Degradation of road tested automotive connectors

The automotive environment is particularly demanding on connector performance, and is characterized by large temperature changes, high humidity and corrosive atmospheres. This paper presents an initial study of connector performance in terms of temperature profiles taken from road vehicles. The temperature profiles are then simulated using empirical relationships to allow prediction of connector performance. Wire harnesses have been investigated to seek evidence of the connector degradation predicted from the temperature data. Initial indications are that the wire harness shows the type of fretting behavior associated with the temperature changes. Evidence of fretting corrosion was found at the contact interface on tin plated terminals from sealed and unsealed connectors

Condition monitoring and prognostic indicators for network reliability

Large-scale investment in transmission and distribution networks are planned over the next 10-15 years to meet future demand and changes in power generation. However, it is important that existing assets continue to operate reliably and their health maintained. A research project is considering the increased use of simulation models that could provide accurate prognostics, targeting maintenance and reduce in service failures. Such models could be further refined with parameters obtained from on-line measurements at the asset. It is also important to consider the future development of the research agenda for condition monitoring of power networks and with colleagues from National Grid, PPA Energy and the Universities of Manchester and Strathclyde, the research team are preparing a Position Paper on this subject

Condition Monitoring of Power Cables

A National Grid funded research project at Southampton has investigated possible methodologies for data acquisition, transmission and processing that will facilitate on-line continuous monitoring of partial discharges in high voltage polymeric cable systems. A method that only uses passive components at the measuring points has been developed and is outlined in this paper. More recent work, funded through the EPSRC Supergen V, UK Energy Infrastructure (AMPerES) grant in collaboration with UK electricity network operators has concentrated on the development of partial discharge data processing techniques that ultimately may allow continuous assessment of transmission asset health to be reliably determined

Randomised trials in the South African Medical Journal, 1948- 1997

Objective. To describe randomised controlled trials (RCTs) published in the South African Medical Journal (SAMJ) over a 50-year period from 1948 to 1997 with regard to number, topic and quality.Methods. We hand searched all issues of the SAMJ published during the study period to identify all published RCTs.Outcome measures. Number, topic and quality of RCTs published from 1948 to 1997.Results. Eight hundred and fifty-eight clinical trials were published during the period reviewed. Eighty-four per cent of RCTs were published as full articles. During the 1980s the number of RCTs published increased rapidly,  with a peak of 35 in 1985, but then declined to only 5 in 1997. The majority (92%) of RCTs were conducted in a hospital setting. A varied range of subjects was covered, with gastroenterology taking the lead and no trials in public health. The sample size in more than 50% of RCTs was smaller than 50 patients. Fifty-one per cent (435 trials) used random allocation and 49% (423) quasi-random methods of allocation. Concealment of treatment allocation was judged to be adequate in 46% of studies (N == 200), blinding of observers assessing outcomes was adequate in 28% (123), and all the allocated test subjects were included in the primary analysis in 28% (123). The follow-up period was more than 1 year in 4% (17) and less than 6 days in 16% (71).Conclusions. Compared with other international journals the SAMJ is highly regarded in terms of the number of trials published. There are, however, a number of deficiencies in the quality of the trials

The novel MAPT mutation K298E:mechanisms of mutant tau toxicity, brain pathology and tau expression in induced fibroblast-derived neurons

Frontotemporal lobar degeneration (FTLD) consists of a group of neurodegenerative diseases characterized by behavioural and executive impairment, language disorders and motor dysfunction. About 20-30 % of cases are inherited in a dominant manner. Mutations in the microtubule-associated protein tau gene (MAPT) cause frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17T). Here we report a novel MAPT mutation (K298E) in exon 10 in a patient with FTDP-17T. Neuropathological studies of post-mortem brain showed widespread neuronal loss and gliosis and abundant deposition of hyperphosphorylated tau in neurons and glia. Molecular studies demonstrated that the K298E mutation affects both protein function and alternative mRNA splicing. Fibroblasts from a skin biopsy of the proband taken at post-mortem were directly induced into neurons (iNs) and expressed both 3-repeat and 4-repeat tau isoforms. As well as contributing new knowledge on MAPT mutations in FTDP-17T, this is the first example of the successful generation of iNs from skin cells retrieved post-mortem

Structure Discovery in Mixed Order Hyper Networks

Background  Mixed Order Hyper Networks (MOHNs) are a type of neural network in which the interactions between inputs are modelled explicitly by weights that can connect any number of neurons. Such networks have a human readability that networks with hidden units lack. They can be used for regression, classification or as content addressable memories and have been shown to be useful as fitness function models in constraint satisfaction tasks. They are fast to train and, when their structure is fixed, do not suffer from local minima in the cost function during training. However, their main drawback is that the correct structure (which neurons to connect with weights) must be discovered from data and an exhaustive search is not possible for networks of over around 30 inputs.  Results  This paper presents an algorithm designed to discover a set of weights that satisfy the joint constraints of low training error and a parsimonious model. The combined structure discovery and weight learning process was found to be faster, more accurate and have less variance than training an MLP.  Conclusions  There are a number of advantages to using higher order weights rather than hidden units in a neural network but discovering the correct structure for those weights can be challenging. With the method proposed in this paper, the use of high order networks becomes tractable