Labor Contracts and the Taft-Hartley Act

The amount of information stored on the internet grows daily and naturally the requirements on the systems used to search for and analyse information increases. As a part in meeting the raised requirements this study investigates if it is possible for a automatised text analysis system to distinguish certain groups and categories of words in a text, and more specifically investigate if it is possible to distinguish words with a high information value from words with a low information value. This is important to enable optimizations of systems for global surveillance and information retrieval. The study is carried out using word spaces, which are often used in text analysis to model language. The distributional character of certain categories of words is examined by studying the intrinsic dimensionality of the space, locally around different words. Based on the result from the study of the intrinsic dimensionality, where there seems to be differences in the distributional character between categories of words, an algorithm is implemented for classifying words based on the dimensionality data. The classification algorithm is tested for different categories. The result strengthens the thesis that there could exist useful differences between the distributional character of different categories of words.I takt med att allt mer information finns tillgänglig på internet växer kraven som ställs på system som används för att söka efter och analysera information. I den här rapporten undersöks huruvida det är möjligt för ett systemför automatiserad textanalys att avgöra vilka ord som är relevanta och informationsbärande i ett sammanhang. Detta är viktigt för att möjlig göra optimering och effektivisering av exempelvis informationssöknings- och omvärldsbevakningssystem. Undersökningen genomförs med hjälp av ordrumsmodeller för att modellera språk. Den distributionella karaktären hos termerna undersöks genom att studeraden intrinsiska dimensionaliteten lokalt i rummet kring olika termer. Baserat på resultaten av denna undersökning, som tycks visa på att det fanns skillnader i den distributionella karaktären hos olika kategorier av ord, implementeras en algoritm för att klassificera ord baserat på dimensionaliteten. Klassificeringsalgoritmen testas för olika kategorier. Resultatet stärker tesen om att det kan finnas vissa användbara skillnader mellan den distributionella karaktären hos olika kategorier av ord

Basket to Purkinje Cell Inhibitory Ephaptic Coupling Is Abolished in Episodic Ataxia Type 1

Dominantly inherited missense mutations of the KCNA1 gene, which encodes the KV1.1 potassium channel subunit, cause Episodic Ataxia type 1 (EA1). Although the cerebellar incoordination is thought to arise from abnormal Purkinje cell output, the underlying functional deficit remains unclear. Here we examine synaptic and non-synaptic inhibition of Purkinje cells by cerebellar basket cells in an adult mouse model of EA1. The synaptic function of basket cell terminals was unaffected, despite their intense enrichment for KV1.1-containing channels. In turn, the phase response curve quantifying the influence of basket cell input on Purkine cell output was maintained. However, ultra-fast non-synaptic ephaptic coupling, which occurs in the cerebellar ‘pinceau’ formation surrounding the axon initial segment of Purkinje cells, was profoundly reduced in EA1 mice in comparison with their wild type littermates. The altered temporal profile of basket cell inhibition of Purkinje cells underlines the importance of Kv1.1 channels for this form of signalling, and may contribute to the clinical phenotype of EA1

Impedance analysis of electrolyte processes in a solid oxide cell

Electrochemical impedance spectroscopy and the distribution of relaxation times are powerful tools to study polarization processes in solid oxide cells (SOC). Commonly the measured polarization resistance is solely attributed to polarization phenomena in the electrodes whereas the electrolyte is assumed to act as purely ohmic series resistance. In this study an electrolyte supported SOC is investigated by impedance spectroscopy from the nominal operating temperature range of 700–900°C down to temperatures as low as 350°C. At such low temperatures the dielectric polarization of the electrolyte is shifted into the accessible frequency range, providing access to additional processes which are deconvoluted and quantified. It is discussed to which extent the additional layers like gadolinia doped ceria diffusion barrier and electrode layers influence the electrolyte processes as grain and grain boundary

Comparison of a solid oxide cell with nickel/gadolinium‐doped ceria fuel electrode during operation with hydrogen/steam and carbon monoxide/carbon dioxide

Solid oxide cells (SOCs) offer the possibility to operate on hydrogen/steam (H$_2$/H$_2$O), carbon monoxide/carbon dioxide (CO/CO$_2$), and mixtures thereof in the fuel cell as well as in the electrolyzer mode. In this study, the electrochemical processes in an electrolyte-supported SOC exhibiting a La$_w$ Sr$_x$ Co$_y$ Fe$_z$ O$_{(3-δ)}$ air electrode and a nickel/gadolinium-doped ceria (Ni/CGO) fuel electrode (FE) were analyzed by electrochemical impedance spectroscopy, and the subsequent impedance data analysis by the distribution of relaxation times for CO/CO$_2$ fuel mixtures. A physicochemical equivalent circuit model was fitted to the measured spectra. With the help of the extracted parameters, a zero-dimensional direct current cell model was parametrized to simulate the current-voltage behavior of the cell. This approach, previously implemented for H$_2$/H$_2$O fuel mixtures, is extended toward CO/CO$_2$ fuels. It will be shown that the same model – with adapted parameters for the FE – can be applied. A comparison of measured and simulated current-voltage curves showed an excellent agreement for both fuels and operating modes (solid oxide fuel cell/solid oxide electrolyzer cell). Simulations reveal that there is nearly no performance difference between H$_2$O and CO$_2$ electrolysis for the electrolyte-supported cell with Ni/CGO FE in comparison to an anode-supported cell with Ni/yttria-stabilized zirconia FE

Electro/magnetoencephalographic signatures of human brain insulin resistance

Human insulin action influences eating behavior, peripheral metabolism and cognition. Detailed insights into the neuronal processes related to human brain insulin action can be obtained by direct measures of neuronal activity with electroencephalography and magnetoencephalography. Results of recent studies show that spontaneous, task and stimulus related neuronal activity is modulated by insulin and that several factors like increased body weight and body composition can result in brain insulin resistance. Recent technological advances even allow the investigation of human brain functions in utero in relation to the metabolic status of the mother and indicate an effect of the mother’s insulin sensitivity on the brain function of the fetus. In conclusion, studies based on direct neuronal measurements may help to determine the developmental trajectory related to insulin action and resistance

Traveling Wave Magnetic Particle Imaging for determining the iron-distribution in rock: Traveling Wave Magnetic Particle Imaging for determining the iron-distribution in rock

Determining the composition of solid materials is of high interest in areas such as material research or quality assurance. There are several modalities at disposal with which various parameters of the material can be observed, but of those only magnetic resonance imaging (MRI) or computer tomography (CT) offer anon-destructive determination of material distribution in 3D. A novel non-destructive imaging method is Magnetic Particle Imaging (MPI), which uses dynamic magnetic fields for a direct determination of the distribution of magnetic materials in 3D. With this approach, it is possible to determine and differentiate magnetic and non-magnetic behaviour. In this paper, the first proof-of-principle measurements of magnetic properties in solid environments are presented using a home-built traveling wave magnetic particle imaging scanner

Breadboard model of the LISA phasemeter

An elegant breadboard model of the LISA phasemeter is currently under development by a Danish-German consortium. The breadboard is build in the frame of an ESA technology development activity to demonstrate the feasibility and readiness of the LISA metrology baseline architecture. This article gives an overview about the breadboard design and its components, including the distribution of key functionalities.Comment: 5 pages, 3 figures, published in ASP Conference Series, Vol. 467, 9th LISA Symposium (2012), pp 271-27

Readout for intersatellite laser interferometry: Measuring low frequency phase fluctuations of HF signals with microradian precision

Precision phase readout of optical beat note signals is one of the core techniques required for intersatellite laser interferometry. Future space based gravitational wave detectors like eLISA require such a readout over a wide range of MHz frequencies, due to orbit induced Doppler shifts, with a precision in the order of $\mu \textrm{rad}/\sqrt{\textrm{Hz}}$ at frequencies between $0.1\,\textrm{mHz}$ and $1\,\textrm{Hz}$. In this paper, we present phase readout systems, so-called phasemeters, that are able to achieve such precisions and we discuss various means that have been employed to reduce noise in the analogue circuit domain and during digitisation. We also discuss the influence of some non-linear noise sources in the analogue domain of such phasemeters. And finally, we present the performance that was achieved during testing of the elegant breadboard model of the LISA phasemeter, that was developed in the scope of an ESA technology development activity.Comment: submitted to Review of Scientific Instruments on April 30th 201

Interaction between the obesity-risk gene FTO and the dopamine D2 receptor gene ANKK1/TaqIA on insulin sensitivity

Variations in FTO are the strongest common genetic determinants of adiposity, and may partly act by influencing dopaminergic signalling in the brain leading to altered reward processing that promotes increased food intake. Therefore, we investigated the impact of such an interaction on body composition, and peripheral and brain insulin sensitivity. Participants from the Tubingen Family study (n = 2245) and the Malmo Diet and Cancer study (n = 2921) were genotyped for FTO SNP rs8050136 and ANKK1 SNP rs1800497. Insulin sensitivity in the caudate nucleus, an important reward area in the brain, was assessed by fMRI in 45 participants combined with intranasal insulin administration. We found evidence of an interaction between variations in FTO and an ANKK1 polymorphism that associates with dopamine (D2) receptor density. In cases of reduced D2 receptor availability, as indicated by the ANKK1 polymorphism, FTO variation was associated with increased body fat and waist circumference and reduced peripheral insulin sensitivity. Similarly, altered central insulin sensitivity was observed in the caudate nucleus in individuals with the FTO obesity-risk allele and diminished D2 receptors. The effects of variations in FTO are dependent on dopamine D2 receptor density (determined by the ANKK1 polymorphism). Carriers of both risk alleles might, therefore, be at increased risk of obesity and diabetes.Peer reviewe