Genomic meningococcal load in the nasopharynx of children with meningococcal disease

This study demonstrates the feasibility of using quantitative real time PCR to measure genomic bacterial load in the nasopharynx of children with invasive meningococcal disease and shows that these loads are exceptionally high (median 6.6 x 105 (Range 1.2 x 105 to 1.1 x 108) genome copies of Neisseria meningitidis per swab).

Effects of temperature and strain rate on the tensile behaviors of SIMP steel in static lead bismuth eutectic

In order to assess the susceptibility of candidate structural materials to liquid metal embrittlement, this work investigated the tensile behaviors of ferritic-martensitic steel in static lead bismuth eutectic (LBE). The tensile tests were carried out in static lead bismuth eutectic under different temperatures and strain rates. Pronounced liquid metal embrittlement phenomenon is observed between 200 °C and 450 °C. Total elongation is reduced greatly due to the liquid metal embrittlement in LBE environment. The range of ductility trough is larger under slow strain rate tensile (SSRT) test.

Aplicações das redes de Bragg na biomecânica

O presente trabalho tem como objectivo o estudo, desenvolvimento e aplicações na área da biomecânica de sensores intrínsecos baseados em redes de Bragg em fibras ópticas (FBG). As aplicações são feitas em modelos biomecânicos in vitro tais como: implantes de anca, prótese de joelho, placas de osteossíntese e implantes dentários. A optimização do desenvolvimento de próteses e respectivos elementos de fixação é actualmente dependente da geração e validação experimental de seus modelos computacionais. A validação destes modelos é normalmente feita utilizando-se dados de ensaios não invasivos e invasivos em modelos sintéticos. Em ensaios in vitro os sensores convencionais têm um princípio de funcionamento eléctrico e apresentam por vezes dimensões inadequadas. Existem situações exploradas no presente trabalho, tais como sensoriamento de superfícies irregulares e junções ou ainda análises de deformações internas, onde é recomendável a utilização de sensores FBG, pois apresentam dimensões reduzidas e flexibilidade o que permite efectuar medidas localizadas. O desenvolvimento de um protocolo de utilização de FBG e a sua aplicação no contexto apresentado demonstrou-se mais adequado, pela precisão e segurança futura oferecidas. Foi desenvolvida uma metodologia experimental para medidas de deformações utilizando FBG ao longo de uma placa de osteossíntese metálica aparafusada a um fémur sintético fracturado. Foi efectuada a monitorização da cura do cimento ósseo utilizado como fixador do prato tibial na artroplastia total do joelho através da medida da sua contracção e temperatura. Foi também desenvolvido um sistema refrigerador com resposta às leituras de temperatura com vista a evitar a necrose do osso. Foram efectuados estudos de deformação nesse cimento após a sua cura, como resultado da aplicação de cargas mecânicas estáticas. Foram efectuados estudos da cura de cimento ósseo aplicado a próteses de anca e também de deformações nestas próteses. Foi ainda efectuado o estudo comparativo de vários implantes dentários através da medida da distribuição de deformações como resposta a excitações mecânicas impulsivas. Para a desmodulação das FBG foram inicialmente utilizados sistemas comerciais. Entretanto algumas aplicações não puderam ser implementadas com estes sistemas comerciais devido à baixa reflectividade das FBG utilizadas, mas fundamentalmente devido à necessidade de executar testes com uma taxa de aquisição maior do que os 5 Hz disponíveis (cerca de 15 kHz). Por estes motivos foi desenvolvido um sistema optoelectrónico completo de desmodulação de FBG baseado num filtro sintonizável e que tem como característica principal a alta taxa de aquisição (até 1,2 MHz) mas também se destaca pela facilidade na reconfiguração dos parâmetros de leitura, pela apresentação duma interface de utilizador amigável e pela capacidade de operar com até 5 FBG na mesma fibra óptica.

ORBS and the limits of static slicing

Observation-based slicing is a recently-introduced, language-independent, slicing technique based on the dependencies observable from program behaviour. Due to the wellknown limits of dynamic analysis, we may only compute an under-approximation of the true observation-based slice. However, because the observation-based slice captures all possible dependence that can be observed, even such approximations can yield insight into the limitations of static slicing. For example, a static slice, S that is strictly smaller than the corresponding observation based slice is guaranteed to be unsafe. We present the results of three sets of experiments on 12 different programs, including benchmarks and larger programs, which investigate the relationship between static and observation-based slicing. We show that, in extreme cases, observation-based slices can find the true static minimal slice, where static techniques cannot. For more typical cases, our results illustrate the potential for observation-based slicing to highlight unsafe static slices. Finally, we report on the sensitivity of observation-based slicing to test quality.

Incipient turn-to-turn winding fault diagnosis of power transformers by the on-load exciting current Extended Park`s Vector Approach

This paper presents the application of the on-load exciting current Extended Park's Vector Approach for diagnosing incipient turn-to-turn winding faults in operating power transformers. Experimental and simulated test results demonstrate the effectiveness of the proposed technique, which is based on the spectral analysis of the AC component of the on-load exciting current Park's Vector modulus.

Transformers on-load exciting current Park`s vector approach as a tool for winding faults diagnostics

This paper presents the development of a new approach for diagnosing the occurrence of inter-turn short-circuits in the windings of three-phase transformers, which is based on the on-line monitoring of the on-load exciting current Park's Vector patterns. Experimental and simulated results demonstrate the effectiveness of the proposed technique for detecting winding inter-turn insulation faults in operating three-phase transformers.

Detection of trasformer intermittent winding faults by the on-load exciting current Park`s vector approach

This paper presents the application of the on-load exciting current Park's Vector Approach for diagnosing permanent and intermittent turn-to-turn winding faults in operating power transformers. First, an experimental investigation of the behaviour of the transformer under the occurrence of both permanent and intermittent winding faults is presented. Finally, experimental test results demonstrate the effectiveness of the proposed diagnostic technique, which is based on the on-line monitoring of the on-load exciting current Park's Vector patterns.

Non-linear analysis of piezolaminated structures

In the recent years the study of smart structures has attracted significant researchers, due to their potential benefits in a wide range of applications, such as shape control, vibration suppression, noise attenuation and damage detection. The applications in aerospace industry are of great relevance, such as in active control of airplane wings, helicopter blade rotor, space antenna. The use of smart materials, such as piezoelectric materials, in the form of layers or patches embedded and/or surface bonded on laminated composite structures, can provide structures that combine the superior mechanical properties of composite materials and the capability to sense and adapt their static and dynamic response, becoming adaptive structures. The piezoelectric materials have the property of generate electrical charge under mechanical load or deformation, and the reverse, applying an electrical field to the material results in mechanical strain or stresses.

EU water framework directive: will the nitrate load reduction from diffuse sources produce the same results in all estuaries?

The impact of urban waste-water and non-point nitrate discharges in estuarine and near-shore coastal waters are analyzed. The study is focused on the effects of applying the European directives 91/271/EEC and 91/676/EEC to these systems. 4 Portuguese estuaries and two coastal lagoons with different characteristics are studied. A modelling system is applied and calibrated in each system. Three nitrate load scenarios are examined. It is shown that the morphologic and hydrodynamic characteristics of the domain largely control the ecological processes in these systems. The primary production limitation factors are split into “biologic” and “hydrodynamic” components. The physical limitation due to hydrodynamic and residence time is the most important factor. The combined limitation of “biologic” factors (temperature, light and nutrients availability) control productivity only in the systems where physical limitation is not important.

An investigation of container train service provision and load factors in Great Britain

The continued growth in the volume of international trade poses considerable economic and sustainability challenges, particularly as transport routes become more congested and concern grows about the role of transport movements in accelerating climate change. Rail freight plays a major role in the inland transport of containers passing through the main British container ports, and potentially could play a more significant role in the future. However, there is little detailed understanding of the nature of this particular rail market, especially in terms its current operating efficiency. This paper examines container train service provision to/from the four main ports, based on analysis of a representative survey of more than 500 container trains between February and August 2007. The extent to which the existing capacity is utilised is presented, and scenarios by which the number of containers carried could be increased without requiring additional train service provision are modelled, to identify the theoretical potential for greater rail volumes. Finally, the paper identifies the challenges involved in achieving higher load factors, emphasising the importance both of wider supply chain considerations and government policy decision-making.

Distributed Agent-Based Load Balancer for Cloud Computing

In this paper we present a concept of an agent-based strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. To provide a base for our research we specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. We also present an early version of simulation environment and a prototype of agent-based load balancer implemented in functional language Scala and Akka framework.

A Meta-Heuristic Load Balancer for Cloud Computing Systems

This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.