Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Study of pK Values and Effective Dielectric Constants of Ionizable Residues in Pentapeptides and in Staphylococcal Nuclease (SNase) Using a Mean-Field Approach

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

Bright solitons in a quasi-one-dimensional reduced model of a dipolar Bose-Einstein condensate with repulsive short-range interactions

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

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

Explorando abordagens de aprendizado sequencial para floresta de caminhos ótimos

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

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Pressure Dependence of N-15 Chemical Shifts in Model Peptides Ac-Gly-Gly-X-Ala-NH2

High pressure NMR spectroscopy has developed into an important tool for studying conformational equilibria of proteins in solution. We have studied the amide proton and nitrogen chemical shifts of the 20 canonical amino acids X in the random-coil model peptide Ac-Gly-Gly-X-Ala-NH2, in a pressure range from 0.1 to 200 MPa, at a proton resonance frequency of 800 MHz. The obtained data allowed the determination of first and second order pressure coefficients with high accuracy at 283 K and pH 6.7. The mean first and second order pressure coefficients <B-1(15N)> and <B-2(15N)> for nitrogen are 2.91 ppm/GPa and -2.32 ppm/GPa(2), respectively. The corresponding values <B-1(1H)> and <B-2(1H)> for the amide protons are 0.52 ppm/GPa and -0.41 ppm/GPa(2). Residual dependent (1)J(1H15N)-coupling constants are shown.

Design-based random permutation models with auxiliary information

We extend the random permutation model to obtain the best linear unbiased estimator of a finite population mean accounting for auxiliary variables under simple random sampling without replacement (SRS) or stratified SRS. The proposed method provides a systematic design-based justification for well-known results involving common estimators derived under minimal assumptions that do not require specification of a functional relationship between the response and the auxiliary variables.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

Eingefrorene Unordnung und Magnetismus in TiFe_1tn2-Laves-Phase-Dünnschichten

In der vorliegenden Arbeit wird die binäre intermetallische Verbindung TixFe1-x im C14 Laves-Phase Stabilitätsbereich anhand von dünnen Schichten untersucht. TiFe2 weist zwei energetisch nahezu entartete magnetische Grundzustände auf. Dies führt zu einer starken Korrelation von strukturellen und magnetischen Eigenschaften, die im Rahmen dieser Arbeit untersucht wurden. Es wurden daher epitaktische Schichten mit variabler Zusammensetzung im C14 Stabilitätsbereich auf Al2O3 (001)-orientierten Substraten mittels Molekularstrahlepitaxie präpariert und strukturell charakterisiert. Die temperatur- und magnetfeldabhängigen magnetischen Eigenschaften dieser Proben wurden mittels DC-SQUID Magnetisierungsmessungen bestimmt. Es zeigte sich eine magnetische Phasenseparation von Antiferromagnetismus und Ferromagnetismus in Abhängigkeit von der Zusammensetzung. Aus den charakteristischen Ordnungstemperaturen konnte ein magnetisches Phasendiagramm für dünne Schichten und niedrige Aligning-Felder erstellt werden. Ein Phasendiagramm für Volumenproben bei hohem Magnetfeld unterscheidet sich von diesem im Wesentlichen durch den Einfluß von Fe-Segregation in den Volumenproben, welche bei der epitaktischen Präparation nicht auftritt. Anhand von Monte-Carlo Verfahren, denen ein „quenched random disorder“ Modell zugrunde lag, wurde das Verhalten der Dünnschichtproben simuliert und daraus ein magnetisches Phasendiagramm abgeleitet. Das simulierte und experimentelle Phasendiagramm stimmt in den wesentlichen Punkten überein. Die Unterschiede sind durch die speziellen Wachstumseigenschaften von TiFe2 erklärbar. Als Ergebnis kann die magnetische Phasenseparation in diesem System als Auswirkung einer Symmetriebrechung durch Substitution in der Einheitszelle beschrieben werden.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

Adjunctive corticosteroids for Pneumocystis jiroveci pneumonia in patients with HIV-infection

BACKGROUND: Pneumocystis jiroveci pneumonia (PCP) remains the most common opportunistic infection in patients infected with the human immunodeficiency virus (HIV). Among patients with HIV infection and PCP the mortality rate is 10 to 20% during the initial infection and increases substantially with the need for mechanical ventilation. It was suggested that in these patients corticosteroids adjunctive to standard treatment for PCP could prevent the need for mechanical ventilation and decrease mortality. OBJECTIVES: To assess the effects of adjunctive corticosteroids on overall mortality and the need for mechanical ventilation in HIV-infected patients with PCP and substantial hypoxemia (arterial oxygen partial pressure <70 mmHg or alveolar-arterial gradient >35 mmHg on room air). SEARCH STRATEGY: We searched Medline (January 1980-December 2004), EMBASE (January 1985-December 2004) and The Cochrane Library (Issue 4, 2004) without language restrictions to identify randomised controlled trials that compared adjunctive corticosteroids to control in HIV-infected patients with PCP. We further reviewed the reference lists from previously published overviews, we searched UptoDate version 2005 and Clinical Evidence Concise (Issue 12, 2004), contacted experts of the field, and searched reference lists of identified publications for citations of additional relevant articles. SELECTION CRITERIA: Trials were considered eligible for this review if they compared corticosteroids to placebo or usual care in HIV-infected patients with PCP in addition to baseline treatment with trimethoprim-sulfamethoxazole, pentamidine or dapsone-trimethoprim, used random allocation, and reported mortality data. We excluded trials in patients with no or mild hypoxemia (arterial oxygen partial pressure >70 mmHg or an alveolar-arterial gradient <35 mmHg on room air) and trials with a follow-up of less than 30 days. DATA COLLECTION AND ANALYSIS: Two teams of reviewers independently evaluated the methodology and extracted data from each primary study. We pooled treatment effects across studies and calculated a weighted average risk ratio of overall mortality in the treatment and control groups by using a random effects model. MAIN RESULTS: Six studies were included in the review and meta-analysis. Risk ratios for overall mortality for adjunctive corticosteroids were 0.56 (95% confidence interval [CI], 0.32-0.98) at 1 month and 0.68 (95% CI, 0.50-0.94) at 3-4 months of follow-up. To prevent 1 death, numbers needed to treat are 9 patients in a setting without highly active antiretroviral therapy (HAART) available, and 23 patients with HAART available. Only the 3 largest trials provided data on the need for mechanical ventilation with a risk ratio of 0.38 (95% CI, 0.20-0.73) in favour of adjunctive corticosteroids. AUTHORS' CONCLUSIONS: The number and size of trials investigating adjunctive corticosteroids for HIV-infected patients with PCP is small, but evidence from this review suggests a beneficial effect for patients with substantial hypoxemia.

Intravenous magnesium for acute myocardial infarction

BACKGROUND: Mortality and morbidity from acute myocardial infarction (AMI) remain high. Intravenous magnesium started early after the onset of AMI is thought to be a promising adjuvant treatment. Conflicting results from earlier trials and meta-analyses warrant a systematic review of available evidence. OBJECTIVES: To examine the effect of intravenous magnesium versus placebo on early mortality and morbidity. SEARCH STRATEGY: We searched CENTRAL (The Cochrane Library Issue 3, 2006), MEDLINE (January 1966 to June 2006) and EMBASE (January 1980 to June 2006), and the Chinese Biomedical Disk (CBM disk) (January 1978 to June 2006). Some core Chinese medical journals relevant to the cardiovascular field were hand searched from their starting date to the first-half year of 2006. SELECTION CRITERIA: All randomized controlled trials that compared intravenous magnesium with placebo in the presence or absence of fibrinolytic therapy in addition to routine treatment were eligible if they reported mortality and morbidity within 35 days of AMI onset. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed the trial quality and extracted data using a standard form. Odds ratio (OR) were used to pool the effect if appropriate. Where heterogeneity of effects was found, clinical and methodological sources of this were explored. MAIN RESULTS: For early mortality where there was evidence of heterogeneity, a fixed-effect meta-analysis showed no difference between magnesium and placebo groups (OR 0.99, 95%CI 0.94 to 1.04), while a random-effects meta-analysis showed a significant reduction comparing magnesium with placebo (OR 0.66, 95% CI 0.53 to 0.82). Stratification by timing of treatment (< 6 hrs, 6+ hrs) reduced heterogeneity, and in both fixed-effect and random-effects models no significant effect of magnesium was found. In stratified analyses, early mortality was reduced for patients not treated with thrombolysis (OR=0.73, 95% CI 0.56 to 0.94 by random-effects model) and for those treated with less than 75 mmol of magnesium (OR=0.59, 95% CI 0.49 to 0.70) in the magnesium compared with placebo groups.Meta-analysis for the secondary outcomes where there was no evidence of heterogeneity showed reductions in the odds of ventricular fibrillation (OR=0.88, 95% CI 0.81 to 0.96), but increases in the odds of profound hypotension (OR=1.13, 95% CI 1.09 to 1.19) and bradycardia (OR=1.49, 95% CI 1.26 to 1.77) comparing magnesium with placebo. No difference was observed for heart block (OR=1.05, 95% CI 0.97-1.14). For those outcomes where there was evidence of heterogeneity, meta-analysis with both fixed-effect and random-effects models showed that magnesium could decrease ventricular tachycardia (OR=0.45, 95% CI 0.31 to 0.66 by fixed-effect model; OR=0.40, 95% CI 0.19 to 0.84 by random-effects model) and severe arrhythmia needing treatment or Lown 2-5 (OR=0.72, 95% CI 0.60 to 0.85 by fixed-effect model; OR=0.51, 95% CI 0.33 to 0.79 by random-effects model) compared with placebo. There was no difference on the effect of cardiogenic shock between the two groups. AUTHORS' CONCLUSIONS: Owing to the likelihood of publication bias and marked heterogeneity of treatment effects, it is essential that the findings are interpreted cautiously. From the evidence reviewed here, we consider that: (1) it is unlikely that magnesium is beneficial in reducing mortality both in patients treated early and in patients treated late, and in patients already receiving thrombolytic therapy; (2) it is unlikely that magnesium will reduce mortality when used at high dose (>=75 mmol); (3) magnesium treatment may reduce the incidence of ventricular fibrillation, ventricular tachycardia, severe arrhythmia needing treatment or Lown 2-5, but it may increase the incidence of profound hypotension, bradycardia and flushing; and (4) the areas of uncertainty regarding the effect of magnesium on mortality remain the effect of low dose treatment (< 75 mmol) and in patients not treate...

Application of MFBD Algorithms to Image Reconstruction Under Anisoplanatic Conditions

All optical systems that operate in or through the atmosphere suffer from turbulence induced image blur. Both military and civilian surveillance, gun-sighting, and target identification systems are interested in terrestrial imaging over very long horizontal paths, but atmospheric turbulence can blur the resulting images beyond usefulness. My dissertation explores the performance of a multi-frame-blind-deconvolution technique applied under anisoplanatic conditions for both Gaussian and Poisson noise model assumptions. The technique is evaluated for use in reconstructing images of scenes corrupted by turbulence in long horizontal-path imaging scenarios and compared to other speckle imaging techniques. Performance is evaluated via the reconstruction of a common object from three sets of simulated turbulence degraded imagery representing low, moderate and severe turbulence conditions. Each set consisted of 1000 simulated, turbulence degraded images. The MSE performance of the estimator is evaluated as a function of the number of images, and the number of Zernike polynomial terms used to characterize the point spread function. I will compare the mean-square-error (MSE) performance of speckle imaging methods and a maximum-likelihood, multi-frame blind deconvolution (MFBD) method applied to long-path horizontal imaging scenarios. Both methods are used to reconstruct a scene from simulated imagery featuring anisoplanatic turbulence induced aberrations. This comparison is performed over three sets of 1000 simulated images each for low, moderate and severe turbulence-induced image degradation. The comparison shows that speckle-imaging techniques reduce the MSE 46 percent, 42 percent and 47 percent on average for low, moderate, and severe cases, respectively using 15 input frames under daytime conditions and moderate frame rates. Similarly, the MFBD method provides, 40 percent, 29 percent, and 36 percent improvements in MSE on average under the same conditions. The comparison is repeated under low light conditions (less than 100 photons per pixel) where improvements of 39 percent, 29 percent and 27 percent are available using speckle imaging methods and 25 input frames and 38 percent, 34 percent and 33 percent respectively for the MFBD method and 150 input frames. The MFBD estimator is applied to three sets of field data and the results presented. Finally, a combined Bispectrum-MFBD Hybrid estimator is proposed and investigated. This technique consistently provides a lower MSE and smaller variance in the estimate under all three simulated turbulence conditions.