334 research outputs found

    Design of a Broadband Amplifier for High Speed Applications

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    This paper provides comprehensive insight into the design approach followed for an amplifier dedicated to high speed base band signals. To demonstrate the methodology, an amplifier consisting of nine PHEMT cascode cells within a distributed amplifier topology was designed. The resulting frequency response is 40 GHz at the 3-dB point, and the output voltage for a 43 Gbps eye diagram is 7.3 Vpp at the chip terminal

    Representation of differential operators in wavelet basis

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    AbstractExisting work on the representation of operators in one-dimensional, compactly-supported, orthonormal wavelet bases is extended to two dimensions. The nonstandard form of the representation of operators is given in separable two-dimensional, periodic, orthonormal wavelet bases. The matrix representation of the partial-differential operators ∂x and ∂y are constructed and a closed form formula for the matrix representation of a general partial-differential operator g(∂x, ∂y) is derived, where g is an analytic function

    Rituximab in the treatment of inflammatory myopathies: a review

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    Several uncontrolled studies have encouraged the use of rituximab (RTX) in patients with myositis. Unfortunately, the first placebo-phase trial to assess the efficacy of RTX in refractory myositis did not show a significant difference between the two treatment groups, and doubts have been expressed about its study design. In this review we present an up-to-date overview of the reported experiences of RTX therapy in myositis. A PubMed search was performed to find all the available cases of refractory myositis patients treated with RTX up to July 2015. The following terms were assessed: inflammatory myopathies OR anti-synthetase syndrome OR polymyositis OR dermatomyositis AND RTX. A total of 48 studies were included. We identified 458 patients with myositis treated with RTX. We found a rate of response to RTX of 78.3%. RTX can play a role in the management of patients with myositis, at least in those with positive myositis-specific autoantibodies

    Prise en charge des complications des fistules artério-veineuses pour hémodialyse chronique

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    La fistule artério-veineuse native est l'accès vasculaire de choix pour  l'hémodialyse chronique en raison de sa longévité, son taux faible de complication et de mortalité par rapport aux pontages artério-veineux et aux cathéters. Cependant, il arrive assez souvent que l'on assiste à des complications qui sont dominées par la sténose et la thrombose. C'est une étude rétrospective des complications ayants survenues pour 31 fistules artério-veineuses pour hémodialyse chronique des 200 fistules réalisées chez 200 patients au sein du service de chirurgie vasculaire du CHU Hassan II de Fès sur une période de trois ans, étendue de Janvier 2007 à  Décembre 2009. Ces complications ont été présentés par les thrombosesdans 14 cas soit 45,15% de l'ensemble des complications, les sténoses dans 4 cas (12,90%,) les anévrismes dans 4 cas (12,90%), les  complications ischémiques dans 3 cas (9,67%), l'infection dans 3 cas (9,67%), l'hémorragie dans 2 cas (6,45%) et l' hyperdébit dans un seul cas soit 3,22%. On a pu conserver 22 fistules soit 70,96% par traitement chirurgical ou endovasculaire, on a confectionné une nouvelle fistule dans 8cas soit 25,80%, et on a adressé une patiente (3,22%) pour pose d'un cathéter veineux tunnelisé permanent. Les complications des fistules artério-veineuses pour l'hémodialyse chronique sont la principale cause de morbidité chez les patients hémodialysés, il est donc important de s'impliquer lors de leur création, et de donner un maximum d'attention quand ils sont manipulés. Ceci suggère la mise en place d'un programme de surveillance de ces fistules en raison de l'impact des complications sur la morbi-mortalité du patient hémodialysé et sur le plan financier

    The geoenvironmental factors influencing slope failures in the Majerda basin, Algerian-Tunisian border

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    In mountainous regions globally, landslides pose severe threats to both human lives and infrastructure, with the Mediterranean region, in particular, being highly susceptible to these destructive events that result in substantial damage to settlements and infrastructure. In this study, we employ a GIS-based approach to comprehensively characterize terrain instabilities along the Algerian-Tunisian border, recognizing the critical need for effective land planning and disaster mitigation strategies in this context. Our methodology integrates geological, geophysical, and geotechnical reconnaissance techniques and multi-criteria analysis, with a particular focus on geotechnical parameters. Our findings reveal significant slope instability within the study area; it is particularly concentrated in the mid-altitude slopes of the eastern basin, with high and very high susceptibility zones covering 20.89% of the study area. Validation of our model through ROC analysis demonstrates its high accuracy, with an area under the curve (AUC) value of 0.92. Crucially, slope gradients and precipitation emerge as key contributors to landslide occurrence, alongside Triassic lithofacies, which is a significant geological factor influencing susceptibility. These results emphasize the necessity of identifying high-landslide-susceptibility regions for sustainable land management and risk reduction, which will ultimately enhance the resilience of the studied region and mitigate the associated natural hazard risks

    PGC-1α controls mitochondrial biogenesis and dynamics in lead-induced neurotoxicity

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    Due to its role in regulation of mitochondrial function, PGC1α is emerging as an important player in ageing and neurodegenerative disorders. PGC1α exerts its neuroprotective effects by promoting mitochondrial biogenesis (MB) and functioning. However, the precise regulatory role of PGC1α in the control of mitochondrial dynamics (MD) and neurotoxicity is still unknown. Here we elucidate the role of PGC1α in vitro and in vivo in the regulatory context of MB and MD in response to lead (II) acetate as a relevant model of neurotoxicity. We show that there is an adaptive response (AR) to lead, orchestrated by the BAP31-calcium signalling system operating between the ER and mitochondria. We find that this hormetic response is controlled by a cell-tolerated increase of PGC1α expression, which in turn induces a balanced expression of fusion/fission genes by binding to their promoters and implying its direct role in regulation of MD. However, dysregulation of PGC1α expression through either stable downregulation or overexpression, renders cells more susceptible to lead insult leading to mitochondrial fragmentation and cell death. Our data provide novel evidence that PGC1α expression is a key regulator of MD and the maintenance of tolerated PGC1α expression may offer a promising strategy for neuroprotective therapies.España Ministerio de Economía y Competitividad SAF2012-3902

    The contribution of deep learning to the semantic segmentation of 3D point-clouds in urban areas

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    peer reviewedSemantic segmentation in a large-scale urban environment is crucial for a deep and rigorous understanding of urban environments. The development of Lidar tools in terms of resolution and precision offers a good opportunity to satisfy the need of developing 3D city models. In this context, deep learning revolutionizes the field of computer vision and demonstrates a good performance in semantic segmentation. To achieve this objective, we propose to design a scientific methodology involving a method of deep learning by integrating several data sources (Lidar data, aerial images, etc) to recognize objects semantically and automatically. We aim at extracting automatically the maximum amount of semantic information in a urban environment with a high accuracy and performance

    Exploring Spatial Interaction and Visualization Paradigms for 3D Cadastral Visualization

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    Effective visualization of spatial data, especially in the realm of 3D cadastral visualization, relies on the utilization of optimal interaction techniques and user interfaces for navigating complex datasets and understanding property delineations. This paper synthesizes findings from diverse studies investigating the efficacy of interaction modalities and user interfaces in 3D visualization across various domains. Drawing parallels to the broader field of 3D visualization, particularly in interaction tasks and user interface paradigms, this paper examines the potential for advancing 3D cadastral visualization systems. The study identifies fundamental interaction tasks crucial for effective 3D cadastral visualization, including object manipulation, widget manipulation, and data selection and annotation. It evaluates a range of user interfaces, from traditional input methods to emerging technologies such as gesture-based interfaces and virtual reality (VR) headsets, highlighting their respective strengths and limitations.Embracing insights from comparative analyses of immersive and non-immersive scenarios, this paper reveals significant insights into the effectiveness of immersive environments, such as virtual reality and augmented reality, in enhancing user experience and task performance for 3D cadastral visualization. Additionally, it aims to address key challenges associated with visualizing 3D cadastral data in immersive environments by proposing a comprehensive framework for evaluating the effectiveness and utility of immersive visualization for 3D cadastral purposes

    Deep Learning Based Semantic Segmentation for BIM Model Generation from RGB-D Sensors

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    RGB-D sensors offer a low-cost and promising solution to streamline the generation of BIM models. This paper introduces a framework designed to automate the creation of detailed and semantically rich BIM models from RGB-D data in indoor environments. The framework leverages advanced computer vision and deep learning techniques to overcome the challenges associated with traditional, labour-intensive BIM modeling methods. The results show that the proposed method is robust and accurate, compared to the high-quality statistic laser scanning TLS. Indeed, 58% of the distances measured between the calculated and the reference point cloud produced by TLS were under 5 cm, and 82% of distances were smaller than 7 cm. Furthermore, the framework achieves 100% accuracy in element extraction. Beyond its accuracy, the proposed framework significantly enhances efficiency in both data acquisition and processing. In contrast to the time-consuming process associated with TLS, our approach remarkably reduces the data collection and processing time by factor of height. This highlights the framework’s substantial improvements in accuracy and efficiency throughout the BIM generation workflows, making it a streamlined and time-effective solution
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