Strictly small representations and a reduction theorem for the unitary dual

First published in Representation Theory in Vol 5, 2001. Published by the American Mathematical Society.To any irreducible unitary representation X of a real reductive Lie group we associate in a canonical way, a Levi subgroup Gsu and a representation of this subgroup. Assuming a conjecture of the authors on the infinitesimal character of X, we show that X is cohomologically induced from a unitary representation of the subgroup Gsu. This subgroup is in some cases smaller than the subgroup Gu that the authors attached to X in earlier work. In those cases this provides a further reduction to the classification problem

Assignació de recursos en Diplotaxis erucoides (L.) DC

Seeds of Diplotaxis erucoides collected un the fields of the ETSEA of Lleida in spring of 1989 were sown in pots in Mars of 1990 after their conservation at lab temperature and humidity. To estimate the biomass: allocation between different organs during the plant life and to know the reproductive effort at the end of this one, we have regularly determined the dry weight of the following plant parts: a) roots, b) stems and leaves, c) flowers, and d) fruits of 20 plants in each analysis. With the results obtnined we can confirm the following observations: a) a high and positive correlation between the biomass of different parts, b) the biornass destined to reproduction represents a 33% of the total plant biomass, c) there is an increase of the reproductive effort with the size of the plant, d) the correlation caefficient between the number of flowers and the vegetative biomass is better than those observed beetween the reproductive and vegetative biomass, and e) there is a decrease of the vegetative growth and radicular system in the last stages of the plant cycle.Les llavors de Diplotaxis erucoides recollides en el camp de practiques de I'ETSEA Lleida durant la primavera de 1989 foren sembrades en testos al març de 1990 després de ser conservades en sec en condicions d'humitat i temperatura de laboratori. Per tal d'avaluar l'assignació de biomassa entre diferents compartiments al llarg del cicle de la planta i determinar l'esforç reproductiu al final del mateix es determina periòdicament mitjançant quatre anàlisis el pes sec dels diferents compartiments considerats -arrels, tiges i fulles, flors i fruits- d'un grup de vint plantes per anàlisi. Els resultats obtinguts ens permeten confirmar les observacions següents: a) existència de correlacions positives i elevades entre la biomassa dels diferents compartiments, b) la biomassa destinada a la reproducció representa un 33% de la biomassa total de la planta, c) es produeix un augment de l'esforç reproductiu amb la mida de la planta, d) el coeficient de correlació entre el nombre de flors i la biomassa vegetativa és sensiblement més alt que entre la biomassa reproductiva i la biomassa vegetativa i e) l'existència d'una disminució del creixement vegetatiu i del sistema radicular en les etapes finals del cicle de la planta.Las sernillas de Diplotaxis erucoides recogidas en el campo de prácticas de la ETSEA Lleida durante la primavera de 1989, fueron sembradas en macetas en el mes de marzo de 1990 previa conservación en seco en condiciones de humedad y temperatura de laboratono. Para evaluar la asignación de biomasa entre distintos com-partimentos durante el ciclo de la planta y determinar el esfuerzo reproductivo al final del misrno, se determinó periódicamente mediante cuatro análisis el peso seco de los distintos compartimentos considerados -raices, tallos y hojas, flores y frutos- de una muestra de veinte plantas por análisis. Los resultados obtenidos nos pemiten confirmar las observaciones siguientes: a) la existencia de correlaciones positivas y elevadas entre la biomasa de los diferentes compartimentos,b) la biomasa destinada a la reproducción representa un 33% del total de la biomasa de la planta, c) se produce un incremento positivo del esfuerzo reproductivo con el peso de la planta, d) el coeficiente de correlación entre el número de flores y la biomasa vegetativa es sensiblemente más alto que el de la biomasa reproductiva con la biomasa vegetativa y e) la existencia de una disminución en el ritmo de crecimiento vegetativo y del sistema radicular en las etapas finales del ciclo de la planta

Pyramidal Stochastic Graphlet Embedding for Document Pattern Classification

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordDocument pattern classification methods using graphs have received a lot of attention because of its robust representation paradigm and rich theoretical background. However, the way of preserving and the process for delineating documents with graphs introduce noise in the rendition of underlying data, which creates instability in the graph representation. To deal with such unreliability in representation, in this paper, we propose Pyramidal Stochastic Graphlet Embedding (PSGE). Given a graph representing a document pattern, our method first computes a graph pyramid by successively reducing the base graph. Once the graph pyramid is computed, we apply Stochastic Graphlet Embedding (SGE) for each level of the pyramid and combine their embedded representation to obtain a global delineation of the original graph. The consideration of pyramid of graphs rather than just a base graph extends the representational power of the graph embedding, which reduces the instability caused due to noise and distortion. When plugged with support vector machine, our proposed PSGE has outperformed the state-of-The-art results in recognition of handwritten words as well as graphical symbols.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainRamon y Cajal FellowshipCERCA Program/Generalitat de Cataluny

Hierarchical stochastic graphlet embedding for graph-based pattern recognition

This is the final version. Available on open access from Springer via the DOI in this recordDespite being very successful within the pattern recognition and machine learning community, graph-based methods are often unusable with many machine learning tools. This is because of the incompatibility of most of the mathematical operations in graph domain. Graph embedding has been proposed as a way to tackle these difficulties, which maps graphs to a vector space and makes the standard machine learning techniques applicable for them. However, it is well known that graph embedding techniques usually suffer from the loss of structural information. In this paper, given a graph, we consider its hierarchical structure for mapping it into a vector space. The hierarchical structure is constructed by topologically clustering the graph nodes, and considering each cluster as a node in the upper hierarchical level. Once this hierarchical structure of graph is constructed, we consider its various configurations of its parts, and use stochastic graphlet embedding (SGE) for mapping them into vector space. Broadly speaking, SGE produces a distribution of uniformly sampled low to high order graphlets as a way to embed graphs into the vector space. In what follows, the coarse-to-fine structure of a graph hierarchy and the statistics fetched through the distribution of low to high order stochastic graphlets complements each other and include important structural information with varied contexts. Altogether, these two techniques substantially cope with the usual information loss involved in graph embedding techniques, and it is not a surprise that we obtain more robust vector space embedding of graphs. This fact has been corroborated through a detailed experimental evaluation on various benchmark graph datasets, where we outperform the state-of-the-art methods.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainGeneralitat de Cataluny

Graph-Based Deep Learning for Graphics Classification

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordGraph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations and we show how they can be used in graphics recognition problems.European Union Horizon 2020FPUMinisterio de Educación, Cultura y Deporte, SpainRamon y Cajal FellowshipCERCA Program/Generalitat de Cataluny

Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordInformation Retrieval (IR) is the activity of obtaining information resources relevant to a questioned information. It usually retrieves a set of objects ranked according to the relevancy to the needed fact. In document analysis, information retrieval receives a lot of attention in terms of symbol and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where the state-of-The-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing relations between a set of objects is a structure where each node delineates an individual element and the similarity between them is represented as a weight on the connecting edge. In this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter scenario.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainFPUCERCA Programme/Generalitat de Cataluny

Evidence for power-law frequency dependence of intrinsic dielectric response in the CaCu3_{3}Ti4_{4}O12_{12}

We investigated the dielectric response of CaCu$_3$Ti$_4$O$_{12}$ (CCTO) thin films grown epitaxially on LaAlO$_3$ (001) substrates by Pulsed Laser Deposition (PLD). The dielectric response of the films was found to be strongly dominated by a power-law in frequency, typical of materials with localized hopping charge carriers, in contrast to the Debye-like response of the bulk material. The film conductivity decreases with annealing in oxygen, and it suggests that oxygen deficit is a cause of the relatively high film conductivity. With increase of the oxygen content, the room temperature frequency response of the CCTO thin films changes from the response indicating the presence of some relatively low conducting capacitive layers to purely power law, and then towards frequency independent response with a relative dielectric constant $\epsilon'\sim10^2$. The film conductance and dielectric response decrease upon decrease of the temperature with dielectric response being dominated by the power law frequency dependence. Below $\sim$80 K, the dielectric response of the films is frequency independent with $\epsilon'$ close to $10^2$. The results provide another piece of evidence for an extrinsic, Maxwell-Wagner type, origin of the colossal dielectric response of the bulk CCTO material, connected with electrical inhomogeneity of the bulk material.Comment: v4: RevTeX, two-column, 9 pages, 7 figures; title modified, minor content change in p.7, reference adde

Complex Tasks Force Hand Laterality and Technological Behaviour in Naturalistically Housed Chimpanzees: Inferences in Hominin Evolution

Clear hand laterality patterns in humans are widely accepted. However, humans only elicit a significant hand laterality pattern when performing complementary role differentiation (CRD) tasks. Meanwhile, hand laterality in chimpanzees is weaker and controversial. Here we have reevaluated our results on hand laterality in chimpanzees housed in naturalistic environments at Fundació Mona (Spain) and Chimfunshi Wild Orphanage (Zambia). Our results show that the difference between hand laterality in humans and chimpanzees is not as great as once thought. Furthermore, we found a link between hand laterality and task complexity and also an even more interesting connection: CRD tasks elicited not only the hand laterality but also the use of tools. This paper aims to turn attention to the importance of this threefold connection in human evolution: the link between CRD tasks, hand laterality, and tool use, which has important evolutionary implications that may explain the development of complex behaviour in early hominins