3D Soil Images Structure Quantification using Relative Entropy

Soil voids manifest the cumulative effect of local pedogenic processes and ultimately influence soil behavior - especially as it pertains to aeration and hydrophysical properties. Because of the relatively weak attenuation of X-rays by air, compared with liquids or solids, non-disruptive CT scanning has become a very attractive tool for generating three-dimensional imagery of soil voids. One of the main steps involved in this analysis is the thresholding required to transform the original (greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice?Boltzmann models (Baveye et al., 2010). The objective of the current work is to apply an innovative approach to quantifying soil voids and pore networks in original X-ray CT imagery using Relative Entropy (Bird et al., 2006; Tarquis et al., 2008). These will be illustrated using typical imagery representing contrasting soil structures. Particular attention will be given to the need to consider the full 3D context of the CT imagery, as well as scaling issues, in the application and interpretation of this index.

An Automatic Quantification and Registration Strategy to Create a Gene Expression Atlas of Zebrafish Embryogenesis

In order to properly understand and model the gene regulatory networks in animals development, it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains. In this paper, we propose a complete computational framework to fulfill this task and create a 3D Atlas of the early zebrafish embryogenesis annotated with both the cellular localizations and the level of expression of different genes at different developmental stages. The strategy to construct such an Atlas is described here with the expression pattern of 5 different genes at 6 hours of development post fertilization.

Crowdsourcing malaria parasite quantification: an online game for analyzing images of infected thick blood smears

Background: There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process that can take more than 20 minutes of an expert microscopist’s time. Objective: This research tests the feasibility of a crowdsourced approach to malaria image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count malaria parasites in digitized images of thick blood smears by playing a Web-based game. Methods: The experimental system consisted of a Web-based game where online volunteers were tasked with detecting parasites in digitized blood sample images coupled with a decision algorithm that combined the analyses from several players to produce an improved collective detection outcome. Data were collected through the MalariaSpot website. Random images of thick blood films containing Plasmodium falciparum at medium to low parasitemias, acquired by conventional optical microscopy, were presented to players. In the game, players had to find and tag as many parasites as possible in 1 minute. In the event that players found all the parasites present in the image, they were presented with a new image. In order to combine the choices of different players into a single crowd decision, we implemented an image processing pipeline and a quorum algorithm that judged a parasite tagged when a group of players agreed on its position. Results: Over 1 month, anonymous players from 95 countries played more than 12,000 games and generated a database of more than 270,000 clicks on the test images. Results revealed that combining 22 games from nonexpert players achieved a parasite counting accuracy higher than 99%. This performance could be obtained also by combining 13 games from players trained for 1 minute. Exhaustive computations measured the parasite counting accuracy for all players as a function of the number of games considered and the experience of the players. In addition, we propose a mathematical equation that accurately models the collective parasite counting performance. Conclusions: This research validates the online gaming approach for crowdsourced counting of malaria parasites in images of thick blood films. The findings support the conclusion that nonexperts are able to rapidly learn how to identify the typical features of malaria parasites in digitized thick blood samples and that combining the analyses of several users provides similar parasite counting accuracy rates as those of expert microscopists. This experiment illustrates the potential of the crowdsourced gaming approach for performing routine malaria parasite quantification, and more generally for solving biomedical image analysis problems, with future potential for telediagnosis related to global health challenges.

Nondestructive quantification of chemical and physical properties of fruits by time-resolved reflectance spectroscopy in the wavelength range 650-1000 nm

Time-resolved reflectance spectroscopy can be used to assess nondestructively the bulk (rather than the superficial) optical properties of highly diffusive media. A fully automated system for time-resolved reflectance spectroscopy was used to evaluate the absorption and the transport scattering spectra of fruits in the red and the near-infrared regions. In particular, data were collected in the range 650-1000 nm from three varieties of apples and from peaches, kiwifruits, and tomatoes. The absorption spectra were usually dominated by the water peak near 970 nm, whereas chlorophyll was detected at 675 nm. For ail species the scattering decreased progressively with increasing wavelength. A best fit to water and chlorophyll absorption line shapes and to Mie theory permitted the estimation of water and chlorophyll content and the average size of scattering centers in the bulls; of intact fruits.

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

Quantification of soluble fibre in feedstuffs for rabbits and evaluation of the interference between the determinations of soluble fibre and intestinal mucin.

This work compared the quantification of soluble fibre in feeds using different chemical and in vitro approaches, and studied the potential interference between soluble fibre and mucin determinations. Six ingredients: sugar beet pulp (SBP), SBP pectins, insoluble SBP, wheat straw, sunflower hulls and lignocellulose, and seven rabbit diets, differing in soluble fibre content, were evaluated. In experiment 1, ingredients and diets were analyzed for total dietary fibre (TDF), insoluble dietary fibre (IDF), soluble dietary fibre (SDF), aNDFom (corrected for protein, aNDFom-cp) and 2-step pepsin/pancreatin in vitro DM indigestibility (corrected for ash and protein, ivDMi2). Soluble fibre was estimated by difference using three procedures: TDF?IDF (SDFIDF), TDF?ivDMi2 (SDFivDMi2), and TDF?aNDFom-cp (SDFaNDFom-cp). Soluble fibre determined directly (SDF) or by difference as SDFivDMi2 were not different (109 g/kg DM, on average). However, when it was calculated as SDFaNDFom-cp the value was 40% higher (153 g/kg DM, P menor que 0.05), whereas SDFIDF (124 g/kg DM) did not differ from any of the other methods. The correlation between the four methods was high (r ? 0.96; P ? 0.001; n = 13), but it decreased or even disappeared when SBP pectins and SBP were excluded and a lower and more narrow range of variation of soluble fibre was used. In experiment 2, the ivDMi2 using crucibles (reference method) were compared to those made using individual or collective ankom bags in order to simplify the determination of SDFivDMi2. The ivDMi2 was not different when using crucibles or individual or collective ankom bags. In experiment 3, the potential interference between soluble fibre and intestinal mucin determinations was studied using rabbit intestinal raw mucus, digesta and SBP pectins, lignocelluloses and a rabbit diet. An interference was observed between the determinations of soluble fibre and crude mucin, as contents of TDF and apparent crude mucin were high in SBP pectins (994 and 709 g/kg DM) and rabbit intestinal raw mucus (571 and 739 g/kg DM). After a pectinase treatment, the coefficient of apparent mucin recovery of SBP pectins was close to zero, whereas that of rabbit mucus was not modified. An estimation of the crude mucin carbohydrates retained in digesta TDF is proposed to correct TDF and soluble fibre digestibility. In conclusion, the values of soluble fibre depend on the methodology used. The contamination of crude mucin with soluble fibre is avoided using pectinase.

Quantification of impacts in artistic gymnastics with accelerometry: an approximation

Intensity and volume of training in Artisti Gymnastics are increasing as the sooner athlete's age of incorporation creating some disturbance in them.

Physical activity quantification in elder women

Cuantificación de la actividad física en mujeres mayores.

QuantiDOPA: A Quantification Software for Dopaminergic Neurotransmission SPECT

Quantification of neurotransmission Single-Photon Emission Computed Tomography (SPECT) studies of the dopaminergic system can be used to track, stage and facilitate early diagnosis of the disease. The aim of this study was to implement QuantiDOPA, a semi-automatic quantification software of application in clinical routine to reconstruct and quantify neurotransmission SPECT studies using radioligands which bind the dopamine transporter (DAT). To this end, a workflow oriented framework for the biomedical imaging (GIMIAS) was employed. QuantiDOPA allows the user to perform a semiautomatic quantification of striatal uptake by following three stages: reconstruction, normalization and quantification. QuantiDOPA is a useful tool for semi-automatic quantification inDAT SPECT imaging and it has revealed simple and flexible

Automatic quantification of matrix cracking and fiber rotation by X-ray computed tomography in shear-deformed carbon fiber-reinforced laminates

The deformation and damage mechanisms of carbon fiber-reinforced epoxy laminates deformed in shear were studied by means of X-ray computed tomography. In particular, the evolution of matrix cracking, interply delamination and fiber rotation was ascertained as a function of the applied strain. In order to provide quantitative information, an algorithm was developed to automatically determine the crack density and the fiber orientation from the tomograms. The investigation provided new insights about the complex interaction between the different damage mechanisms (i.e. matrix cracking and interply delamination) as a function of the applied strain, ply thickness and ply location within the laminate as well as quantitative data about the evolution of matrix cracking and fiber rotation during deformation

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.

Modal analysis of buildings : quantification of uncertainties and model updating

Una estructura vibra con la suma de sus infinitos modos de vibración, definidos por sus parámetros modales (frecuencias naturales, formas modales y coeficientes de amortiguamiento). Estos parámetros se pueden identificar a través del Análisis Modal Operacional (OMA). Así, un equipo de investigación de la Universidad Politécnica de Madrid ha identificado las propiedades modales de un edificio de hormigón armado en Madrid con el método Identificación de los sub-espacios estocásticos (SSI). Para completar el estudio dinámico de este edificio, se ha desarrollado un modelo de elementos finitos (FE) de este edificio de 19 plantas. Este modelo se ha calibrado a partir de su comportamiento dinámico obtenido experimentalmente a través del OMA. Los objetivos de esta tesis son; (i) identificar la estructura con varios métodos de SSI y el uso de diferentes ventanas de tiempo de tal manera que se cuantifican incertidumbres de los parámetros modales debidos al proceso de estimación, (ii) desarrollar FEM de este edificio y calibrar este modelo a partir de su comportamiento dinámico, y (iii) valorar la bondad del modelo. Los parámetros modales utilizados en esta calibración han sido; espesor de las losas, densidades de los materiales, módulos de elasticidad, dimensiones de las columnas y las condiciones de contorno de la cimentación. Se ha visto que el modelo actualizado representa el comportamiento dinámico de la estructura con una buena precisión. Por lo tanto, este modelo puede utilizarse dentro de un sistema de monitorización estructural (SHM) y para la detección de daños. En el futuro, podrá estudiar la influencia de los agentes medioambientales, tales como la temperatura o el viento, en los parámetros modales. A structure vibrates according to the sum of its vibration modes, defined by their modal parameters (natural frequencies, damping ratios and modal shapes). These parameters can be identified through Operational Modal Analysis (OMA). Thus, a research team of the Technical University of Madrid has identified the modal properties of a reinforced-concrete-frame building in Madrid using the Stochastic Subspace Identification (SSI) method and a time domain technique for the OMA. To complete the dynamic study of this building, a finite element model (FE) of this 19-floor building has been developed throughout this thesis. This model has been updated from its dynamic behavior identified by the OMA. The objectives of this thesis are to; (i) identify the structure with several SSI methods and using different time blocks in such a way that uncertainties due to the modal parameter estimation are quantified, (ii) develop a FEM of this building and tune this model from its dynamic behavior, and (iii) Assess the quality of the model, the modal parameters used in this updating process have been; thickness of slabs, material densities, modulus of elasticity, column dimensions and foundation boundary conditions. It has been shown that the final updated model represents the structure with a very good accuracy. Thus, this model might be used within a structural health monitoring framework (SHM). The study of the influence of changing environmental factors (such as temperature or wind) on the model parameters might be considered as a future work.