How general is a female mating preference for clustered males in lekking species? a meta-analysis

A principal hypothesis for the evolution of leks (rare and intensely competitive territorial aggregations) is that leks result from females preferring to mate with clustered males. This hypothesis predicts more female visits and higher mating success per male on larger leks. Evidence for and against this hypothesis has been presented by different studies, primarily of individual populations, but its generality has not yet been formally investigated. We took a meta-analytical approach towards formally examining the generality of such a female bias in lekking species. Using available published data and using female visits as an index of female mating bias, we estimated the shape of the relationship between lek size and total female visits to a lek, female visits per lekking male and, where available, per capita male mating success. Individual analyses showed that female visits generally increased with lek size across the majority of taxa surveyed; the meta-analysis indicated that this relationship with lek size was disproportionately positive. The findings from analysing per capita female visits were mixed, with an increase with lek size detected in half of the species, which were, however, widely distributed taxonomically. Taken together, these findings suggest that a female bias for clustered males may be a general process across lekking species. Nevertheless, the substantial variation seen in these relationships implies that other processes are also important. Analyses of per capita copulation success suggested that, more generally, increased per capita mating benefits may be an important selective factor in lek maintenance.

Subject independent human action recognition using spatio-depth information and meta-cognitive RBF network

In this paper, we present a machine learning approach for subject independent human action recognition using depth camera, emphasizing the importance of depth in recognition of actions. The proposed approach uses the flow information of all 3 dimensions to classify an action. In our approach, we have obtained the 2-D optical flow and used it along with the depth image to obtain the depth flow (Z motion vectors). The obtained flow captures the dynamics of the actions in space time. Feature vectors are obtained by averaging the 3-D motion over a grid laid over the silhouette in a hierarchical fashion. These hierarchical fine to coarse windows capture the motion dynamics of the object at various scales. The extracted features are used to train a Meta-cognitive Radial Basis Function Network (McRBFN) that uses a Projection Based Learning (PBL) algorithm, referred to as PBL-McRBFN, henceforth. PBL-McRBFN begins with zero hidden neurons and builds the network based on the best human learning strategy, namely, self-regulated learning in a meta-cognitive environment. When a sample is used for learning, PBLMcRBFN uses the sample overlapping conditions, and a projection based learning algorithm to estimate the parameters of the network. The performance of PBL-McRBFN is compared to that of a Support Vector Machine (SVM) and Extreme Learning Machine (ELM) classifiers with representation of every person and action in the training and testing datasets. Performance study shows that PBL-McRBFN outperforms these classifiers in recognizing actions in 3-D. Further, a subject-independent study is conducted by leave-one-subject-out strategy and its generalization performance is tested. It is observed from the subject-independent study that McRBFN is capable of generalizing actions accurately. The performance of the proposed approach is benchmarked with Video Analytics Lab (VAL) dataset and Berkeley Multimodal Human Action Database (MHAD). (C) 2013 Elsevier Ltd. All rights reserved.

Study of structures, energies and vibrational frequencies of (O-2)(n)(+) (n=2-5) clusters by GGA and meta-GGA density functional methods

Using Generalized Gradient Approximation (GGA) and meta-GGA density functional methods, structures, binding energies and harmonic vibrational frequencies for the clusters O-4(+), O-6(+), O-8(+) and O-10(+) have been calculated. The stable structures of O-4(+), O-6(+), O-8(+) and O-10(+) have point groups D-2h, D-3h, D-4h, and D-5h optimized on the quartet, sextet, octet and dectet potential energy surfaces, respectively. Rectangular (D-2h) O-4(+) has been found to be more stable compared to trans-planar (C-2h) on the quartet potential energy surface. Cyclic structure (D-3h) of CA cluster ion has been calculated to be more stable than other structures. Binding energy (B.E.) of the cyclic O-6(+) is in good agreement with experimental measurement. The zero-point corrected B.E. of O-8(+) with D4h symmetry on the octet potential energy surface and zero-point corrected B.E. of O-10(+) with D-5h symmetry on the dectet potential energy surface are also in good agreement with experimental values. The B.E. value for O-4(+) is close to the experimental value when single point energy is calculated by Brueckner coupled-cluster method, BD(T). (C) 2014 Elsevier B.V. All rights reserved.

Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

Action Recognition from Motion Capture Data using Meta-cognitive RBF Network Classifier

Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Dos asambleas sinodales y una misma meta : estudiar los desafíos pastorales sobre la familia en el contexto de la evangelización

Resumen: Para toda la Iglesia, el presente año se caracteriza por la preparación de un Sínodo de los obispos de tipo extraordinario que preparará uno ordinario para el año próximo. Esta novedad metodológica ayuda a repasar el mencionado instituto teológico que, gracias al último Concilio Ecuménico, hace cincuenta años reviste el carácter de permanente. Los temas a tratar persiguen un mismo fin: estudiar los desafíos pastorales sobre la familia en el contexto de la evangelización. Propuesto como tema, también es continuidad de un método pontificio que solicita caminar en conjunto con el colegio de los obispos y por ende con todo el Pueblo de Dios. Finalmente se hace una propuesta que ayude a mejorar la terminología para hablar de matrimonio y familia en orden a un mejor acompañamiento canónico y pastoral de todas las realidades.

Primeiro quadrimestre de 2009, cumprimento de meta fiscal ...

Conteúdo: Cumprimento da meta fiscal no primeiro quadrimestre -- Evolução dos resultados no setor público -- Evolução da dívida pública federal em mercado no quadrimestre -- Receitas e despesas até abril -- Política fiscal : despesas com investimentos -- Segunda avaliação orçamentária -- Cenário macroeconômico e parâmetros fiscais -- Metas quadrimestrais em 2009 -- Arrecadação das receitas administradas no primeiro quadrimestre de 2009 -- Arrecadação das receitas não administradas no primeiro quadrimestre de 2009 -- Receita prevista para o exercício de 2009.

Optimización dinámica con información híbrida: dos casos prácticos

[ES] La programación dinámica es un método de optimización de sistemas o de su representación matemática, donde se opera por fases, es decir, las decisiones se toman en forma secuencial.

Redefinição da meta primária de junho de 2013 : relatório de avaliação de receitas e despesas do 3º bimestre : Decreto nº 8062 (29/07) : Portaria MP 267 (30/07)

Consultoria de Orçamento e Fiscalização Financeira. Núcleo de Assuntos Econômico-Fiscais

Observações sobre PLº 1, de 2013 - CN : alteração da LDO para 2013 : esforço primário da União meta de Estados e Municípios

Consultoria de Orçamento e Fiscalização Financeira. Núcleo de Assuntos Econômico-Fiscais

Viabilidade do Financiamento do PNE : (meta 20) : (abordagem preliminar)

Este estudo como objetivo chamar a atenção para as dificuldades que a União, os Estados e os Municípios terão para cumprir a Meta 11 20 do PNE, qual seja: a destinação de montante de recursos públicos equivalente a 10% do PIB até 2024.

Catechol 2,3-dioxygenase-assisted cleavage of aromatics by “anaerobic” termite gut spirochetes and genomic evidence of a complete meta-pathway

The termite hindgut microbial ecosystem functions like a miniature lignocellulose-metabolizing natural bioreactor, has significant implications to nutrient cycling in the terrestrial environment, and represents an array of microbial metabolic diversity. Deciphering the intricacies of this microbial community to obtain as complete a picture as possible of how it functions as a whole, requires a combination of various traditional and cutting-edge bioinformatic, molecular, physiological, and culturing approaches. Isolates from this ecosystem, including Treponema primitia str. ZAS-1 and ZAS-2 as well as T. azotonutricium str. ZAS-9, have been significant resources for better understanding the termite system. While not all functions predicted by the genomes of these three isolates are demonstrated in vitro, these isolates do have the capacity for several metabolisms unique to spirochetes and critical to the termite system’s reliance upon lignocellulose. In this thesis, work culturing, enriching for, and isolating diverse microorganisms from the termite hindgut is discussed. Additionally, strategies of members of the termite hindgut microbial community to defend against O₂-stress and to generate acetate, the “biofuel” of the termite system, are proposed. In particular, catechol 2,3-dioxygenase and other meta-cleavage catabolic pathway genes are described in the “anaerobic” termite hindgut spirochetes T. primitia str. ZAS-1 and ZAS-2, and the first evidence for aromatic ring cleavage in the phylum (division) Spirochetes is also presented. These results suggest that the potential for O₂-dependent, yet nonrespiratory, metabolisms of plant-derived aromatics should be re-evaluated in termite hindgut communities. Potential future work is also illustrated.