Light-activated amplification in SiC Tandem devices: A capacitive active filter model

Characteristics of tunable wavelength pi'n/pin filters based on a-SiC:H multilayered stacked cells are studied both experimentally and theoretically. Results show that the device combines the demultiplexing operation with the simultaneous photodetection and self amplification of the signal. An algorithm to decode the multiplex signal is established. A capacitive active band-pass filter model is presented and supported by an electrical simulation of the state variable filter circuit. Experimental and simulated results show that the device acts as a state variable filter. It combines the properties of active high-pass and low-pass filter sections into a capacitive active band-pass filter using a changing capacitance to control the power delivered to the load.

Estimation of signal subspace on hyperspectral data

Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.

Performance Model for MRC Receivers with Adaptive Modulation and Coding in Rayleigh Fading Correlated Channels with Imperfect CSIT

RTUWO Advances in Wireless and Optical Communications 2015 (RTUWO 2015). 5-6 Nov Riga, Latvia.

New visualization model for large scale biosignals analysis

Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.

Search for the Standard Model Higgs boson produced in association with top quarks and decaying into bb in pp collisions at √s = 8 TeV with the ATLAS detector

A search for the Standard Model Higgs boson produced in association with a pair of top quarks, tt¯H, is presented. The analysis uses 20.3 fb−1 of pp collision data at s√ = 8 TeV, collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the H to bb¯ decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b-tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominated by tt¯+jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible tt¯+bb¯ background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95% confidence level. The ratio of the measured tt¯H signal cross section to the Standard Model expectation is found to be μ=1.5±1.1 assuming a Higgs boson mass of 125 GeV.

Search for the bb¯ decay of the Standard Model Higgs boson in associated (W/Z)H production with the ATLAS detector

A search for the bb¯ decay of the Standard Model Higgs boson is performed with the ATLAS experiment using the full dataset recorded at the LHC in Run 1. The integrated luminosities used from pp collisions at s√=7 and 8 TeV are 4.7 and 20.3 fb−1, respectively. The processes considered are associated (W/Z)H production, where W→eν/μν, Z→ee/μμ and Z→νν. The observed (expected) deviation from the background-only hypothesis corresponds to a significance of 1.4 (2.6) standard deviations and the ratio of the measured signal yield to the Standard Model expectation is found to be μ=0.52±0.32(stat.)±0.24(syst.) for a Higgs boson mass of 125.36 GeV. The analysis procedure is validated by a measurement of the yield of (W/Z)Z production with Z→bb¯ in the same final states as for the Higgs boson search, from which the ratio of the observed signal yield to the Standard Model expectation is found to be 0.74±0.09(stat.)±0.14(syst.).

Investigation of field and diffusion time dependence of the diffusion-weighted signal at ultrahigh magnetic fields.

Over the last decade, there has been a significant increase in the number of high-magnetic-field MRI magnets. However, the exact effect of a high magnetic field strength (B0 ) on diffusion-weighted MR signals is not yet fully understood. The goal of this study was to investigate the influence of different high magnetic field strengths (9.4 T and 14.1 T) and diffusion times (9, 11, 13, 15, 17 and 24 ms) on the diffusion-weighted signal in rat brain white matter. At a short diffusion time (9 ms), fractional anisotropy values were found to be lower at 14.1 T than at 9.4 T, but this difference disappeared at longer diffusion times. A simple two-pool model was used to explain these findings. The model describes the white matter as a first hindered compartment (often associated with the extra-axonal space), characterized by a faster orthogonal diffusion and a lower fractional anisotropy, and a second restricted compartment (often associated with the intra-axonal space), characterized by a slower orthogonal diffusion (i.e. orthogonal to the axon direction) and a higher fractional anisotropy. Apparent T2 relaxation time measurements of the hindered and restricted pools were performed. The shortening of the pseudo-T2 value from the restricted compartment with B0 is likely to be more pronounced than the apparent T2 changes in the hindered compartment. This study suggests that the observed differences in diffusion tensor imaging parameters between the two magnetic field strengths at short diffusion time may be related to differences in the apparent T2 values between the pools. Copyright © 2013 John Wiley & Sons, Ltd.

Distribution of free and liposomal doxorubicin after isolated lung perfusion in a sarcoma model

Rapport de synthèse : Introduction : La perfusion isolée du poumon à l'aide de Doxorubicine libre et une nouvelle forme de Doxorubicine liposomale pégylée (Liporubicine) est comparé en terme de pénétration et accumulation de Doxorubicine dans le tissu tumoral et pulmonaire dans un modèle de rats porteurs de tumeur sarcomateuse au niveau du poumon gauche. Matériel et méthode : Une tumeur sarcomateuse unique a été générée dans le poumon gauche de 39 Fischer rats, suivi 10 jours plus tard, par une perfusion isolée du poumon gauche (n =36) avec Doxorubicine libre (n=18) et Liporubicine (n=18) à une dose de 100 µg (n=9) et 400 µg (n=9) pour chaque formulation de Doxorubicine. Dans chaque poumon perfusé, la concentration de l'agent cytostatique et sa distribution ont été investiguées dans la tumeur et trois parties du poumon normal par HLPC (n=6) et par microscopie de florescence (n=3). Des analyses histologiques et inmunohistochimiques (facteur von Willebrand) ont été effectuées sur trois animaux non traités. Résultats : Les tumeurs sarcomateuses dans les animaux de contrôle démontraient une bonne vascularisation avec de fines branches capillaires qui étaient présentes partout dans les tumeurs. La perfusion isolée du poumon démontrait une distribution de l'agent cytostatique d'une manière hétérogène dans le poumon perfusé et une concentration de Doxorubicine inférieure dans les tumeurs par rapport au tissu pulmonaire sein pour les deux formulations de Doxorubicine et les deux doses appliquées. La perfusion isolée du poumon avec Doxorubicine libre démontrait une concentration significativement plus élevée que Liporubicine dans la tumeur et le parenchyme pulmonaire pour les deux doses appliquées (p < 0,01). Néanmoins, le coefficient de concentration tumorale et pulmonaire était plus bas pour Doxorubicine libre que pour Liporubicine pour une dose de 100 µg (0.27 ± 0.1 vs 0.53 ± 0.5, p=0.23) tandis qu'il était similaire pour les deux formulations de Doxorubicine à une dose de 400 µg (0.67 ± 0.2 vs 0.54 ± 0.2, p=0.34). Les deux formulations de Doxorubicine émergeaient un signal de fluorescence provenant de tous les compartiments du parenchyme pulmonaire mais seulement un signal sporadique et faible émergeant des tumeurs, provenant de la périphérie de la tumeur et des vaisseaux situés à l'intérieur de la tumeur, pour les deux doses appliquées. Conclusion : La perfusion isolée du poumon démontrait une distribution hétérogène de la Doxorubicine et sa forme liposomale dans le poumon perfusé et une accumulation plus faible dans la tumeur que dans le tissu parenchymateux adjacent pour les deux formulations de Doxorubicine et les deux doses appliquées.

Increased neurotransmitter release at the neuromuscular junction in a mouse model of polyglutamine disease.

In Huntington's disease (HD), the expansion of polyglutamine (polyQ) repeats at the N terminus of the ubiquitous protein huntingtin (htt) leads to neurodegeneration in specific brain areas. Neurons degenerating in HD develop synaptic dysfunctions. However, it is unknown whether mutant htt impacts synaptic function in general. To investigate that, we have focused on the nerve terminals of motor neurons that typically do not degenerate in HD. Here, we have studied synaptic transmission at the neuromuscular junction of transgenic mice expressing a mutant form of htt (R6/1 mice). We have found that the size and frequency of miniature endplate potentials are similar in R6/1 and control mice. In contrast, the amplitude of evoked endplate potentials in R6/1 mice is increased compared to controls. Consistent with a presynaptic increase of release probability, synaptic depression under high-frequency stimulation is higher in R6/1 mice. In addition, no changes were detected in the size and dynamics of the recycling synaptic vesicle pool. Moreover, we have found increased amounts of the synaptic vesicle proteins synaptobrevin 1,2/VAMP 1,2 and cysteine string protein-α, and the SNARE protein SNAP-25, concomitant with normal levels of other synaptic vesicle markers. Our results reveal that the transgenic expression of a mutant form of htt leads to an unexpected gain of synaptic function. That phenotype is likely not secondary to neurodegeneration and might be due to a primary deregulation in synaptic protein levels. Our findings could be relevant to understand synaptic toxic effects of proteins with abnormal polyQ repeats.

New insights into dendritic cell biology and histiocytosis through a transgenic tumor model

SUMMARY The effective development of an immune response depends on the careful interplay and the regulation between innate and adaptive immunity. As the dendritic cells (DCs) are equipped with many receptors, such as Toll-like receptors, which can detect the presence of infection by recognizing different component of bacteria, fungi and even viruses, they are the among the first cells to respond to the infection. Upon pathogen challenge, the DCs interpret the innate system activation as a maturation signal, resulting in the migration of the DCS to a draining lymph node site. There, activated DCs present efficiently antigens to naïve T cells, which are in turn activated and initiate adaptive immunity. Therefore, DCs are the main connectors between innate and adaptive immune systems. In addition to be the most efficient antigen- presenting cells, DCs play a central role in the regulation of immune responses and immune tolerance. Despite extensive research, many aspects related to DC biology are still unsolved and/or controversial. The low frequency of DCs in vivo often hamper study of DC biology and in vitro-derived DCs are not suited to address certain questions, such as the development of DC. We sought of transforming in vivo the DCs through the specific expression of an oncogene, in order to obtain unlimited numbers of these cells. To achieve this goal, transgenic mouse lines expressing the SV40 Large T oncogene under the control of the CD1 1 c promoter were generated. These transgenic mice are healthy until the age of three to four months without alterations in the DC biology. Thereafter transgenic mice develop a fatal disease that shows features of a human pathology, named histiocytosis, involving DCs. We demonstrate that the disease development in the transgenic mice correlates with a massive accumulation of transformed DCs in the affected organs. Importantly, transformed DCs are immature and fully conserve their capacity to mature in antigen presenting cells. We observe hyperproliferation of transformed DCs only in the sick transgenic mice. Surprisingly, transformed DCs do not proliferate in vitro, but transfer of the transformed DCs into immunodeficient or tolerant host leads to tumor formation. Altoghether, the transgenic mouse lines we have generated represent a valuable tumor model for human histiocytosis, and provide excellent tools to study DC biology. RESUME Le développement d'une réponse immunitaire efficace dépend d'une minutieuse interaction et régulation entre l'immunité innée et adaptative. Comme les cellules dendritiques (DCs) sont équipées de nombreux récepteurs, tels que les récepteurs Toll-like, qui peuvent détecter la présence d'une infection en reconnaissant différents composants bactériens, issus de champignons ou même viraux, elles sont parmi les premières cellules à répondre à l'infection. Suite à la stimulation induite par le pathogène, les DCs interprètent l'activation du système immunitaire inné comme un signal de maturation, résultant dans la migration des DCs vers le ganglion drainant le site d'infection. Là, les DCs actives présentent efficacement des antigènes aux cellules T, qui sont à leur tour activées et initient les systèmes d'immunité adaptative. Ainsi, les DCs forment le lien principal entre les réponses immunitaires innées et adaptatives. En plus d'être les cellules présentatrices d'antigènes les plus efficaces, les DCs jouent un rôle central dans la régulation du système immunitaire et dans le phénomène de tolérance. Malgré des recherches intensives, de nombreux aspects liés à la biologie des DCs sont encore irrésolus et/ou controversés. La faible fréquence des DCs in vivo gêne souvent l'étude de la biologie de ces cellules et les DCs dérivées in vitro ne sont pas adéquates pour adresser certaines questions, telles que le développement des DCs. Afin d'obtenir des quantités illimitées de DCs, nous avons songé à transformer in vivo les DC grâce à l'expression spécifique d'un oncogène. Afin d'atteindre ce but, nous avons généré des lignées de souris transgéniques qui expriment l'oncogène SV40 Large T sous le contrôle du promoter CD1 le. Ces souris transgéniques sont saines jusqu'à l'âge de trois à quatre mois et ne présentent pas d'altération dans la biologie des DCs. Ensuite, les souris transgéniques développent une maladie présentant les traits caractéristiques d'une pathologie humaine nommée histiocytose, qui implique les DCs. Nous montrons que le développement de cette maladie corrèle avec une accumulation massive des DCs transformées dans les organes touchés. De plus, les DCs transformées sont immatures et conservent leur capacité à différencier en cellules présentatrices d'antigène. Nous observons une hyper-prolifération des DCs transformées seulement dans les souris transgéniques malades. Etonnament, les DC transformées ne prolifèrent pas in vitro, par contre, le transfert des DCs transformées dans des hôtes immuno-déficients ou tolérant conduit à la formation de tumeurs. Globalement, les lignées de souris transgéniques que nous avons générées représentent un modèle valide pour l'histiocytose humaine, et de plus, offrent d'excellents outils pour étudier la biologie des DCs.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Detection of neuronal activity and metabolism in a model of dehydration-induced anorexia in rats at 14.1 T using manganese-enhanced MRI and 1H MRS.

In this study, hypothalamic activation was performed by dehydration-induced anorexia (DIA) and overnight food suppression (OFS) in female rats. The assessment of the hypothalamic response to these challenges by manganese-enhanced MRI showed increased neuronal activity in the paraventricular nuclei (PVN) and lateral hypothalamus (LH), both known to be areas involved in the regulation of food intake. The effects of DIA and OFS were compared by generating T-score maps. Increased neuronal activation was detected in the PVN and LH of DIA rats relative to OFS rats. In addition, the neurochemical profile of the PVN and LH were measured by (1) H MRS at 14.1T. Significant increases in metabolite levels were measured in DIA and OFS relative to control rats. Statistically significant increases in γ-aminobutyric acid were found in DIA (p=0.0007) and OFS (p<0.001) relative to control rats. Lactate increased significantly in DIA (p=0.03), but not in OFS, rats. This work shows that manganese-enhanced MRI coupled to (1) H MRS at high field is a promising noninvasive method for the investigation of the neural pathways and mechanisms involved in the control of food intake, in the autonomic and endocrine control of energy metabolism and in the regulation of body weight.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.