932 resultados para Dynamic performance
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Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.
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Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.
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Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.
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Key performance features of a miniature laser ablation time-of-flight mass spectrometer designed for in situ investigations of the chemical composition of planetary surfaces are presented. This mass spectrometer is well suited for elemental and isotopic analysis of raw solid materials with high sensitivity and high spatial resolution. In this study, ultraviolet laser radiation with irradiances suitable for ablation (< 1 GW/cm2) is used to achieve stable ion formation and low sample consumption. In comparison to our previous laser ablation studies at infrared wavelengths, several improvements to the experimental setup have been made, which allow accurate control over the experimental conditions and good reproducibility of measurements. Current performance evaluations indicate significant improvements to several instrumental figures of merit. Calibration of the mass scale is performed within a mass accuracy (Δm/m) in the range of 100 ppm, and a typical mass resolution (m/Δm) ~600 is achieved at the lead mass peaks. At lower laser irradiances, the mass resolution is better, about (m/Δm) ~900 for lead, and limited by the laser pulse duration of 3 ns. The effective dynamic range of the instrument was enhanced from about 6 decades determined in previous study up to more than 8 decades at present. Current studies show high sensitivity in detection of both metallic and non-metallic elements. Their abundance down to tens of ppb can be measured together with their isotopic patterns. Due to strict control of the experimental parameters, e.g. laser characteristics, ion-optical parameters and sample position, by computer control, measurements can be performed with high reproducibility. Copyright © 2012 John Wiley & Sons, Ltd.
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Einleitung Aktuelle empirische Befunde deuten darauf hin, dass Sportler/innen durch Stress und erhöhte Angst eine reduzierte Effizienz bei der Entscheidungsfindung aufweisen (Wilson, 2008). Erklärt werden kann dieser Befund durch die Attentional-Control-Theory (ACT, Eysenck et al., 2007), die postuliert, dass aufmerksamkeitslenkende Prozesse unter Angst gestört werden. Um diese Annahme für komplexe Situationen im Sport zu prüfen, wurden Fußballspieler unter erhöhten und regulären Druckbedingungen verglichen. Methode Je 11 Experten und Nicht-Experten hatten aus der Perspektive des Abwehrspielers die Aufgabe, in zwei mal 24 Spielsituationen so schnell und korrekt wie möglich verbal anzugeben, welche Aktion der ballführende Spieler (in naher vs. ferner Spielsituation) nach Ausblendung der Szene ausführen wird. Während im ersten Block der Druck nicht erhöht wurde, wurden Druckbedingungen im zweiten Block u.a. durch eine Wettkampfsituation und „falscher“ Ergebnisrückmeldung gesteigert. Entscheidungs- und Blickverhalten (u.a. Anzahl Fixationen), Pupillengröße, Zustandsangst und „Mental Effort“ (Wilson, 2008) wurden erfasst. Neben Expertiseunterschieden wurde erwartet, dass erhöhte Angst die Entscheidungseffizienz sowie das Blickverhalten stört (ACT-Annahme), was mit 2 (Experten/Nicht-Experten) x 2 (nahe/ferne Spielsituation) x 2 (hohe/reguläre Druckbedingung) ANOVAs (? = .05) mit Messwiederholungen auf den letzten beiden Faktoren geprüft wurde. Ergebnisse Druckmanipulationen führten zu höherer Zustandsangst und größeren Pupillendurchmessern. Neben Expertiseunterschieden – Experten antworteten schneller, korrekter und zeigten ein situationsangepasstes visuelles Suchverhalten – wiesen beide Gruppen in Drucksituationen längere Antwortzeiten und höheren Mental Effort auf. Erhöhter Druck führte bei Experten zur Reduktion der Fixationsortwechsel für ferne Spielsituationen. Nicht-Experten differenzierten ihr Suchverhalten weder zwischen Bedingungen noch für Spielsituationen. Diskussion Die Resultate bestätigen die ACT-Annahme, dass Angst und Stress die sportliche Leistung durch längere Reaktionszeiten, höhere kognitive Anstrengung und ein teilweise ineffizientes visuelles Suchverhalten negativ beeinflusst. Eine gestörte Balance zwischen Top-Down und Bottom-Up-Prozessen könnte die Ursache sein (Eysenck et al., 2007). Literatur Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336–353. Wilson, M. (2008). From processing efficiency to attentional control: A mechanistic account of the anxiety-performance relationship. International Review of Sport and Exercise Psychology, 1, 184– 201. 2 Vorträge und Poster
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STUDY DESIGN Biomechanical cadaveric study. OBJECTIVE To determine whether augmentation positively influence screw stability or not. SUMMARY OF BACKGROUND DATA Implantation of pedicle screws is a common procedure in spine surgery to provide an anchorage of posterior internal fixation into vertebrae. Screw performance is highly correlated to bone quality. Therefore, polymeric cement is often injected through specifically designed perforated pedicle screws into osteoporotic bone to potentially enhance screw stability. METHODS Caudocephalic dynamic loading was applied as quasi-physiological alternative to classical pull-out tests on 16 screws implanted in osteoporotic lumbar vertebrae and 20 screws in nonosteoporotic specimen. Load was applied using 2 different configurations simulating standard and dynamic posterior stabilization devices. Screw performance was quantified by measurement of screwhead displacement during the loading cycles. To reduce the impact of bone quality and morphology, screw performance was compared for each vertebra and averaged afterward. RESULTS All screws (with or without cement) implanted in osteoporotic vertebrae showed lower performances than the ones implanted into nonosteoporotic specimen. Augmentation was negligible for screws implanted into nonosteoporotic specimen, whereas in osteoporotic vertebrae pedicle screw stability was significantly increased. For dynamic posterior stabilization system an increase of screwhead displacement was observed in comparison with standard fixation devices in both setups. CONCLUSION Augmentation enhances screw performance in patients with poor bone stock, whereas no difference is observed for patients without osteoporosis. Furthermore, dynamic stabilization systems have the possibility to fail when implanted in osteoporotic bone.
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AIM MRI and PET with 18F-fluoro-ethyl-tyrosine (FET) have been increasingly used to evaluate patients with gliomas. Our purpose was to assess the additive value of MR spectroscopy (MRS), diffusion imaging and dynamic FET-PET for glioma grading. PATIENTS, METHODS 38 patients (42 ± 15 aged, F/M: 0.46) with untreated histologically proven brain gliomas were included. All underwent conventional MRI, MRS, diffusion sequences, and FET-PET within 3±4 weeks. Performances of tumour FET time-activity-curve, early-to-middle SUVmax ratio, choline / creatine ratio and ADC histogram distribution pattern for gliomas grading were assessed, as compared to histology. Combination of these parameters and respective odds were also evaluated. RESULTS Tumour time-activity-curve reached the best accuracy (67%) when taken alone to distinguish between low and high-grade gliomas, followed by ADC histogram analysis (65%). Combination of time-activity-curve and ADC histogram analysis improved the sensitivity from 67% to 86% and the specificity from 63-67% to 100% (p < 0.008). On multivariate logistic regression analysis, negative slope of the tumour FET time-activity-curve however remains the best predictor of high-grade glioma (odds 7.6, SE 6.8, p = 0.022). CONCLUSION Combination of dynamic FET-PET and diffusion MRI reached good performance for gliomas grading. The use of FET-PET/MR may be highly relevant in the initial assessment of primary brain tumours.
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We tested the predictions of Attentional Control Theory (ACT) by examining how anxiety affects visual search strategies, performance efficiency, and performance effectiveness using a dynamic, temporal-constrained anticipation task. Higher and lower skilled players viewed soccer situations under 2 task constraints (near vs. far situation) and were tested under high (HA) and low (LA) anxiety conditions. Response accuracy (effectiveness) and response time, perceived mental effort, and eye-movements (all efficiency) were recorded. A significant increase in anxiety was evidenced by higher state anxiety ratings on the MRF-L scale. Increased anxiety led to decreased performance efficiency because response times and mental effort increased for both skill groups whereas response accuracy did not differ. Anxiety influenced search strategies, with higher skilled players showing a decrease in number of fixation locations for far situations under HA compared with LA condition when compared with lower skilled players. Findings provide support for ACT with anxiety impairing processing efficiency and, potentially, top-down attentional control across different task constraints.
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More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^
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Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.
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Current nanometer technologies suffer within-die parameter uncertainties, varying workload conditions, aging, and temperature effects that cause a serious reduction on yield and performance. In this scenario, monitoring, calibration, and dynamic adaptation become essential, demanding systems with a collection of multi purpose monitors and exposing the need for light-weight monitoring networks. This paper presents a new monitoring network paradigm able to perform an early prioritization of the information. This is achieved by the introduction of a new hierarchy level, the threshing level. Targeting it, we propose a time-domain signaling scheme over a single-wire that minimizes the network switching activity as well as the routing requirements. To validate our approach, we make a thorough analysis of the architectural trade-offs and expose two complete monitoring systems that suppose an area improvement of 40% and a power reduction of three orders of magnitude compared to previous works.
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The traditional ballast track structures are still being used in high speed railways lines with success, however technical problems or performance features have led to non-ballast track solution in some cases. A considerable maintenance work is needed for ballasted tracks due to the track deterioration. Therefore it is very important to understand the mechanism of track deterioration and to predict the track settlement or track irregularity growth rate in order to reduce track maintenance costs and enable new track structures to be designed. The objective of this work is to develop the most adequate and efficient models for calculation of dynamic traffic load effects on railways track infrastructure, and then evaluate the dynamic effect on the ballast track settlement, using a ballast track settlement prediction model, which consists of the vehicle/track dynamic model previously selected and a track settlement law. The calculations are based on dynamic finite element models with direct time integration, contact between wheel and rail and interaction with railway cars. A initial irregularity profile is used in the prediction model. The track settlement law is considered to be a function of number of loading cycles and the magnitude of the loading, which represents the long-term behavior of ballast settlement. The results obtained include the track irregularity growth and the contact force in the final interaction of numerical simulation
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This paper reports the studies carried out to develop and calibrate the optimal models for the objectives of this work. In particular, quarter bogie model for vehicle, rail-wheel contact with Lagrangian multiplier method, 2D spatial discretization were selected as the optimal decisions. Furthermore, the 3D model of coupled vehicle-track also has been developed to contrast the results obtained in the 2D model. The calculations were carried out in the time domain and envelopes of relevant results were obtained for several track profiles and speed ranges. Distributed elevation irregularities were generated based on power spectral density (PSD) distributions. The results obtained include the wheel-rail contact forces, forces transmitted to the bogie by primary suspension. The latter loads are relevant for the purpose of evaluating the performance of the infrastructure
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This paper introduces a method to analyze and predict stability and transient performance of a distributed system where COTS (Commercial-off-the-shelf) modules share an input filter. The presented procedure is based on the measured data from the input and output terminals of the power modules. The required information for the analysis is obtained by performing frequency response measurements for each converter. This attained data is utilized to compute special transfer functions, which partly determine the source and load interactions within the converters. The system level dynamic description is constructed based on the measured and computed transfer functions introducing cross-coupling mechanisms within the system. System stability can be studied based on the well-known impedance- related minor-loop gain at an arbitrary interface within the system.
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Based on our needs, that is to say, through precise simulation of the impact phenomena that may occur inside a jet engine turbine with an explicit non-linear finite element code, four new material models are postulated. Each one of is calibrated for four high-performance alloys that can be encountered in a modern jet engine. A new uncoupled material model for high strain and ballistic is proposed. Based on a Johnson-Cook type model, the proposed formulation introduces the effect of the third deviatoric invariant by means of three different Lode angle dependent functions. The Lode dependent functions are added to both plasticity and failure models. The postulated model is calibrated for a 6061-T651 aluminium alloy with data taken from the literature. The fracture pattern predictability of the JCX material model is shown performing numerical simulations of various quasi-static and dynamic tests. As an extension of the above-mentioned model, a modification in the thermal softening behaviour due to phase transformation temperatures is developed (JCXt). Additionally, a Lode angle dependent flow stress is defined. Analysing the phase diagram and high temperature tests performed, phase transformation temperatures of the FV535 stainless steel are determined. The postulated material model constants for the FV535 stainless steel are calibrated. A coupled elastoplastic-damage material model for high strain and ballistic applications is presented (JCXd). A Lode angle dependent function is added to the equivalent plastic strain to failure definition of the Johnson-Cook failure criterion. The weakening in the elastic law and in the Johnson-Cook type constitutive relation implicitly introduces the Lode angle dependency in the elastoplastic behaviour. The material model is calibrated for precipitation hardened Inconel 718 nickel-base superalloy. The combination of a Lode angle dependent failure criterion with weakened constitutive equations is proven to predict fracture patterns of the mechanical tests performed and provide reliable results. A transversely isotropic material model for directionally solidified alloys is presented. The proposed yield function is based a single linear transformation of the stress tensor. The linear operator weighs the degree of anisotropy of the yield function. The elastic behaviour, as well as the hardening, are considered isotropic. To model the hardening, a Johnson-Cook type relation is adopted. A material vector is included in the model implementation. The failure is modelled with the Cockroft-Latham failure criterion. The material vector allows orienting the reference orientation in any other that the user may need. The model is calibrated for the MAR-M 247 directionally solidified nickel-base superalloy.