Desenvolvimento e Estudo da Validade Facial do Questionário de Motivações para Revelar/Não Revelar a Parentalidade Não-Genética por Doação de Gâmetas

Introdução: A parentalidade é um papel muito valorizado socialmente. No entanto, para casais com infertilidade o desempenho deste papel pode implicar tratamentos de fertilidade, alguns deles com recurso a gâmetas de dador. Para os casais que recorrem a gâmetas de dador, surge uma outra preocupação: contar à criança a origem da sua conceção ou manter segredo. Ainda que as motivações que influenciam este processo de decisão tenham sido alvo de estudo, em Portugal a investigação relativa a este tema é escassa. Objetivos: A presente investigação pretendeu desenvolver e estudar a validade facial do Questionário de Motivações para Revelar/Não Revelar a Parentalidade não Genética por Doação de Gâmetas (QMRDG), o qual se destina a avaliar as principais motivações que influenciam o processo de tomada de decisão dos pais que recorrem a gâmetas de dador relativamente a contar ou não contar ao/à seu/sua filho/a a origem da sua conceção. Pretendeu-se ainda explorar a relação entre os sintomas emocionais negativos e o sentido de competência parental nos diferentes grupos em estudo (pais que já contaram à criança, pais que decidiram não contar e pais que ainda não contaram). Metodologia: Estudo exploratório conduzido numa amostra de 21 participantes que recorrem a tratamento de fertilidade com recurso a gâmetas de dador, tendo tido filhos resultantes desse mesmo tratamento, com idades compreendidas entre os 30 e 49 anos. Os participantes preencheram um conjunto de questionários numa plataforma online, tendo o estudo sido divulgado pela Associação Portuguesa de Fertilidade. Resultados: Os dados obtidos indicam que a maioria dos pais ainda não contou ao/à seu/sua filho/a sua origem genética devido ao facto de a criança ser ainda muito pequena, encontrando-se estes com intenção de revelar à criança. Dos pais que já contaram, as motivações que mais influenciaram a decisão basearam-se na falta de motivos para omitir, na importância dada à honestidade, no direito do conhecimento das origens genéticas e na transparência no seio familiar. Face às motivações para não contar, das que mais influenciaram os pais salienta-se a pouca importância dada à genética. O QMRDG revelou possuir validade facial não tendo sido reportada a existência de itens ambíguos ou de difícil compreensão. Discussão: A tendência dos pais no presente estudo foi de contar ao/à seu/sua filho/a a origem da sua conceção, sendo também esta a tendência reportada em estudos mais recentes. Verificou-se a existência de algumas limitações no estudo, nomeadamente o tamanho da amostra. No entanto, o QMRDG mostrou possuir validade facial, podendo constituir-se como um instrumento útil na prática clínica e na investigação com pessoas que estejam a realizar tratamento de fertilidade com recurso a gâmetas de dador. / Introduction: Parenting is a highly valued social role. However, for couples dealing with infertility this role can involve fertility treatments, and for some of them donorassisted reproduction. For couples who use third party reproduction, another concern can emerge: tell the child about the donor conception, or preserve secrecy. Although arguments for decision making have been studied, in Portugal research on this topic is scanty. Objectives: The current study sought out to develop and study the facial validity of Motivations for Disclosing/Not Disclosing Non-genetic Parenthood through Gamete Donation (QMRDG), which is designed to assess motivations that influence the decision-making process of parents who use gamete donation regarding tell or not to tell to his/her son/daughter his/her conception. The existence of differences concerning emotional negative symptoms and parenting sense of competence in three groups (parents that already disclosed, parents that decided not to disclose and parents that did not decide what to do) was also explored. Methods: This exploratory study was conducted in sample of 21 participants who undergone third-party reproduction treatment and became parents. Participants´ age ranged from 30 to 49 years. Participants completed a set of questionnaires through an online platform. The study was advertised by Associação Portuguesa de Fertilidade. Results: Data showed that most parents did not disclose to their child their donor conception due to the fact that the child is still very young, but their intention seems to be to disclose in the future. For parents who have disclosed, core motivations for that decision are based on the lack of reasons for omitting, on the importance of honesty, on the right to know genetic origins and on transparency in the family. Concerning motivations for not disclosing the little importance given to genetics emerges as one of the most important ones. QMRDG revealed good facial validity. The existence of ambiguous or difficult to understand items has not been reported. Discussion: In our study parent’s tendency was to disclose to his/her son/daughter his/her donor conception and this is also the trend reported in recent studies. There are some methodological limitations that should be considered mainly due to the sample size. However, the QMRDG proved to be an instrument showing facial validity, and it can be a useful tool in clinical practice and research with people who are pursuing fertility treatment with gamete donation.

Competition-related factors directly influence preferences for facial cues of dominance in allies

Alliance formation is a critical dimension of social intelligence in political, social and biological systems. As some allies may provide greater ‘leverage’ than others during social conflict, the cognitive architecture that supports alliance formation in humans may be shaped by recent experience, for example in light of the outcomes of violent or non-violent forms intrasexual competition. Here we used experimental priming techniques to explore this issue. Consistent with our predictions, while men’s preference for dominant allies strengthened following losses (compared to victories) in violent intrasexual contests, women’s preferences for dominant allies weakened following losses (compared to victories) in violent intrasexual contests. Our findings suggest that while men may prefer dominant (i.e. masculine) allies following losses in violent confrontation in order to facilitate successful resource competition, women may ‘tend and befriend’ following this scenario and seek support from prosocial (i.e. feminine) allies and/or avoid the potential costs of dominant allies as long-term social partners. Moreover, they demonstrate facultative responses to signals related to dominance in allies, which may shape sex differences in sociality in light of recent experience and suggest that intrasexual selection has shaped social intelligence in humans.

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Documenting reproduction and inequality : revisiting Jean Anyon’s “Social class and school knowledge”

Jean Anyon’s (1981) “Social class and school knowledge” was a landmark work in North American educational research. It provided a richly detailed qualitative description of differential, social-class-based constructions of knowledge and epistemological stance. This essay situates Anyon’s work in two parallel traditions of critical educational research: the sociology of the curriculum and classroom interaction and discourse analysis. It argues for the renewed importance of both quantitative and qualitative research on social reproduction and equity in the current policy context.

Selecting, optimizing and fusing ‘salient’ Gabor features for facial expression recognition

This paper describes a novel framework for facial expression recognition from still images by selecting, optimizing and fusing ‘salient’ Gabor feature layers to recognize six universal facial expressions using the K nearest neighbor classifier. The recognition comparisons with all layer approach using JAFFE and Cohn-Kanade (CK) databases confirm that using ‘salient’ Gabor feature layers with optimized sizes can achieve better recognition performance and dramatically reduce computational time. Moreover, comparisons with the state of the art performances demonstrate the effectiveness of our approach.

Facial feature detection for in-car environment

Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.

Exploring visual features through Gabor representations for facial expression detection

Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.

Temporal-based support vector machines for facial expression recognition

When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Reproduction, mediation, and experience : virtual reality, motion capture and early modern theatre

This article investigates virtual reality representations of performance in London’s late sixteenth-century Rose Theatre, a venue that, by means of current technology, can once again challenge perceptions of space, performance, and memory. The VR model of The Rose represents a virtual recreation of this venue in as much detail as possible and attempts to recover graphic demonstrations of the trace memories of the performance modes of the day. The VR model is based on accurate archeological and theatre historical records and is easy to navigate. The introduction of human figures onto The Rose’s stage via motion capture allows us to explore the relationships between space, actor and environment. The combination of venue and actors facilitates a new way of thinking about how the work of early modern playwrights can be stored and recalled. This virtual theatre is thus activated to intersect productively with contemporary studies in performance; as such, our paper provides a perspective on and embodiment of the relation between technology, memory and experience. It is, at its simplest, a useful archiving project for theatrical history, but it is directly relevant to contemporary performance practice as well. Further, it reflects upon how technology and ‘re-enactments’ of sorts mediate the way in which knowledge and experience are transferred, and even what may be considered ‘knowledge.’ Our work provides opportunities to begin addressing what such intermedial confrontations might produce for ‘remembering, experiencing, thinking and imagining.’ We contend that these confrontations will enhance live theatre performance rather than impeding or disrupting contemporary performance practice. Our ‘paper’ is in the form of a video which covers the intellectual contribution while also permitting a demonstration of the interventions we are discussing.

Toward a more robust facial expression recognition in occluded images using randomly sampled Gabor based templates

Occlusion is a big challenge for facial expression recognition (FER) in real-world situations. Previous FER efforts to address occlusion suffer from loss of appearance features and are largely limited to a few occlusion types and single testing strategy. This paper presents a robust approach for FER in occluded images and addresses these issues. A set of Gabor based templates is extracted from images in the gallery using a Monte Carlo algorithm. These templates are converted into distance features using template matching. The resulting feature vectors are robust to occlusion. Occluded eyes and mouth regions and randomly places occlusion patches are used for testing. Two testing strategies analyze the effects of these occlusions on the overall recognition performance as well as each facial expression. Experimental results on the Cohn-Kanade database confirm the high robustness of our approach and provide useful insights about the effects of occlusion on FER. Performance is also compared with previous approaches.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.