Food Competition in a Semi-Free-Ranging Cebus apella Group

The competitive regime faced by individuals is fundamental to modelling the evolution of social organization. In this paper, we assess the relative importance of contest and scramble food competition on the social dynamics of a provisioned semi-free-ranging Cebus apella group (n=18). Individuals competed directly for provisioned and clumped foods. Effects of indirect competition were apparent with individuals foraging in different areas and with increased group dispersion during periods of low food abundance. We suggest that both forms of competition can act simultaneously and to some extent synergistically in their influence on social dynamics; the combination of social and ecological opportunities for competition and how those opportunities are exploited both influence the nature of the relationships within social groups of primates and underlie the evolved social structure. Copyright (c) 2008 S. Karger AG, Basel

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Metals and semi-metals in street soils of So Paulo city, Brazil

So Paulo is the largest city in Brazil and South America with about 20 million inhabitants in the metropolitan area, more than nine million motor vehicles and intense industrial activity, which are responsible for increasing pollution in the region. Nevertheless, little is known concerning metal and semi-metal content in the soils of this metropolitan region. This type of information could be extremely useful as a fingerprint of environmental pollution. The present study determined the elements As, Ba, Co, Cr, Sb, and Zn concentrations in soils adjacent to avenues of highly dense traffic in So Paulo city to assess their levels and possible sources. The analytical technique employed was Instrumental neutron activation analysis. The results showed, except for Co, concentration levels higher than the reference values for soils of So Paulo, according to the Environmental Protection Agency of the State of So Paulo guidelines. When compared to similar studies in other cities around the world, So Paulo soils presented higher levels, probably due to its high density traffic and industrial activity. The concentrations obtained for As and Cr indicate anthropogenic origin. The high levels of the traffic-related elements Ba, Sb, and Zn in soils nearby high density traffic avenues indicate they may originate from vehicular exhausts.

Shearless transport barriers in magnetically confined plasmas

Shearless transport barriers appear in confined plasmas due to non-monotonic radial profiles and cause localized reduction of transport even after they have been broken. In this paper we summarize our recent theoretical and experimental research on shearless transport barriers in plasmas confined in toroidal devices. In particular, we discuss shearless barriers in Lagrangian magnetic field line transport caused by non-monotonic safety factor profiles. We also discuss evidence of particle transport barriers found in the TCABR Tokamak (University of Sao Paulo) and the Texas Helimak (University of Texas at Austin) in biased discharges with non-monotonic plasma flows.

On the Milnor fibre and L numbers of semi-weighted homogeneous arrangements

Inthispaperwestudygermsofpolynomialsformedbytheproductofsemi-weighted homogeneous polynomials of the same type, which we call semi-weighted homogeneous arrangements. It is shown how the L numbers of such polynomials are computed using only their weights and degree of homogeneity. A key point of the main theorem is to find the number called polar ratio of this polynomial class. An important consequence is the description of the Euler characteristic of the Milnor fibre of such arrangements only depending on their weights and degree of homogeneity. The constancy of the L numbers in families formed by such arrangements is shown, with the deformed terms having weighted degree greater than the weighted degree of the initial germ. Moreover, using the results of Massey applied to families of function germs, we obtain the constancy of the homology of the Milnor fibre in this family of semi-weighted homogeneous arrangements.

Semi-supervised learning guided by the modularity measure in complex networks

Semi-supervised learning techniques have gained increasing attention in the machine learning community, as a result of two main factors: (1) the available data is exponentially increasing; (2) the task of data labeling is cumbersome and expensive, involving human experts in the process. In this paper, we propose a network-based semi-supervised learning method inspired by the modularity greedy algorithm, which was originally applied for unsupervised learning. Changes have been made in the process of modularity maximization in a way to adapt the model to propagate labels throughout the network. Furthermore, a network reduction technique is introduced, as well as an extensive analysis of its impact on the network. Computer simulations are performed for artificial and real-world databases, providing a numerical quantitative basis for the performance of the proposed method.

Seasonal dynamics of cyanobacteria in a eutrophic reservoir (Arcoverde) in a semi-arid region of Brazil

Environmental conditions favor the predominance of dense populations of cyanobacteria in reservoirs in northeastern Brazil. The aim of this study was to understand cyanobacterial population dynamics in the rainy and dry seasons at two depths in the Arcoverde reservoir. Microalgae and cyanobacteria samples were collected during 24 hours with intervals of 4 hours (nycthemeral) at sub-surface and 10 m using a van Dorn bottle and a determined biomass. Physical and chemical variables were obtained and the data were analyzed using the principal component analysis (PCA). No nycthemeral variations in the taxonomic composition or distribution of the populations of cyanobacteria were found between the different times of day in either the rainy or dry season. In both seasons, the greatest biomass of the phytoplankton community was made up of cyanobacteria at two depths and all times of the day. Cylindrospermopsis raciborskii (Woloszynska) Seenayya et Subba Raju was dominant at all times of the day on both the surface and at the bottom. In the rainy season, the differences in cyanobacterial biomass between the surface and bottom were less significant than in the dry season. The differences in cyanobacterial biomass between surface and bottom were less pronounced than those found in the dry season. We concluded that a) physical variables better explain the alterations of species in the phytoplankton community in an environment dominated by cyanobacteria throughout the year; b) seasonal climatic factors associated to periods of stratification and de-stratification are important for alterations in the community and variations in biomass and, c) the turbidity caused by rainfall favored the emergence and establishment of other cyanobacteria, especially Planktothrix agardhii (Gomont) Anagnostidis & Komarek.

GREB1 tissue expression is associated with organ-confined prostate cancer

Objective: By reason of its heterogeneous behavior, it is difficult to determine the prognosis of many prostate cancer cases. Patients with the same clinicopathologic conditions may present varying clinical findings and rates of progression. We determined the role of new genes as potential molecular markers for prostate cancer prognosis. Materials and methods: We performed a microarray analysis of two pools of patients with prostate cancer divided according to their clinicopathologic characteristics. After that, we validated these results by testing the genes with most different expressions between the two pools using the quantitative real time polymerase chain reaction method. We analyzed gene expression in 33 patients with localized prostate cancer according to prostate specific antigen (PSA), pathologic stage, Gleason score, and biochemical recurrence. For statistical analysis we used the Mann-Whitney Test. Results: The microarray analysis revealed that 4,147 genes presented a different expression between the two pools. Among them, 3 genes, TMEFF2, GREB1, and THIL,, were at least 13-times overexpressed, and 1 gene, IGH3, which was at least 5times under-expressed in pool 1 (good prognosis) compared with pool 2 (bad prognosis), were selected for analysis. After the validation tests, GREB1 was significantly more overexpressed among patients with stage T2 compared with T3 (P = 0.020). The expressions of other 3 genes did not present significant differences according to the clinicopatholoOcal variables. Conclusions: Tissue expression of GREB1 is associated with organ-confined prostate cancer and may constitute a gene associated with a favorable prognosis. (C) 2012 Elsevier Inc. All rights reserved.

A generalized finite element method with global-local enrichment functions for confined plasticity problems

The main feature of partition of unity methods such as the generalized or extended finite element method is their ability of utilizing a priori knowledge about the solution of a problem in the form of enrichment functions. However, analytical derivation of enrichment functions with good approximation properties is mostly limited to two-dimensional linear problems. This paper presents a procedure to numerically generate proper enrichment functions for three-dimensional problems with confined plasticity where plastic evolution is gradual. This procedure involves the solution of boundary value problems around local regions exhibiting nonlinear behavior and the enrichment of the global solution space with the local solutions through the partition of unity method framework. This approach can produce accurate nonlinear solutions with a reduced computational cost compared to standard finite element methods since computationally intensive nonlinear iterations can be performed on coarse global meshes after the creation of enrichment functions properly describing localized nonlinear behavior. Several three-dimensional nonlinear problems based on the rate-independent J (2) plasticity theory with isotropic hardening are solved using the proposed procedure to demonstrate its robustness, accuracy and computational efficiency.

Bioclimatic characterization of outdoor and confined systems for pregnant sows

Pregnant sows confinement systems were created in order to maximize the productivity, however there are problems concerning the animal welfare. The aim of this research was to evaluate pregnant sows in outdoors and in confinement systems in relation to the thermal environment and physiological animal responses. The experiment was conducted in a commercial farm in Monte Mor city, Sao Paulo, Brazil. The physiological evaluation was performed by recording physiological variables, such as respiratory frequency and skin temperature. Furthermore, variables like dry bulb temperature, wet bulb temperature, and black globe temperature were also evaluated to characterize the ambient by means of enthalpy and black globe humidity index. In each treatment six animals were evaluated. The experimental design was completely randomized in a split-plot version whose averages were compared by the Tukey test. The findings of the experiment revealed higher values for all the bioclimatic variables in the confined treatment. Hence, the outdoor system provided better thermal conditioning for pigs, resulting in a lower heat stress.

Experimental study on vortex-induced motions of a semi-submersible platform with four square columns, Part I: Effects of current incidence angle and hull appendages

An experimental study on Vortex-Induced Motion (VIM) of the semi-submersible platform concept with four square columns is presented. Model tests were carried out to check the influence of different headings and hull appendages (riser supports located at the pontoons; fairleads and the mooring stretches located vertically at the external column faces; and hard pipes located vertically at the internal column faces). The results comprise in-line, transverse and yaw motions, as well as combined motions in the XY plane, drag and lift forces and spectral analysis. The main results showed that VIM in the transverse direction occurred in a range of reduced velocity 4.0 up to 14.0 with amplitude peaks around reduced velocities around 7.0 and 8.0. The largest transverse amplitudes obtained were around 40% of the column width for 30 degrees and 45 degrees incidences. Another important result observed was a considerable yaw motion oscillation, in which a synchronization region could be identified as a resonance phenomenon. The largest yaw motions were verified for the 0 degrees incidence and the maxima amplitudes around 4.5 degrees. The hull appendages located at columns had the greatest influence on the VIM response of the semi-submersible. (C) 2012 Elsevier Ltd. All rights reserved.

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Soil carbon balance in a tropical grassland: Estimation of soil respiration and its partitioning using a semi-empirical model

In savannah and tropical grasslands, which account for 60% of grasslands worldwide, a large share of ecosystem carbon is located below ground due to high root:shoot ratios. Temporal variations in soil CO2 efflux (R-S) were investigated in a grassland of coastal Congo over two years. The objectives were (1) to identify the main factors controlling seasonal variations in R-S and (2) to develop a semi-empirical model describing R-S and including a heterotrophic component (R-H) and an autotrophic component (R-A). Plant above-ground activity was found to exert strong control over soil respiration since 71% of seasonal R-S variability was explained by the quantity of photosynthetically active radiation absorbed (APAR) by the grass canopy. We tested an additive model including a parameter enabling R-S partitioning into R-A and R-H. Assumptions underlying this model were that R-A mainly depended on the amount of photosynthates allocated below ground and that microbial and root activity was mostly controlled by soil temperature and soil moisture. The model provided a reasonably good prediction of seasonal variations in R-S (R-2 = 0.85) which varied between 5.4 mu mol m(-2) s(-1) in the wet season and 0.9 mu mol m(-2) s(-1) at the end of the dry season. The model was subsequently used to obtain annual estimates of R-S, R-A and R-H. In accordance with results reported for other tropical grasslands, we estimated that R-H accounted for 44% of R-S, which represented a flux similar to the amount of carbon brought annually to the soil from below-ground litter production. Overall, this study opens up prospects for simulating the carbon budget of tropical grasslands on a large scale using remotely sensed data. (C) 2012 Elsevier B.V. All rights reserved.

Detailed H-1 and C-13 NMR structural assignment and relative stereochemistry determination for three new and one known semi-synthetic sesquiterpene lactones

In this work is described a complete H-1 and C-13 NMR analysis for a group of four sesquiterpene lactones, three previously unknown. The unequivocal assignments were achieved by H-1 NMR, C-13{H-1} NMR, gCOSY. gHMQC, gHMBC and NOESY experiments and no ambiguities were left behind. All hydrogen coupling constants were measured, clarifying all hydrogen signals multiplicities. (C) 2011 Elsevier B.V. All rights reserved.