282 research outputs found

    Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce

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    The kernel kk-means is an effective method for data clustering which extends the commonly-used kk-means algorithm to work on a similarity matrix over complex data structures. The kernel kk-means algorithm is however computationally very complex as it requires the complete data matrix to be calculated and stored. Further, the kernelized nature of the kernel kk-means algorithm hinders the parallelization of its computations on modern infrastructures for distributed computing. In this paper, we are defining a family of kernel-based low-dimensional embeddings that allows for scaling kernel kk-means on MapReduce via an efficient and unified parallelization strategy. Afterwards, we propose two methods for low-dimensional embedding that adhere to our definition of the embedding family. Exploiting the proposed parallelization strategy, we present two scalable MapReduce algorithms for kernel kk-means. We demonstrate the effectiveness and efficiency of the proposed algorithms through an empirical evaluation on benchmark data sets.Comment: Appears in Proceedings of the SIAM International Conference on Data Mining (SDM), 201

    PHP62 VALUE OF CONGRESS ABSTRACTS OF COST-EFFECTIVENESS STUDIES FOR DECISION MAKERS

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    Evaluation of native microalgae from Tunisia using the pulse-amplitude-modulation measurement of chlorophyll fluorescence and a performance study in semi-continuous mode for biofuel production

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    Background: Microalgae are attracting much attention as a promising feedstock for renewable energy production, while simultaneously providing environmental benefits. So far, comparison studies for microalgae selection for this purpose were mainly based on data obtained from batch cultures, where the lipid content and the growth rate were the main selection parameters. The present study evaluates the performance of native microalgae strains in semi-continuous mode, considering the suitability of the algal-derived fatty acid composition and the saponifiable lipid productivity as selection criteria for microalgal fuel production. Evaluation of the photosynthetic performance and the robustness of the selected strain under outdoor conditions was conducted to assess its capability to grow and tolerate harsh environmental growth conditions. Results: In this study, five native microalgae strains from Tunisia (one freshwater and four marine strains) were isolated and evaluated as potential raw material to produce biofuel. Firstly, molecular identification of the strains was performed. Then, experiments in semi-continuous mode at different dilution rates were carried out. The local microalgae strains were characterized in terms of biomass and lipid productivity, in addition to protein content, and fatty acid profile, content and productivity. The marine strain Chlorella sp. showed, at 0.20 1/day dilution rate, lipid and biomass productivities of 35.10 mg/L day and 0.2 g/L day, respectively. Moreover, data from chlorophyll fluorescence measurements demonstrated the robustness of this strain as it tolerated extreme outdoor conditions including high (38 ° C) and low (10 ° C) temperature, and high irradiance (1600 µmol/m2 s). Conclusions: Selection of native microalgae allows identifying potential strains suitable for use in the production of biofuels. The selected strain Chlorella sp. demonstrated adequate performance to be scaled up to outdoor conditions. Although experiments were performed at laboratory conditions, the methodology used in this paper allows a robust evaluation of microalgae strains for potential market applications.This study was supported by the Marine Microalgae Biotechnology Group at the University of Almer'a (BIO 173) and the Campus de Excelencia Internacional Agroalimentario (ceiA3) within the joint framework of supervised theses between the University of Almeria, Spain and the University of Sfax, Tunisia.Scopu

    Selection of native Tunisian microalgae for simultaneous wastewater treatment and biofuel production

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    This paper focuses on the selection of native microalgae strains suitable for wastewater treatment and biofuel production. Four Chlorophyceae strains were isolated from North-eastern Tunisia. Their performances were compared in continuous mode at a 0.3 1/day dilution rate. The biomass productivity and nutrient removal capacity of each microalgae strain were studied. The most efficient strain was identified as Scenedesmus sp. and experiments at different dilution rates from 0.2 to 0.8 1/day were carried out. Maximal biomass productivity of 0.92 g/L·day was obtained at 0.6 1/day. The removal of chemical oxygen demand (COD), ammonium and phosphorus was in the range of 92-94%, 61-99% and 93-99%, respectively. Carbohydrates were the major biomass fraction followed by lipids and then proteins. The saponifiable fatty acid content was in the 4.9-13.2% dry biomass range, with more than 50% of total fatty acids being composed of saturated and monosaturated fatty acids

    Detecting failure of a material handling system through a cognitive twin

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    This paper describes a methodology for developing a digital twin (DT) based on a rich semantic model and principles of system engineering. The aim is to provide a general model of digital twins (DT) that can improve decision making based on semantic reasoning on real-time system monitoring. The methodology has been tested on a laboratory pilot plant that acts as a material handling system. The key contribution of this research is to propose a generic information model for DT using foundational ontology and principles of systems engineering. The efficacy of the proposed methodology is demonstrated by the automatic detection of a component level failure using semantic reasoning

    Cross-Reactive Human IgM-Derived Monoclonal Antibodies that Bind to HIV-1 Envelope Glycoproteins

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    Elicitation of antibodies with potent and broad neutralizing activity against HIV by immunization remains a challenge. Several monoclonal antibodies (mAbs) isolated from humans with HIV-1 infection exhibit such activity but vaccine immunogens based on structures containing their epitopes have not been successful for their elicitation. All known broadly neutralizing mAbs (bnmAbs) are immunoglobulin (Ig) Gs (IgGs) and highly somatically hypermutated which could impede their elicitation. Ig Ms (IgMs) are on average significantly less divergent from germline antibodies and are relevant for the development of vaccine immunogens but are underexplored compared to IgGs. Here we describe the identification and characterization of several human IgM-derived mAbs against HIV-1 which were selected from a large phage-displayed naive human antibody library constructed from blood, lymph nodes and spleens of 59 healthy donors. These antibodies bound with high affinity to recombinant envelope glycoproteins (gp140s, Envs) of HIV-1 isolates from different clades. They enhanced or did not neutralize infection by some of the HIV-1 primary isolates using CCR5 as a coreceptor but neutralized all CXCR4 isolates tested although weakly. One of these antibodies with relatively low degree of somatic hypermutation was more extensively characterized. It bound to a highly conserved region partially overlapping with the coreceptor binding site and close to but not overlapping with the CD4 binding site. These results suggest the existence of conserved structures that could direct the immune response to non-neutralizing or even enhancing antibodies which may represent a strategy used by the virus to escape neutralizing immune responses. Further studies will show whether such a strategy plays a role in HIV infection of humans, how important that role could be, and what the mechanisms of infection enhancement are. The newly identified mAbs could be used as reagents to further characterize conserved non-neutralizing, weakly neutralizing or enhancing epitopes and modify or remove them from candidate vaccine immunogens

    Arthroscopic removal of an osteoid osteoma of the acetabulum

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    In this case report, we describe the arthroscopic removal of an osteoid osteoma from the acetabulum in a young adolescent. After identifying the osteoid osteoma close to the cartilage with MRI and CT investigations, we decided that in this case, arthroscopic removal was the best treatment. In the case of an osteoid osteoma in the acetabulum close to the cartilage, arthroscopic removal should be considered as one can treat the associated osteochondritic lesion during this procedure

    Opposing Roles for Membrane Bound and Soluble Fas Ligand in Glaucoma-Associated Retinal Ganglion Cell Death

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    Glaucoma, the most frequent optic neuropathy, is a leading cause of blindness worldwide. Death of retinal ganglion cells (RGCs) occurs in all forms of glaucoma and accounts for the loss of vision, however the molecular mechanisms that cause RGC loss remain unclear. The pro-apoptotic molecule, Fas ligand, is a transmembrane protein that can be cleaved from the cell surface by metalloproteinases to release a soluble protein with antagonistic activity. Previous studies documented that constitutive ocular expression of FasL maintained immune privilege and prevented neoangeogenesis. We now show that FasL also plays a major role in retinal neurotoxicity. Importantly, in both TNFα triggered RGC death and a spontaneous model of glaucoma, gene-targeted mice that express only full-length FasL exhibit accelerated RGC death. By contrast, FasL-deficiency, or administration of soluble FasL, protected RGCs from cell death. These data identify membrane-bound FasL as a critical effector molecule and potential therapeutic target in glaucoma
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