Effect of Amino Acid Supplementation on the Nutritive Value of the Protein in Oats

Biochemistr

Madrid L6 chondrite (fall 1896): ESEM-cathodoluminescence survey

Depto. de Geodinámica, Estratigrafía y PaleontologíaFac. de Ciencias GeológicasTRUEpu

Modular Multi-level Converter Hardware-in-the-Loop Simulation on low-cost System-on-Chip devices

Comunicació presentada a IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society (October 21-23, 2018 Washington D.C., USA.)System-on-Chip (SoC) devices combine powerful general purpose processors, a Field-Programmable Gate Array (FPGA) and other peripherals which make them very convenient for Hardware-in-the-Loop (HIL) simulation. One of the limitations of these devices is that control engineers are not particularly familiarized with FPGA programming, which need extensive expertise in order to code these highly sophisticated algorithms using Hardware Description Languages (HDL). Notwithstanding, there exist High-Level Synthesis (HLS) tools which allow to program these devices using more generic programming languages such as C, C++ and SystemC. This paper evaluates SoC devices to implement a Modular Multi-Level Converter (MMC) model using HLS tools for being implemented in the FPGA fabric in order to perform HIL verification of control algorithms in a single low-cost device

High precision fundamental constants at the TeV scale

This report summarizes the proceedings of the 2014 Mainz Institute for Theoretical Physics (MITP) scientific program on "High precision fundamental constants at the TeV scale". The two outstanding parameters in the Standard Model dealt with during the MITP scientific program are the strong coupling constant $\alpha_s$ and the top-quark mass $m_t$. Lacking knowledge on the value of those fundamental constants is often the limiting factor in the accuracy of theoretical predictions. The current status on $\alpha_s$ and $m_t$ has been reviewed and directions for future research have been identified.Comment: 57 pages, 24 figures, pdflate

Cardiovascular risk estimated after 13 years of follow-up in a low-incidence Mediterranean region with high-prevalence of cardiovascular risk factors

<p>Abstract</p> <p>Background</p> <p>Murcia (south-east Spain) shows increased cardiovascular (CV) morbimortality as compared to other Spanish regions. Our objective was to assess the CV risk associated with major risk factors (RF) among adult population of Murcia.</p> <p>Methods</p> <p>A cohort of 2314 subjects (18-70 years) with full biochemical and questionnaire data was followed-up for 13 years. Incident cases of ischemic heart disease and stroke were identified by record linkage, individual questionnaires and revision of medical records. Relative risks were obtained by multivariate Cox regression stratified by age and sex, and ischemic risk attributable to CVRF was calculated.</p> <p>Results</p> <p>After more than 26276 person-years of follow-up, 57 incident ischemic events (77% men) and 37 stroke cases (62% men) were identified. Independent risk factors of ischemic heart disease (IHD) and all CV events combined, with RR ranging from 1.6 to 2.6, were total serum cholesterol ≥ 240 mg/dl (HR = 2.6, 95%CI:1.3-5.1), blood pressure levels ≥ 140/90 mmHg (HR = 2.6, 95%CI:1.4-4.8), ever tobacco smoking (HR = 2.2; 95%CI:1.1-4.5), and diabetes (HR = 2.0; 95%CI: 1.0-3.8). No increased CV risk was detected for known participants under treatment who showed cholesterol and blood pressure values below the clinical risk threshold. Smoking was significantly associated with stroke. For all events combined, the major risk factors were hypercholesterolemia, hypertension and ever use of tobacco. Despite its high prevalence, obesity was not associated to CV risk. Most of the IHD cases were attributable to smoking (44%), hypertension (38%) and hypercholesterolemia (26%).</p> <p>Conclusions</p> <p>In the Region of Murcia, smoking accounted for the largest proportion of cardiovascular risk, whereas hypertension displaced hypercholesterolemia as the second leading cause of CV disease. Our study deepens in our understanding of the cardiovascular epidemiology in Spanish areas of Mediterranean Europe with relatively high cardiovascular morbimortality, that are poorly represented by the available risk equations.</p

High-precision αs\alpha_s measurements from LHC to FCC-ee

This document provides a writeup of all contributions to the workshop on "High precision measurements of $\alpha_s$: From LHC to FCC-ee" held at CERN, Oct. 12--13, 2015. The workshop explored in depth the latest developments on the determination of the QCD coupling $\alpha_s$ from 15 methods where high precision measurements are (or will be) available. Those include low-energy observables: (i) lattice QCD, (ii) pion decay factor, (iii) quarkonia and (iv) $\tau$ decays, (v) soft parton-to-hadron fragmentation functions, as well as high-energy observables: (vi) global fits of parton distribution functions, (vii) hard parton-to-hadron fragmentation functions, (viii) jets in $e^\pm$p DIS and $\gamma$-p photoproduction, (ix) photon structure function in $\gamma$-$\gamma$, (x) event shapes and (xi) jet cross sections in $e^+e^-$ collisions, (xii) W boson and (xiii) Z boson decays, and (xiv) jets and (xv) top-quark cross sections in proton-(anti)proton collisions. The current status of the theoretical and experimental uncertainties associated to each extraction method, the improvements expected from LHC data in the coming years, and future perspectives achievable in $e^+e^-$ collisions at the Future Circular Collider (FCC-ee) with $\cal{O}$(1--100 ab$^{-1}$) integrated luminosities yielding 10$^{12}$ Z bosons and jets, and 10$^{8}$ W bosons and $\tau$ leptons, are thoroughly reviewed. The current uncertainty of the (preliminary) 2015 strong coupling world-average value, $\alpha_s(m_Z)$ = 0.1177 $\pm$ 0.0013, is about 1\%. Some participants believed this may be reduced by a factor of three in the near future by including novel high-precision observables, although this opinion was not universally shared. At the FCC-ee facility, a factor of ten reduction in the $\alpha_s$ uncertainty should be possible, mostly thanks to the huge Z and W data samples available.Comment: 135 pages, 56 figures. CERN-PH-TH-2015-299, CoEPP-MN-15-13. This document is dedicated to the memory of Guido Altarell

Micro and nano-patterning of single-crystal diamond by swift heavy ion irradiation

This paper presents experimental data and analysis of the structural damage caused by swift-heavy ion irradiation of single-crystal diamond. The patterned buried structural damage is shown to generate, via swelling, a mirror- pattern on the sample surface, which remains largely damage-free. While extensive results are available for light ion implantations, this effect is reported here for the first time in the heavy ion regime,where a completely different range of input parameters (in terms of ion species, energy, stopping power, etc.) is available for customized irradiation. The chosen ion species are Au and Br, in the energy range 10–40 MeV. The observed patterns, as characterized by profilometry and atomic force microscopy, are reported in a series ofmodel experiments,which show swelling patterns ranging from a few nm to above 200 nm. Moreover, a systematic phenomenological modeling is presented, inwhich surface swelling measurements are correlated to buried crystal damage. A comparison ismade with data for light ion implantations, showing good compatibilitywith the proposedmodels. The modeling presented in thiswork can be useful for the design and realization of micropatterned surfaces in single crystal diamond, allowing generating highly customized structures by combining appropriately chosen irradiation parameters and masks

Single cell profiling of COVID-19 patients: an international data resource from multiple tissues

In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration

Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics

elocation-id: 2020.11.15.378125elocation-id: 2020.11.15.378125The spatial organization of cell types in tissues fundamentally shapes cellular interactions and function, but the high-throughput spatial mapping of complex tissues remains a challenge. We present сell2location, a principled and versatile Bayesian model that integrates single-cell and spatial transcriptomics to map cell types in situ in a comprehensive manner. We show that сell2location outperforms existing tools in accuracy and comprehensiveness and we demonstrate its utility by mapping two complex tissues. In the mouse brain, we use a new paired single nucleus and spatial RNA-sequencing dataset to map dozens of cell types and identify tissue regions in an automated manner. We discover novel regional astrocyte subtypes including fine subpopulations in the thalamus and hypothalamus. In the human lymph node, we resolve spatially interlaced immune cell states and identify co-located groups of cells underlying tissue organisation. We spatially map a rare pre-germinal centre B-cell population and predict putative cellular interactions relevant to the interferon response. Collectively our results demonstrate how сell2location can serve as a versatile first-line analysis tool to map tissue architectures in a high-throughput manner.Competing Interest StatementThe authors have declared no competing interest