SIZE AS A LINE OF LEAST RESISTANCE II: DIRECT SELECTION ON SIZE OR CORRELATED RESPONSE DUE TO CONSTRAINTS?

Evolutionary change in New World Monkey (NWM) skulls occurred primarily along the line of least resistance defined by size (including allometric) variation (g(max)). Although the direction of evolution was aligned with this axis, it was not clear whether this macroevolutionary pattern results from the conservation of within population genetic covariance patterns (long-term constraint) or long-term selection along a size dimension, or whether both, constraints and selection, were inextricably involved. Furthermore, G-matrix stability can also be a consequence of selection, which implies that both, constraints embodied in g(max) and evolutionary changes observed on the trait averages, would be influenced by selection Here, we describe a combination of approaches that allows one to test whether any particular instance of size evolution is a correlated by-product due to constraints (g(max)) or is due to direct selection on size and apply it to NWM lineages as a case study. The approach is based on comparing the direction and amount of evolutionary change produced by two different simulated sets of net-selection gradients (beta), a size (isometric and allometric size) and a nonsize set. Using this approach it is possible to distinguish between the two hypotheses (indirect size evolution due to constraints or direct selection on size), because although both may produce an evolutionary response aligned with g(max), the amount of change produced by random selection operating through the variance/covariance patterns (constraints hypothesis) will be much smaller than that produced by selection on size (selection hypothesis). Furthermore, the alignment of simulated evolutionary changes with g(max) when selection is not on size is not as tight as when selection is actually on size, allowing a statistical test of whether a particular observed case of evolution along the line of least resistance is the result of selection along it or not. Also, with matrix diagonalization (principal components [PC]) it is possible to calculate directly the net-selection gradient on size alone (first PC [PC1]) by dividing the amount of phenotypic difference between any two populations by the amount of variation in PC1, which allows one to benchmark whether selection was on size or not

Diet and food selection by small mammals in an old-growth Atlantic forest of south-eastern Brazil

Here we describe the stomach contents of nine small mammal species (seven rodents and two didelphid marsupials) co-occurring in an old-growth Atlantic forest area. For four terrestrial rodents, we also compared the importance of arthropods in the diet and the selection of arthropod groups by comparing consumption with availability. Small mammals and arthropods were sampled in a 36-ha grid containing 25 sampling stations spaced every 150 m, and 47 stomach contents were analysed. While plant matter was the predominant item in the stomach contents of two rodents (Oligoryzomys nigripes and Rhipidomys mastacalis), four species presented arthropods as the main food item (the rodents Brucepattersonius soricinus and Oxymycterus dasytrichus, and the marsupials Monodelphis n. sp. and Marmosops incanus) and three consumed more plant matter than arthropods, but had significant amounts of both items (the rodents Delomys sublineatus, Euryoryzomys russatus and Thaptomys nigrita). Our results suggest that differences in diet, coupled with differences in habit and microhabitat preferences, are important factors allowing resource partition among species of the diverse group of co-occurring terrestrial small mammals in Atlantic forest areas. Moreover, arthropods were not preyed opportunistically by any of the four terrestrial rodents, since consumption was not proportional to availability. Rather, selection or rejection of arthropod groups seems to be determined by aspects other than availability, such as nutritional value, easiness of capture and handling or palatability.

SEASONAL MICROHABITAT SELECTION BY TERRESTRIAL RODENTS IN AN OLD-GROWTH ATLANTIC FOREST

We tested the hypothesis that microhabitat variables, abundance of terrestrial rodents, and microhabitat selection patterns of terrestrial rodents vary between the cool-dry and warm-wet season in the Atlantic forest of Brazil. We selected variables associated with ecological factors potentially important to terrestrial rodents (physical structure of litter and woody debris, and arthropod availability) and established 25 small, independent sampling units covering 36 ha of a homogenous, mature Atlantic forest patch. Litter humidity and height, amount of small woody debris, arthropod availability, and terrestrial rodent abundance increased, whereas the quantity of large woody debris decreased in the warm-wet season. Greater spatial segregation among terrestrial rodents also was observed in this season, especially between morphologically similar species. The distribution of 3 of the 4 most common terrestrial rodents was influenced by microhabitat variables in at least I of the seasons, and these species also differed in their pattern of microhabitat selection between seasons. In general, the amount of small woody debris and litter humidity were more important for the microscale distribution of terrestrial rodents in the cool-dry season, whereas in the mild warm-wet season species distributions were associated with food availability or were not clearly influenced by the measured variables. The patterns of microhabitat selection by 3 common terrestrial rodents, which were associated with features that characterize old-growth forest, may be responsible for their vulnerability to forest fragmentation.

Mitochondrial sequence data and Dipsacales phylogeny: Mixed models, partitioned Bayesian analyses, and model selection

Phylogenetic analyses of chloroplast DNA sequences, morphology, and combined data have provided consistent support for many of the major branches within the angiosperm, clade Dipsacales. Here we use sequences from three mitochondrial loci to test the existing broad scale phylogeny and in an attempt to resolve several relationships that have remained uncertain. Parsimony, maximum likelihood, and Bayesian analyses of a combined mitochondrial data set recover trees broadly consistent with previous studies, although resolution and support are lower than in the largest chloroplast analyses. Combining chloroplast and mitochondrial data results in a generally well-resolved and very strongly supported topology but the previously recognized problem areas remain. To investigate why these relationships have been difficult to resolve we conducted a series of experiments using different data partitions and heterogeneous substitution models. Usually more complex modeling schemes are favored regardless of the partitions recognized but model choice had little effect on topology or support values. In contrast there are consistent but weakly supported differences in the topologies recovered from coding and non-coding matrices. These conflicts directly correspond to relationships that were poorly resolved in analyses of the full combined chloroplast-mitochondrial data set. We suggest incongruent signal has contributed to our inability to confidently resolve these problem areas. (c) 2007 Elsevier Inc. All rights reserved.

Morphine treatment during pregnancy modulates behavioral selection in lactating rats

Previous studies have demonstrated that treatment of postpartum female rats with morphine inhibits maternal behavior and stimulates foraging. Exposure to drugs of abuse may result in a progressive enhancement of their reinforcing effects. Puerperal treatment with morphine leads to reverse tolerance to this drug. The present study investigated whether repeated morphine treatment during late pregnancy may influence the effects of different morphine dosages on behavioral selection in lactating rats. Females were simultaneously exposed to pups and insects, and the choice between taking care of the pups and hunting insects was observed. Female Wistar rats were treated with morphine (3.5 mg/kg/day, subcutaneous [s.c.]) or saline for 5 days beginning on pregnancy day 17. On day 5 of lactation, animals were acutely challenged with morphine (0.5, 1.0, or 1.5 mg/kg, s.c.; MM0.5, MM1.0, and MM1.5 groups, respectively) or saline (MS group) and tested for predatory hunting and maternal behavior. Control groups were pretreated with saline and challenged with morphine (SM0.5, SM1.0, and SM1.5 groups) or saline (SS group). Animals treated with morphine during late pregnancy and acutely challenged with 1.0 mg/kg morphine (MM1.0 group) exhibited significantly decreased maternal behavior and enhanced hunting. This effect was not evident with the 0.5 mg/kg dose. The 1.5 mg/kg morphine dose decreased maternal behavior and increased hunting in both the MM1.5 group and in animals challenged with morphine after previous saline treatment (SM1.5 group). These results provide evidence of plasticity of the opioidergic role in behavioral selection during lactation. (C) 2010 Elsevier Inc. All rights reserved.

Nutrient Selection in the Absence of Taste Receptor Signaling

When allowed to choose between different macronutrients, most animals display a strong attraction toward carbohydrates compared with proteins. It remains uncertain, however, whether this food selection pattern depends primarily on the sensory properties intrinsic to each nutrient or, alternatively, metabolic signals can act independently of the hedonic value of sweetness to stimulate elevated sugar intake. Here we show that Trpm5(-/-) mice, which lack the cellular mechanisms required for sweet and several forms of L-amino acid taste transduction, develop a robust preference for D-glucose compared with isocaloric L-serine independently of the perception of sweetness. Moreover, a close relationship was found between glucose oxidation and taste-independent nutrient intake levels, with animals increasing intake as a function of glucose oxidation rates. Furthermore, microdialysis measurements revealed nutrient-specific dopaminergic responses in accumbens and dorsal striatum during intragastric infusions of glucose or serine. Specifically, intragastric infusions of glucose induced significantly higher levels of dopamine release compared with isocaloric serine in both ventral and dorsal striatum. Intragastric stimulation of dopamine release seemed to depend on glucose utilization, because administration of an anti-metabolic glucose analog resulted in lower dopamine levels in striatum, an effect that was reversed by intravenous glucose infusions. Together, our findings suggest that carbohydrate-specific preferences can develop independently of taste quality or caloric load, an effect associated with the ability of a given nutrient to regulate glucose metabolism and stimulate brain dopamine centers.

Selection of an ivermectin-resistant strain of Rhipicephalus microplus (Acari: Ixodidae) in Brazil

Resistance to ivermectin (IVM) in field Populations of Rhipicephalus microplus of Brazil has been observed since 2001 In this work, four selection methods (infestations with: (I) IVM-treated larvae, (2) larvae from IVM-treated adult female ticks, (3) larvae from IVM-treated adult female ticks on an IVM-treated host, and (4) larvae obtained from W-treated females that produced eggs with a high eclosion rate) were used oil a field population with an initial ivermectin (IVM) resistance ratio at LC50 (RR50) of 1 37 with the objective to obtain experimentally a highly-resistant strain After ten generations, using these methods combined, the final RR50 was 8 06 This work shows for the first time that it was possible to increase IVM resistance in R. microplus in laboratory conditions. The establishment of a drug resistant R microplus strain is a fundamental first step for further research into the mechanisms of ivermectin-resistance in R. microplus and potentially methods to control this resistance (C) 2009 Elsevier B V All rights reserved

An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

Partitions selection strategy for set of clustering solutions

Clustering is a difficult task: there is no single cluster definition and the data can have more than one underlying structure. Pareto-based multi-objective genetic algorithms (e.g., MOCK Multi-Objective Clustering with automatic K-determination and MOCLE-Multi-Objective Clustering Ensemble) were proposed to tackle these problems. However, the output of such algorithms can often contains a high number of partitions, becoming difficult for an expert to manually analyze all of them. In order to deal with this problem, we present two selection strategies, which are based on the corrected Rand, to choose a subset of solutions. To test them, they are applied to the set of solutions produced by MOCK and MOCLE in the context of several datasets. The study was also extended to select a reduced set of partitions from the initial population of MOCLE. These analysis show that both versions of selection strategy proposed are very effective. They can significantly reduce the number of solutions and, at the same time, keep the quality and the diversity of the partitions in the original set of solutions. (C) 2010 Elsevier B.V. All rights reserved.

Towards improving cluster-based feature selection with a simplified silhouette filter

This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.

The curve selection lemma and the Morse-Sard theorem

We use an inequality due to Bochnak and Lojasiewicz, which follows from the Curve Selection Lemma of real algebraic geometry in order to prove that, given a C(r) function f : U subset of R(m) -> R, we have lim(y -> xy is an element of crit(f)) vertical bar f(y) - f(x)vertical bar/vertical bar y - x vertical bar(r) = 0, for all x is an element of crit(f)` boolean AND U, where crit( f) = {x is an element of U vertical bar df ( x) = 0}. This shows that the so-called Morse decomposition of the critical set, used in the classical proof of the Morse-Sard theorem, is not necessary: the conclusion of the Morse decomposition lemma holds for the whole critical set. We use this result to give a simple proof of the classical Morse-Sard theorem ( with sharp differentiability assumptions).

A unified view on lifetime distributions arising from selection mechanisms

In this paper, we formulate a flexible density function from the selection mechanism viewpoint (see, for example, Bayarri and DeGroot (1992) and Arellano-Valle et al. (2006)) which possesses nice biological and physical interpretations. The new density function contains as special cases many models that have been proposed recently in the literature. In constructing this model, we assume that the number of competing causes of the event of interest has a general discrete distribution characterized by its probability generating function. This function has an important role in the selection procedure as well as in computing the conditional personal cure rate. Finally, we illustrate how various models can be deduced as special cases of the proposed model. (C) 2011 Elsevier B.V. All rights reserved.

Chaotic phase synchronization and desynchronization in an oscillator network for object selection

Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial Visual systems. Chaotic phase synchronization takes place in cases involving almost identical dynamical systems and it means that the phase difference between the systems is kept bounded over the time, while their amplitudes remain chaotic and may be uncorrelated. Instead of complete synchronization, phase synchronization is believed to be a mechanism for neural integration in brain. In this paper, an object selection model is proposed. Oscillators in the network representing the salient object in a given scene are phase synchronized, while no phase synchronization occurs for background objects. In this way, the salient object can be extracted. In this model, a shift mechanism is also introduced to change attention from one object to another. Computer simulations show that the model produces some results similar to those observed in natural vision systems.

A network of integrate and fire neurons for visual selection

Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.

U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.