745 research outputs found

    Cycling Rate-Induced Spatially-Resolved Heterogeneities in Commercial Cylindrical Li-Ion Batteries

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    Synchrotron high-energy X-ray diffraction computed tomography has been employed to investigate, for the first time, commercial cylindrical Li-ion batteries electrochemically cycled over the two cycling rates of C/2 and C/20. This technique yields maps of the crystalline components and chemical species as a cross-section of the cell with high spatiotemporal resolution (550 × 550 images with 20 × 20 × 3 µm3 voxel size in ca. 1 h). The recently developed Direct Least-Squares Reconstruction algorithm is used to overcome the well-known parallax problem and led to accurate lattice parameter maps for the device cathode. Chemical heterogeneities are revealed at both electrodes and are attributed to uneven Li and current distributions in the cells. It is shown that this technique has the potential to become an invaluable diagnostic tool for real-world commercial batteries and for their characterization under operating conditions, leading to unique insights into “real” battery degradation mechanisms as they occur

    Search for sterile neutrino mixing in the MINOS long-baseline experiment

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    A search for depletion of the combined flux of active neutrino species over a 735 km baseline is reported using neutral-current interaction data recorded by the MINOS detectors in the NuMI neutrino beam. Such a depletion is not expected according to conventional interpretations of neutrino oscillation data involving the three known neutrino flavors. A depletion would be a signature of oscillations or decay to postulated noninteracting sterile neutrinos, scenarios not ruled out by existing data. From an exposure of 3.18×1020 protons on target in which neutrinos of energies between ~500¿¿MeV and 120 GeV are produced predominantly as ¿µ, the visible energy spectrum of candidate neutral-current reactions in the MINOS far detector is reconstructed. Comparison of this spectrum to that inferred from a similarly selected near-detector sample shows that of the portion of the ¿µ flux observed to disappear in charged-current interaction data, the fraction that could be converting to a sterile state is less than 52% at 90% confidence level (C.L.). The hypothesis that active neutrinos mix with a single sterile neutrino via oscillations is tested by fitting the data to various models. In the particular four-neutrino models considered, the mixing angles ¿24 and ¿34 are constrained to be less than 11° and 56° at 90% C.L., respectively. The possibility that active neutrinos may decay to sterile neutrinos is also investigated. Pure neutrino decay without oscillations is ruled out at 5.4 standard deviations. For the scenario in which active neutrinos decay into sterile states concurrently with neutrino oscillations, a lower limit is established for the neutrino decay lifetime t3/m3>2.1×10-12¿¿s/eV at 90% C.L

    Characterization of Leishmania spp. causing cutaneous leishmaniasis in Manaus, Amazonas, Brazil

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    In the State of Amazonas, American tegumentary leishmaniasis is endemic and presents a wide spectrum of clinical variability due to the large diversity of circulating species in the region. Isolates from patients in Manaus and its metropolitan region were characterized using monoclonal antibodies and isoenzymes belonging to four species of the parasite: Leishmania (Viannia) guyanensis, 73% (153/209); Leishmania (Viannia) braziliensis, 14% (30/209); Leishmania (Leishmania) amazonensis, 8% (17/209); and Leishmania (Viannia) naiffii, 4% (9/209). The most prevalent species was L. (V.) guyanensis. The principal finding of this study was the important quantity of infections involving more than one parasite species, representing 14% (29/209) of the total. The findings obtained in this work regarding the parasite are further highlighted by the fact that these isolates were obtained from clinical samples collected from single lesions

    Evaluation of different total leishmania amazonensis antigens for the development of a first-generation vaccine formulated with a toll-like receptor-3 agonist to prevent cutaneous leishmaniasis

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    Unfortunately, no any vaccine against leishmaniasis has been developed for human use. Therefore, a vaccine based on total Leishmania antigens could be a good and economic approach; and there are different methodologies to obtain these antigens. However, it is unknown whether the method to obtain the antigens affects the integrity and immune response caused by them. OBJECTIVES: to compare the protein profile and immune response generated by total L. amazonensis antigens (TLA) produced by different methods, as well as to analyse the immune response and protection by a first-generation vaccine formulated with sonicated TLA (sTLA) and polyinosinic:polycytidylic acid [Poly (I:C)]. METHODS: TLA were obtained by four different methodologies and their integrity and immune response were evaluated. Finally, sTLA was formulated with Poly (I:C) and their protective immune response was measured. FINDINGS: sTLA presented a conserved protein profile and induced a strong immune response. In addition, Poly (I:C) improved the immune response generated by sTLA. Finally, sTLA + Poly (I:C) formulation provided partial protection against L. amazonensis infection. MAIN CONCLUSIONS: The protein profile and immune response depend on the methodology used to obtain the antigens. Also, the formulation sTLA + Poly (I:C) provides partial protection against cutaneous leishmaniasis in mice.Fil: Germano, Maria Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Lozano, Esteban Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Sanchez, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Bruna, Flavia Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Garcia Bustos, Maria Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Patología Experimental. Universidad Nacional de Salta. Facultad de Ciencias de la Salud. Instituto de Patología Experimental; ArgentinaFil: Sosa Lochedino, Arianna Lourdes. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Salomón, María Cristina. Universidad Nacional de Cuyo; ArgentinaFil: Fernandes, Ana Paula. Universidade Federal de Minas Gerais; BrasilFil: Mackern Oberti, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Cargnelutti, Diego Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; Argentin

    Pattern Recognition Software and Techniques for Biological Image Analysis

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    The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays
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