Perfil Epidemiológico e Tendências Temporais das Internações por Sepse no Brasil: Um Estudo de 2019 a 2023

More prevalent in people with compromised immune systems and chronic illnesses, sepsis is the body's inflammatory response to a serious infection that can affect multiple organs. This condition is a global problem, with millions of cases annually, resulting in high mortality rates, especially in Brazil. The study seeks to describe the epidemiological profile of hospital morbidity due to septicemia in Brazil. This is an ecological, descriptive and retrospective study, using data from the SUS Information and IT Department (DATASUS) on hospital admissions. Individuals hospitalized for septicemia in the country, from 2019 to 2023, were included. The variables analyzed were region, character service, sex and color/race. The majority of hospitalizations were urgent (95.29%), with a higher prevalence in patients aged 80 or over (21.42%). There was an almost equal distribution between the sexes, with a slight male predominance (52.05%). Regarding color/race, the majority of patients were brown (38.15%), followed by white (37.76%). From this analysis, the relevance of patient care to prevent the development of sepsis and address it appropriately stands out.Mais prevalente em pessoas com sistema imunológico comprometido e doenças crônicas, a sepse é uma resposta inflamatória do corpo a uma infecção grave, podendo afetar vários órgãos. Essa condição é um problema global, com milhões de casos anuais, resultando em altas taxas de mortalidade, especialmente no Brasil. O estudo busca descrever o perfil epidemiológico da morbidade hospitalar por septicemia no Brasil. Trata-se de um estudo ecológico, descritivo e retrospectivo, utilizando dados do Departamento de Informações e Informática do SUS (DATASUS) sobre internações hospitalares Foram inseridos indivíduos com internação por septicemia no país, de 2019 a 2023. As variáveis analisadas foram região, caráter de atendimento, sexo e cor/raça. A maioria das internações foi urgente como urgência (95,29%), com maior prevalência em pacientes com 80 anos ou mais (21,42%). Houve uma distribuição quase igual entre os sexos, com ligeira predominância masculina (52,05%). Quanto à cor/raça, a maioria dos pacientes era parda (38,15%), seguida por branca (37,76%). A partir desta análise, destaca-se a relevância da assistência ao paciente para prevenir o desenvolvimento da sepse e abordá-lo de maneira adequad

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume I Introduction to DUNE

International audienceThe preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE's physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation