Linking the embryonic clock with temporal collinearity of Hox gene activation

Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Interactive Correlation Environment (ICE) - A Statistical Web Tool for Data Collinearity Analysis

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

A comment on the article “A collinearity diagnosis of the GNSS geocenter determination” by P. Rebischung, Z. Altamimi, and T. Springer

Meindl et al. (Adv Space Res 51(7):1047–1064, 2013) showed that the geocenter z -component estimated from observations of global navigation satellite systems (GNSS) is strongly correlated to a particular parameter of the solar radiation pressure (SRP) model developed by Beutler et al. (Manuscr Geod 19:367–386, 1994). They analyzed the forces caused by SRP and the impact on the satellites’ orbits. The authors achieved their results using perturbation theory and celestial mechanics. Rebischung et al. (J Geod doi:10.1016/j.asr.2012.10.026, 2013) also deal with the geocenter determination with GNSS. The authors carried out a collinearity diagnosis of the associated parameter estimation problem. They conclude “without much exaggerating that current GNSS are insensitive to any component of geocenter motion”. They explain this inability by the high degree of collinearity of the geocenter coordinates mainly with satellite clock corrections. Based on these results and additional experiments, they state that the conclusions drawn by Meindl et al. (Adv Space Res 51(7):1047–1064, 2013) are questionable. We do not agree with these conclusions and present our arguments in this article. In the first part, we review and highlight the main characteristics of the studies performed by Meindl et al. (Adv Space Res 51(7):1047–1064, 2013) to show that the experiments are quite different from those performed by Rebischung et al. (J Geod doi:10.1016/j.asr.2012.10.026,2013) . In the second part, we show that normal equation (NEQ) systems are regular when estimating geocenter coordinates, implying that the covariance matrices associated with the NEQ systems may be used to assess the sensitivity to geocenter coordinates in a standard way. The sensitivity of GNSS to the components of the geocenter is discussed. Finally, we comment on the arguments raised by Rebischung et al. (J Geod doi:10.1016/j.asr.2012.10.026, 2013) against the results of Meindl et al. (Adv Space Res 51(7):1047–1064, 2013).

Modelos de regressão lineares para estimativa de produtividade da soja no oeste do Paraná, utilizando dados espectrais

The main objective of this work was to evaluate the linear regression between spectral response and soybean yield in regional scale. In this study were monitored 36 municipalities from the west region of the states of Parana using five images of Landsat 5/TM during 2004/05 season. The spectral response was converted in physical values, apparent and surface reflectances, by radiometric transformation and atmospheric corrections and both used to calculate NDVI and GVI vegetation indices. Those ones were compared by multiple and simple regression with government official yield values (IBGE). Diagnostic processing method to identify influents values or collinearity was applied to the data too. The results showed that the mean surface reflectance value from all images was more correlated with yield than individual dates. Further, the multiple regressions using all dates and both vegetation indices gave better results than simple regression.

Education Level Explains Differences in Stroke Incidence among City Districts in Joinville, Brazil: A Three-Year Population-Based Study

Background: Current evidence suggests an inverse association between socioeconomic status and stroke incidence. Our aim was to measure the variation in incidence among different city districts (CD) and their association with socioeconomic variables. Methods: We prospectively ascertained all possible stroke cases occurring in the city of Joinville during the period 2005-2007. We determined the incidence for each of the 38 CD, age-adjusted to the population of Joinville. By linear regression analysis, we correlated incidence data with mean years of education (MYE) and mean income per month (MIPM). Results: Of the 1,734 stroke cases registered, 1,034 were first-ever strokes. In the study period, the crude incidence in Joinville was 69.5 per 100,000 (95% confidence interval, 65.3-73.9). The stroke incidence among CD ranged from 37.5 (22.2-64.6) to 151.0 per 100,000 (69.0-286.6). The stroke incidence was inversely correlated with years of education (r = -0.532; p<0.001). MYE and MIPM were strongly related (R = 0.958), resulting in exclusion of MIPM by collinearity. Conclusions: Years of education can explain a wide incidence variation among CD. These results may be useful to guide the allocation of resources in primary prevention policies. Copyright (C) 2011 S. Karger AG, Basel

Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

A Multi–Agent Brokerage Platform for Media Content Recommendation

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

L’impact différencié de la satisfaction envers les bonis individuels et les bonis collectifs sur l’intention de rester des travailleurs du secteur des technologies de l’information et des communications (TIC)

L’objectif de ce mémoire est d’étudier l’impact différencié de la satisfaction envers les bonis individuels et les bonis collectifs sur l’intention de rester (au sein d’une entreprise donnée) des travailleurs du secteur des technologies de l’information et des communications. Afin d’étudier cette question, trois hypothèses de recherche ont été émises à l’aide des théories suivantes : 1- la théorie de l’agence, 2- la théorie des attentes et 3- la théorie de l’échange social de Blau (1964). Selon la première hypothèse, la satisfaction envers les bonis individuels contribue à accroître l’intention de rester des travailleurs du secteur des TIC. La seconde hypothèse avance que la satisfaction envers les bonis collectifs contribue à accroître l’intention de rester des travailleurs du secteur des TIC. Enfin, la dernière hypothèse soutient que la satisfaction envers les bonis individuels a un impact plus important sur l’intention de rester des travailleurs du secteur des TIC que la satisfaction envers les bonis collectifs. Les données utilisées pour valider nos hypothèses ont été recueillies dans le cadre d'une enquête portant sur « les relations entre la rémunération, la formation et le développement des compétences avec l’attraction et la rétention des employés clés ». Ces données de nature longitudinale, proviennent d'une entreprise canadienne du secteur des TIC. La population étudiée regroupe les nouveaux employés embauchés entre le 1er avril 2009 et le 30 septembre 2010. Nos résultats confirment l’Hypothèse 1 voulant que la satisfaction envers les bonis individuels contribue à accroître l’intention de rester des travailleurs du secteur des TIC. À l’inverse, ces résultats infirment l’Hypothèse 2. La satisfaction envers les bonis collectifs n’a donc pas d’impact significatif sur l’intention de rester. Malgré un problème de colinéarité, nos résultats suggèrent de confirmer l’Hypothèse 3 voulant que la satisfaction envers les bonis individuels ait un impact plus important sur l’intention de rester des travailleurs du secteur des TIC que la satisfaction envers les bonis collectifs. Les résultats indiquent également que le niveau de scolarité et l’engagement organisationnel ont un impact positif sur l’intention de rester des travailleurs. Les analyses longitudinales révèlent que les différences entre les caractéristiques des travailleurs expliquent davantage l’intention de rester, que les différences à travers les temps chez un même travailleur.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.

Natural genetic variation in caesium (Cs) accumulation by Arabidopsis thaliana

Ingestion of caesium (Cs) radioisotopes poses a health risk to humans. Crop varieties that accumulate less Cs in their edible tissues may provide a useful countermeasure. This study was performed to determine whether quantitative genetics on a model plant (Arabidopsis thaliana) might inform such 'safe'-crop strategies. Arabidopsis accessions and recombinant inbred lines (RILs), from Landsberg erecta (Ler) x Cape Verdi Island (Cvi), Ler x Columbia (Col), and Niederzenz (Nd) x Col mapping populations, were grown on agar supplemented with subtoxic levels of Cs. Shoot Cs concentration varied up to three-fold, and shoot f. wt varied up to 25-fold within populations. The heritability of growth and Cs accumulation traits ranged from 0.06 to 0.28. Four quantitative trait loci (QTL) accounted for > 80 of the genetic contribution to the total phenotypic variation in shoot Cs concentration in the Ler x Col population. QTL identified in this study, in particular, QTL co-localizing to the top and bottom regions of Chromosomes I and V in two different mapping populations, are amenable to positional cloning and, through collinearity, may inform selection or breeding strategies for the development of 'safe' crops.

Characterization of the lipoxygenase (LOX) gene family in the Chinese white pear (Pyrus bretschneideri) and comparison with other members of the Rosaceae

Background Lipoxygenases (LOXs), a type of non-haem iron-containing dioxygenase, are ubiquitous enzymes in plants and participate in the formation of fruit aroma which is a very important aspect of fruit quality. Amongst the various aroma volatiles, saturated and unsaturated alcohols and aldehydes provide the characteristic aroma of the fruit. These compounds are formed from unsaturated fatty acids through oxidation, pyrolysis and reduction steps. This biosynthetic pathway involves at least four enzymes, including LOX, the enzyme responsible for lipid oxidation. Although some studies have been conducted on the LOX gene family in several species including Arabidopsis, soybean, cucumber and apple, there is no information from pear; and the evolutionary history of this gene family in the Rosaceae is still not resolved. Results In this study we identified 107 LOX homologous genes from five Rosaceous species (Pyrus bretschneideri, Malus × domestica, Fragaria vesca, Prunus mume and Prunus persica); 23 of these sequences were from pear. By using structure analysis, phylogenic analysis and collinearity analysis, we identified variation in gene structure and revealed the phylogenetic evolutionary relationship of this gene family. Expression of certain pear LOX genes during fruit development was verified by analysis of transcriptome data. Conclusions 23 LOX genes were identified in pear and these genes were found to have undergone a duplication 30–45 MYA; most of these 23 genes are functional. Specific gene duplication was found on chromosome4 in the pear genome. Useful information was provided for future research on the evolutionary history and transgenic research on LOX genes.

Analysis of the genome of Spodoptera frugiperda nucleopolyhedrovirus (SfMNPV-19) and of the high genomic heterogeneity in group II nucleopolyhedroviruses

The genome of the most virulent among 22 Brazilian geographical isolates of Spodoptera frugiperda nucleopolyhedrovirus, isolate 19 (SfMNPV-1 9), was completely sequenced and shown to comprise 132 565 bp and 141 open reading frames (ORFs). A total of 11 ORFs with no homology to genes in the GenBank database were found. Of those, four had typical baculovirus; promoter motifs and polyadenylation sites. Computer-simulated restriction enzyme cleavage patterns of SfMNPV-1 9 were compared with published physical maps of other SfMNPV isolates. Differences were observed in terms of the restriction profiles and genome size. Comparison of SfMNPV-1 9 with the sequence of the SfMNPV isolate 3AP2 indicated that they differed due to a 1427 bp deletion, as well as by a series of smaller deletions and point mutations. The majority of genes of SfMNPV-1 9 were conserved in the closely related Spodoptera exigua NPV (SeMNPV) and Agrotis segetum NPV (AgseMNPV-A), but a few regions experienced major changes and rearrangements. Synthenic maps for the genomes of group 11 NPVs revealed that gene collinearity was observed only within certain clusters. Analysis of the dynamics of gene gain and loss along the phylogenetic tree of the NPVs showed that group 11 had only five defining genes and supported the hypothesis that these viruses form ten highly divergent ancient lineages. Crucially, more than 60% of the gene gain events followed a power-law relation to genetic distance among baculoviruses, indicative of temporal organization in the gene accretion process.

Análise da precificação de imóveis na cidade do Rio de Janeiro utilizando Modelagem Hedônica e os efeitos da autocorrelação espacial

A escolha da cidade do Rio de Janeiro como sede de grandes eventos esportivos mundiais, a Copa do Mundo de Futebol de 2014 e os Jogos Olímpicos de 2016, colocou-a no centro de investimentos em infraestrutura, mobilidade urbana e segurança pública, com consequente impacto no mercado imobiliário, tanto de novos lançamentos de empreendimentos, quanto na revenda de imóveis usados. Acredita-se que o preço de um imóvel dependa de uma relação entre suas características estruturais como quantidade de quartos, suítes, vagas de garagem, presença de varanda, tal como sua localização, proximidade com centros de trabalho, entretenimento e áreas valorizadas ou degradadas. Uma das técnicas para avaliar a contribuição dessas características para a formação do preço do imóvel, conhecido na Econométrica como Modelagem Hedônica de Preços, é uma aplicação de regressão linear multivariada onde a variável dependente é o preço e as variáveis independentes, as respectivas características que deseja-se modelar. A utilização da regressão linear implica em observar premissas que devem ser atendidas para a confiabilidade dos resultados a serem analisados, tais como independência e homoscedasticidade dos resíduos e não colinearidade entre as variáveis independentes. O presente trabalho objetiva aplicar a modelagem hedônica de preços para imóveis localizados na cidade do Rio de Janeiro em um modelo de regressão linear multivariada, em conjunto com outras fontes de dados para a construção de variáveis de acessibilidade e socioambiental a fim de verificar a relação de importância entre elas para a formação do preço e, em particular, exploramos brevemente a tendência de preços em função da distância a favelas. Em atenção aos pré-requisitos observados para a aplicação de regressão linear, verificamos que a premissa de independência dos preços não pode ser atestada devido a constatação da autocorrelação espacial entre os imóveis, onde não apenas as características estruturais e de acessibilidade são levadas em consideração para a precificação do bem, mas principalmente a influência mútua que os imóveis vizinhos exercem um ao outro.