Series representations of the remainders in the expansions for certain functions with applications

We present a summary of the series representations of the remainders in the expansions in ascending powers of t of 2/(et+1)2/(et+1) , sech t and coth t and establish simple bounds for these remainders when t>0t>0 . Several applications of these expansions are given which enable us to deduce some inequalities and completely monotonic functions associated with the ratio of two gamma functions. In addition, we derive a (presumably new) quadratic recurrence relation for the Bernoulli numbers Bn.

Continuum tensor network field states, path integral representations and spatial symmetries

A natural way to generalize tensor network variational classes to quantum field systems is via a continuous tensor contraction. This approach is first illustrated for the class of quantum field states known as continuous matrix-product states (cMPS). As a simple example of the path-integral representation we show that the state of a dynamically evolving quantum field admits a natural representation as a cMPS. A completeness argument is also provided that shows that all states in Fock space admit a cMPS representation when the number of variational parameters tends to infinity. Beyond this, we obtain a well-behaved field limit of projected entangled-pair states (PEPS) in two dimensions that provide an abstract class of quantum field states with natural symmetries. We demonstrate how symmetries of the physical field state are encoded within the dynamics of an auxiliary field system of one dimension less. In particular, the imposition of Euclidean symmetries on the physical system requires that the auxiliary system involved in the class' definition must be Lorentz-invariant. The physical field states automatically inherit entropy area laws from the PEPS class, and are fully described by the dissipative dynamics of a lower dimensional virtual field system. Our results lie at the intersection many-body physics, quantum field theory and quantum information theory, and facilitate future exchanges of ideas and insights between these disciplines.

The Real-Quaternionic Indicator of Irreducible Self-Conjugate Representations of Real Reductive Algebraic Groups and A Comment on the Local Langlands Correspondence of GL(2, F )

The real-quaternionic indicator, also called the $\delta$ indicator, indicates if a self-conjugate representation is of real or quaternionic type. It is closely related to the Frobenius-Schur indicator, which we call the $\varepsilon$ indicator. The Frobenius-Schur indicator $\varepsilon(\pi)$ is known to be given by a particular value of the central character. We would like a similar result for the $\delta$ indicator. When $G$ is compact, $\delta(\pi)$ and $\varepsilon(\pi)$ coincide. In general, they are not necessarily the same. In this thesis, we will give a relation between the two indicators when $G$ is a real reductive algebraic group. This relation also leads to a formula for $\delta(\pi)$ in terms of the central character. For the second part, we consider the construction of the local Langlands correspondence of $GL(2,F)$ when $F$ is a non-Archimedean local field with odd residual characteristics. By re-examining the construction, we provide new proofs to some important properties of the correspondence. Namely, the construction is independent of the choice of additive character in the theta correspondence.

Neural representations of social and non-social uncertainty in human decision making

The social landscape is filled with an intricate web of species-specific desired objects and course of actions. Humans are highly social animals and, as they navigate this landscape, they need to produce adapted decision-making behaviour. Traditionally social and non-social neural mechanisms affecting choice have been investigated using different approaches. Recently, in an effort to unite these findings, two main theories have been proposed to explain how the brain might encode social and non-social motivational decision-making: the extended common currency and the social valuation specific schema (Ruff & Fehr 2014). One way to test these theories is to directly compare neural activity related to social and non-social decision outcomes within the same experimental setting. Here we address this issue by focusing on the neural substrates of social and non-social forms of uncertainty. Using functional magnetic resonance imaging (fMRI) we directly compared the neural representations of reward and risk prediction and errors (RePE and RiPE) in social and non- social situations using gambling games. We used a trust betting game to vary uncertainty along a social dimension (trustworthiness), and a card game (Preuschoff et al. 2006) to vary uncertainty along a non-social dimension (pure risk). The trust game was designed to maintain the same structure of the card game. In a first study, we exposed a divide between subcortical and cortical regions when comparing the way these regions process social and non-social forms of uncertainty during outcome anticipation. Activity in subcortical regions reflected social and non-social RePE, while activity in cortical regions correlated with social RePE and non-social RiPE. The second study focused on outcome delivery and integrated the concept of RiPE in non-social settings with that of fairness and monetary utility maximisation in social settings. In particular these results corroborate recent models of anterior insula function (Singer et al. 2009; Seth 2013), and expose a possible neural mechanism that weights fairness and uncertainty but not monetary utility. The third study focused on functionally defined regions of the early visual cortex (V1) showing how activity in these areas, traditionally considered only visual, might reflect motivational prediction errors in addition to known perceptual prediction mechanisms (den Ouden et al 2012). On the whole, while our results do not support unilaterally one or the other theory modeling the underlying neural dynamics of social and non-social forms of decision making, they provide a working framework where both general mechanisms might coexist.

Children's mental representations of attachment: associations with attachment security and parent-child narrative quality

The goal of this study was to examine the antecedents and correlates of children’s mental representations of attachment at 5 years (Attachment Story Completion Task, Bretherton, Ridgeway, & Cassidy, 1990; MacArthur Story Stem Battery, Bretherton, Oppenheim, Buchsbaum, Emde, & the MacArthur Narrative Group, 1990). Predictors included children’s attachment security with mothers and fathers assessed via the Attachment Q-Set (AQS, Waters, 1987) at 3 years, and parent-child narrative quality regarding positive and negative events at 5 years. Participants included 71 children and their mothers and fathers. Structural equation models (SEM) indicated that children’s attachment security exerted a significant indirect effect on children’s mental representations through parent-child narrative quality. Specifically, children’s attachment security with fathers was related to their mental representations via father-child reminiscing about positive events, and children’s attachment security with mothers was related to their mental representations via mother-child reminiscing about negative events. Results are discussed in terms of the development and implications of attachment relationships within the family context.

Which way is up? Grounded mental representations of space

Processing language is postulated to involve a mental simulation, or re-enactment of perceptual, motor, and introspective states that were acquired experientially (Barsalou, 1999, 2008). One such aspect that is mentally simulated during processing of certain concepts is spatial location. For example, upon processing the word “moon” the prominent spatial location of the concept (e.g. ‘upward’) is mentally simulated. In six eye-tracking experiments, we investigate how mental simulations of spatial location affect processing. We first address a conflict in previous literature whereby processing is shown to be impacted in both a facilitatory and inhibitory way. Two of our experiments showed that mental simulations of spatial association facilitate saccades launched toward compatible locations; however, a third experiment showed an inhibitory effect on saccades launched towards incompatible locations. We investigated these differences with further experiments, which led us to conclude that the nature of the effect (facilitatory or inhibitory) is dependent on the demands of the task and, in fitting with the theory of Grounded Cognition (Barsalou, 2008), that mental simulations impact processing in a dynamic way. Three further experiments explored the nature of verticality – specifically, whether ‘up’ is perceived as away from gravity, or above our head. Using similar eye-tracking methods, and by manipulating the position of participants, we were able to dissociate these two possible standpoints. The results showed that mental simulations of spatial location facilitated saccades to compatible locations, but only when verticality was dissociated from gravity (i.e. ‘up’ was above the participant’s head). We conclude that this is not due to an ‘embodied’ mental simulation, but rather a result of heavily ingrained visuo-motor association between vertical space and eye movements.

IDEATIONAL REPRESENTATIONS OF EDENTULISM AND PROSTHETIC REHABILITATION FROM THE POINT OF VIEW OF THE ELDERLY

Objetivo: Identificar as representações ideativas de idosos edêntulos uni ou bimaxilares acerca das perdas dentárias e da reabilitação protética oral. Métodos: Estudo qualitativo, realizado entre janeiro e março de 2011 com sete idosos residentes em uma Instituição Pública de Longa Permanência do Recife-PE, com 14 idosos em atendimento na Clínica de Prótese Dentária da Universidade Federal de Pernambuco (UFPE). Coletaram-se os dados através de uma entrevista semiestruturada que passou por análise de conteúdo. Resultados: Os achados possibilitaram identificar que, para os idosos, os dentes contribuíam tanto para a saúde quanto como para facilitar interações sociais, enquanto o edentulismo foi associado a uma pluralidade de sentimentos negativos. Quanto à reabilitação protética, eles enfatizaram os prejuízos para a saúde devido a próteses mal adaptadas. Conclusão: Os idosos acreditam que o edentulismo e a reabilitação protética estão associados, principalmente, a um conceito mecanicista da profissão, amplamente difundido entre os profissionais que privilegiam mais a odontologia curativa em detrimento da prevenção. Nesse contexto, para que o envelhecimento possa ser considerado uma etapa da vida com as mesmas qualidades e dificuldades de qualquer outra, sugere-se aos gestores e aos próprios profissionais em saúde que se comprometam mais com uma prática odontológica humanizadora e preventiva, a fim de proverem os requisitos mínimos para um envelhecimento com dignidade.

Social representations of nursing students about hospital assistance and primary health care

Objective: To analyze how social representations of hospital and community care are structured in two groups of nursing students – 1st and 4th years. Method: Qualitative research oriented by the Theory of Social Representations. We used a questionnaire with Free Association of Words. Data were analyzed in the Software IRaMuTeQ 0.6 alpha 3. Results: We applied the method of Descending Hierarchical Classifi cation and obtained four classes. Class 4 has the largest social representation (30.41%) within the corpus. The two organizational axes are nurse and disease/patient in the central core. On the periphery are the care and help related to the nurse and the treatment and prevention associated with the disease. Conclusion: Social representations focus on disease/patient and on the role of nurses in the treatment, prevention, and care. Health promotion and the social determinants of health are absent from the social representations of students.

The other of myself: representations of portuguese teachers about intercultural education related concepts

Having into consideration that we live in a multicultural society, it is important to analyse how far people view and accept each other. Therefore, one should reflect upon concepts such as: representations and stereotypes, because they are interpersonal constructs which are (re)built during the interaction of different sociocultural groups. In this study, we focus our attention on the representations a sociocultural group – Portuguese teachers - has of intercultural education and the role of teachers and educators in the promotion of an intercultural approach at school. We believe that teachers have the responsibility to: find out the representations students have of the Other; reconfigure stereotyped representations; and create representations which favor dialogue and relationship with the Other flourish. Following a sociolinguistic approach (Müller, 1998; Vasseur, 2001; Vasseur & Hudelot, 1998), which is related to the construction and diffusion of representations in discourse, we analyse the discourse of teachers during a workshop called ‘The Other and Myself’, in which they build and discuss about a didactic mask that portrays their own vision of both themselves and their ideas of intercultural education.

Input-state-output representations of concatenated 2D convolutional codes

In this paper we investigate a novel model of concatenation of a pair of two-dimensional (2D) convolutional codes. We consider finite-support 2D convolutional codes and choose the so-called Fornasini-Marchesini input-state-output (ISO) model to represent these codes. More concretely, we interconnect in series two ISO representations of two 2D convolutional codes and derive the ISO representation of the ob- tained 2D convolutional code. We provide necessary condition for this representation to be minimal. Moreover, structural properties of modal reachability and modal observability of the resulting 2D convolutional codes are investigated.

Learning Binary Code Representations for Effective and Efficient Image Retrieval

The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.

Efficient Image and Video Representations for Retrieval

Image (Video) retrieval is an interesting problem of retrieving images (videos) similar to the query. Images (Videos) are represented in an input (feature) space and similar images (videos) are obtained by finding nearest neighbors in the input representation space. Numerous input representations both in real valued and binary space have been proposed for conducting faster retrieval. In this thesis, we present techniques that obtain improved input representations for retrieval in both supervised and unsupervised settings for images and videos. Supervised retrieval is a well known problem of retrieving same class images of the query. We address the practical aspects of achieving faster retrieval with binary codes as input representations for the supervised setting in the first part, where binary codes are used as addresses into hash tables. In practice, using binary codes as addresses does not guarantee fast retrieval, as similar images are not mapped to the same binary code (address). We address this problem by presenting an efficient supervised hashing (binary encoding) method that aims to explicitly map all the images of the same class ideally to a unique binary code. We refer to the binary codes of the images as `Semantic Binary Codes' and the unique code for all same class images as `Class Binary Code'. We also propose a new class­ based Hamming metric that dramatically reduces the retrieval times for larger databases, where only hamming distance is computed to the class binary codes. We also propose a Deep semantic binary code model, by replacing the output layer of a popular convolutional Neural Network (AlexNet) with the class binary codes and show that the hashing functions learned in this way outperforms the state­ of ­the art, and at the same time provide fast retrieval times. In the second part, we also address the problem of supervised retrieval by taking into account the relationship between classes. For a given query image, we want to retrieve images that preserve the relative order i.e. we want to retrieve all same class images first and then, the related classes images before different class images. We learn such relationship aware binary codes by minimizing the similarity between inner product of the binary codes and the similarity between the classes. We calculate the similarity between classes using output embedding vectors, which are vector representations of classes. Our method deviates from the other supervised binary encoding schemes as it is the first to use output embeddings for learning hashing functions. We also introduce new performance metrics that take into account the related class retrieval results and show significant gains over the state­ of­ the art. High Dimensional descriptors like Fisher Vectors or Vector of Locally Aggregated Descriptors have shown to improve the performance of many computer vision applications including retrieval. In the third part, we will discuss an unsupervised technique for compressing high dimensional vectors into high dimensional binary codes, to reduce storage complexity. In this approach, we deviate from adopting traditional hyperplane hashing functions and instead learn hyperspherical hashing functions. The proposed method overcomes the computational challenges of directly applying the spherical hashing algorithm that is intractable for compressing high dimensional vectors. A practical hierarchical model that utilizes divide and conquer techniques using the Random Select and Adjust (RSA) procedure to compress such high dimensional vectors is presented. We show that our proposed high dimensional binary codes outperform the binary codes obtained using traditional hyperplane methods for higher compression ratios. In the last part of the thesis, we propose a retrieval based solution to the Zero shot event classification problem - a setting where no training videos are available for the event. To do this, we learn a generic set of concept detectors and represent both videos and query events in the concept space. We then compute similarity between the query event and the video in the concept space and videos similar to the query event are classified as the videos belonging to the event. We show that we significantly boost the performance using concept features from other modalities.