Negative capacitance in organic semiconductor devices: bipolar injection and charge recombination mechanism

We report negative capacitance at low frequencies in organic semiconductor based diodes and show that it appears only under bipolar injection conditions. We account quantitatively for this phenomenon by the recombination current due to electron-hole annihilation. Simple addition of the recombination current to the well established model of space charge limited current in the presence of traps, yields excellent fits to the experimentally measured admittance data. The dependence of the extracted characteristic recombination time on the bias voltage is indicative of a recombination process which is mediated by localized traps.Comment: 3 pages, 3 figures, accepted for publication in Applied Physics Letter

Combining Appearance and Motion for Human Action Classification in Videos

We study the question of activity classification in videos and present a novel approach for recognizing human action categories in videos by combining information from appearance and motion of human body parts. Our approach uses a tracking step which involves Particle Filtering and a local non - parametric clustering step. The motion information is provided by the trajectory of the cluster modes of a local set of particles. The statistical information about the particles of that cluster over a number of frames provides the appearance information. Later we use a “Bag ofWords” model to build one histogram per video sequence from the set of these robust appearance and motion descriptors. These histograms provide us characteristic information which helps us to discriminate among various human actions and thus classify them correctly. We tested our approach on the standard KTH and Weizmann human action datasets and the results were comparable to the state of the art. Additionally our approach is able to distinguish between activities that involve the motion of complete body from those in which only certain body parts move. In other words, our method discriminates well between activities with “gross motion” like running, jogging etc. and “local motion” like waving, boxing etc

Semi-supervised Analysis of Human fMRI Data

Kernel Canonical Correlation Analysis (KCCA) is a general technique for subspace learning that incorporates principal components analysis (PCA) and Fisher linear discriminant analysis (LDA) as special cases. By finding directions that maximize correlation, CCA learns representations tied more closely to underlying process generating the the data and can ignore high-variance noise directions. However, for data where acquisition in a given modality is expensive or otherwise limited, CCA may suffer from small sample effects. We propose to use semisupervised Laplacian regularization to utilize data that are present in only one modality. This approach is able to find highly correlated directions that also lie along the data manifold, resulting in a more robust estimate of correlated subspaces. Functional magnetic resonance imaging (fMRI) acquired data are naturally amenable to subspace techniques as data are well aligned. fMRI data of the human brain are a particularly interesting candidate. In this study we implemented various supervised and semi-supervised versions of CCA on human fMRI data, with regression to single and multivariate labels (corresponding to video content subjects viewed during the image acquisition). In each variate condition, the semi-supervised variants of CCA performed better than the supervised variants, including a supervised variant with Laplacian regularization. We additionally analyze the weights learned by the regression in order to infer brain regions that are important to different types of visual processing

Self-consistent model of unipolar transport in organic semiconductor diodes: accounting for a realistic density-of-states distribution

A self-consistent, mean-field model of charge-carrier injection and unipolar transport in an organic semiconductor diode is developed utilizing the effective transport energy concept and taking into account a realistic density-of-states distribution as well as the presence of trap states in an organic material. The consequences resulting from the model are discussed exemplarily on the basis of an indium tin oxide/organic semiconductor/metallic conductor structure. A comparison of the theory to experimental data of a unipolar indium tin oxide/poly-3-hexyl-thiophene/Al device is presented.Comment: 6 pages, 2 figures; to be published in Journal of Applied Physic

Characterisation of an n-type segmented BEGe detector

A four-fold segmented n-type point-contact "Broad Energy" high-purity germanium detector, SegBEGe, has been characterised at the Max-Planck-Institut f\"ur Physik in Munich. The main characteristics of the detector are described and first measurements concerning the detector properties are presented. The possibility to use mirror pulses to determine source positions is discussed as well as charge losses observed close to the core contact

Bisphenol A Binds to the Local Anesthetic Receptor Site to Block the Human Cardiac Sodium Channel

Bisphenol A (BPA) has attracted considerable public attention as it leaches from plastic used in food containers, is detectable in human fluids and recent epidemiologic studies link BPA exposure with diseases including cardiovascular disorders. As heart-toxicity may derive from modified cardiac electrophysiology, we investigated the interaction between BPA and hNav1.5, the predominant voltage-gated sodium channel subtype expressed in the human heart. Electrophysiology studies of heterologously-expressed hNav1.5 determined that BPA blocks the channel with a Kd of 25.4±1.3 µM. By comparing the effects of BPA and the local anesthetic mexiletine on wild type hNav1.5 and the F1760A mutant, we demonstrate that both compounds share an overlapping binding site. With a key binding determinant thus identified, an homology model of hNav1.5 was generated based on the recently-reported crystal structure of the bacterial voltage-gated sodium channel NavAb. Docking predictions position both ligands in a cavity delimited by F1760 and contiguous with the DIII–IV pore fenestration. Steered molecular dynamics simulations used to assess routes of ligand ingress indicate that the DIII–IV pore fenestration is a viable access pathway. Therefore BPA block of the human heart sodium channel involves the local anesthetic receptor and both BPA and mexiletine may enter the closed-state pore via membrane-located side fenestrations

Desdobramento da estratégia para avaliação de desempenho: implantação do Balanced Scorecard (BSC) no processo produtivo da pecuária de corte bovina.

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Carbon footprint in different beef production systems on a southern Brazilian farm: a case study.

The carbon footprint (CF) of beef production is one of the most widely discussed environmental issues within the current agricultural community due to its association with climate change. Because of these relevant and serious concerns, the beef cattle industry is under increasing pressure to reduce production or implement technological changes with significant consequences in terms of beef marketing. The goals of this study were to evaluate the CF per 1 kg of live weight gain (LWG) at the farm gate for different beef production systems in the southern part of Brazil. Aberdeen Angus beef-bred cattle were assigned to one of seven categories: natural grass; improved natural grass; natural grass plus ryegrass; improved natural grass plus sorghum; cultivated ryegrass and sorghum; natural grass supplemented with protein mineralised salt; and natural grass supplemented with protein-energetic mineralised salt. Monte Carlo analysis was employed to analyse the effect of variations of dry matter intake digestibility (DMID), total digestible nutrients (TDN) and crude protein (CP) parameters in methane (CH4) enteric, CH4 manure, nitrous oxide (N2O) manure and N2O N-fertiliser. The method used was a comparative life cycle assessment (LCA) centred on the CF. The CF varied from 18.3 kg CO2 equivalent/kg LWG for the ryegrass and sorghum pasture system to 42.6 kg CO2 equivalent/kg LWG for the natural grass system, including the contributions of cows, calves and steers. Among all grassland-based cattle farms, production systems with DMID from 52 to 59% achieved the lowest CO2 emissions and the highest feed conversion rate, thereby generating lower CH4 and N2O emissions per production system. Because the feed intake and feed conversion rate are one of the most important production parameters in beef cattle production with an obvious risk of data uncertainty, accurate feed data, which include quantity and quality, are important in estimates of CF for LWG. The choice of adequate feeding strategies to mitigate greenhouse gas (GHG) emissions may result in better environmental advantages