Testing phenomenological and theoretical models of dark matter density profiles with galaxy clusters

We use the stacked gravitational lensingmass profile of four high-mass (M 1015M ) galaxy clusters around z≈0.3 from Umetsu et al. to fit density profiles of phenomenological [Navarro– Frenk–White (NFW), Einasto, S´ersic, Stadel, Baltz–Marshall–Oguri (BMO) and Hernquist] and theoretical (non-singular Isothermal Sphere, DARKexp and Kang & He) models of the dark matter distribution. We account for large-scale structure effects, including a two-halo term in the analysis.We find that the BMO model provides the best fit to the data as measured by the reduced χ2. It is followed by the Stadel profile, the generalized NFW profile with a free inner slope and by the Einasto profile. The NFW model provides the best fit if we neglect the two-halo term, in agreement with results from Umetsu et al. Among the theoretical profiles, the DARKexp model with a single form parameter has the best performance, very close to that of the BMO profile. This may indicate a connection between this theoretical model and the phenomenology of dark matter haloes, shedding light on the dynamical basis of empirical profiles which emerge from numerical simulations.

PRoSPer: perceptual similarity queries in medical CBIR systems through user profiles

In this paper, we present a novel approach to perform similarity queries over medical images, maintaining the semantics of a given query posted by the user. Content-based image retrieval systems relying on relevance feedback techniques usually request the users to label relevant/irrelevant images. Thus, we present a highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The profiles maintain the settings desired for each user, allowing tuning of the similarity assessment, which encompasses the dynamic change of the distance function employed through an interactive process. Experiments on medical images show that the method is effective and can improve the decision making process during analysis.

Lipid and glucose profiles of dairy buffaloes during lactation and dry period

The purpose of this study was to analyze the influence of lactation and dry period in the constituents of lipid and glucose metabolism of buffaloes. One hundred forty-seven samples of serum and plasma were collected between November 2009 and July 2010, from properties raising Murrah, Mediterranean and crossbred buffaloes, located in the State of Sao Paulo, Brazil. Biochemical analysis was obtained by determining the contents of serum cholesterol, triglycerides, beta-hydroxybutyrate (β-HBO), non-esterified fatty acids (NEFA) and plasma glucose. Values for arithmetic mean and standard error mean were calculated using the SAS procedure, version 9.2. Tests for normality of residuals and homogeneity of variances were performed using the SAS Guide Data Analysis. Data were analyzed by ANOVA using the SAS procedure Glimmix. The group information (Lactation), Farm and Age were used in the statistical models. Means of groups were compared using Least Square Means (LSMeans) of SAS, where significant difference was observed at P ≤ 0.05. It was possible to conclude that buffaloes during peak lactation need to metabolize body reserves to supplement the lower amounts of bloodstream lipids, when they remain in negative energy balance. In the dry period, there were significant changes in the lipid profile, characterized by decrease of nutritional requirements, with consequent improvement in the general conditions of the animals.

Carbon flux, nutrient retention efficiency and the curvature of respiration depth-profiles in the ocean water column

Trabajo realizado por: Packard, T. T., Osma, N., Fernández Urruzola, I., Gómez, M

Beach Profiles: Complying with the EU Directive

Interpretación realizada por las alumnas en prácticas de la Facultad de Traducción e Interpretación, Danaide Rodríguez Hernández, Esther Ramírez Millares y Estíbaliz López-Leiton Trujillo, ,

Application of evolutionary algorithms and the boundary element method in the optimization of noise barrier profiles

[EN]This Ph.D. thesis presents a general, robust methodology that may cover any type of 2D acoustic optimization problem. A procedure involving the coupling of Boundary Elements (BE) and Evolutionary Algorithms is proposed for systematic geometric modifications of road barriers that lead to designs with ever-increasing screening performance. Numerical simulations involving single- and multi-objective optimizations of noise barriers of varied nature are included in this document. results disclosed justify the implementation of this methodology by leading to optimal solutions of previously defined topologies that, in general, greatly outperform the acoustic efficiency of classical, widely used barrier designs normally erected near roads.

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Development of the optimal estimation method for inversion of stratospheric emission spectra and validation of HNO3 profiles

This doctoral thesis focuses on ground-based measurements of stratospheric nitric acid (HNO3)concentrations obtained by means of the Ground-Based Millimeter-wave Spectrometer (GBMS). Pressure broadened HNO3 emission spectra are analyzed using a new inversion algorithm developed as part of this thesis work and the retrieved vertical profiles are extensively compared to satellite-based data. This comparison effort I carried out has a key role in establishing a long-term (1991-2010), global data record of stratospheric HNO3, with an expected impact on studies concerning ozone decline and recovery. The first part of this work is focused on the development of an ad hoc version of the Optimal Estimation Method (Rodgers, 2000) in order to retrieve HNO3 spectra observed by means of GBMS. I also performed a comparison between HNO3 vertical profiles retrieved with the OEM and those obtained with the old iterative Matrix Inversion method. Results show no significant differences in retrieved profiles and error estimates, with the OEM providing however additional information needed to better characterize the retrievals. A final section of this first part of the work is dedicated to a brief review on the application of the OEM to other trace gases observed by GBMS, namely O3 and N2O. The second part of this study deals with the validation of HNO3 profiles obtained with the new inversion method. The first step has been the validation of GBMS measurements of tropospheric opacity, which is a necessary tool in the calibration of any GBMS spectra. This was achieved by means of comparisons among correlative measurements of water vapor column content (or Precipitable Water Vapor, PWV) since, in the spectral region observed by GBMS, the tropospheric opacity is almost entirely due to water vapor absorption. In particular, I compared GBMS PWV measurements collected during the primary field campaign of the ECOWAR project (Bhawar et al., 2008) with simultaneous PWV observations obtained with Vaisala RS92k radiosondes, a Raman lidar, and an IR Fourier transform spectrometer. I found that GBMS PWV measurements are in good agreement with the other three data sets exhibiting a mean difference between observations of ~9%. After this initial validation, GBMS HNO3 retrievals have been compared to two sets of satellite data produced by the two NASA/JPL Microwave Limb Sounder (MLS) experiments (aboard the Upper Atmosphere Research Satellite (UARS) from 1991 to 1999, and on the Earth Observing System (EOS) Aura mission from 2004 to date). This part of my thesis is inserted in GOZCARDS (Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere), a multi-year project, aimed at developing a long-term data record of stratospheric constituents relevant to the issues of ozone decline and expected recovery. This data record will be based mainly on satellite-derived measurements but ground-based observations will be pivotal for assessing offsets between satellite data sets. Since the GBMS has been operated for more than 15 years, its nitric acid data record offers a unique opportunity for cross-calibrating HNO3 measurements from the two MLS experiments. I compare GBMS HNO3 measurements obtained from the Italian Alpine station of Testa Grigia (45.9° N, 7.7° E, elev. 3500 m), during the period February 2004 - March 2007, and from Thule Air Base, Greenland (76.5°N 68.8°W), during polar winter 2008/09, and Aura MLS observations. A similar intercomparison is made between UARS MLS HNO3 measurements with those carried out from the GBMS at South Pole, Antarctica (90°S), during the most part of 1993 and 1995. I assess systematic differences between GBMS and both UARS and Aura HNO3 data sets at seven potential temperature levels. Results show that, except for measurements carried out at Thule, ground based and satellite data sets are consistent within the errors, at all potential temperature levels.

Risk profiles and penetrance estimations in multiple endocrine neoplasia type 2A caused by germline RET mutations located in exon 10

Multiple endocrine neoplasia type 2 is characterized by germline mutations in RET. For exon 10, comprehensive molecular and corresponding phenotypic data are scarce. The International RET Exon 10 Consortium, comprising 27 centers from 15 countries, analyzed patients with RET exon 10 mutations for clinical-risk profiles. Presentation, age-dependent penetrance, and stage at presentation of medullary thyroid carcinoma (MTC), pheochromocytoma, and hyperparathyroidism were studied. A total of 340 subjects from 103 families, age 4-86, were registered. There were 21 distinct single nucleotide germline mutations located in codons 609 (45 subjects), 611 (50), 618 (94), and 620 (151). MTC was present in 263 registrants, pheochromocytoma in 54, and hyperparathyroidism in 8 subjects. Of the patients with MTC, 53% were detected when asymptomatic, and among those with pheochromocytoma, 54%. Penetrance for MTC was 4% by age 10, 25% by 25, and 80% by 50. Codon-associated penetrance by age 50 ranged from 60% (codon 611) to 86% (620). More advanced stage and increasing risk of metastases correlated with mutation in codon position (609?620) near the juxtamembrane domain. Our data provide rigorous bases for timing of premorbid diagnosis and personalized treatment/prophylactic procedure decisions depending on specific RET exon 10 codons affected.

Retrieval simulations of the vertical profiles of water vapour and other chemical species in the Martian atmosphere using PACS

Water vapour, despite being a minor constituent in the Martian atmosphere with its precipitable amount of less than 70 pr. μm, attracts considerable attention in the scientific community because of its potential importance for past life on Mars. The partial pressure of water vapour is highly variable because of its seasonal condensation onto the polar caps and exchange with a subsurface reservoir. It is also known to drive photochemical processes: photolysis of water produces H, OH, HO2 and some other odd hydrogen compounds, which in turn destroy ozone. Consequently, the abundance of water vapour is anti-correlated with ozone abundance. The Herschel Space Observatory provides for the first time the possibility to retrieve vertical water profiles in the Martian atmosphere. Herschel will contribute to this topic with its guaranteed-time key project called "Water and related chemistry in the solar system". Observations of Mars by Heterodyne Instrument for the Far Infrared (HIFI) and Photodetector Array Camera and Spectrometer (PACS) onboard Herschel are planned in the frame of the programme. HIFI with its high spectral resolution enables accurate observations of vertically resolved H2O and temperature profiles in the Martian atmosphere. Unlike HIFI, PACS is not capable of resolving the line-shape of molecular lines. However, our present study of PACS observations for the Martian atmosphere shows that the vertical sensitivity of the PACS observations can be improved by using multiple-line observations with different line opacities. We have investigated the possibility of retrieving vertical profiles of temperature and molecular abundances of minor species including H2O in the Martian atmosphere using PACS. In this paper, we report that PACS is able to provide water vapour vertical profiles for the Martian atmosphere and we present the expected spectra for future PACS observations. We also show that the spectral resolution does not allow the retrieval of several studied minor species, such as H2O2, HCl, NO, SO2, etc.