Body condition score of Nellore beef cows: a heritable measure to improve the selection of reproductive and maternal traits

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

Phylogeny of Lundia (Bignoniaceae) based on ndhF and PepC sequences

The circumscription of genera belonging to tribe Bignonieae (Bignoniaceae) has traditionally been complex, with only a few genera having stable circumscriptions in the various classification systems proposed for the tribe. The genus Lundia, for instance, is well characterized by a series of morphological synapomorphies and its circumscription has remained quite stable throughout its history. Despite the stable circumscription of Lundia, the circumscription of species within the genus has remained problematic. This study aims to reconstruct the phylogeny of Lundia in order to refine species circumscriptions, gain a better understanding of relationships between taxa, and identify potential morphological synapomorphies for species and major clades. We sampled 26 accessions representing 13 species of Lundia, and 5 outgroups, and reconstructed the phylogeny of the genus using a chloroplast (ndhF) and a nuclear marker (PepC). Data derived from sequences of the individual loci were analyzed using parsimony and Bayesian inference, and the combined molecular dataset was analyzed with Bayesian methods. The monophyly of Lundia nitidula, a species with a particularly complex circumscription, was tested using Shimodaira-Hasegawa (SH) test and the approximately unbiased test for phylogenetic tree selection (AU test). In addition, 40 morphological characters were mapped onto the tree that resulted from the analysis of the combined molecular dataset in order to identify morphological synapomorphies of individual species and major clades. Lundia and most species currently recognized within the genus were strongly supported as monophyletic in all analyses. One species, Lundia nitidula, was not resolved as monophyletic, but the monophyly of this species was not rejected by the AU and SH tests. Lundia sect. Eriolundia is resolved as paraphyletic in all analyses, while Lundia sect. Eulundia is monophyletic and supported by the same morphological characters traditionally used to circumscribe this section. The phylogeny of Lundia contributed important information for a better circumscription of species and served as basis the taxonomic revision of the genus.

Cointegration: Bayesian Significance Test

To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999) highlighted that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results". The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.

Genetic relationship between growth and reproductive traits in Nellore cattle

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 +/- 0.00, 0.42 +/- 0.02, 0.49 +/- 0.01, 0.11 +/- 0.01 and 0.19 +/- 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.

Phylogeography of the neotropical Anopheles triannulatus complex (Diptera: Culicidae) supports deep structure and complex patterns

Abstract Background The molecular phylogenetic relationships and population structure of the species of the Anopheles triannulatus complex: Anopheles triannulatus s.s., Anopheles halophylus and the putative species Anopheles triannulatus C were investigated. Methods The mitochondrial COI gene, the nuclear white gene and rDNA ITS2 of samples that include the known geographic distribution of these taxa were analyzed. Phylogenetic analyses were performed using Bayesian inference, Maximum parsimony and Maximum likelihood approaches. Results Each data set analyzed septely yielded a different topology but none provided evidence for the seption of An. halophylus and An. triannulatus C, consistent with the hypothesis that the two are undergoing incipient speciation. The phylogenetic analyses of the white gene found three main clades, whereas the statistical parsimony network detected only a single metapopulation of Anopheles triannulatus s.l. Seven COI lineages were detected by phylogenetic and network analysis. In contrast, the network, but not the phylogenetic analyses, strongly supported three ITS2 groups. Combined data analyses provided the best resolution of the trees, with two major clades, Amazonian (clade I) and trans-Andean + Amazon Delta (clade II). Clade I consists of multiple subclades: An. halophylus + An. triannulatus C; trans-Andean Venezuela; central Amazonia + central Bolivia; Atlantic coastal lowland; and Amazon delta. Clade II includes three subclades: Panama; cis-Andean Colombia; and cis-Venezuela. The Amazon delta specimens are in both clades, likely indicating local sympatry. Spatial and molecular variance analyses detected nine groups, corroborating some of subclades obtained in the combined data analysis. Conclusion Combination of the three molecular markers provided the best resolution for differentiation within An. triannulatus s.s. and An. halophylus and C. The latest two species seem to be very closely related and the analyses performed were not conclusive regarding species differentiation. Further studies including new molecular markers would be desirable to solve this species status question. Besides, results of the study indicate a trans-Andean origin for An. triannulatus s.l. The potential implications for malaria epidemiology remain to be investigated.

Reconstruction from image correspondences

A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.

Effetti dell'integrazione visuo-acustica in pazienti con disturbo di campo visivo

Human brain is provided with a flexible audio-visual system, which interprets and guides responses to external events according to spatial alignment, temporal synchronization and effectiveness of unimodal signals. The aim of the present thesis was to explore the possibility that such a system might represent the neural correlate of sensory compensation after a damage to one sensory pathway. To this purpose, three experimental studies have been conducted, which addressed the immediate, short-term and long-term effects of audio-visual integration on patients with Visual Field Defect (VFD). Experiment 1 investigated whether the integration of stimuli from different modalities (cross-modal) and from the same modality (within-modal) have a different, immediate effect on localization behaviour. Patients had to localize modality-specific stimuli (visual or auditory), cross-modal stimulus pairs (visual-auditory) and within-modal stimulus pairs (visual-visual). Results showed that cross-modal stimuli evoked a greater improvement than within modal stimuli, consistent with a Bayesian explanation. Moreover, even when visual processing was impaired, cross-modal stimuli improved performance in an optimal fashion. These findings support the hypothesis that the improvement derived from multisensory integration is not attributable to simple target redundancy, and prove that optimal integration of cross-modal signals occurs in processing stage which are not consciously accessible. Experiment 2 examined the possibility to induce a short term improvement of localization performance without an explicit knowledge of visual stimulus. Patients with VFD and patients with neglect had to localize weak sounds before and after a brief exposure to a passive cross-modal stimulation, which comprised spatially disparate or spatially coincident audio-visual stimuli. After exposure to spatially disparate stimuli in the affected field, only patients with neglect exhibited a shifts of auditory localization toward the visual attractor (the so called Ventriloquism After-Effect). In contrast, after adaptation to spatially coincident stimuli, both neglect and hemianopic patients exhibited a significant improvement of auditory localization, proving the occurrence of After Effect for multisensory enhancement. These results suggest the presence of two distinct recalibration mechanisms, each mediated by a different neural route: a geniculo-striate circuit and a colliculus-extrastriate circuit respectively. Finally, Experiment 3 verified whether a systematic audio-visual stimulation could exert a long-lasting effect on patients’ oculomotor behaviour. Eye movements responses during a visual search task and a reading task were studied before and after visual (control) or audio-visual (experimental) training, in a group of twelve patients with VFD and twelve controls subjects. Results showed that prior to treatment, patients’ performance was significantly different from that of controls in relation to fixations and saccade parameters; after audiovisual training, all patients reported an improvement in ocular exploration characterized by fewer fixations and refixations, quicker and larger saccades, and reduced scanpath length. Similarly, reading parameters were significantly affected by the training, with respect to specific impairments observed in left and right hemisphere–damaged patients. The present findings provide evidence that a systematic audio-visual stimulation may encourage a more organized pattern of visual exploration with long lasting effects. In conclusion, results from these studies clearly demonstrate that the beneficial effects of audio-visual integration can be retained in absence of explicit processing of visual stimulus. Surprisingly, an improvement of spatial orienting can be obtained not only when a on-line response is required, but also after either a brief or a long adaptation to audio-visual stimulus pairs, so suggesting the maintenance of mechanisms subserving cross-modal perceptual learning after a damage to geniculo-striate pathway. The colliculus-extrastriate pathway, which is spared in patients with VFD, seems to play a pivotal role in this sensory compensation.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Novel approach for genotyping varicella-zoster virus strains from Germany

In this study, we present a novel genotyping scheme to classify German wild-type varicella-zoster virus (VZV) strains and to differentiate them from the Oka vaccine strain (genotype B). This approach is based on analysis of four loci in open reading frames (ORFs) 51 to 58, encompassing a total length of 1,990 bp. The new genotyping scheme produced identical clusters in phylogenetic analyses compared to full-genome sequences from well-characterized VZV strains. Based on genotype A, D, B, and C reference strains, a dichotomous identification key (DIK) was developed and applied for VZV strains obtained from vesicle fluid and liquor samples originating from 42 patients suffering from varicella or zoster between 2003 and 2006. Sequencing of regions in ORFs 51, 52, 53, 56, 57, and 58 identified 18 single-nucleotide polymorphisms (SNPs), including two novel ones, SNP 89727 and SNP 92792 in ORF51 and ORF52, respectively. The DIK as well as phylogenetic analysis by Bayesian inference showed that 14 VZV strains belonged to genotype A, and 28 VZV strains were classified as genotype D. Neither Japanese (vaccine)-like B strains nor recombinant-like C strains were found within the samples from Germany. The novel genotyping scheme and the DIK were demonstrated to be practical and simple and allow the highly efficient replication of phylogenetic patterns in VZV initially derived from full-genome DNA sequence analyses. Therefore, this approach may allow us to draw a more comprehensive picture of wild-type VZV strains circulating in Germany and Central Europe by high-throughput procedures in the future.

ENVISIONING QUEER THROUGH DIGITAL MEDIA: DEVELOPING A COMMUNITY-BASED WORKSHOP IN MEDIA ANALYSIS FOR LGBTQIA+ YOUTH

This project consists of a proposed curriculum for a semester-long, community-based workshop for LGBTQIA+ (lesbian, gay, bisexual, trans*, queer or questioning, intersex, asexual or ally, "+" indicating other identifications that deviate from heterosexual) youth ages 16-18. The workshop focuses on an exploration of LGBTQIA+ identity and community through discussion and collaborative rhetorical analysis of visual and social media. Informed by queer theory and history, studies on youth work, and visual media studies and incorporating rhetorical criticism as well as liberatory pedagogy and community literacy practices, the participation-based design of the workshop seeks to involve participants in selection of media texts, active analytical viewership, and multimodal response. The workshop is designed to engage participants in reflection on questions of individual and collective responsibility and agency as members and allies of various communities. The goal of the workshop is to strengthen participants' abilities to analyze the complex ways in which television, film, and social media influence their own and others’ perceptions of issues surrounding queer identities. As part of the reflective process, participants are challenged to consider how they can in turn actively and collaboratively respond to and potentially help to shape these perceptions. My project report details the theoretical framework, pedagogical rationale, methods of text selection and critical analysis, and guidelines for conduct that inform and structure the workshop.

Individual socialization or politocultural context? The cultural roots of volunteering in Switzerland

Volunteering rates in Switzerland vary substantially across language regions. In this article, we investigate the cultural roots of this variation by presenting and empirically testing two different conceptualizations of how linguistic culture is related to individual volunteering. Whereas the first perspective perceives the individual as belonging to a particular language community and its norms and values as crucial for individual volunteering, the other sees the linguistic culture mainly as an important context in which an individual lives and which therefore influences individual volunteering. Empirically, we base our analysis on new survey data from 60 Swiss communes and apply a Bayesian multi-level analysis in order to disentangle the linguistic group from contextual effects. Our analysis supports the view that cultural patterns of civic self-organization can indeed explain regional volunteering behaviour in Switzerland. Whereas the propensity to volunteer is generally highest in German-speaking Switzerland, our findings reveal that it is the group of French speakers that exhibits the highest propensity to volunteer when controlling for language region.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Beyond questionnaires – Exploring adult education teachers' mathematical beliefs with pictures and interviews

Because of the impact that mathematical beliefs have on an individual’s behaviour, they are generally well researched. However, little mathematical belief research has taken place in the field of adult education. This paper presents preliminary results from a study conducted in this field in Switzerland. It is based on Ernest’s (1989) description of mathematics as an instrumental, Platonist or problem solving construct. The analysis uses pictures drawn by the participants and interviews conducted with them as data. Using a categorising scheme developed by Rolka and Halverscheid (2011), the author argues that adults’ mathematical beliefs are complex and especially personal aspects are difficult to capture with said scheme. Particularly the analysis of visual data requires a more refined method of analysis.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.