present a fully-distributed self-healing algorithm DEX, that maintains a constant degree expander network in a dynamic setting. To the best of our knowledge, our algorithm provides the first efficient distributed construction of expanders - whose expansion properties hold deterministically - that works even under an all-powerful adaptive adversary that controls the dynamic changes to the network (the adversary has unlimited computational power and knowledge of the entire network state, can decide which nodes join and leave and at what time, and knows the past random choices made by the algorithm). Previous distributed expander constructions typically provide only probabilistic guarantees on the network expansion which rapidly degrade in a dynamic setting, in particular, the expansion properties can degrade even more rapidly under adversarial insertions and deletions. Our algorithm provides efficient maintenance and incurs a low overhead per insertion/deletion by an adaptive adversary: only O(log n) rounds and O(log n) messages are needed with high probability (n is the number of nodes currently in the network). The algorithm requires only a constant number of topology changes. Moreover, our algorithm allows for an efficient implementation and maintenance of a distributed hash table (DHT) on top of DEX, with only a constant additional overhead. Our results are a step towards implementing efficient self-healing networks that have guaranteed properties (constant bounded degree and expansion) despite dynamic changes.

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In this paper, we first provide a theoretical validation for a low-complexity transmit diversity algorithm which employs only one RF chain and a low-complexity switch for transmission. Our theoretical analysis is compared to the simulation results and proved to be accurate. We then apply the transmit diversity scheme to multiple-input and multiple-output (MIMO) systems with bit-interleaved coded modulation (BICM). © 2012 IEEE.

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With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

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The propagation of UWB signals for body-centric communications within a modern classroom/conference room environment was investigated. Presented results demonstrate that the body-antenna mounting position has a marked impact on the received power levels and positioning the antenna on the chest as opposed to the shoulder or wrist creates more extreme values in receive power, mean excess delay and rms delay spread. Additionally, the best fit models for each scenario are presented and highlight the difference between the chest and other compared antenna locations. The work concluded that the chest is a poor choice of mounting position for the antenna due to significant body shadowing effects, with the wrist or shoulder considered better options for UWB systems.

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A low-profile wearable antenna suitable for integration into low-cost, disposable medical vital signs monitors is presented. Simulated and measured antenna performance was characterized on a layered human tissue phantom, representative of the thorax region of a range of human bodies. The wearable antenna has sufficient bandwidth for the 868 MHz Industrial, Scientific and Medical frequency band. Wearable radiation efficiency of up to 30 % is reported when mounted in close proximity to the novel human tissue phantom antenna test-bed at 868 MHz.

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Human occupants within indoor environments are not always stationary and their movement will lead to temporal channel variations that strongly affect the quality of indoor wireless communication systems. This paper describes a statistical channel characterization, based on experimental measurements, of human body effects on line-of-sight indoor narrowband propagation at 5.2 GHz. The analysis shows that, as the number of pedestrians within the measurement location increases, the Ricean K-factor that best fits the empirical data tends to decrease proportionally, ranging from K=7 with 1 pedestrian to K=0 with 4 pedestrians. Level crossing rate results were Rice distributed, while average fade duration results were significantly higher than theoretically computed Rice and Rayleigh, due to the fades caused by pedestrians. A novel CDF that accurately characterizes the 5.2 GHz channel in the considered indoor environment is proposed. For the first time, the received envelope CDF is explicitly described in terms of a quantitative measurement of pedestrian traffic within the indoor environment.

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The goal of the POBICOS project is a platform that facilitates the development and deployment of pervasive computing applications destined for networked, cooperating objects. POBICOS object communities are heterogeneous in terms of the sensing, actuating, and computing resources contributed by each object. Moreover, it is assumed that an object community is formed without any master plan; for example, it may emerge as a by-product of acquiring everyday, POBICOS-enabled objects by a household. As a result, the target object community is, at least partially, unknown to the application programmer, and so a POBICOS application should be able to deliver its functionality on top of diverse object communities (we call this opportunistic computing). The POBICOS platform includes a middleware offering a programming model for opportunistic computing, as well as development and monitoring tools. This paper briefly describes the tools produced in the first phase of the project. Also, the stakeholders using these tools are identified, and a development process for both the middleware and applications is presented. © 2009 IEEE.

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This paper describes middleware-level support for agent mobility, targeted at hierarchically structured wireless sensor and actuator network applications. Agent mobility enables a dynamic deployment and adaptation of the application on top of the wireless network at runtime, while allowing the middleware to optimize the placement of agents, e.g., to reduce wireless network traffic, transparently to the application programmer. The paper presents the design of the mechanisms and protocols employed to instantiate agents on nodes and to move agents between nodes. It also gives an evaluation of a middleware prototype running on Imote2 nodes that communicate over ZigBee. The results show that our implementation is reasonably efficient and fast enough to support the envisioned functionality on top of a commodity multi-hop wireless technology. Our work is to a large extent platform-neutral, thus it can inform the design of other systems that adopt a hierarchical structuring of mobile components. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.