Arc Phenomena in low-voltage current limiting circuit breakers

Circuit breakers are an important safety feature in most electrical circuits, and they act to prevent excessive currents caused by short circuits, for example. Low-voltage current limiting circuit breakers are activated by a trip solenoid when a critical current is exceeded. The solenoid moves two contacts apart to break the circuit. However, as soon as the contacts are separated an electric arc forms between them, ionising the air in the gap, increasing the electrical conductivity of air to that of the hot plasma that forms, and current continues to flow. The currents involved may be as large as 80,000 amperes. Critical to the success of the circuit breaker is that it is designed to cause the arc to move away from the contacts, into a widening wedge-shaped region. This lengthens the arc, and then moves it onto a series of separator plates called an arc divider or splitter. The arc divider raises the voltage required to sustain the arcs across it, above the voltage that is provided across the breaker, so that the circuit is broken and the arcing dies away. This entire process occurs in milliseconds, and is usually associated with a sound like an explosion and a bright ash from the arc. Parts of the contacts and the arc divider may melt and/or vapourise. The question to be addressed by the Study Group was to mathematically model the arc motion and extinction, with the overall aim of an improved understanding that would help the design of a better circuit breaker. Further discussion indicated that two key mechanisms are believed to contribute to the movement of the arc away from the contacts, one being self-magnetism (where the magnetic field associated with the arc and surrounding circuitry acts to push it towards the arc divider), and the other being air flow (where expansion of air combined with the design of the chamber enclosing the arc causes gas flow towards the arc divider). Further discussion also indicated that a key aspect of circuit breaker design was that it is desirable to have as fast a quenching of the arc as possible, that is, the faster the circuit breaker can act to stop current flow, the better. The relative importance of magnetic and air pressure effects on quenching speed is of central interest to circuit design

Structural Neuroimaging of Anorexia Nervosa: Future Directions in the Quest for Mechanisms Underlying Dynamic Alterations.

Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual brain scans, and AN may be a valuable model disorder to study structural neuroplasticity. Structural magnetic resonance imaging studies have found reduced gray matter volume and cortical thinning in acutely underweight patients to normalize following successful treatment. However, some well-controlled studies have found regionally greater gray matter and persistence of structural alterations following long-term recovery. Findings from diffusion tensor imaging studies of white matter integrity and connectivity are also inconsistent. Furthermore, despite the severity of AN, the number of existing structural neuroimaging studies is still relatively low, and our knowledge of the underlying cellular and molecular mechanisms for macrostructural brain changes is rudimentary. We critically review the current state of structural neuroimaging in AN and discuss the potential neurobiological basis of structural brain alterations in the disorder, highlighting impediments to progress, recent developments, and promising future directions. In particular, we argue for the utility of more standardized data collection, adopting a connectomics approach to understanding brain network architecture, employing advanced magnetic resonance imaging methods that quantify biomarkers of brain tissue microstructure, integrating data from multiple imaging modalities, strategic longitudinal observation during weight restoration, and large-scale data pooling. Our overarching objective is to motivate carefully controlled research of brain structure in eating disorders, which will ultimately help predict therapeutic response and improve treatment

Regulation of synaptic connectivity: levels of fasciclin II influence synaptic growth in the Drosophila CNS

Much of our understanding of synaptogenesis comes from studies that deal with the development of the neuromuscular junction (NMJ). Although well studied, it is not clear how far the NMJ represents an adequate model for the formation of synapses within the CNS. Here we investigate the role of Fasciclin II (Fas II) in the development of synapses between identified motor neurons and cholinergic interneurons in the CNS of Drosophila. Fas II is a neural cell adhesion molecule homolog that is involved in both target selection and synaptic plasticity at the NMJ in Drosophila. In this study, we show that levels of Fas II are critical determinants of synapse formation and growth in the CNS. The initial establishment of synaptic contacts between these identified neurons is seemingly independent of Fas II. The subsequent proliferation of these synaptic connections that occurs postembryonically is, in contrast, significantly retarded by the absence of Fas II. Although the initial formation of synaptic connectivity between these neurons is seemingly independent of Fas II, we show that their formation is, nevertheless, significantly affected by manipulations that alter the relative balance of Fas II in the presynaptic and postsynaptic neurons. Increasing expression of Fas II in either the presynaptic or postsynaptic neurons, during embryogenesis, is sufficient to disrupt the normal level of synaptic connectivity that occurs between these neurons. This effect of Fas II is isoform specific and, moreover, phenocopies the disruption to synaptic connectivity observed previously after tetanus toxin light chain-dependent blockade of evoked synaptic vesicle release in these neurons

Nanocomposites and methods for synthesis and use thereof

Nanocomposite compositions and methods of synthesis of the compositions are described. In particular, liquid crystal-functionalized nanoparticles, liquid crystal-templated nanoparticles, nanocomposite compositions including the nanoparticles, and composite compositions including the nanocomposites are detailed.Board of Regents, University of Texas Syste

Brain putamen volume changes in newly-diagnosed patients with obstructive sleep apnea.

Obstructive sleep apnea (OSA) is accompanied by cognitive, motor, autonomic, learning, and affective abnormalities. The putamen serves several of these functions, especially motor and autonomic behaviors, but whether global and specific sub-regions of that structure are damaged is unclear. We assessed global and regional putamen volumes in 43 recently-diagnosed, treatment-naïve OSA (age, 46.4 ± 8.8 years; 31 male) and 61 control subjects (47.6 ± 8.8 years; 39 male) using high-resolution T1-weighted images collected with a 3.0-Tesla MRI scanner. Global putamen volumes were calculated, and group differences evaluated with independent samples t-tests, as well as with analysis of covariance (covariates; age, gender, and total intracranial volume). Regional differences between groups were visualized with 3D surface morphometry-based group ratio maps. OSA subjects showed significantly higher global putamen volumes, relative to controls. Regional analyses showed putamen areas with increased and decreased tissue volumes in OSA relative to control subjects, including increases in caudal, mid-dorsal, mid-ventral portions, and ventral regions, while areas with decreased volumes appeared in rostral, mid-dorsal, medial-caudal, and mid-ventral sites. Global putamen volumes were significantly higher in the OSA subjects, but local sites showed both higher and lower volumes. The appearance of localized volume alterations points to differential hypoxic or perfusion action on glia and other tissues within the structure, and may reflect a stage in progression of injury in these newly-diagnosed patients toward the overall volume loss found in patients with chronic OSA. The regional changes may underlie some of the specific deficits in motor, autonomic, and neuropsychologic functions in OSA

Increasing power for voxel-wise genome-wide association studies : the random field theory, least square kernel machines and fast permutation procedures

Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics has attracted growing attention and interest, most brain-wide genome-wide association studies focus on voxel-wise single-locus approaches, without taking advantage of the spatial information in images or combining the effect of multiple genetic variants. In this paper we present a fast implementation of voxel- and cluster-wise inferences based on the random field theory to fully use the spatial information in images. The approach is combined with a multi-locus model based on least square kernel machines to associate the joint effect of several single nucleotide polymorphisms (SNP) with imaging traits. A fast permutation procedure is also proposed which significantly reduces the number of permutations needed relative to the standard empirical method and provides accurate small p-value estimates based on parametric tail approximation. We explored the relation between 448,294 single nucleotide polymorphisms and 18,043 genes in 31,662 voxels of the entire brain across 740 elderly subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. We find method to be more sensitive compared with voxel-wise single-locus approaches. A number of genes were identified as having significant associations with volumetric changes. The most associated gene was GRIN2B, which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit and affects both the parietal and temporal lobes in human brains. Its role in Alzheimer's disease has been widely acknowledged and studied, suggesting the validity of the approach. The various advantages over existing approaches indicate a great potential offered by this novel framework to detect genetic influences on human brains

Validating the use of intrinsic markers in body feathers to identify inter-individual differences in non-breeding areas of northern fulmars

Acknowledgments We thank Claire Deacon, Gareth Norton and Andrea Raab for help with laboratory work at the University of Aberdeen, and Barry Thornton and Gillian Martin for running stable isotope analysis at the James Hutton Institute. Thanks to all involved in the collection and processing of dead fulmars through the North Sea plastic pollution project at IMARES, with special thanks to Jens-Kjeld Jensen, Bergur Olsen and Elisa Bravo Rebolledo for samples from the Faroe Islands and Susanne Kühn for those from Iceland. Thanks to Orkney Islands Council for access to Eynhallow and to all the fieldworkers involved in deployment and recovery of the GLS tags. All ringing work was carried out under permit from the BTO, and feather sampling was carried out under licence from the Home Office. We are grateful to James Fox of Migrate Technologies for recovering data from GLS loggers which would not download, and Richard Phillips and Janet Silk of BAS for advice on GLS analysis. We thank Deborah Dawson of the NERC Biomolecular Analysis Facility, University of Sheffield and Stuart Piertney of University of Aberdeen for molecular sexing of the fulmars. Lucy Quinn was supported by a NERC Studentship and additional funding to support fieldwork was gratefully received from Talisman Energy (UK) Ltd. We thank Yves Cherel and two anonymous reviewers for their constructive comments on the manuscript.Peer reviewedPublisher PD

Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression

We present a new method for the detection of gene pathways associated with a multivariate quantitative trait, and use it to identify causal pathways associated with an imaging endophenotype characteristic of longitudinal structural change in the brains of patients with Alzheimer's disease (AD). Our method, known as pathways sparse reduced-rank regression (PsRRR), uses group lasso penalised regression to jointly model the effects of genome-wide single nucleotide polymorphisms (SNPs), grouped into functional pathways using prior knowledge of gene-gene interactions. Pathways are ranked in order of importance using a resampling strategy that exploits finite sample variability. Our application study uses whole genome scans and MR images from 464 subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. 66,182 SNPs are mapped to 185 gene pathways from the KEGG pathways database. Voxel-wise imaging signatures characteristic of AD are obtained by analysing 3D patterns of structural change at 6, 12 and 24 months relative to baseline. High-ranking, AD endophenotype-associated pathways in our study include those describing chemokine, Jak-stat and insulin signalling pathways, and tight junction interactions. All of these have been previously implicated in AD biology. In a secondary analysis, we investigate SNPs and genes that may be driving pathway selection, and identify a number of previously validated AD genes including CR1, APOE and TOMM40