Design of a microwave radiometer for monitoring high voltage insulator contamination level

Microwave radiometry is a novel method for monitoring contamination levels on high voltage insulators. The microwave radiometer described measures energy emitted from the contamination layer and could provide a safe, reliable, contactless monitoring method that is effective under dry conditions. The design of the system has focused on optimizing accuracy, stability and sensitivity using a relatively low cost architecture. Experimental results demonstrate that the output from the radiometer is able to clearly distinguish between samples with different contamination levels under dry conditions. This contamination monitoring method could potentially provide advance warning of the future failure of wet insulators in climates where insulators can experience dry conditions for extended periods

Michael Young: an innovative social entrepreneur

This chapter attempts to locate Michael Young, the architect of the party's state-centric 1945 election manifesto and subsequent social democratic 'radical' in his advocacy of social programmes based on community, family and individual initiatives, in longer historic traditions of Labour's non-state socialist development. It charts the trajectory of Young’s ‘post-socialist’ development and assesses his contribution to thinking about social democratic and progressive alternatives to Labour’s more traditionally state socialist concerns, perspectives and presentation. It suggests that Young was an early post-war pioneer of the kind of non-statist, decentred, participatory and community-based brand of liberal socialism that was to reappear in Labour’s ‘post-revisionist’ social democracy from the mid-1970s and in the Social Democratic Party (SDP) after 1981 through to 'New' Labour and beyond. This was part of a much longer tradition of British socialism, including G.D.H. Cole’s Guild Socialism, concerned with decentralised and devolved, associational and participatory forms of social and political organisation, which has subsequently been marginalised in the Labour pantheon by dominant paradigms and narratives of Labour’s state-centred development

Candida costochondritis associated with recent intravenous drug use

Candida osteoarticular infections are being reported with increasing frequency, possibly due to an expanding population at risk. However, Candida costochondritis is uncommon. We report two cases of Candida costochondritis in patients who presented with subacute-onset chest wall swelling and whose only identifiable risk factor was a history of recent intravenous drug use

Candida costochondritis associated with recent intravenous drug use

Candida osteoarticular infections are being reported with increasing frequency, possibly due to an expanding population at risk. However, Candida costochondritis is uncommon. We report two cases of Candida costochondritis in patients who presented with subacute-onset chest wall swelling and whose only identifiable risk factor was a history of recent intravenous drug use

A convolutional neural network based deep learning methodology for recognition of partial discharge patterns from high voltage cables

It is a great challenge to differentiate partial discharge (PD) induced by different types of insulation defects in high-voltage cables. Some types of PD signals have very similar characteristics and are specifically difficult to differentiate, even for the most experienced specialists. To overcome the challenge, a convolutional neural network (CNN)-based deep learning methodology for PD pattern recognition is presented in this paper. First, PD testing for five types of artificial defects in ethylene-propylene-rubber cables is carried out in high voltage laboratory to generate signals containing PD data. Second, 3500 sets of PD transient pulses are extracted, and then 33 kinds of PD features are established. The third stage applies a CNN to the data; typical CNN architecture and the key factors which affect the CNN-based pattern recognition accuracy are described. Factors discussed include the number of the network layers, convolutional kernel size, activation function, and pooling method. This paper presents a flowchart of the CNN-based PD pattern recognition method and an evaluation with 3500 sets of PD samples. Finally, the CNN-based pattern recognition results are shown and the proposed method is compared with two more traditional analysis methods, i.e., support vector machine (SVM) and back propagation neural network (BPNN). The results show that the proposed CNN method has higher pattern recognition accuracy than SVM and BPNN, and that the novel method is especially effective for PD type recognition in cases of signals of high similarity, which is applicable for industrial applications

Candida albicans Hypha Formation and Mannan Masking of β-Glucan Inhibit Macrophage Phagosome Maturation

Received 28 August 2014 Accepted 28 October 2014 Published 2 December 2014 This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license. ACKNOWLEDGMENTS We thank Janet Willment, Aberdeen Fungal Group, University of Aberdeen, for kindly providing the soluble Dectin-1-Fc reporter. All microscopy was performed with the assistance of the University of Aberdeen Core Microscopy & Histology Facility, and we thank the IFCC for their assistance with flow cytometry. We thank the Wellcome Trust for funding (080088, 086827, 075470, 099215, 097377, and 101873). E.R.B. and A.J.P.B. are funded by the European Research Council (ERC-2009-AdG-249793), and J.L. is funded by a Medical Research Council Clinical Training Fellowship.Peer reviewedPublisher PD

Quantification of the performance of iterative and non-iterative computational methods of locating partial discharges using RF measurement techniques

Partial discharge (PD) is an electrical discharge phenomenon that occurs when the insulation materialof high voltage equipment is subjected to high electric field stress. Its occurrence can be an indication ofincipient failure within power equipment such as power transformers, underground transmission cableor switchgear. Radio frequency measurement methods can be used to detect and locate discharge sourcesby measuring the propagated electromagnetic wave arising as a result of ionic charge acceleration. Anarray of at least four receiving antennas may be employed to detect any radiated discharge signals, thenthe three dimensional position of the discharge source can be calculated using different algorithms. These algorithms fall into two categories; iterative or non-iterative. This paper evaluates, through simulation, the location performance of an iterative method (the standardleast squares method) and a non-iterative method (the Bancroft algorithm). Simulations were carried outusing (i) a "Y" shaped antenna array and (ii) a square shaped antenna array, each consisting of a four-antennas. The results show that PD location accuracy is influenced by the algorithm's error bound, thenumber of iterations and the initial values for the iterative algorithms, as well as the antenna arrangement for both the non-iterative and iterative algorithms. Furthermore, this research proposes a novel approachfor selecting adequate error bounds and number of iterations using results of the non-iterative method, thus solving some of the iterative method dependencies

The evolutionary dynamics of variant antigen genes in Babesia reveal a history of genomic innovation underlying host-parasite interaction

Babesia spp. are tick-borne, intraerythrocytic hemoparasites that use antigenic variation to resist host immunity, through sequential modification of the parasite-derived variant erythrocyte surface antigen (VESA) expressed on the infected red blood cell surface. We identified the genomic processes driving antigenic diversity in genes encoding VESA (ves1) through comparative analysis within and between three Babesia species, (B. bigemina, B. divergens and B. bovis). Ves1 structure diverges rapidly after speciation, notably through the evolution of shortened forms (ves2) from 5′ ends of canonical ves1 genes. Phylogenetic analyses show that ves1 genes are transposed between loci routinely, whereas ves2 genes are not. Similarly, analysis of sequence mosaicism shows that recombination drives variation in ves1 sequences, but less so for ves2, indicating the adoption of different mechanisms for variation of the two families. Proteomic analysis of the B. bigemina PR isolate shows that two dominant VESA1 proteins are expressed in the population, whereas numerous VESA2 proteins are co-expressed, consistent with differential transcriptional regulation of each family. Hence, VESA2 proteins are abundant and previously unrecognized elements of Babesia biology, with evolutionary dynamics consistently different to those of VESA1, suggesting that their functions are distinct

Detection of brown dwarf-like objects in the core of NGC3603

We use near-infrared data obtained with the Wide Field Camera 3 (WFC3) on the Hubble Space Telescope to identify objects having the colors of brown dwarfs (BDs) in the field of the massive galactic cluster NGC 3603. These are identified through use of a combination of narrow and medium band filters spanning the J and H bands, and which are particularly sensitive to the presence of the 1.3-1.5{\mu}m H2O molecular band - unique to BDs. We provide a calibration of the relationship between effective temperature and color for both field stars and for BDs. This photometric method provides effective temperatures for BDs to an accuracy of {\pm}350K relative to spectroscopic techniques. This accuracy is shown to be not significantly affected by either stellar surface gravity or uncertainties in the interstellar extinction. We identify nine objects having effective temperature between 1700 and 2200 K, typical of BDs, observed J-band magnitudes in the range 19.5-21.5, and that are strongly clustered towards the luminous core of NGC 3603. However, if these are located at the distance of the cluster, they are far too luminous to be normal BDs. We argue that it is unlikely that these objects are either artifacts of our dataset, normal field BDs/M-type giants or extra-galactic contaminants and, therefore, might represent a new class of stars having the effective temperatures of BDs but with luminosities of more massive stars. We explore the interesting scenario in which these objects would be normal stars that have recently tidally ingested a Hot Jupiter, the remnants of which are providing a short-lived extended photosphere to the central star. In this case, we would expect them to show the signature of fast rotation.Comment: 26 Pages, 8 Figures, Accepted for publication on Ap

Random forest based optimal feature selection for partial discharge pattern recognition in HV cables

Optimal selection of features of Partial Discharge (PD) signals recorded from defects in High Voltage (HV) cables will contribute not only to the improvement of PD pattern recognition accuracy and efficiency but also to PD parameter visualization in HV cable condition monitoring and diagnostics. This paper presents a novel Random Forest (RF)-based feature selection algorithm for PD pattern recognition of HV cables. The algorithm is applied to feature selection of both PD signals and interference signals with the aim of obtaining the optimal features for data processing. Firstly, the experimental data acquisition and feature extraction processes are introduced. PD signals were captured from faults created in a cable to obtain the raw PD data, then a set of 3500 transient PD pulses and a set of 3500 typical interference pulses were extracted, based on which 34 PD features were extracted for further processing. Furthermore, 119 two-dimensional features and 1082 three-dimensional features were generated. The paper then discusses the basic principle of the RF algorithm. Finally, RF-based feature selection was implemented to determine the optimal features for PD pattern recognition. The results were obtained and evaluated with the Back Propagation Neural Network (BPNN) and Support Vector Machine (SVM). Results show that the proposed RF-based method is effective for PD feature selection of HV cables with the potential for application to additional HV power apparatus