A contextual-compositional approach to discover associations between health determinants and health indicators for neonatal mortality rate monitoring in situations of anomalies.

Introduction: Epidemiology is considered both a field of research and a methodological approach within the broader health sciences. It aims to understand health-related events' causes and effects and provide the evidence necessary to prevent disease and implement effective control and prevention strategies. One of the main focuses of epidemiology is identifying the determinant factors in the health situation of populations since health-related anomalies are not randomly distributed among people.

Evaluation of statistical process control charts for infant mortality monitoring in Brazilian cities with different population sizes.

Objectives: The control chart is a classic statistical technique in epidemiology for identifying trends, patterns, or alerts. One meaningful use is monitoring and tracking Infant Mortality Rates, which is a priority both domestically and for the World Health Organization, as it reflects the effectiveness of public policies and the progress of nations. This study aims to evaluate the applicability and performance of this technique in Brazilian cities with different population sizes using infant mortality data.

A comprehensive integrated dataset on Brazilian health facilities: from 2005 to 2021.

Objectives: The National Registry of Healthcare Facilities is a system with the registry of every healthcare facility in Brazil with information on the capacity building and healthcare workforce regarding its public or private nature. Despite being publicly available, it can only be accessed in separated disjoint tables, with different primary units of analysis. The objective is to offer an interoperable dataset containing monthly data from 2005 to 2021 with information on healthcare facilities, including their physical and human resources, services and teams, enriched with municipal information.

Dataset on infant mortality rates in Brazil.

Objectives: Surveillance of infant and fetal deaths is of paramount importance in thinking about government strategies to reduce these rates, provide greater visibility of these mortality figures in the country, enable the adoption of prevention measures, as well as contribute to a better record of deaths.

Data Description: The dataset comprises fetal, neonatal, early neonatal, late neonatal, and perinatal Mortality Rates of Brazilian municipalities with their respective information, between 2010 to 2020, aggregated by epidemiological week.

Primary health care coverage in Brazil: a dataset from 1998 to 2020.

Objectives: Primary health care builds the backbone of an effective healthcare system and can improve population health, reduce cost growth, and lessen inequality. We offer a machine-readable and open-access dataset on primary health care coverage in Brazil from 1998 to 2020. This dataset is interoperable with epidemiological data from two major studies and reusable by the research community worldwide for other purposes, such as monitoring progress toward universal health coverage and studying the association between primary health care and health outcomes.

Applying Gestalt approach as a method for teaching computer science practice in the classroom: A case study in primary schools in Brazil.

The use of information technology in the academic environment has grown. Building different didactic techniques to help students learn and practice with Information Technology (IT) resources is common. However, applying these techniques does not necessarily mean that students may acquire knowledge.

A novel sEMG data augmentation based on WGAN-GP.

The classification of sEMG signals is fundamental in applications that use mechanical prostheses, making it necessary to work with generalist databases that improve the accuracy of those classifications. Therefore, synthetic signal generation can be beneficial in enriching a database to make it more generalist. This work proposes using a variant of generative adversarial networks to produce synthetic biosignals of sEMG.

An Edge-Fog Architecture for Distributed 3D Reconstruction and Remote Monitoring of a Power Plant Site in the Context of 5G.

It is well known that power plants worldwide present access to difficult and hazardous environments, which may cause harm to on-site employees. The remote and autonomous operations in such places are currently increasing with the aid of technology improvements in communications and processing hardware. Virtual and augmented reality provide applications for crew training and remote monitoring, which also rely on 3D environment reconstruction techniques with near real-time requirements for environment inspection.

Brazilian spatial, demographic, and socioeconomic data from 1996 to 2020.

Objectives: We present a database on Brazilian spatial, demographic, and socioeconomic characteristics from 1996 to 2020. This database aims for integration and harmonization with epidemiological data from two major studies. It can also be a valuable database for designing and conducting various types of epidemiologic research, such as health inequality studies, ecological studies (mapping and time-trends), and multi-level analysis.

Fuzzy Gain-Scheduling PID for UAV Position and Altitude Controllers.

Unmanned aerial vehicle (UAV) applications have evolved to a wide range of fields in the last decade. One of the main challenges in autonomous tasks is the UAV stability during maneuvers. Thus, attitude and position control play a crucial role in stabilizing the vehicle in the desired orientation and path.

Database on the coverage of the "Bolsa-Família" conditioning cash-transfer program: Brazil, 2005 to 2021.

Objectives: The "Bolsa-Família" Program (PBF) is a Brazilian conditional cash-transfer program in which families should comply with health, education, and social assistance conditionalities. The program aims to fight poverty and hunger, promoting nutrition and health services for low-income populations. This paper presents a database on the coverage of monitoring and compliance with the PBF health conditionalities in Brazil from January 2005 to July 2021.

Photogrammetric Process to Monitor Stress Fields Inside Structural Systems.

This research employs displacement fields photogrammetrically captured on the surface of a solid or structure to estimate real-time stress distributions it undergoes during a given loading period. The displacement fields are determined based on a series of images taken from the solid surface while it experiences deformation. Image displacements are used to estimate the deformations in the plane of the beam surface, and Poisson's Method is subsequently applied to reconstruct these surfaces, at a given time, by extracting triangular meshes from the corresponding points clouds.

Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI.

Due to its impact, COVID-19 has been stressing the academy to search for curing, mitigating, or controlling it. It is believed that under-reporting is a relevant factor in determining the actual mortality rate and, if not considered, can cause significant misinformation. Therefore, this work aims to estimate the under-reporting of cases and deaths of COVID-19 in Brazilian states using data from the InfoGripe.

Dynamic Optimization and Heuristics Based Online Coverage Path Planning in 3D Environment for UAVs.

Path planning is one of the most important issues in the robotics field, being applied in many domains ranging from aerospace technology and military tasks to manufacturing and agriculture. Path planning is a branch of autonomous navigation. In autonomous navigation, dynamic decisions about the path have to be taken while the robot moves towards its goal.

Neonatal mortality rates in Brazilian municipalities: from 1996 to 2017.

Objectives: Neonatal mortality is a global public health problem, and the efforts to reduce child mortality is one of the goals of the 2030 Agenda for Sustainable Development, launched in 2015 by the United Nations. The availability of historical neonatal mortality rates (NMR) data in Brazilian municipalities is crucial to evaluate trends at local, regional and national level, identifying gaps and vulnerable territories. Therefore, the objective of this article is to offer an integrated dataset containing monthly data in a historical series from 1996 to 2017 with information on all births, neonatal deaths, and NMR (total, early and late components) enriched with information related to the municipality.

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection.

Different practical applications have emerged in the last few years, requiring periodic and detailed inspections to verify possible structural changes. Inspections using Unmanned Aerial Vehicles (UAVs) should minimize flight time due to battery time restrictions and identify the terrain's topographic features. In this sense, Coverage Path Planning (CPP) aims at finding the best path to coverage of a determined area respecting the operation's restrictions.

Deep Learning Applied to Vegetation Identification and Removal Using Multidimensional Aerial Data.

When performing structural inspection, the generation of three-dimensional (3D) point clouds is a common resource. Those are usually generated from photogrammetry or through laser scan techniques. However, a significant drawback for complete inspection is the presence of covering vegetation, hiding possible structural problems, and making difficult the acquisition of proper object surfaces in order to provide a reliable diagnostic.

A Heterogeneous Edge-Fog Environment Supporting Digital Twins for Remote Inspections.

The increase in the development of digital twins brings several advantages to inspection and maintenance, but also new challenges. Digital models capable of representing real equipment for full remote inspection demand the synchronization, integration, and fusion of several sensors and methodologies such as stereo vision, monocular Simultaneous Localization and Mapping (SLAM), laser and RGB-D camera readings, texture analysis, filters, thermal, and multi-spectral images. This multidimensional information makes it possible to have a full understanding of given equipment, enabling remote diagnosis.

A Robotic Cognitive Architecture for Slope and Dam Inspections.

Big construction enterprises, such as electrical power generation dams and mining slopes, demand continuous visual inspections. The sizes of these structures and the necessary level of detail in each mission requires a conflicting set of multi-objective goals, such as performance, quality, and safety. It is challenging for human operators, or simple autonomous path-following drones, to process all this information, and thus, it is common that a mission must be repeated several times until it succeeds.

Sensors Fusion and Multidimensional Point Cloud Analysis for Electrical Power System Inspection.

Thermal inspection is a powerful tool that enables the diagnosis of several components at its early stages. One critical aspect that influences thermal inspection outputs is the infrared reflection from external sources. This situation may change the readings, demanding that an expert correctly define the camera position, which is a time consuming and expensive operation.

An integrated dataset of malaria notifications in the Legal Amazon.

Objectives: Malaria is an infectious disease that annually presents around 200,000 cases in Brazil. The availability of data on malaria is crucial for enabling and supporting studies that can promote actions to prevent it. Therefore, the goal of this paper is to contribute to such studies by offering an integrated dataset containing data on reported and suspected cases of malaria in the Brazilian Legal Amazon comprising the period from the years 2009 to 2019.

Geochemical signature of NORM waste in Brazilian oil and gas industry.

The Brazilian Nuclear Energy Agency (CNEN) is responsible for any radioactive waste storage and disposal in the country. The storage of radioactive waste is carried out in the facilities under CNEN regulation and its disposal is operated, managed and controlled by the CNEN. Oil NORM (Naturally Occurring Radioactive Materials) in this article refers to waste coming from oil exploitation.