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.

Dynamic mental representations of habitual behaviours: Food choice on a web-based environment

Aim: Rather than being rigid, habitual behaviours may be determined by dynamic mental representations that can adapt to context changes. This adaptive potential may result from particular conditions dependent on the interaction between two sources of mental constructs activation: perceived context applicability and cognitive accessibility . Method: T wo web-shopping simulations of fering the choice between habitually chosen and non-habitually chosen food products were presented to participants. This considered two choice contexts dif fering in the habitual behaviour perceived applicability (low vs. high) and a measure of habitual behaviour chronicity . Results: Study 1 demonstrated a perceived applicability ef fect, with more habitual (non-organic) than non-habitual (organic) food products chosen in a high perceived applicability (familiar) than in a low perceived applicability (new) context. The adaptive potential of habitual behaviour was evident in the habitual products choice consistency across three successive choices, despite the decrease in perceived applicability . Study 2 evidenced the adaptive potential in strong habitual behaviour participants – high chronic accessibility – who chose a habitual product (milk) more than a non-habitual product (orange juice), even when perceived applicability was reduced (new context). Conclusion: Results portray consumers as adaptive decision makers that can flexibly cope with changes in their (inner and outer) choice contexts.

Veteranness : Representations of Combat-related PTSD in U.S. Popular Visual Media

Posttraumatic stress and PTSD are becoming familiar terms to refer to what we often call the invisible wounds of war, yet these are recent additions to a popular discourse in which images of and ideas about combat-affected veterans have long circulated. A legacy of ideas about combat veterans and war trauma thus intersects with more recent clinical information about PTSD to become part of a discourse of visual media that has defined and continues to redefine veteran for popular audiences. In this dissertation I examine realist combat veteran representations in selected films and other visual media from three periods: during and after World Wars I and II (James Allen from I Am a Fugitive from a Chain Gang, Fred Derry and Al Stephenson from The Best Years of Our Lives); after the Vietnam War (Michael from The Deer Hunter, Eriksson from Casualties of War), and post 9/11 (Will James from The Hurt Locker, a collection of veterans from Wartorn: 1861-2010.) Employing a theoretical framework informed by visual media studies, Barthes’ concept of myth, and Foucault’s concept ofdiscursive unity, I analyze how these veteran representations are endowed with PTSD symptom-like behaviors and responses that seem reasonable and natural within the narrative arc. I contend that veteran myths appear through each veteran representation as the narrative develops and resolves. I argue that these veteran myths are many and varied but that they crystallize in a dominant veteran discourse, a discursive unity that I term veteranness. I further argue that veteranness entangles discrete categories such as veteran, combat veteran, and PTSD with veteran myths, often tying dominant discourse about combat-related PTSD to outdated or outmoded notions that significantly affect our attitudes about and treatment of veterans. A basic premise of my research is that unless and until we learn about the lasting effects of the trauma inherent to combat, we hinder our ability to fulfill our responsibilities to war veterans. A society that limits its understanding of posttraumatic stress, PTSD and post-war experiences of actual veterans affected by war trauma to veteranness or veteran myths risks normalizing or naturalizing an unexamined set of sociocultural expectations of all veterans, rendering them voice-less, invisible, and, ultimately disposable.

Towards flexible parsing of structured textual model representations

Existing parsers for textual model representation formats such as XMI and HUTN are unforgiving and fail upon even the smallest inconsistency between the structure and naming of metamodel elements and the contents of serialised models. In this paper, we demonstrate how a fuzzy parsing approach can transparently and automatically resolve a number of these inconsistencies, and how it can eventually turn XML into a human-readable and editable textual model representation format for particular classes of models.

Defending the 'public interest': an assessment of competing actor representations of 'solutions' to growing natural resource deficiencies.

This paper applies a SRT framework to the study of two case studies, namely the recent campaign of opposition to the legalization of hydraulic fracking in the State of New York and the more ongoing debate on land leasing in Africa. In relation to both campaigns, the analysis accounts for the arguments of a major financial institution and industry representatives who stress the safe and value-adding dimensions of these practices, as well as the views of opponents who refute the validity of industry's position and point to the unacceptable risks posed to the community, health and the environment. In spite of a number of obvious differences between these two case studies, not least differences arising from contrasting socio-economic and geo-political settings, there were also some notable similarities. First, was a tendency amongst protesters in both cases to formulate their role as contemporaries in a historically extended struggle for democratic justice. All perceived of themselves as guardians of their community's right to resist a corporate 'invasion' of their territories, like their forefathers and mothers before them. A theme of colonialism was explored in both settings through various identity and thematic anchoring devices that deliberately evoked shared understandings and historical memories of exploitation and human suffering. The evocation of powerful symbols of identity through visual narratives of protest further reinforced the cultural comprehensibility of opponents' message of protest in both contexts.

The potential of symbolic approximation. Disentangling the effects of approximation vs. calculation demands in nonsymbolic and symbolic representations.

Mathematical skills that we acquire during formal education mostly entail exact numerical processing. Besides this specifically human faculty, an additional system exists to represent and manipulate quantities in an approximate manner. We share this innate approximate number system (ANS) with other nonhuman animals and are able to use it to process large numerosities long before we can master the formal algorithms taught in school. Dehaene´s (1992) Triple Code Model (TCM) states that also after the onset of formal education, approximate processing is carried out in this analogue magnitude code no matter if the original problem was presented nonsymbolically or symbolically. Despite the wide acceptance of the model, most research only uses nonsymbolic tasks to assess ANS acuity. Due to this silent assumption that genuine approximation can only be tested with nonsymbolic presentations, up to now important implications in research domains of high practical relevance remain unclear, and existing potential is not fully exploited. For instance, it has been found that nonsymbolic approximation can predict math achievement one year later (Gilmore, McCarthy, & Spelke, 2010), that it is robust against the detrimental influence of learners´ socioeconomic status (SES), and that it is suited to foster performance in exact arithmetic in the short-term (Hyde, Khanum, & Spelke, 2014). We provided evidence that symbolic approximation might be equally and in some cases even better suited to generate predictions and foster more formal math skills independently of SES. In two longitudinal studies, we realized exact and approximate arithmetic tasks in both a nonsymbolic and a symbolic format. With first graders, we demonstrated that performance in symbolic approximation at the beginning of term was the only measure consistently not varying according to children´s SES, and among both approximate tasks it was the better predictor for math achievement at the end of first grade. In part, the strong connection seems to come about from mediation through ordinal skills. In two further experiments, we tested the suitability of both approximation formats to induce an arithmetic principle in elementary school children. We found that symbolic approximation was equally effective in making children exploit the additive law of commutativity in a subsequent formal task as a direct instruction. Nonsymbolic approximation on the other hand had no beneficial effect. The positive influence of the symbolic approximate induction was strongest in children just starting school and decreased with age. However, even third graders still profited from the induction. The results show that also symbolic problems can be processed as genuine approximation, but that beyond that they have their own specific value with regard to didactic-educational concerns. Our findings furthermore demonstrate that the two often con-founded factors ꞌformatꞌ and ꞌdemanded accuracyꞌ cannot be disentangled easily in first graders numerical understanding, but that children´s SES also influences existing interrelations between the different abilities tested here.

ESL teacher profiles of ICT integration in their classroom practices and assessment activities : a portrait viewed through the lens of some Quebec teachers’ social representations

Abstract : Information and communication technologies (ICTs, henceforth) have become ubiquitous in our society. The plethora of devices competing with the computer, from iPads to the Interactive whiteboard, just to name a few, has provided teachers and students alike with the ability to communicate and access information with unprecedented accessibility and speed. It is only logical that schools reflect these changes given that their purpose is to prepare students for the future. Surprisingly enough, research indicates that ICT integration into teaching activities is still marginal. Many elementary and secondary schoolteachers are not making effective use of ICTs in their teaching activities as well as in their assessment practices. The purpose of the current study is a) to describe Quebec ESL teachers’ profiles of using ICTs in their daily teaching activities; b) to describe teachers’ ICT integration and assessment practices; and c) to describe teachers’ social representations regarding the utility and relevance of ICT use in their daily teaching activities and assessment practices. In order to attain our objectives, we based our theoretical framework, principally, on the social representations (SR, henceforth) theory and we defined most related constructs which were deemed fundamental to the current thesis. We also collected data from 28 ESL elementary and secondary school teachers working in public and private sectors. The interview guide used to that end included a range of items to elicit teachers’ SR in terms of ICT daily use in teaching activities as well as in assessment practices. In addition, we carried out our data analyses from a textual statistics perspective, a particular mode of content analysis, in order to extract the indicators underlying teachers’ representations of the teachers. The findings suggest that although almost all participants use a wide range of ICT tools in their practices, ICT implementation is seemingly not exploited to its fullest potential and, correspondingly, is likely to produce limited effects on students’ learning. Moreover, none of the interviewees claim that they use ICTs in their assessment practices and they still hold to the traditional paper-based assessment (PBA, henceforth) approach of assessing students’ learning. Teachers’ common discourse reveals a gap between the positive standpoint with regards to ICT integration, on the one hand, and the actual uses of instructional technology, on the other. These results are useful for better understanding the way ESL teachers in Quebec currently view their use of ICTs, particularly for evaluation purposes. In fact, they provide a starting place for reconsidering the implementation of ICTs in elementary and secondary schools. They may also be useful to open up avenues for the development of a future research program in this regard.

Social representations about the Portuguese adolescent alcohol consumption

Alcohol is currently the most widely consumed psychoactive substance in the world and Portugal is the second country where such consumption is greater, registering a large increase in consumption by young people. Currently continue still, beliefs, myths and prejudices that because they are well rooted culturally serve as good reasons for drinking. This study sought therefore to identify the myths associated by adolescents to alcohol consumption. A questionnaire was developed for this purpose (74 items, α = 0.947) and applied to a sample of 1176 adolescents schooled between 14 and 18 years old, with a return rate of 42.6% (margin of error of 5% for a confidence level of 95%) in the district of Beja, Portugal, in 2012. The collected data were statistically analyzed using measures of association, factor analysis and linear regression. The results show that many myths are unknown among adolescents, verifying the presence of many questions, among which stands out: alcohol "warm", "thirst quenching", "gives strength", "facilitates digestion" "whet the appetite", "is a medicine", "is aphrodisiac", "facilitates social relations", among others. Age and sex are variables significantly affected the myths and objectives of alcohol consumption. These results clearly point to the need to be disassembled beliefs and wrong conceptions about the effects of alcohol consumption, particularly in the school environment, reducing the risk of the consequences and promoting adolescent health, preventing any future dependence on this psychoactive substance.