3DPatBody: 3D dataset of human bodies of a patagonian population and their anthropometric measurements.

The study of human body shape using classical anthropometric techniques is often problematic due to several error sources. Instead, 3D models and representations provide more accurate registrations, which are stable across acquisitions, and enable more precise, systematic, and fast measuring capabilities. Thus, the same person can be scanned several times and precise differential measurements can be established in an accurate manner.

Dataset of clinical cases, images, image labels and captions from open access case reports from PubMed Central (1990-2023).

This paper details the acquisition, structure and preprocessing of the MultiCaRe Dataset, a multimodal case report dataset which contains data from 75,382 open access PubMed Central articles spanning the period from 1990 to 2023. The dataset includes 96,428 clinical cases, 135,596 images, and their corresponding labels and captions. Data extraction was performed using different APIs and packages such as Biopython, requests, Beautifulsoup, BioC API for PMC and EuropePMC RESTful API.

Assessment of Landsat-8 and Sentinel-2 Water Indices: A Case Study in the Southwest of the Buenos Aires Province (Argentina).

The accuracy assessment of three different Normalized Difference Water indices (NDWIs) was performed in La Salada, a typical lake in the Pampean region. Data were gathered during April 2019, a period in which floods occurred in a large area in the Southwest of the Buenos Aires Province (Argentina). The accuracy of the estimations using spaceborne medium-resolution multi-spectral imaging and the reliability of three NDWIs to highlight shallow water features in satellite images were evaluated using a high-resolution airbone imagery as ground truth.

GEMA-An Automatic Segmentation Method for Real-Time Analysis of Mammalian Cell Growth in Microfluidic Devices.

Nowadays, image analysis has a relevant role in most scientific and research areas. This process is used to extract and understand information from images to obtain a model, knowledge, and rules in the decision process. In the case of biological areas, images are acquired to describe the behavior of a biological agent in time such as cells using a mathematical and computational approach to generate a system with automatic control.

ErgoExplorer: Interactive Ergonomic Risk Assessment from Video Collections.

Ergonomic risk assessment is now, due to an increased awareness, carried out more often than in the past. The conventional risk assessment evaluation, based on expert-assisted observation of the workplaces and manually filling in score tables, is still predominant. Data analysis is usually done with a focus on critical moments, although without the support of contextual information and changes over time.

Assessing Multi-Site rs-fMRI-Based Connectomic Harmonization Using Information Theory.

Several harmonization techniques have recently been proposed for connectomics/networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) acquired at multiple sites. These techniques have the objective of mitigating site-specific biases that complicate its subsequent analysis and, therefore, compromise the quality of the results when these images are analyzed together. Thus, harmonization is indispensable when large cohorts are required in which the data obtained must be independent of the particular condition of each resonator, its make and model, its calibration, and other features or artifacts that may affect the significance of the acquisition.

Reconstruction of Iberian ceramic potteries using generative adversarial networks.

Several aspects of past culture, including historical trends, are inferred from time-based patterns observed in archaeological artifacts belonging to different periods. The presence and variation of these objects provides important clues about the Neolithic revolution and given their relative abundance in most archaeological sites, ceramic potteries are significantly helpful in this purpose. Nonetheless, most available pottery is fragmented, leading to missing morphological information.

Essential oils loaded on polymeric nanoparticles: bioefficacy against economic and medical insect pests and risk evaluation on terrestrial and aquatic non-target organisms.

This paper introduces the lethal, sublethal, and ecotoxic effects of peppermint and palmarosa essential oils (EOs) and their polymeric nanoparticles (PNs). The physicochemical analyses indicated that peppermint PNs were polydisperse (PDI > 0.4) with sizes of 381 nm and loading efficiency (LE) of 70.

Mining Early Life Risk and Resiliency Factors and Their Influences in Human Populations from PubMed: A Machine Learning Approach to Discover DOHaD Evidence.

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how early life exposures shape lifecycle health. To date, no comprehensive list of these exposures and their interactions has been developed, which limits our ability to predict trajectories of risk and resiliency in humans. To address this gap, we developed a model that uses text-mining, machine learning, and natural language processing approaches to automate search, data extraction, and content analysis from DOHaD-related research articles available in PubMed.

Bulsarapp: Interactive Visual Analysis for Surname Trend Exploration.

The study of surnames for a given population, together with their distribution and spatial patterns identification, has been a long-standing problem in the fields of human biology, public health, and social sciences. The ancestry inferred from surname information can be a useful means to understand the dynamics of human populations. This knowledge allows us to characterize geographically the ethnicity of populations, and to understand the complex relationships between identity, migration, and health issues in a demographic view.

3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices.

Current point cloud extraction methods based on photogrammetry generate large amounts of spurious detections that hamper useful 3D mesh reconstructions or, even worse, the possibility of adequate measurements. Moreover, noise removal methods for point clouds are complex, slow and incapable to cope with semantic noise. In this work, we present body2vec, a model-based body segmentation tool that uses a specifically trained Neural Network architecture.

Noise reduction using novel loss functions to compute tissue mineral density and trabecular bone volume fraction on low resolution QCT.

Micro-structural parameters of the thoracic or lumbar spine generally carry insufficient accuracy and precision for clinical in vivo studies when assessed on quantitative computed tomography (QCT). We propose a 3D convolutional neural network with specific loss functions for QCT noise reduction to compute micro-structural parameters such as tissue mineral density (TMD) and bone volume ratio (BV/TV) with significantly higher accuracy than using no or standard noise reduction filters. The vertebra-phantom study contained high resolution peripheral and clinical CT scans with simulated in vivo CT noise and nine repetitions of three different tube currents (100, 250 and 360 mAs).

Early life risk and resiliency factors and their influences on developmental outcomes and disease pathways: a rapid evidence review of systematic reviews and meta-analyses.

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how environmental exposures in early life shape lifecycle health. Our understanding and the ability to prevent poor health outcomes and enrich for resiliency remain limited, in part, because exposure-outcome relationships are complex and poorly defined. We, therefore, aimed to determine the major DOHaD risk and resilience factors.

Body shape: Implications in the study of obesity and related traits.

Objectives: The diagnosis and treatment of obesity are usually based on traditional anthropometric variables including weight, height, and several body perimeters. Here we present a three-dimensional (3D) image-based computational approach aimed to capture the distribution of abdominal adipose tissue as an aspect of shape rather than a relationship among classical anthropometric measures.

Methods: A morphometric approach based on landmarks and semilandmarks placed upon the 3D torso surface was performed in order to quantify abdominal adiposity shape variation and its relation to classical indices.

A Comparison of Radial and Linear Charts for Visualizing Daily Patterns.

Radial charts are generally considered less effective than linear charts. Perhaps the only exception is in visualizing periodical time-dependent data, which is believed to be naturally supported by the radial layout. It has been demonstrated that the drawbacks of radial charts outweigh the benefits of this natural mapping.

NIR-based Sudan I to IV and Para-Red food adulterants screening.

Spices are added in order to enhance the organoleptic characteristics of food and culinary dishes, making them more attractive for consumers. The use of illicit cheap colourants might be profitable along the food supply chain, posing undue risks to human health. This work evaluates the feasibility of NIR spectroscopy with chemometrics as a rapid, simple, non-destructive and affordable screening tool to determine the presence of Sudan I, II, III, IV and Para-red dyes in paprika.

Three-dimensional multifractal analysis of trabecular bone under clinical computed tomography.

Purpose: An adequate understanding of bone structural properties is critical for predicting fragility conditions caused by diseases such as osteoporosis, and in gauging the success of fracture prevention treatments. In this work we aim to develop multiresolution image analysis techniques to extrapolate high-resolution images predictive power to images taken in clinical conditions.

Methods: We performed multifractal analysis (MFA) on a set of 17 ex vivo human vertebrae clinical CT scans.

A new algorithm for estimating the rod volume fraction and the trabecular thickness from in vivo computed tomography.

Purpose: Existing microstructure parameters are able to predict vertebral in vitro failure load, but for noisy in vivo data more complex algorithms are needed for a robust assessment.

Methods: A new algorithm is proposed for the microstructural analysis of trabecular bone under in vivo quantitative computed tomography (QCT). Five fractal parameters are computed: (1) the average local fractal dimension FD, (2) its standard deviation FD.

Local texture descriptors for the assessment of differences in diffusion magnetic resonance imaging of the brain.

Purpose: Descriptors extracted from magnetic resonance imaging (MRI) of the brain can be employed to locate and characterize a wide range of pathologies. Scalar measures are typically derived within a single-voxel unit, but neighborhood-based texture measures can also be applied. In this work, we propose a new set of descriptors to compute local texture characteristics from scalar measures of diffusion tensor imaging (DTI), such as mean and radial diffusivity, and fractional anisotropy.

Evaluation of sublethal effects of polymer-based essential oils nanoformulation on the german cockroach.

The German cockroach, Blattella germanica (L.), is a serious household and public health pest worldwide. The aim of the present study was to evaluate the sublethal activity of polymer-based essential oils (EOs) nanoparticles (NPs) on adults of B.

Multifractal spectrum and lacunarity as measures of complexity of osseointegration.

Objectives: The goal of this study is to contribute to a better quantitative description of the early stages of osseointegration, by application of fractal, multifractal, and lacunarity analysis.

Materials And Methods: Fractal, multifractal, and lacunarity analysis are performed on scanning electron microscopy (SEM) images of titanium implants that were first subjected to different treatment combinations of i) sand blasting, ii) acid etching, and iii) exposition to calcium phosphate, and were then submersed in a simulated body fluid (SBF) for 30 days. All the three numerical techniques are applied to the implant SEM images before and after SBF immersion, in order to provide a comprehensive set of common quantitative descriptors.

Structure-from-motion approach for characterization of bioerosion patterns using UAV imagery.

The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina.