Poder empresarial e cobertura de analistas financeiros

Este estudo buscou investigar duas relações de interesse: a relação entre poder e cobertura de analistas financeiros no mercado acionário brasileiro, e a relação entre poder e assimetria informacional neste mercado, nos períodos de 2000 a 2010. O objetivo desta pesquisa envolveu verificar se o poder empresarial aumenta a assimetria informacional decorrentes dos custos de agência envolvidos e possibilidade de expropriação de valor (Jensen & Meckling, 1976), ou diminui a assimetria, uma vez que administração da empresa não se sente vulnerável a demissões ou possíveis embaraços a sua atuação, e opta por não omitir informações aos stakeholders (Bertrand & Mullainathan, 2003). Ainda relacionado ao ambiente informacional impactado pelo poder empresarial, buscou-se verificar se os analistas financeiros acompanham empresas que apresentam uma maior assimetria informacional, e assim cumprindo sua função de monitoramento da gestão empresarial (Healy & Palepu, 2001), ou menor assimetria, em decorrência dos custos envolvidos em se obter informações privadas (Frankel, Kothari & Weber, 2006). Com o uso de proxies criadas pela análise fatorial para capturar as especificidades relacionadas a poder empresarial e assimetria informacional no ambiente empresarial brasileiro, foram observadas uma relação negativa entre cobertura de analistas financeiros e poder empresarial e uma relação positiva entre assimetria e poder empresarial. Pelas hipóteses esquematizadas por Jiraporn, Liu e Kim (2012), que abarcam todas as relações possíveis entre assimetria, poder empresarial e cobertura de analistas financeiros, os resultados se enquadram na Hipótese da Opacidade.

Concepciones sobre las tecnologías de la información y la comunicación (TIC) y sus implicaciones educativas: un estudio exploratorio con profesorado de la provincia de Ñuble, Chile

El propósito de este estudio fue conocer las concepciones de profesores de educación primaria sobre las tecnologías educativas en dos dimensiones: a) conocimiento de las tecnologías de la información y comunicación; y b) creencias sobre el uso educativo que el profesorado da a estas herramientas. Se opta por un enfoque metodológico cuantitativo y un diseño no-experimental descriptivo del tipo encuesta. El análisis de los datos se realizó mediante paquete estadístico SPSS 14.0 y las técnicas utilizadas fueron descriptivos, frecuencias y porcentajes, técnicas de reducción de datos (análisis factorial) e inferencia estadística (comparación de medias y porcentajes). Los resultados demuestran que la mayoría de los profesores reconocen el interés que las tecnologías despiertan en el alumnado y las oportunidades de aprendizaje que ofrecen principalmente en relación con los diferentes ritmos de aprendizaje y las necesidades educativas especiales. Se identifica la búsqueda de información como una competencia fundamental, así como se evidencia que existe una relación causal entre el nivel de formación, la importancia que el profesor otorga al recurso y el uso educativo. Los resultados hacen aconsejable promover programas de formación continua en esta área y fortalecer la formación inicial docente.

Hatékony leadership magatartások szlovák szervezeti környezetben (Effective leadership behaviors in Slovak organizational environment – Introduction to the Slovak implict leadership theories –Results of the GLOBE research)

Az itt bemutatott kutatás célja az volt, hogy azonosítsa és feltárja a szlovák vállalati környezetben követett és kívánatosnak tartott leadership dimenziókat és bemutassa azokat az implicit leadership elmélet alapján meghatározott magatartásokat, amelyek a sikeres leadershipet támogató magatartásokként jelennek meg (az implicit leadership elmélet szerint az egyének magatartásokhoz kapcsolódó hiedelmeik, meggyőződéseik és értékítéleteik alapján határozzák meg, kit tekintenek vezetőnek, illetve hogyan különböztetik meg a hatékony vezetést a nem hatékonytól). Ehhez a GLOBE (Global Leadership and Organization Behavior Effectiveness) kutatását használta fel a szerző empirikus alapként. A faktorelemzéssel előállított kutatási eredmények azt bizonyítják, hogy definiálhatók a nemzetközi mintán elkülöníthető implicit leadership elméletektől jól megkülönböztethető szlovák implicit leadership elméletek. Statisztikai próbáinak eredményei azt mutatják, hogy léteznek olyan leadership faktorok, melyek a szlovák és a magyar vállalati környezetben is megjelennek, illetve feltárhatók olyan implicit leadership elméletek, melyek megítélése ebben a régióban egységesnek tekinthető. _____ The aim of this research is to identify and explore the committed and desirable leadership dimensions in the Slovak organizational environment. This article presents those on the basis of implicit leadership theories identified behaviors which appear as successful leadership supported behaviors. To it the GLOBE (Global Leadership and Organization Behavior Effectiveness) research is used as the empirical basis by the author. Research results which were produced by factor analysis demonstrate that the Slovak implicit leadership theories can be identified because those can be clearly distinguished from implicit leadership theories available in the international sample.

Adolescent readers' self-perceptions of affective factors related to performance on standardized tests

The purpose of this study was to investigate which affective factors of adolescent high school readers were related to high-level readers, middle-level readers and low-level readers. The research problem was to determine the relationship between adolescent high school students' self-perceived reading self-efficacy factors and the students' reading performance on a standardized reading assessment considering demographic factors of age, gender and socio-economic status as covariates. The research design was ex post facto making inferences without direct intervention. The sample was obtained from one large, diverse, urban high school, consisting of 9th and 10th grade adolescent students (N = 176). Students voluntarily completed a self-report, reading self-efficacy survey. School records were used to obtain standardized reading level scores, age, gender, and socio-economic status data. An exploratory factor analysis of the self-efficacy survey responses resulted in the identification of 7 underlying factors. The striving (low-level) readers had significantly lower self-perceptions on 5 of the 7 affective factors than the middle-level readers, and strong (high-level) readers, p < .05. The 5 affective factors on which the striving readers had significantly lower self-perceptions were: (a) Observational Comparison, (b) Progress, (c) Lack of Progress, (d) Lack of Anxiety, and (e) Positive Social Feedback. The 2 affective factors which were not significantly different for reader level were Anxiety and Negative Social Feedback. Girls had significantly less anxiety than boys for both of the factors in the Anxiety category. Statistical results showed that none of the demographic covariates tested; age, gender, or socio-economic status, moderated the relationship between affective reader self-efficacy factors and reader level. This study concluded that there were distinguishable differences for striving, middle, and strong readers' self-efficacy factors. Determining affective factors related to reading can be used to create better instructional environments and instruction for adolescent students.

Seed dispersal and reproduction patterns among Everglades plants

In this study three aspects of sexual reproduction in Everglades plants were examined to more clearly understand seed dispersal and the allocation of resources to sexual reproduction—spatial dispersal process, temporal dispersal of seeds (seedbank), and germination patterns in the dominant species, sawgrass (Cladium jamaicense). Community assembly rules for fruit dispersal were deduced by analysis of functional traits associated with this process. Seedbank ecology was investigated by monitoring emergence of germinants from sawgrass soil samples held under varying water depths to determine the fate of dispersed seeds. Fine-scale study of sawgrass fruits yielded information on contributions to variation in sexually produced propagules in this species, which primarily reproduces vegetatively. It was hypothesized that Everglades plants possess a set of functional traits that enhance diaspore dispersal. To test this, 14 traits were evaluated among 51 species by factor analysis. The factorial plot of this analysis generated groups of related traits, with four suites of traits forming dispersal syndromes. Hydrochory traits were categorized by buoyancy and appendages enhancing buoyancy. Anemochory traits were categorized by diaspore size and appendages enhancing air movement. Epizoochory traits were categorized by diaspore size, buoyancy, and appendages allowing for attachment. Endozoochory traits were categorized by diaspore size, buoyancy, and appendages aiding diaspore presentation. These patterns/trends of functional trait organization also represent dispersal community assembly rules. Seeds dispersed by hydrochory were hypothesized to be caught most often in the edge of the north side of sawgrass patches. Patterns of germination and dispersal mode of all hydrochorous macrophytes with propagules in the seedbank were elucidated by germination analysis from 90 soil samples collected from 10 sawgrass patches. Mean site seed density was 486 seeds/m2 from 13 species. Most seeds collected at the north side of patches and significantly in the outer one meter of the patch edge (p = 0.013). Sawgrass seed germination was hypothesized to vary by site, among individual plants, and within different locations of a plant’s infructescence. An analysis of sawgrass fruits with nested ANOVAs found that collection site and interaction of site x individual plant significantly affect germination ability, seed viability, and fruit size (p ≤ 0.050). Fruit location within a plant’s infructescence did not significantly affect germination. As for allocation of resources to sexual reproduction, only 17.9% of sawgrass seeds germinated and only 4.8% of ungerminated seeds with fleshy endosperm were presumed viable, but dormant. Collectively, only 22% of all sawgrass seeds produced were viable.

Seed Dispersal and Reproduction Patterns Among Everglades Plants

In this study three aspects of sexual reproduction in Everglades plants were examined to more clearly understand seed dispersal and the allocation of resources to sexual reproduction— spatial dispersal process, temporal dispersal of seeds (seedbank), and germination patterns in the dominant species, sawgrass (Cladium jamaicense). Community assembly rules for fruit dispersal were deduced by analysis of functional traits associated with this process. Seedbank ecology was investigated by monitoring emergence of germinants from sawgrass soil samples held under varying water depths to determine the fate of dispersed seeds. Fine-scale study of sawgrass fruits yielded information on contributions to variation in sexually produced propagules in this species, which primarily reproduces vegetatively. It was hypothesized that Everglades plants possess a set of functional traits that enhance diaspore dispersal. To test this, 14 traits were evaluated among 51 species by factor analysis. The factorial plot of this analysis generated groups of related traits, with four suites of traits forming dispersal syndromes. Hydrochory traits were categorized by buoyancy and appendages enhancing buoyancy. Anemochory traits were categorized by diaspore size and appendages enhancing air movement. Epizoochory traits were categorized by diaspore size, buoyancy, and appendages allowing for attachment. Endozoochory traits were categorized by diaspore size, buoyancy, and appendages aiding diaspore presentation. These patterns/trends of functional trait organization also represent dispersal community assembly rules. Seeds dispersed by hydrochory were hypothesized to be caught most often in the edge of the north side of sawgrass patches. Patterns of germination and dispersal mode of all hydrochorous macrophytes with propagules in the seedbank were elucidated by germination analysis from 90 soil samples collected from 10 sawgrass patches. Mean site seed density was 486 seeds/m2 from 13 species. Most seeds collected at the north side of patches and significantly in the outer one meter of the patch edge (p = 0.013). Sawgrass seed germination was hypothesized to vary by site, among individual plants, and within different locations of a plant’s infructescence. An analysis of sawgrass fruits with nested ANOVAs found that collection site and interaction of site x individual plant significantly affect germination ability, seed viability, and fruit size (p < 0.050). Fruit location within a plant’s infructescence did not significantly affect germination. As for allocation of resources to sexual reproduction, only 17.9% of sawgrass seeds germinated and only 4.8% of ungerminated seeds with fleshy endosperm were presumed viable, but dormant. Collectively, only 22% of all sawgrass seeds produced were viable.

Multi-body simulation of a canine hind limb: model development, experimental validation and calculation of ground reaction forces

Background: Among other causes the long-term result of hip prostheses in dogs is determined by aseptic loosening. A prevention of prosthesis complications can be achieved by an optimization of the tribological system which finally results in improved implant duration. In this context a computerized model for the calculation of hip joint loadings during different motions would be of benefit. In a first step in the development of such an inverse dynamic multi-body simulation (MBS-) model we here present the setup of a canine hind limb model applicable for the calculation of ground reaction forces. Methods: The anatomical geometries of the MBS-model have been established using computer tomography- (CT-) and magnetic resonance imaging- (MRI-) data. The CT-data were collected from the pelvis, femora, tibiae and pads of a mixed-breed adult dog. Geometric information about 22 muscles of the pelvic extremity of 4 mixed-breed adult dogs was determined using MRI. Kinematic and kinetic data obtained by motion analysis of a clinically healthy dog during a gait cycle (1 m/s) on an instrumented treadmill were used to drive the model in the multi-body simulation. Results and Discussion: As a result the vertical ground reaction forces (z-direction) calculated by the MBS-system show a maximum deviation of 1.75%BW for the left and 4.65%BW for the right hind limb from the treadmill measurements. The calculated peak ground reaction forces in z- and y-direction were found to be comparable to the treadmill measurements, whereas the curve characteristics of the forces in y-direction were not in complete alignment. Conclusion: In conclusion, it could be demonstrated that the developed MBS-model is suitable for simulating ground reaction forces of dogs during walking. In forthcoming investigations the model will be developed further for the calculation of forces and moments acting on the hip joint during different movements, which can be of help in context with the in silico development and testing of hip prostheses.

Development and Validation of a Model-Based Combustion Controller for Water Injection Management

This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Enzyme replacement therapy with agalsidase alfa in patients with Fabry's disease: an analysis of registry data.

BACKGROUND: We analysed 5-year treatment with agalsidase alfa enzyme replacement therapy in patients with Fabry's disease who were enrolled in the Fabry Outcome Survey observational database (FOS). METHODS: Baseline and 5-year data were available for up to 181 adults (126 men) in FOS. Serial data for cardiac mass and function, renal function, pain, and quality of life were assessed. Safety and sensitivity analyses were done in patients with baseline and at least one relevant follow-up measurement during the 5 years (n=555 and n=475, respectively). FINDINGS: In patients with baseline cardiac hypertrophy, treatment resulted in a sustained reduction in left ventricular mass (LVM) index after 5 years (from 71.4 [SD 22.5] g/m(2.7) to 64.1 [18.7] g/m(2.7), p=0.0111) and a significant increase in midwall fractional shortening (MFS) from 14.3% (2.3) to 16.0% (3.8) after 3 years (p=0.02). In patients without baseline hypertrophy, LVM index and MFS remained stable. Mean yearly fall in estimated glomerular filtration rate versus baseline after 5 years of enzyme replacement therapy was -3.17 mL/min per 1.73 m(2) for men and -0.89 mL/min per 1.73 m(2) for women. Average pain, measured by Brief Pain Inventory score, improved significantly, from 3.7 (2.3) at baseline to 2.5 (2.4) after 5 years (p=0.0023). Quality of life, measured by deviation scores from normal EuroQol values, improved significantly, from -0.24 (0.3) at baseline to -0.17 (0.3) after 5 years (p=0.0483). Findings were confirmed by sensitivity analysis. No unexpected safety concerns were identified. INTERPRETATION: By comparison with historical natural history data for patients with Fabry's disease who were not treated with enzyme replacement therapy, long-term treatment with agalsidase alfa leads to substantial and sustained clinical benefits. FUNDING: Shire Human Genetic Therapies AB.

Functional analysis: evaluation of response intensities--tailoring ANOVA for lists of expression subsets.

Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a two-way ANOVA to examine these criteria. The significance of the results was evaluated according to the self-contained null hypothesis, using label sampling or by inferring the null distribution from normally distributed random data. Evaluations performed on simulated data revealed that FAERI outperforms currently available methods for each type of set tested. We then applied the FAERI method to analyze three real-world datasets on hypoxia response. FAERI was able to detect more genesets than other methodologies, and the genesets selected were coherent with current knowledge of cellular response to hypoxia. Moreover, the genesets selected by FAERI were confirmed when the analysis was repeated on two additional related datasets. Conclusions: The expression values of genesets are associated with several biological effects. The underlying mathematical structure of the genesets allows for analysis of data from several genes at the same time. Focusing on expression levels, the direction of the expression changes, and correlations, we showed that two-step data reduction allowed us to significantly improve the performance of geneset analysis using a modified two-way ANOVA procedure, and to detect genesets that current methods fail to detect.

Analysis of susceptibility to human immunodeficiency virus 1 (HIV-1) by comparative genetics

Summary [résumé français voir ci-dessous] From the beginning of the 20th century the world population has been confronted with the human immune deficiency virus 1 (HIV-1). This virus has the particularity to mutate fast, and could thus evade and adapt to the human host. Our closest evolutionary related organisms, the non-human primates, are less susceptible to HIV-1. In a broader sense, primates are differentially susceptible to various retrovirus. Species specificity may be due to genetic differences among primates. In the present study we applied evolutionary and comparative genetic techniques to characterize the evolutionary pattern of host cellular determinants of HIV-1 pathogenesis. The study of the evolution of genes coding for proteins participating to the restriction or pathogenesis of HIV-1 may help understanding the genetic basis of modern human susceptibility to infection. To perform comparative genetics analysis, we constituted a collection of primate DNA and RNA to allow generation of de novo sequence of gene orthologs. More recently, release to the public domain of two new primate complete genomes (bornean orang-utan and common marmoset) in addition of the three previously available genomes (human, chimpanzee and Rhesus monkey) help scaling up the evolutionary and comparative genome analysis. Sequence analysis used phylogenetic and statistical methods for detecting molecular adaptation. We identified different selective pressures acting on host proteins involved in HIV-1 pathogenesis. Proteins with HIV-1 restriction properties in non-human primates were under strong positive selection, in particular in regions of interaction with viral proteins. These regions carried key residues for the antiviral activity. Proteins of the innate immunity presented an evolutionary pattern of conservation (purifying selection) but with signals of relaxed constrain if we compared them to the average profile of purifying selection of the primate genomes. Large scale analysis resulted in patterns of evolutionary pressures according to molecular function, biological process and cellular distribution. The data generated by various analyses served to guide the ancestral reconstruction of TRIM5a a potent antiviral host factor. The resurrected TRIM5a from the common ancestor of Old world monkeys was effective against HIV-1 and the recent resurrected hominoid variants were more effective against other retrovirus. Thus, as the result of trade-offs in the ability to restrict different retrovirus, human might have been exposed to HIV-1 at a time when TRIM5a lacked the appropriate specific restriction activity. The application of evolutionary and comparative genetic tools should be considered for the systematical assessment of host proteins relevant in viral pathogenesis, and to guide biological and functional studies. Résumé La population mondiale est confrontée depuis le début du vingtième siècle au virus de l'immunodéficience humaine 1 (VIH-1). Ce virus a un taux de mutation particulièrement élevé, il peut donc s'évader et s'adapter très efficacement à son hôte. Les organismes évolutivement le plus proches de l'homme les primates nonhumains sont moins susceptibles au VIH-1. De façon générale, les primates répondent différemment aux rétrovirus. Cette spécificité entre espèces doit résider dans les différences génétiques entre primates. Dans cette étude nous avons appliqué des techniques d'évolution et de génétique comparative pour caractériser le modèle évolutif des déterminants cellulaires impliqués dans la pathogenèse du VIH- 1. L'étude de l'évolution des gènes, codant pour des protéines impliquées dans la restriction ou la pathogenèse du VIH-1, aidera à la compréhension des bases génétiques ayant récemment rendu l'homme susceptible. Pour les analyses de génétique comparative, nous avons constitué une collection d'ADN et d'ARN de primates dans le but d'obtenir des nouvelles séquences de gènes orthologues. Récemment deux nouveaux génomes complets ont été publiés (l'orang-outan du Bornéo et Marmoset commun) en plus des trois génomes déjà disponibles (humain, chimpanzé, macaque rhésus). Ceci a permis d'améliorer considérablement l'étendue de l'analyse. Pour détecter l'adaptation moléculaire nous avons analysé les séquences à l'aide de méthodes phylogénétiques et statistiques. Nous avons identifié différentes pressions de sélection agissant sur les protéines impliquées dans la pathogenèse du VIH-1. Des protéines avec des propriétés de restriction du VIH-1 dans les primates non-humains présentent un taux particulièrement haut de remplacement d'acides aminés (sélection positive). En particulier dans les régions d'interaction avec les protéines virales. Ces régions incluent des acides aminés clé pour l'activité de restriction. Les protéines appartenant à l'immunité inné présentent un modèle d'évolution de conservation (sélection purifiante) mais avec des traces de "relaxation" comparé au profil général de sélection purifiante du génome des primates. Une analyse à grande échelle a permis de classifier les modèles de pression évolutive selon leur fonction moléculaire, processus biologique et distribution cellulaire. Les données générées par les différentes analyses ont permis la reconstruction ancestrale de TRIM5a, un puissant facteur antiretroviral. Le TRIM5a ressuscité, correspondant à l'ancêtre commun entre les grands singes et les groupe des catarrhiniens, est efficace contre le VIH-1 moderne. Les TRIM5a ressuscités plus récents, correspondant aux ancêtres des grands singes, sont plus efficaces contre d'autres rétrovirus. Ainsi, trouver un compromis dans la capacité de restreindre différents rétrovirus, l'homme aurait été exposé au VIH-1 à une période où TRIM5a manquait d'activité de restriction spécifique contre celui-ci. L'application de techniques d'évolution et de génétique comparative devraient être considérées pour l'évaluation systématique de protéines impliquées dans la pathogenèse virale, ainsi que pour guider des études biologiques et fonctionnelles

Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data

We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

Statistical Analysis of Highway Needs Condition Data: Manual vs. Automated, TR-494

This project examines similarities and differences between the automated condition data collected on and off county paved roads and the manual condition data collected by Iowa Department of Transportation (DOT) staff in 2000 and 2001. Also, the researchers will provide staff support to the advisory committee in exploring other options to the highway need process. The results show that the automated condition data can be used in a converted highway needs process with no major differences between the two methods. Even though the foundation rating difference was significant, the foundation rating weighting factor in HWYNEEDS is minimal and should not have a major impact. In terms of RUTF formula based distribution, the results clearly show the superiority of the condition-based analysis compared to the non-condition based. That correlation can be further enhanced by adding more distress variables to the analysis.