Model Order Selection Rules For Covariance Structure Classification

The adaptive classification of the interference covariance matrix structure for radar signal processing applications is addressed in this paper. This represents a key issue because many detection architectures are synthesized assuming a specific covariance structure which may not necessarily coincide with the actual one due to the joint action of the system and environment uncertainties. The considered classification problem is cast in terms of a multiple hypotheses test with some nested alternatives and the theory of Model Order Selection (MOS) is exploited to devise suitable decision rules. Several MOS techniques, such as the Akaike, Takeuchi, and Bayesian information criteria are adopted and the corresponding merits and drawbacks are discussed. At the analysis stage, illustrating examples for the probability of correct model selection are presented showing the effectiveness of the proposed rules

A workload-aware energy model for virtual machine migration

Energy consumption has become a significant issue for data centres. Assessing their consumption requires precise and detailed models. In the latter years, many models have been proposed, but most of them either do not consider energy consumption related to virtual machine migration or do not consider the variation of the workload on (1) the virtual machines (VM) and (2) the physical machines hosting the VMs. In this paper, we show that omitting migration and workload variation from the models could lead to misleading consumption estimates. Then, we propose a new model for data centre energy consumption that takes into account the previously omitted model parameters and provides accurate energy consumption predictions for paravirtualised virtual machines running on homogeneous hosts. The new model's accuracy is evaluated with a comprehensive set of operational scenarios. With the use of these scenarios we present a comparative analysis of our model with similar state-of-the-art models for energy consumption of VM Migration, showing an improvement up to 24% in accuracy of prediction. © 2015 IEEE

Diagnóstico em comunicação na Embrapa Pantanal.

Com o objetivo de diagnosticar pontos fortes e fracos da comunicação interna e externa da Embrapa Pantanal e iniciar um planejamento em comunicação, a equipe da ACN (Área de Comunicação e Negócios) da Unidade aplicou, em 2007, duas pesquisas de opinião com os públicos interno e externo. A finalidade desta publicação é registrar os resultados desses levantamentos e algumas iniciativas de comunicação implementadas logo após as pesquisas para que possam subsidiar, a qualquer momento, com as devidas atualizações, outras ações em comunicação ou mesmo transferência de tecnologias. Diagnósticos como estes são o ponto de partida para qualquer ação operacional, tática ou estratégica em comunicação.bitstream/CPAP-2010/57369/1/DOC107.pd

Robust PCA and MIC statistics of baryons in early minihaloes

We present a novel approach, based on robust principal components analysis (RPCA) and maximal information coefficient (MIC), to study the redshift dependence of halo baryonic properties. Our data are composed of a set of different physical quantities for primordial minihaloes: dark matter mass (M-dm), gas mass (M-gas), stellar mass (M-star), molecular fraction (x(mol)), metallicity (Z), star formation rate (SFR) and temperature. We find that M-dm and M-gas are dominant factors for variance, particularly at high redshift. Nonetheless, with the emergence of the first stars and subsequent feedback mechanisms, x(mol), SFR and Z start to have a more dominant role. Standard PCA gives three principal components (PCs) capable to explain more than 97 per cent of the data variance at any redshift (two PCs usually accounting for no less than 92 per cent), whilst the first PC from the RPCA analysis explains no less than 84 per cent of the total variance in the entire redshift range (with two PCs explaining greater than or similar to 95 per cent anytime). Our analysis also suggests that all the gaseous properties have a stronger correlation with M-gas than with M-dm, while M-gas has a deeper correlation with x(mol) than with Z or SFR. This indicates the crucial role of gas molecular content to initiate star formation and consequent metal pollution from Population III and Population II/I regimes in primordial galaxies. Finally, a comparison between MIC and Spearman correlation coefficient shows that the former is a more reliable indicator when halo properties are weakly correlated

The Overlooked Potential of Generalized Linear Models in Astronomy - I: Binomial Regression

Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought. Contemporary data analysis problems often elude the capabilities of classical statistical techniques, suggesting the use of cutting edge statistical methods. In this light, astronomers have overlooked a whole family of statistical techniques for exploratory data analysis and robust regression, the so-called Generalized Linear Models (GLMs). In this paper -- the first in a series aimed at illustrating the power of these methods in astronomical applications -- we elucidate the potential of a particular class of GLMs for handling binary/binomial data, the so-called logit and probit regression techniques, from both a maximum likelihood and a Bayesian perspective. As a case in point, we present the use of these GLMs to explore the conditions of star formation activity and metal enrichment in primordial minihaloes from cosmological hydro-simulations including detailed chemistry, gas physics, and stellar feedback. We predict that for a dark mini-halo with metallicity $\approx 1.3 \times 10^{-4} Z_{\bigodot}$, an increase of $1.2 \times 10^{-2}$ in the gas molecular fraction, increases the probability of star formation occurrence by a factor of 75%. Finally, we highlight the use of receiver operating characteristic curves as a diagnostic for binary classifiers, and ultimately we use these to demonstrate the competitive predictive performance of GLMs against the popular technique of artificial neural networks.Comment: 20 pages, 10 figures, 3 tables, accepted for publication in Astronomy and Computin

Socioeconomic Gradients in Chronic Disease Risk Factors in Middle-Income Countries: Evidence of Effect Modification by Urbanicity in Argentina

Objectives. We investigated associations of socioeconomic position (SEP) with chronic disease risk factors, and heterogeneity in this patterning by provincial-level urbanicity in Argentina. Methods. We used generalized estimating equations to determine the relationship between SEP and body mass index, high blood pressure, diabetes, low physical activity, and eating fruit and vegetables, and examined heterogeneity by urbanicity with nationally representative, cross-sectional survey data from 2005. All estimates were age adjusted and gender stratified. Results. Among men living in less urban areas, higher education was either not associated with the risk factors or associated adversely. In more urban areas, higher education was associated with better risk factor profiles (P<.05 for 4 of 5 risk factors). Among women, higher education was associated with better risk factor profiles in all areas and more strongly in more urban than in less urban areas (P<0.05 for 3 risk factors). Diet (in men) and physical activity (in men and women) were exceptions to this trend. Conclusions. These results provide evidence for the increased burden of chronic disease risk among those of lower SEP, especially in urban areas

O jornalismo de proximidade e a cobertura de ações de mobilização social: um retrato midiático da epidemia de dengue em Marília.

O jornalismo de proximidade é um conceito que atribui características a uma prática profissional que conjuga as ideias de espaço geográfico e de temas de interesse de uma determinada coletividade. O tratamento midiático inclui a concessão de voz e espaço aos atores locais. Este artigo retoma o conceito e o enquadra na discussão sobre as posturas editoriais dos jornais Diário e Jornal da Manhã, ambos de Marília, cidade do interior paulista, durante a cobertura da epidemia de dengue vivenciada localmente nos primeiros meses de 2015. Conclui que, em parte, os dois veículos se encaixam na perspectiva do jornalismo de proximidade, porém, um deles abre mais espaço para a divulgação de iniciativas que envolvem a mobilização social

Functional and structural leaf plasticity determine photosynthetic performances during drought stress and recovery in two platanus orientalis populations from contrasting habitats.

In the context of climatic change, more severe and long-lasting droughts will modify the fitness of plants, with potentially worse consequences on the relict trees. We have investigated the leaf phenotypic (anatomical, physiological and biochemical) plasticity in well-watered, drought- stressed and re-watered plants of two populations of Platanus orientalis, an endangered species in the west of the Mediterranean area. The two populations originated in contrasting climate (drier and warmer, Italy (IT) population; more humid and colder, Bulgaria (BG) population). The IT control plants had thicker leaves, enabling them to maintain higher leaf water content in the dry environment, and more spongy parenchyma, which could improve water conductivity of these plants and may result in easier CO2 diffusion than in BG plants. Control BG plants were also characterized by higher photorespiration and leaf antioxidants compared to IT plants. BG plants responded to drought with greater leaf thickness shrinkage. Drought also caused substantial reduction in photosynthetic parameters of both IT and BG plants. After re-watering, photosynthesis did not fully recover in either of the two populations. However, IT leaves became thicker, while photorespiration in BG plants further increased, perhaps indicating sustained activation of defensive mechanisms. Overall, our hypothesis, that plants with a fragmented habitat (i.e., the IT population) lose phenotypic plasticity but acquire traits allowing better resistance to the climate where they became adapted, remains confirmed

Therapeutic sequences in patients with grade 1−2 neuroendocrine tumors (NET): an observational multicenter study from the ELIOS group

Purpose: Many different treatments are suggested by guidelines to treat grade 1−2 (G1−G2) neuroendocrine tumors (NET). However, a precise therapeutic algorithm has not yet been established. This study aims at identifying and comparing the main therapeutic sequences in G1−G2 NET. Methods: A retrospective observational Italian multicenter study was designed to collect data on therapeutic sequences in NET. Median progression-free survival (PFS) was compared between therapeutic sequences, as well as the number and grade of side effects and the rate of dose reduction/treatment discontinuation. Results: Among 1182 patients with neuroendocrine neoplasia included in the ELIOS database, 131 G1–G2 gastroenteropancreatic, lung and unknown primary NET, unresectable or persistent/relapsing after surgery, treated with ≥2 systemic treatments, were included. Four main therapeutic sequences were identified in 99 patients: (A) somatostatin analogs (SSA) standard dose to SSA high dose (n = 36), (B) SSA to everolimus (n = 31), (C) SSA to chemotherapy (n = 17), (D) SSA to peptide receptor radionuclide therapy (PRRT) (n = 15). Median PFS of the second-line treatment was not reached in sequence A, 33 months in sequence B, 20 months in sequence C, 30 months in sequence D (p = 0.16). Both total number and severity of side effects were significantly higher in sequences B and C than A and D (p = 0.04), as well as the rate of dose reduction/discontinuation (p = 0.03). Conclusions: SSA followed by SSA high dose, everolimus, chemotherapy or PRRT represent the main therapeutic sequences in G1−G2 NET. Median PFS was not significantly different between sequences. However, the sequences with SSA high dose or PRRT seem to be better tolerated than sequences with everolimus or chemotherapy

The degeneracy between star-formation parameters in dwarf galaxy simulations and the Mstar-Mhalo relation

We present results based on a set of N-Body/SPH simulations of isolated dwarf galaxies. The simulations take into account star formation, stellar feedback, radiative cooling and metal enrichment. The dark matter halo initially has a cusped profile, but, at least in these simulations, starting from idealised, spherically symmetric initial conditions, a natural conversion to a core is observed due to gas dynamics and stellar feedback. A degeneracy between the efficiency with which the interstellar medium absorbs energy feedback from supernovae and stellar winds on the one hand, and the density threshold for star formation on the other, is found. We performed a parameter survey to determine, with the aid of the observed kinematic and photometric scaling relations, which combinations of these two parameters produce simulated galaxies that are in agreement with the observations. With the implemented physics we are unable to reproduce the relation between the stellar mass and the halo mass as determined by Guo et al. (2010), however we do reproduce the slope of this relation.Comment: Accepted for publication in MNRAS | 12 pages, 8 figure