800 resultados para cloud computing datacenter performance QoS


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Continuum parallel robots (CPRs) are manipulators employing multiple flexible beams arranged in parallel and connected to a rigid end-effector. CPRs promise higher payload and accuracy than serial CRs while keeping great flexibility. As the risk of injury during accidental contacts between a human and a CPR should be reduced, CPRs may be used in large-scale collaborative tasks or assisted robotic surgery. There exist various CPR designs, but the prototype conception is rarely based on performance considerations, and the CPRs realization in mainly based on intuitions or rigid-link parallel manipulators architectures. This thesis focuses on the performance analysis of CPRs, and the tools needed for such evaluation, such as workspace computation algorithms. In particular, workspace computation strategies for CPRs are essential for the performance assessment, since the CPRs workspace may be used as a performance index or it can serve for optimal-design tools. Two new workspace computation algorithms are proposed in this manuscript, the former focusing on the workspace volume computation and the certification of its numerical results, while the latter aims at computing the workspace boundary only. Due to the elastic nature of CPRs, a key performance indicator for these robots is the stability of their equilibrium configurations. This thesis proposes the experimental validation of the equilibrium stability assessment on a real prototype, demonstrating limitations of some commonly used assumptions. Additionally, a performance index measuring the distance to instability is originally proposed in this manuscript. Differently from the majority of the existing approaches, the clear advantage of the proposed index is a sound physical meaning; accordingly, the index can be used for a more straightforward performance quantification, and to derive robot specifications.

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Recent technological advancements have played a key role in seamlessly integrating cloud, edge, and Internet of Things (IoT) technologies, giving rise to the Cloud-to-Thing Continuum paradigm. This cloud model connects many heterogeneous resources that generate a large amount of data and collaborate to deliver next-generation services. While it has the potential to reshape several application domains, the number of connected entities remarkably broadens the security attack surface. One of the main problems is the lack of security measures to adapt to the dynamic and evolving conditions of the Cloud-To-Thing Continuum. To address this challenge, this dissertation proposes novel adaptable security mechanisms. Adaptable security is the capability of security controls, systems, and protocols to dynamically adjust to changing conditions and scenarios. However, since the design and development of novel security mechanisms can be explored from different perspectives and levels, we place our attention on threat modeling and access control. The contributions of the thesis can be summarized as follows. First, we introduce a model-based methodology that secures the design of edge and cyber-physical systems. This solution identifies threats, security controls, and moving target defense techniques based on system features. Then, we focus on access control management. Since access control policies are subject to modifications, we evaluate how they can be efficiently shared among distributed areas, highlighting the effectiveness of distributed ledger technologies. Furthermore, we propose a risk-based authorization middleware, adjusting permissions based on real-time data, and a federated learning framework that enhances trustworthiness by weighting each client's contributions according to the quality of their partial models. Finally, since authorization revocation is another critical concern, we present an efficient revocation scheme for verifiable credentials in IoT networks, featuring decentralization, demanding minimum storage and computing capabilities. All the mechanisms have been evaluated in different conditions, proving their adaptability to the Cloud-to-Thing Continuum landscape.

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The scientific success of the LHC experiments at CERN highly depends on the availability of computing resources which efficiently store, process, and analyse the amount of data collected every year. This is ensured by the Worldwide LHC Computing Grid infrastructure that connect computing centres distributed all over the world with high performance network. LHC has an ambitious experimental program for the coming years, which includes large investments and improvements both for the hardware of the detectors and for the software and computing systems, in order to deal with the huge increase in the event rate expected from the High Luminosity LHC (HL-LHC) phase and consequently with the huge amount of data that will be produced. Since few years the role of Artificial Intelligence has become relevant in the High Energy Physics (HEP) world. Machine Learning (ML) and Deep Learning algorithms have been successfully used in many areas of HEP, like online and offline reconstruction programs, detector simulation, object reconstruction, identification, Monte Carlo generation, and surely they will be crucial in the HL-LHC phase. This thesis aims at contributing to a CMS R&D project, regarding a ML "as a Service" solution for HEP needs (MLaaS4HEP). It consists in a data-service able to perform an entire ML pipeline (in terms of reading data, processing data, training ML models, serving predictions) in a completely model-agnostic fashion, directly using ROOT files of arbitrary size from local or distributed data sources. This framework has been updated adding new features in the data preprocessing phase, allowing more flexibility to the user. Since the MLaaS4HEP framework is experiment agnostic, the ATLAS Higgs Boson ML challenge has been chosen as physics use case, with the aim to test MLaaS4HEP and the contribution done with this work.

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The current dominance of African runners in long-distance running is an intriguing phenomenon that highlights the close relationship between genetics and physical performance. Many factors in the interesting interaction between genotype and phenotype (eg, high cardiorespiratory fitness, higher hemoglobin concentration, good metabolic efficiency, muscle fiber composition, enzyme profile, diet, altitude training, and psychological aspects) have been proposed in the attempt to explain the extraordinary success of these runners. Increasing evidence shows that genetics may be a determining factor in physical and athletic performance. But, could this also be true for African long-distance runners? Based on this question, this brief review proposed the role of genetic factors (mitochondrial deoxyribonucleic acid, the Y chromosome, and the angiotensin-converting enzyme and the alpha-actinin-3 genes) in the amazing athletic performance observed in African runners, especially the Kenyans and Ethiopians, despite their environmental constraints.

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A rapid, sensitive and specific method for quantifying propylthiouracil in human plasma using methylthiouracil as the internal standard (IS) is described. The analyte and the IS were extracted from plasma by liquid-liquid extraction using an organic solvent (ethyl acetate). The extracts were analyzed by high performance liquid chromatography coupled with electrospray tandem mass spectrometry (HPLC-MS/MS) in negative mode (ES-). Chromatography was performed using a Phenomenex Gemini C18 5μm analytical column (4.6mm×150mm i.d.) and a mobile phase consisting of methanol/water/acetonitrile (40/40/20, v/v/v)+0.1% of formic acid. For propylthiouracil and I.S., the optimized parameters of the declustering potential, collision energy and collision exit potential were -60 (V), -26 (eV) and -5 (V), respectively. The method had a chromatographic run time of 2.5min and a linear calibration curve over the range 20-5000ng/mL. The limit of quantification was 20ng/mL. The stability tests indicated no significant degradation. This HPLC-MS/MS procedure was used to assess the bioequivalence of two propylthiouracil 100mg tablet formulations in healthy volunteers of both sexes in fasted and fed state. The geometric mean and 90% confidence interval CI of Test/Reference percent ratios were, without and with food, respectively: 109.28% (103.63-115.25%) and 115.60% (109.03-122.58%) for Cmax, 103.31% (100.74-105.96%) and 103.40% (101.03-105.84) for AUClast. This method offers advantages over those previously reported, in terms of both a simple liquid-liquid extraction without clean-up procedures, as well as a faster run time (2.5min). The LOQ of 20ng/mL is well suited for pharmacokinetic studies. The assay performance results indicate that the method is precise and accurate enough for the routine determination of the propylthiouracil in human plasma. The test formulation with and without food was bioequivalent to reference formulation. Food administration increased the Tmax and decreased the bioavailability (Cmax and AUC).

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The aim of this study was to evaluate the performance of the Centers for Dental Specialties (CDS) in the country and associations with sociodemographic indicators of the municipalities, structural variables of services and primary health care organization in the years 2004-2009. The study used secondary data from procedures performed in the CDS to the specialties of periodontics, endodontics, surgery and primary care. Bivariate analysis by χ2 test was used to test the association between the dependent variable (performance of the CDS) with the independents. Then, Poisson regression analysis was performed. With regard to the overall achievement of targets, it was observed that the majority of CDS (69.25%) performance was considered poor/regular. The independent factors associated with poor/regular performance of CDS were: municipalities belonging to the Northeast, South and Southeast regions, with lower Human Development Index (HDI), lower population density, and reduced time to deployment. HDI and population density are important for the performance of the CDS in Brazil. Similarly, the peculiarities related to less populated areas as well as regional location and time of service implementation CDS should be taken into account in the planning of these services.

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To examine the influence of l-arginine supplementation in combination with physical training on mitochondrial biomarkers from gastrocnemius muscle and its relationship with physical performance. Male Wistar rats were divided into four groups: control sedentary (SD), sedentary supplemented with l-arginine (SDLA), trained (TR) and trained supplemented with l-arginine (TRLA). Supplementation of l-arginine was administered by gavage (62.5mg/ml/day/rat). Physical training consisted of 60min/day, 5days/week, 0% grade, speed of 1.2km/h. The study lasted 8weeks. Skeletal muscle mitochondrial enriched fraction as well as cytoplasmic fractions were obtained for Western blotting and biochemical analyses. Protein expressions of transcriptor coactivator (PGC-1α), transcriptor factors (mtTFA), ATP synthase subunit c, cytochrome oxidase (COXIV), constitutive nitric oxide synthases (eNOS and nNOS), Cu/Zn-superoxide dismutase (SOD) and manganese-SOD (Mn-SOD) were evaluated. We also assessed in plasma: lipid profile, glycemia and malondialdehyde (MDA) levels. The nitrite/nitrate (NOx(-)) levels were measured in both plasma and cytosol fraction of the gastrocnemius muscle. 8-week l-arginine supplementation associated with physical training was effective in promoting greater tolerance to exercise that was accompanied by up-regulation of the protein expressions of mtTFA, PGC-1α, ATP synthase subunit c, COXIV, Cu/Zn-SOD and Mn-SOD. The upstream pathway was associated with improvement of NO bioavailability, but not in NO production since no changes in nNOS or eNOS protein expressions were observed. This combination would be an alternative approach for preventing cardiometabolic diseases given that in overt diseases a profound impairment in the physical performance of the patients is observed.

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Objective Adapt the 6 minutes walking test (6MWT) to artificial gait in complete spinal cord injured (SCI) patients aided by neuromuscular electrical stimulation. Method Nine male individuals with paraplegia (AIS A) participated in this study. Lesion levels varied between T4 and T12 and time post injured from 4 to 13 years. Patients performed 6MWT 1 and 6MWT 2. They used neuromuscular electrical stimulation, and were aided by a walker. The differences between two 6MWT were assessed by using a paired t test. Multiple r-squared was also calculated. Results The 6MWT 1 and 6MWT 2 were not statistically different for heart rate, distance, mean speed and blood pressure. Multiple r-squared (r2 = 0.96) explained 96% of the variation in the distance walked. Conclusion The use of 6MWT in artificial gait towards assessing exercise walking capacity is reproducible and easy to apply. It can be used to assess SCI artificial gait clinical performance.

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The pathological mechanisms underlying cognitive dysfunction in multiple sclerosis (MS) are not yet fully understood and, in addition to demyelinating lesions and gray-matter atrophy, subclinical disease activity may play a role. To evaluate the contribution of asymptomatic gadolinium-enhancing lesions to cognitive dysfunction along with gray-matter damage and callosal atrophy in relapsing-remitting MS (RRMS) patients. Forty-two treated RRMS and 30 controls were evaluated. MRI (3T) variables of interest were brain white-matter and cortical lesion load, cortical and deep gray-matter volumes, corpus callosum volume and presence of gadolinium-enhancing lesions. Outcome variables included EDSS, MS Functional Composite (MSFC) subtests and the Brief Repeatable Battery of Neuropsychological tests. Cognitive dysfunction was classified as deficits in two or more cognitive subtests. Multivariate regression analyses assessed the contribution of MRI metrics to outcomes. Patients with cognitive impairment (45.2%) had more cortical lesions and lower gray-matter and callosal volumes. Patients with subclinical MRI activity (15%) had worse cognitive performance. Clinical disability on MSFC was mainly associated with putaminal atrophy. The main independent predictors for cognitive deficits were high burden of cortical lesions and number of gadolinium-enhancing lesions. Cognitive dysfunction was especially related to high burden of cortical lesions and subclinical disease activity. Cognitive studies in MS should look over subclinical disease activity as a potential contributor to cognitive impairment.

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cDNA arrays are a powerful tool for discovering gene expression patterns. Nylon arrays have the advantage that they can be re-used several times. A key issue in high throughput gene expression analysis is sensitivity. In the case of nylon arrays, signal detection can be affected by the plastic bags used to keep membranes humid. In this study, we evaluated the effect of five types of plastics on the radioactive transmittance, number of genes with a signal above the background, and data variability. A polyethylene plastic bag 69 μm thick had a strong shielding effect that blocked 68.7% of the radioactive signal. The shielding effect on transmittance decreased the number of detected genes and increased the data variability. Other plastics which were thinner gave better results. Although plastics made from polyvinylidene chloride, polyvinyl chloride (both 13 μm thick) and polyethylene (29 and 7 μm thick) showed different levels of transmittance, they all gave similarly good performances. Polyvinylidene chloride and polyethylene 29 mm thick were the plastics of choice because of their easy handling. For other types of plastics, it is advisable to run a simple check on their performance in order to obtain the maximum information from nylon cDNA arrays.

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Handball is a sport that demands endurance associated with fast and powerful actions such as jumps, blocks, sprints and throws. The aim of this study was to evaluate the effects of a 38-week systematic physical training applied to a women's under 21 handball team on upper and lower limb power, 30m sprints speed and endurance. The periodization applied was an adaptation of the Verkhoshansky theory, and aimed at two performance peaks during the season with six data collections. The median and range values for three kg medicine ball throwing was: 2.98m (2.15-3.50); 2.84m (2.43-3.20); 2.90m (2.60-3.38); 3.10 (2.83-3.81); 2.84 (2.55-3.57) and 3.34 (2.93-3.83). Regarding the three-pass running test: 5.60m (4.93-6.58); 5.37m (5.04-6.38); 5.36m (4.93-6.12); 5.65m (4.80-6.78); 5.63m (5.00-6.40) and 5.83m (5.14-6.05). Regarding the 30-m sprint test: 5.8m/s (5.45-6.44); 6,64 m/s (6,24-7,09); 5.65m/s (5.17-5.95); (there was not IV moment for this test); 6.19 m/s (5.57-6.26) and 5.83 (5.14-6.05).Regarding the 30-m sprint endurance test until 10% decrease: 4 sprints (4-6); 5 sprints (4-9); 4,5 sprints (4-16); (there was not IV moment for this test); 6 sprints (4-12) and 5 sprints (4-5). Significant differences (p<0.05) were observed in three kg medicine ball throwing and three-pass running tests at least in one of the performance peak planned, with no significant differences in 30-m sprint speed or endurance tests. The applied physical training was efficient at improving the specific physical fitness in the performance peaks, as well as giving support for better physical training adjustment for the upcoming season.

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Universidade Estadual de Campinas. Faculdade de Educação Física