A hydrodynamical view on the mass accretion onto massive halos

This Thesis presents the results of my work on how galaxy clusters form by the accretion of sub-clumps and diffuse materials, and how the accreted energy is distributed in the X-ray emitting plasma. Indeed, on scales larger than tens of millions of light years, the Universe is self-organised by gravity into a spiderweb, the Cosmic Web. Galaxy clusters are the knots of this Cosmic Web, but a strong definition of filaments (which link different knots) and their physical proprieties, is still uncertain. Even if this pattern was determined by studying the spatial distribution of galaxies in the optical band, recently, also in the X-rays probes of filamentary structures around galaxy clusters were obtained. Therefore, given these observational facilities, the galaxy clusters’ outskirts are the best candidate regions to detect filaments and study their physical characteristics. However, from X-rays observations, we have only a few detections of cosmic filaments to date. On the other hand, it is crucial to understand how the accreted energy is dissipated in the baryon content of galaxy clusters and groups. Indeed, it is well known that in the central region of galaxy clusters and groups, the baryon fraction increases with the halo mass. On the outer region, the lack of X-rays constraints influences our understanding of the evolution of baryons in the halos volume. The standard assumption of “closed-box” system, for which the baryon fraction should approach the cosmological ratio Omega_bar/Omega_m, for galaxy clusters and groups seems to be too strong, especially for less massive objects. Moreover, a complete redshift evolution of baryons in galaxy clusters and groups is still missing.

PV system modeling by five parameters and in situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

PV system modeling by five parameters and in Situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.

Dispersivity Determination Through a Modeling Approach From a Tracer Test Based on Total Br Concentration in Soil Samples

Determination of reliable solute transport parameters is an essential aspect for the characterization of the mechanisms and processes involved in solute transport (e.g., pesticides, fertilizers, contaminants) through the unsaturated zone. A rapid inexpensive method to estimate the dispersivity parameter at the field scale is presented herein. It is based on the quantification by the X-ray fluorescence solid-state technique of total bromine in soil, along with an inverse numerical modeling approach. The results show that this methodology is a good alternative to the classic Br− determination in soil water by ion chromatography. A good agreement between the observed and simulated total soil Br is reported. The results highlight the potential applicability of both combined techniques to infer readily solute transport parameters under field conditions.

Harmonic Distortion State Estimation Using an Evolutionary Strategy

This paper presents a new methodology to estimate harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The main advantage in using such a technique relies upon its modeling facilities as well as its potential to solve fairly complex problems. The problem-solving algorithm herein proposed makes use of data from various power-quality (PQ) meters, which can either be synchronized by high technology global positioning system devices or by using information from a fundamental frequency load flow. This second approach makes the overall PQ monitoring system much less costly. The algorithm is applied to an IEEE test network, for which sensitivity analysis is performed to determine how the parameters of the ES can be selected so that the algorithm performs in an effective way. Case studies show fairly promising results and the robustness of the proposed method.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

A combination of ascorbic acid and α-tocopherol to test the effectiveness and safety in the fragile X syndrome: study protocol for a phase II, randomized, placebo-controlled trial.

BACKGROUND Fragile X syndrome (FXS) is an inherited neurodevelopmental condition characterised by behavioural, learning disabilities, physical and neurological symptoms. In addition, an important degree of comorbidity with autism is also present. Considered a rare disorder affecting both genders, it first becomes apparent during childhood with displays of language delay and behavioural symptoms.Main aim: To show whether the combination of 10 mg/kg/day of ascorbic acid (vitamin C) and 10 mg/kg/day of α-tocopherol (vitamin E) reduces FXS symptoms among male patients ages 6 to 18 years compared to placebo treatment, as measured on the standardized rating scales at baseline, and after 12 and 24 weeks of treatment.Secondary aims: To assess the safety of the treatment. To describe behavioural and cognitive changes revealed by the Developmental Behaviour Checklist Short Form (DBC-P24) and the Wechsler Intelligence Scale for Children-Revised. To describe metabolic changes revealed by blood analysis. To measure treatment impact at home and in an academic environment. METHODS/DESIGN A phase II randomized, double-blind pilot clinical trial. SCOPE male children and adolescents diagnosed with FXS, in accordance with a standardized molecular biology test, who met all the inclusion criteria and none of the exclusion criteria. INSTRUMENTATION clinical data, blood analysis, Wechsler Intelligence Scale for Children-Revised, Conners parent and teacher rating scale scores and the DBC-P24 results will be obtained at the baseline (t0). Follow up examinations will take place at 12 weeks (t1) and 24 weeks (t2) of treatment. DISCUSSION A limited number of clinical trials have been carried out on children with FXS, but more are necessary as current treatment possibilities are insufficient and often provoke side effects. In the present study, we sought to overcome possible methodological problems by conducting a phase II pilot study in order to calculate the relevant statistical parameters and determine the safety of the proposed treatment. The results will provide evidence to improve hyperactivity control and reduce behavioural and learning problems using ascorbic acid (vitamin C) and α-tocopherol (vitamin E). The study protocol was approved by the Regional Government Committee for Clinical Trials in Andalusia and the Spanish agency for drugs and health products. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01329770 (29 March 2011).

Correlations between trabecular bone score, measured using anteroposterior dual-energy x-ray absorptiometry acquisition, and 3-dimensional parameters of bone microarchitecture: an experimental study on human cadaver vertebrae.

Developing a novel technique for the efficient, noninvasive clinical evaluation of bone microarchitecture remains both crucial and challenging. The trabecular bone score (TBS) is a new gray-level texture measurement that is applicable to dual-energy X-ray absorptiometry (DXA) images. Significant correlations between TBS and standard 3-dimensional (3D) parameters of bone microarchitecture have been obtained using a numerical simulation approach. The main objective of this study was to empirically evaluate such correlations in anteroposterior spine DXA images. Thirty dried human cadaver vertebrae were evaluated. Micro-computed tomography acquisitions of the bone pieces were obtained at an isotropic resolution of 93μm. Standard parameters of bone microarchitecture were evaluated in a defined region within the vertebral body, excluding cortical bone. The bone pieces were measured on a Prodigy DXA system (GE Medical-Lunar, Madison, WI), using a custom-made positioning device and experimental setup. Significant correlations were detected between TBS and 3D parameters of bone microarchitecture, mostly independent of any correlation between TBS and bone mineral density (BMD). The greatest correlation was between TBS and connectivity density, with TBS explaining roughly 67.2% of the variance. Based on multivariate linear regression modeling, we have established a model to allow for the interpretation of the relationship between TBS and 3D bone microarchitecture parameters. This model indicates that TBS adds greater value and power of differentiation between samples with similar BMDs but different bone microarchitectures. It has been shown that it is possible to estimate bone microarchitecture status derived from DXA imaging using TBS.

Seed quality parameters of three interspecific hybrids of elephant grass x pearl millet

An interspecific hybrid resulting from the crossing of elephant grass (Pennisetum purpureum Schumach) x pearl millet (Pennisetum glaucum (L.) R. Brown) has been developed. This hybrid, however, revealed low phenotypic uniformity and low production of pure seeds. Through recurrent selection, two improved populations were obtained (genotypes Corte and Pastoreio). The aim of this study was assessing seed quality of the three hybrids (genotypes Corte, Pastoreio and Paraiso) by tests of: seed purity; seed germination; accelerated aging test, at 42 ºC; 1,000 seeds weight; drying curves; and sorption and desorption isotherms. Recurrent selection altered the seed size and increased initial quality of population for genotype Pastoreio. Drying curves for the three hybrids have shown similar behavior and reached moisture contents of 2.1%, 1.9%, and 1.8%, respectively, after 63 days. The accelerated aging test showed that hybrid Pastoreio was the most vigorous.

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimative of genetic parameters in progeny test of Pinus caribaea Morelet var. hondurensis Barret & Golfari by quantitative traits and microsatellite markers

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Study of alternative schemes for the parameterization step of the continuation power flow method based on physical parameters, part I: Mathematical modeling

The conventional power flow method is considered to be inadequate to obtain the maximum loading point because of the singularity of Jacobian matrix. Continuation methods are efficient tools for solving this kind of problem since different parameterization schemes can be used to avoid such ill-conditioning problems. This paper presents the details of new schemes for the parameterization step of the continuation power flow method. The new parameterization options are based on physical parameters, namely, the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, and transmission line power losses (real and reactive). The simulation results obtained with the new approach for the IEEE test systems (14, 30, 57, and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are not only preserved but also improved.