12 resultados para Distributed Traffic Control

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Objectives: Recent anatomical-functional studies have transformed our understanding of cerebral motor control away from a hierarchical structure and toward parallel and interconnected specialized circuits. Subcortical electrical stimulation during awake surgery provides a unique opportunity to identify white matter tracts involved in motor control. For the first time, this study reports the findings on motor modulatory responses evoked by subcortical stimulation and investigates the cortico-subcortical connectivity of cerebral motor control. Experimental design: Twenty-one selected patients were operated while awake for frontal, insular, and parietal diffuse low-grade gliomas. Subcortical electrostimulation mapping was used to search for interference with voluntary movements. The corresponding stimulation sites were localized on brain schemas using the anterior and posterior commissures method. Principal observations: Subcortical negative motor responses were evoked in 20/21 patients, whereas acceleration of voluntary movements and positive motor responses were observed in three and five patients, respectively. The majority of the stimulation sites were detected rostral of the corticospinal tract near the vertical anterior-commissural line, and additional sites were seen in the frontal and parietal white matter. Conclusions: The diverse interferences with motor function resulting in inhibition and acceleration imply a modulatory influence of the detected fiber network. The subcortical stimulation sites were distributed veil-like, anterior to the primary motor fibers, suggesting descending pathways originating from premotor areas known for negative motor response characteristics. Further stimulation sites in the parietal white matter as well as in the anterior arm of the internal capsule indicate a large-scale fronto-parietal motor control network. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.

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Biomarkers are currently best used as mechanistic "signposts" rather than as "traffic lights" in the environmental risk assessment of endocrine-disrupting chemicals (EDCs). In field studies, biomarkers of exposure [e.g., vitellogenin (VTG) induction in male fish] are powerful tools for tracking single substances and mixtures of concern. Biomarkers also provide linkage between field and laboratory data, thereby playing an important role in directing the need for and design of fish chronic tests for EDCs. It is the adverse effect end points (e.g., altered development, growth, and/or reproduction) from such tests that are most valuable for calculating adverseNOEC (no observed effect concentration) or adverseEC10 (effective concentration for a 10% response) and subsequently deriving predicted no effect concentrations (PNECs). With current uncertainties, biomarkerNOEC or biomarkerEC10 data should not be used in isolation to derive PNECs. In the future, however, there may be scope to increasingly use biomarker data in environmental decision making, if plausible linkages can be made across levels of organization such that adverse outcomes might be envisaged relative to biomarker responses. For biomarkers to fulfil their potential, they should be mechanistically relevant and reproducible (as measured by interlaboratory comparisons of the same protocol). VTG is a good example of such a biomarker in that it provides an insight to the mode of action (estrogenicity) that is vital to fish reproductive health. Interlaboratory reproducibility data for VTG are also encouraging; recent comparisons (using the same immunoassay protocol) have provided coefficients of variation (CVs) of 38-55% (comparable to published CVs of 19-58% for fish survival and growth end points used in regulatory test guidelines). While concern over environmental xenoestrogens has led to the evaluation of reproductive biomarkers in fish, it must be remembered that many substances act via diverse mechanisms of action such that the environmental risk assessment for EDCs is a broad and complex issue. Also, biomarkers such as secondary sexual characteristics, gonadosomatic indices, plasma steroids, and gonadal histology have significant potential for guiding interspecies assessments of EDCs and designing fish chronic tests. To strengthen the utility of EDC biomarkers in fish, we need to establish a historical control database (also considering natural variability) to help differentiate between statistically detectable versus biologically significant responses. In conclusion, as research continues to develop a range of useful EDC biomarkers, environmental decision-making needs to move forward, and it is proposed that the "biomarkers as signposts" approach is a pragmatic way forward in the current risk assessment of EDCs.

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Tonoplast, the membrane delimiting plant vacuoles, regulates ion, water and nutrient movement between the cytosol and the vacuolar lumen through the activity of its membrane proteins. Correct traffic of proteins from the endoplasmic reticulum (ER) to the tonoplast requires (i) approval by the ER quality control, (ii) motifs for exit from the ER and (iii) motifs that promote sorting to the tonoplast. Recent evidence suggests that this traffic follows different pathways that are protein-specific and could also reflect vacuole specialization for lytic or storage function. The routes can be distinguished based on their sensitivity to drugs such as brefeldin A and C834 as well as using mutant plants that are defective in adaptor proteins of vesicle coats, or dominant-negative mutants of Rab GTPases.

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Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.

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The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

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This paper is a summary of the main contribu- tions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the commu- nication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with con- tributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is intro- duced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a metho- dology for robust, reliable and accurate software-based energy-estimation, which is calculated at network run- time on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adap- tively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communi- cations in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the perfor- mance degrading effects of packet corruption and trans- mission failures when transmitting data over multiple hops. The performance of all developed protocols are eval- uated on a self-developed real-world WSN testbed and achieve superior performance over selected existing ap- proaches, especially where traffic load and channel condi- tions are suspect to rapid variations over time.

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Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

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The present topical review deals with the motor control of facial expressions in humans. Facial expressions are a central part of human communication. Emotional face expressions have a crucial role in human non-verbal behavior, allowing a rapid transfer of information between individuals. Facial expressions can be both voluntarily or emotionally controlled. Recent studies in non-human primates and humans revealed that the motor control of facial expressions has a distributed neural representation. At least 5 cortical regions on the medial and lateral aspects of each hemisphere are involved: the primary motor cortex, the ventral lateral premotor cortex, the supplementary motor area on the medial wall, and, finally, the rostral and caudal cingulate cortex. The results of studies in humans and non-human primates suggest that the innervation of the face is bilaterally controlled for the upper part, and mainly contralaterally controlled for the lower part. Furthermore, the primary motor cortex, the ventral lateral premotor cortex, and the supplementary motor area are essential for the voluntary control of facial expressions. In contrast, the cingulate cortical areas are important for emotional expression, since they receive input from different structures of the limbic system. This article is protected by copyright. All rights reserved.

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Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

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The 15N ratio of nitrogen oxides (NOx) emitted from vehicles, measured in the air adjacent to a highway in the Swiss Middle Land, was very high [δ15N(NO2) = +5.7‰]. This high 15N abundance was used to estimate long-term NO2 dry deposition into a forest ecosystem by measuring δ15N in the needles and the soil of potted and autochthonous spruce trees [Picea abies (L.) Karst] exposed to NO2 in a transect orthogonal to the highway. δ15N in the current-year needles of potted trees was 2.0‰ higher than that of the control after 4 months of exposure close to the highway, suggesting a 25% contribution to the N-nutrition of these needles. Needle fall into the pots was prevented by grids placed above the soil, while the continuous decomposition of needle litter below the autochthonous trees over previous years has increased δ15N values in the soil, resulting in parallel gradients of δ15N in soil and needles with distance from the highway. Estimates of NO2 uptake into needles obtained from the δ15N data were significantly correlated with the inputs calculated with a shoot gas exchange model based on a parameterisation widely used in deposition modelling. Therefore, we provide an indication of estimated N inputs to forest ecosystems via dry deposition of NO2 at the receptor level under field conditions.

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Analogue model experiments using both brittle and viscous materials were performed to investigate the development and interaction of strike-slip faults in zones of distributed shear deformation. At low strain, bulk dextral shear deformation of an initial rectangular model is dominantly accommodated by left-stepping, en echelon strike-slip faults (Riedel shears, R) that form in response to the regional (bulk) stress field. Push-up zones form in the area of interaction between adjacent left-stepping Riedel shears. In cross sections, faults bounding push-up zones have an arcuate shape or merge at depth. Adjacent left-stepping R shears merge by sideways propagation or link by short synthetic shears that strike subparallel to the bulk shear direction. Coalescence of en echelon R shears results in major, through-going faults zones (master faults). Several parallel master faults develop due to the distributed nature of deformation. Spacing between master faults is related to the thickness of the brittle layers overlying the basal viscous layer. Master faults control to a large extent the subsequent fault pattern. With increasing strain, relatively short antithetic and synthetic faults develop mostly between old, but still active master faults. The orientation and evolution of the new faults indicate local modifications of the stress field. In experiments lacking lateral borders, closely spaced parallel antithetic faults (cross faults) define blocks that undergo clockwise rotation about a vertical axis with continuing deformation. Fault development and fault interaction at different stages of shear strain in our models show similarities with natural examples that have undergone distributed shear.