14 resultados para High-performance computing resources

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


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Carnitine is an amino acid derivative that plays a key role in energy metabolism. Endogenous carnitine is found in its free form or esterified with acyl groups of several chain lengths. Quantification of carnitine and acylcarnitines is of particular interest for screening for research and metabolic disorders. We developed a method with online solid-phase extraction coupled to high-performance liquid chromatography and tandem mass spectrometry to quantify carnitine and three acylcarnitines with different polarity (acetylcarnitine, octanoylcarnitine, and palmitoylcarnitine). Plasma samples were deproteinized with methanol, loaded on a cation exchange trapping column and separated on a reversed-phase C8 column using heptafluorobutyric acid as an ion-pairing reagent. Considering the endogenous nature of the analytes, we quantified with the standard addition method and with external deuterated standards. Solid-phase extraction and separation were achieved within 8 min. Recoveries of carnitine and acylcarnitines were between 98 and 105 %. Both quantification methods were equally accurate (all values within 84 to 116 % of target concentrations) and precise (day-to-day variation of less than 18 %) for all carnitine species and concentrations analyzed. The method was used successfully for determination of carnitine and acylcarnitines in different human samples. In conclusion, we present a method for simultaneous quantification of carnitine and acylcarnitines with a rapid sample work-up. This approach requires small sample volumes and a short analysis time, and it can be applied for the determination of other acylcarnitines than the acylcarnitines tested. The method is useful for applications in research and clinical routine.

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A convenient and rapid method for the simultaneous determination by HPLC of 3-hydroxyanthranilic acid and the dimer derived by its oxidation, cinnabarinic acid, is described. Buffers or biological samples containing these two Trp metabolites were acidified to pH 2.0 and extracted with ethyl acetate with recoveries of 96.5 +/- 0.5 and 93.4 +/- 3.7% for 3-hydroxyanthranilic and cinnabarinic acid, respectively. The two compounds were separated on a reversed-phase (C18) column combined with ion-pair chromatography and detected photometrically or electrochemically. The method was applied successfully to biological systems in which formation of either 3-hydroxyanthranilic or cinnabarinic acid had been described previously. Thus, interferon-gamma-treated human peripheral blood mononuclear cells formed and released significant amounts of 3-hydroxyanthranilic acid into the culture medium and mouse liver nuclear fraction possessed high "cinnabarinic acid synthase" activity. In contrast, addition of 3-hydroxyanthranilic acid to human erythrocytes resulted in only marginal formation of cinnabarinic acid. We conclude that the method described is specific, sensitive, and suitable for the detection of the two Trp metabolites in biological systems.

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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 increasing interest in autonomous coordinated driving and in proactive safety services, exploiting the wealth of sensing and computing resources which are gradually permeating the urban and vehicular environments, is making provisioning of high levels of QoS in vehicular networks an urgent issue. At the same time, the spreading model of a smart car, with a wealth of infotainment applications, calls for architectures for vehicular communications capable of supporting traffic with a diverse set of performance requirements. So far efforts focused on enabling a single specific QoS level. But the issues of how to support traffic with tight QoS requirements (no packet loss, and delays inferior to 1ms), and of designing a system capable at the same time of efficiently sustaining such traffic together with traffic from infotainment applications, are still open. In this paper we present the approach taken by the CONTACT project to tackle these issues. The goal of the project is to investigate how a VANET architecture, which integrates content-centric networking, software-defined networking, and context aware floating content schemes, can properly support the very diverse set of applications and services currently envisioned for the vehicular environment.

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BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

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OBJECT: Disturbed ionic and neurotransmitter homeostasis are now recognized as probably the most important mechanisms contributing to the development of secondary brain swelling after traumatic brain injury (TBI). Evidence obtained in animal models indicates that posttraumatic neuronal excitation by excitatory amino acids leads to an increase in extracellular potassium, probably due to ion channel activation. The purpose of this study was therefore to measure dialysate potassium in severely head injured patients and to correlate these results with measurements of intracranial pressure (ICP), patient outcome, and levels of dialysate glutamate and lactate, and cerebral blood flow (CBF) to determine the role of ischemia in this posttraumatic ion dysfunction. METHODS: Eighty-five patients with severe TBI (Glasgow Coma Scale Score < 8) were treated according to an intensive ICP management-focused protocol. All patients underwent intracerebral microdialyis. Dialysate potassium levels were analyzed using flame photometry, and dialysate glutamate and dialysate lactate levels were measured using high-performance liquid chromatography and an enzyme-linked amperometric method in 72 and 84 patients, respectively. Cerebral blood flow studies (stable xenon computerized tomography scanning) were performed in 59 patients. In approximately 20% of the patients, dialysate potassium values were increased (dialysate potassium > 1.8 mM) for 3 hours or more. A mean amount of dialysate potassium greater than 2 mM throughout the entire monitoring period was associated with ICP above 30 mm Hg and fatal outcome, as were progressively rising levels of dialysate potassium. The presence of dialysate potassium correlated positively with dialysate glutamate (p < 0.0001) and lactate (p < 0.0001) levels. Dialysate potassium was significantly inversely correlated with reduced CBF (p = 0.019). CONCLUSIONS: Dialysate potassium was increased after TBI in 20% of measurements. High levels of dialysate potassium were associated with increased ICP and poor outcome. The simultaneous increase in dialysate potassium, together with dialysate glutamate and lactate, supports the concept that glutamate induces ionic flux and consequently increases ICP, which the authors speculate may be due to astrocytic swelling. Reduced CBF was also significantly correlated with increased levels of dialysate potassium. This may be due to either cell swelling or altered vasoreactivity in cerebral blood vessels caused by higher levels of potassium after trauma. Additional studies in which potassium-sensitive microelectrodes are used are needed to validate these ionic events more clearly.

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Disturbed ionic and neurotransmitter homeostasis are now recognized to be probably the most important mechanisms contributing to the development of secondary brain swelling after traumatic brian injury (TBI). Evidence obtained from animal models indicates that posttraumatic neuronal excitation via excitatory amino acids leads to an increase in extracellular potassium, probably due to ion channel activation. The purpose of this study was therefore to measure dialysate potassium in severely head injured patients and to correlate these results with intracranial pressure (ICP), outcome, and also with the levels of dialysate glutamate, lactate, and cerebral blood flow (CBF) so as to determine the role of ischemia in this posttraumatic ionic dysfunction. Eighty-five patients with severe TBI (Glasgow Coma Scale score < 8) were treated according to an intensive ICP management-focused protocol. All patients underwent intracerebral microdialyis. Dialysate potassium levels were analyzed by flame photometry, as were dialysate glutamate and dialysate lactate levels, which were measured using high-performance liquid chromatography and an enzyme-linked amperometric method in 72 and 84 patients respectively. Cerebral blood flow studies (stable Xenon--computerized tomography scanning) were performed in 59 patients. In approximately 20% of the patients, potassium values were increased (dialysate potassium > 1.8 mmol). Mean dialysate potassium (> 2 mmol) was associated with ICP above 30 mm Hg and fatal outcome. Dialysate potassium correlated positively with dialysate glutamate (p < 0.0001) and lactate levels (p < 0.0001). Dialysate potassium was significantly inversely correlated with reduced CBF (p = 0.019). Dialysate potassium was increased after TBI in 20% of measurements. High levels of dialysate potassium were associated with increased ICP and poor outcome. The simultaneous increase of potassium, together with dialysate glutamate and lactate, supports the hypothesis that glutamate induces ionic flux and consequently increases ICP due to astrocytic swelling. Reduced CBF was also significantly correlated with increased levels of dialysate potassium. This may be due to either cell swelling or altered potassium reactivity in cerebral blood vessels after trauma.

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To date, despite a large body of evidence in favor of the advantage of an effect-related focus of attention compared with a movement-related focus of attention in motor control and learning, the role of vision in this context remains unclear. Therefore, in a golf-putting study, the relation between attentional focus and gaze behavior (in particular, quiet eye, or QE) was investigated. First, the advantage of an effect-related focus, as well as of a long QE duration, could be replicated. Furthermore, in the online-demanding task of golf putting, high performance was associated with later QE offsets. Most decisively, an interaction between attentional focus and gaze behavior was revealed in such a way that the efficiency of the QE selectively manifested under movement-related focus instructions. As these findings suggest neither additive effects nor a causal chain, an alternative hypothesis is introduced explaining positive QE effects by the inhibition of not-to-be parameterized movement variants.

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Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

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Historic records of α-dicarbonyls (glyoxal, methylglyoxal), carboxylic acids (C6–C12 dicarboxylic acids, pinic acid, p-hydroxybenzoic acid, phthalic acid, 4-methylphthalic acid), and ions (oxalate, formate, calcium) were determined with annual resolution in an ice core from Grenzgletscher in the southern Swiss Alps, covering the time period from 1942 to 1993. Chemical analysis of the organic compounds was conducted using ultra-high-performance liquid chromatography (UHPLC) coupled to electrospray ionization high-resolution mass spectrometry (ESI-HRMS) for dicarbonyls and long-chain carboxylic acids and ion chromatography for short-chain carboxylates. Long-term records of the carboxylic acids and dicarbonyls, as well as their source apportionment, are reported for western Europe. This is the first study comprising long-term trends of dicarbonyls and long-chain dicarboxylic acids (C6–C12) in Alpine precipitation. Source assignment of the organic species present in the ice core was performed using principal component analysis. Our results suggest biomass burning, anthropogenic emissions, and transport of mineral dust to be the main parameters influencing the concentration of organic compounds. Ice core records of several highly correlated compounds (e.g., p-hydroxybenzoic acid, pinic acid, pimelic, and suberic acids) can be related to the forest fire history in southern Switzerland. P-hydroxybenzoic acid was found to be the best organic fire tracer in the study area, revealing the highest correlation with the burned area from fires. Historical records of methylglyoxal, phthalic acid, and dicarboxylic acids adipic acid, sebacic acid, and dodecanedioic acid are comparable with that of anthropogenic emissions of volatile organic compounds (VOCs). The small organic acids, oxalic acid and formic acid, are both highly correlated with calcium, suggesting their records to be affected by changing mineral dust transport to the drilling site.