Esta palestra tem o objetivo de apresentar e discutir metodologias utilizadas para modelar e integrar o conhecimento clássico em nutrição animal, e o produzido por novas ciências moleculares como ...nutrigenoma, proteoma e metaboloma. Estas ciências e a bioinformática estão ajudando a expandir rapidamente o conhecimento dos sistemas biológicos de interesse em nutrição animal. Na palestra discutirei como é importante dedicar parte de nosso tempo a integrar o conhecimento existente para esclarecer os problemas em pesquisa, utilizando as ferramentas mais adequadas para evitar duplicação de pesquisas, que causam desperdício de recursos humanos, econômicos, e de tempo. A modelagem matemática por compartimentos utilizando programas de computador pode ser a melhor maneira de acumular estas informações, integrar diferentes descobertas, e comunicar o conhecimento atual dos sistemas, e do metabolismo de nutrientes às novas gerações, e avançar na determinação mais adequada das exigências nutricionais.This presentation aims to present and discuss methodologies used to model and integrate classical knowledge in animal nutrition, and new discoveries produced by new molecular sciences like nutrigenomics, proteomics and metabolomics. These sciences and bioinformatics are helping to expand >very quickly the knowledge of the biological systems of interest in animal nutrition. I will discuss the importance of dedicating part of our efforts to integrate current knowledge to prioritize research problems using the most adequate tools. This will help to avoid research duplication that causes waste of valuable resources. Compartmental mathematical modeling using computer software could be one of the best ways to accumulate this information. It can help to integrate new discoveries, communicate the knowledge about animal systems and nutrient metabolism to a new generation of scientists, and advance to more accurate determination of nutrient requirements.
Large Liquid Argon Time Projection Chambers (LArTPCs) are being increasingly adopted in neutrino oscillation experiments because of their superb imaging capabilities through the combination of both ...tracking and calorimetry in a fully active volume. Active LArTPC neutrino detectors at or near the Earth's surface, such as the MicroBooNE experiment, present a unique analysis challenge because of the large flux of cosmic-ray muons and the slow drift of ionization electrons. We present a novel Wire-Cell-based high-performance generic neutrino-detection technique implemented in MicroBooNE. The cosmic-ray background is reduced by a factor of 1.4\(\times10^{5}\) resulting in a 9.7\% cosmic contamination in the selected neutrino candidate events, for visible energies greater than 200~MeV, while the neutrino signal efficiency is retained at 88.4\% for \(\nu_{\mu}\) charged-current interactions in the fiducial volume in the same energy region. This significantly improved performance compared to existing reconstruction algorithms, marks a major milestone toward reaching the scientific goals of LArTPC neutrino oscillation experiments operating near the Earth's surface.
The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as those from a ...supernova neutrino burst. The low energies of the supernova neutrinos and the intense cosmic-ray background flux due to the near-surface detector location makes triggering on these events very challenging. Instead, MicroBooNE relies on a delayed trigger generated by SNEWS (the Supernova Early Warning System) for detecting supernova neutrinos. The continuous readout of the LArTPC generates large data volumes, and requires the use of real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA (field-programmable gate array) in the readout electronics. We present the results of the optimization of the data reduction algorithms, and their operational performance. To demonstrate the capability of the continuous stream to detect low-energy electrons, a sample of Michel electrons from stopping cosmic-ray muons is reconstructed and compared to a similar sample from the lossless triggered readout stream.
For a large liquid argon time projection chamber (LArTPC) operating on or near the Earth's surface to detect neutrino interactions, the rejection of cosmogenic background is a critical and ...challenging task because of the large cosmic ray flux and the long drift time of the TPC. We introduce a superior cosmic background rejection procedure based on the Wire-Cell three-dimensional (3D) event reconstruction for LArTPCs. From an initial 1:20,000 neutrino to cosmic-ray background ratio, we demonstrate these tools on data from the MicroBooNE experiment and create a high performance generic neutrino event selection with a cosmic contamination of 14.9\% (9.7\%) for a visible energy region greater than O(200)~MeV. The neutrino interaction selection efficiency is 80.4\% and 87.6\% for inclusive \(\nu_\mu\) charged-current and \(\nu_e\) charged-current interactions, respectively. This significantly improved performance compared to existing reconstruction algorithms, marks a major milestone toward reaching the scientific goals of LArTPC neutrino oscillation experiments operating near the Earth's surface.
In this letter we present the first measurements of an exclusive electron
neutrino cross section with the MicroBooNE experiment using data from the
Booster Neutrino Beamline at Fermilab. These ...measurements are made for a
selection of charged-current electron neutrinos without final-state pions.
Differential cross sections are extracted in energy and angle with respect to
the beam for the electron and the leading proton. The differential cross
section as a function of proton energy is measured using events with protons
both above and below the visibility threshold. This is done by including a
separate selection of electron neutrino events without reconstructed proton
candidates in addition to those with proton candidates. Results are compared to
the predictions from several modern generators, and we find the data agrees
well with these models. The data shows best agreement, as quantified by
$p$-value, with the generators that predict a lower overall cross section, such
as GENIE v3 and NuWro.
We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the probabilities of ...\(e^-\), \(\gamma\), \(\mu^-\), \(\pi^\pm\), and protons in a single liquid argon time projection chamber (LArTPC) readout plane. The network extends the single particle identification network previously developed by MicroBooNE. MPID takes as input an image either cropped around a reconstructed interaction vertex or containing only activity connected to a reconstructed vertex, therefore relieving the tool from inefficiencies in vertex finding and particle clustering. The network serves as an important component in MicroBooNE's deep learning based \(\nu_e\) search analysis. In this paper, we present the network's design, training, and performance on simulation and data from the MicroBooNE detector.
We present a measurement of the combined \(\nu_e\) + \(\bar{\nu}_e\) flux-averaged charged-current inclusive cross section on argon using data from the MicroBooNE liquid argon time projection chamber ...(LArTPC) at Fermilab. Using the off-axis flux from the NuMI beam, MicroBooNE has reconstructed 214 candidate \(\nu_e\) + \(\bar{\nu}_e\) interactions with an estimated exposure of 2.4\(\times10^{20}\) protons on target. Given the estimated purity of 38.6\%, this implies the observation of 80 \(\nu_e\) + \(\bar{\nu}_e\) events in argon, the largest such sample to date. The analysis includes the first demonstration of a fully automated application of a dE/dx-based particle discrimination technique of electron and photon induced showers in a LArTPC neutrino detector. We measure the \(\nu_e + \bar{\nu}_e\) flux-averaged charged-current total cross section to be \({6.84\pm\!1.51~\textrm{(stat.)}\pm\!2.33~\textrm{(sys.)}\!\times\!10^{-39}~\textrm{cm}^{2}/~\textrm{nucleon}}\), for neutrino energies above 250 MeV and an average neutrino flux energy of 905 MeV when this threshold is applied. The measurement is sensitive to neutrino events where the final state electron momentum is above 48 MeV/c, includes the entire angular phase space of the electron, and is in agreement with the theoretical predictions from \texttt{GENIE} and \texttt{NuWro}. This measurement is also the first demonstration of electron neutrino reconstruction in a surface LArTPC in the presence of cosmic ray backgrounds, which will be a crucial task for surface experiments like those that comprise the Short-Baseline Neutrino (SBN) Program at Fermilab.
Inclusive electron scattering from nuclear targets has been measured to extract the nuclear dependence of the inelastic cross section in Hall C at the Thomas Jefferson National Accelerator facility. ...Results are presented for 2H, 3He, 4He, 9B, 12C, 63Cu and 197Au at an incident electron beam energy of 5.77 GeV for a range of momentum transfer from Q^2 = 2 to 7 (GeV/c)^2. These data improve the precision of the existing measurements of the EMC effect in the nuclear targets at large x, and allow for more detailed examinations of the A dependence of the EMC effect.
Most candidates for hematopoietic stem cell transplantation (HSCT) lack a human leukocyte antigen (HLA)-identical sibling donor. Some patients may have a related donor with whom they are mismatched ...at 1 antigen/allele. It is not known whether such a match is preferable to a matched unrelated donor (MUD). We evaluated the outcomes (survival, relapse, nonrelapse mortality NRM) of all 28 patients with a single HLA antigen/allele mismatch identified through high-resolution HLA typing at HLA-A, -B, -C, -DRB1, and -DQB1, and all 318 patients with myeloid malignancies who received transplants from a 10/10 MUD treated during the same period of time at a single institution. Overall, outcomes for patients treated from a 1-antigen/allele mismatch related donor were significantly worse than from a MUD, primarily because of increased NRM. Overall survival (OS) rates at 3 years for 1-antigen/allele mismatched related donor and MUD transplant recipients were 19% and 45% ( P = .007), and NRM rates were 40% and 26% ( P = .05), respectively. Patients with class I mismatches appeared to have poorer OS than did patients with class II mismatches. A higher incidence of graft rejection was identified in the mismatched related donor group ( P = .02). These results indicate that transplant outcomes are better with a MUD than with a 1 antigen/allele-mismatched related donor.
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