O efeito do sorriso na percepção psicológica da pessoa

O objectivo do estudo foi o de verificar o efeito do sorriso na percepção psicológica da pessoa em jovens, adultos, idosos e jovens negros. Pretendia-se verificar se o sorriso contribui para os traços diferenciais entre os grupos humanos em estudo e se o mesmo era descritor de género. O estudo envolveu um delineamento transversal analítico ou estudo não-experimental, também classificado por estudo pós-facto, estudo de observação passiva ou estudo correlacional e de observação, de comparação entre grupos, mediante o juízo ou julgamento psicológico da face neutra e do tipo de sorriso contrastados, de matriz factorial 4 x 2 x 2 (face neutra, sorriso fechado, sorriso superior, sorriso largo; género dos estímulos; género dos respondentes) e a sua finalidade foi descrever a percepção psicológica do sorriso em função das variáveis género do estímulo, género do respondente e grupo étnico, na Escala de Percepção do Sorriso (EPS), em formato diferenciador semântico, com 19 itens bipolares opostos, tendo a avaliação sido feita numa escala ordinal de 1 a 7 pontos, nas dimensões Avaliação (12 itens) e Movimento Expressivo (7 itens) resultante dos estudos preliminares sobre a atractividade facial (estudo preliminar 1) e a escolha de dípolos de adjectivos preditores para percepção psicológica da face neutra (estudo preliminar 2). Nos estudos principais 1, 2 e 3 foram utilizados 24 estímulos fotográficos apresentando o tipo de sorriso (fechado, superior e largo) e a face neutra (12 do estímulo mulher e 12 do estímulo homem) referentes aos três grupos etários (18-25 anos, 40-50 anos e 60-70 anos) e a Escala de Percepção do Sorriso (EPS) foi aplicada a uma amostra não probabilística ou intencional do tipo homogénea de 480 participantes portugueses de ambos os géneros (240 mulheres e 240 homens) distribuídos por grupos etários de jovens (80 mulheres e 80 homens, média: 22.2 anos), adultos (80 mulheres e 80 homens, média: 43.1 anos) e idosos (80 mulheres e 80 homens, média: 65.0 anos) No estudo principal 4, foram utilizados 8 estímulos fotográficos apresentando o tipo de sorriso (fechado, superior e largo) e a face neutra (4 do estímulo mulher e 4 do estímulo homem) de universitários de Cabo Verde, a estudar em Portugal, e a Escala de Percepção do Sorriso (EPS) foi aplicada a uma amostra não probabilística ou intencional do tipo homogénea de 160 participantes de ambos os géneros (80 mulheres e 80 homens) e estudantes universitários portugueses (média: 21.8 anos). Os resultados revelam e confirmam o efeito do sorriso na percepção psicológica da pessoa, à semelhança de outros estudos, isto é, sorrir torna a percepção psicológica mais positiva ou negativa e verifica-se que tal sucede em função do género do estímulo e do género do respondente. As diferenças significativas na percepção da face neutra e tipo de sorriso contrastados são justificadas pela pertença de género de quem os percepciona e pela pertença do género de quem é percepcionado. Tal apenas não sucede no factor Avaliação do grupo dos adultos. Os resultados obtidos indicam que, quer no factor Avaliação quer no factor Movimento Expressivo, os tipos de sorriso largo e superior são os que registam médias ponderadas mais elevadas. Pelo contrário, a face neutra e o sorriso fechado registam valores menos elevados na percepção. A análise da percepção da pessoa em função da face neutra e tipo de sorriso contrastados revelou uma correspondência entre a expressão facial, o género do estímulo e o género do respondente. No factor Avaliação, a mulher é percepcionada mais positivamente que o homem, verificando-se o inverso no factor Movimento Expressivo no grupo dos adultos e dos idosos. Verificou-se efeito do sorriso na percepção psicológica dos estímulos de cor negra. No grupo dos jovens que percepcionaram estímulos de cor negra, o homem é considerado mais positivo que a mulher em ambos os factores. O efeito significativo do género revela que a sua percepção é condicionada pelo seu próprio género. Os resultados apontam ainda para a configuração pronunciada de uma hierarquização ascendente da face neutra e tipo de sorriso contrastados em dois conjuntos bem delimitados e distinguindo diferentes formas topográficas de sorrir: a face neutra e o sorriso fechado e o sorriso superior e o sorriso largo.

O efeito do sorriso na percepção psicológica da pessoa

O objectivo do estudo foi o de verificar o efeito do sorriso na percepção psicológica da pessoa em jovens, adultos, idosos e jovens negros. Pretendia-se verificar se o sorriso contribui para os traços diferenciais entre os grupos humanos em estudo e se o mesmo era descritor de género. O estudo envolveu um delineamento transversal analítico ou estudo não-experimental, também classificado por estudo pós-facto, estudo de observação passiva ou estudo correlacional e de observação, de comparação entre grupos, mediante o juízo ou julgamento psicológico da face neutra e do tipo de sorriso contrastados, de matriz factorial 4 x 2 x 2 (face neutra, sorriso fechado, sorriso superior, sorriso largo; género dos estímulos; género dos respondentes) e a sua finalidade foi descrever a percepção psicológica do sorriso em função das variáveis género do estímulo, género do respondente e grupo étnico, na Escala de Percepção do Sorriso (EPS), em formato diferenciador semântico, com 19 itens bipolares opostos, tendo a avaliação sido feita numa escala ordinal de 1 a 7 pontos, nas dimensões Avaliação (12 itens) e Movimento Expressivo (7 itens) resultante dos estudos preliminares sobre a atractividade facial (estudo preliminar 1) e a escolha de dípolos de adjectivos preditores para percepção psicológica da face neutra (estudo preliminar 2). Nos estudos principais 1, 2 e 3 foram utilizados 24 estímulos fotográficos apresentando o tipo de sorriso (fechado, superior e largo) e a face neutra (12 do estímulo mulher e 12 do estímulo homem) referentes aos três grupos etários (18-25 anos, 40-50 anos e 60-70 anos) e a Escala de Percepção do Sorriso (EPS) foi aplicada a uma amostra não probabilística ou intencional do tipo homogénea de 480 participantes portugueses de ambos os géneros (240 mulheres e 240 homens) distribuídos por grupos etários de jovens (80 mulheres e 80 homens, média: 22.2 anos), adultos (80 mulheres e 80 homens, média: 43.1 anos) e idosos (80 mulheres e 80 homens, média: 65.0 anos) No estudo principal 4, foram utilizados 8 estímulos fotográficos apresentando o tipo de sorriso (fechado, superior e largo) e a face neutra (4 do estímulo mulher e 4 do estímulo homem) de universitários de Cabo Verde, a estudar em Portugal, e a Escala de Percepção do Sorriso (EPS) foi aplicada a uma amostra não probabilística ou intencional do tipo homogénea de 160 participantes de ambos os géneros (80 mulheres e 80 homens) e estudantes universitários portugueses (média: 21.8 anos). Os resultados revelam e confirmam o efeito do sorriso na percepção psicológica da pessoa, à semelhança de outros estudos, isto é, sorrir torna a percepção psicológica mais positiva ou negativa e verifica-se que tal sucede em função do género do estímulo e do género do respondente. As diferenças significativas na percepção da face neutra e tipo de sorriso contrastados são justificadas pela pertença de género de quem os percepciona e pela pertença do género de quem é percepcionado. Tal apenas não sucede no factor Avaliação do grupo dos adultos. Os resultados obtidos indicam que, quer no factor Avaliação quer no factor Movimento Expressivo, os tipos de sorriso largo e superior são os que registam médias ponderadas mais elevadas. Pelo contrário, a face neutra e o sorriso fechado registam valores menos elevados na percepção. A análise da percepção da pessoa em função da face neutra e tipo de sorriso contrastados revelou uma correspondência entre a expressão facial, o género do estímulo e o género do respondente. No factor Avaliação, a mulher é percepcionada mais positivamente que o homem, verificando-se o inverso no factor Movimento Expressivo no grupo dos adultos e dos idosos. Verificou-se efeito do sorriso na percepção psicológica dos estímulos de cor negra. No grupo dos jovens que percepcionaram estímulos de cor negra, o homem é considerado mais positivo que a mulher em ambos os factores. O efeito significativo do género revela que a sua percepção é condicionada pelo seu próprio género. Os resultados apontam ainda para a configuração pronunciada de uma hierarquização ascendente da face neutra e tipo de sorriso contrastados em dois conjuntos bem delimitados e distinguindo diferentes formas topográficas de sorrir: a face neutra e o sorriso fechado e o sorriso superior e o sorriso largo.

Work values as predictors of entrepreneurial career intentions: A longitudinal analysis of gender effects

Purpose - Work values are an important characteristic to understand gender differences in career intentions, but how gender affects the relationship between values and career intentions is not well established. The purpose of this paper is to investigate whether gender moderates the effects of work values on level and change of entrepreneurial intentions (EI). Design/methodology/approach - In total, 218 German university students were sampled regarding work values and with EI assessed three times over the course of 12 months. Data were analysed with latent growth modelling. Findings - Self-enhancement and openness to change values predicted higher levels and conservation values lower levels of EI. Gender moderated the effects of enhancement and conservation values on change in EI. Research limitations/implications - The authors relied on self-reported measures and the sample was restricted to university students. Future research needs to verify to what extent these results generalize to other samples and different career fields, such as science or nursing. Practical implications - The results imply that men and women are interested in an entrepreneurial career based on the same work values but that values have different effects for men and women regarding individual changes in EI. The results suggest that the prototypical work values of a career domain seem important regarding increasing the career intent for the gender that is underrepresented in that domain. Originality/value - The results enhance understanding of how gender affects the relation of work values and a specific career intention, such as entrepreneurship.

Spatial analysis of corresponding fingerprint features from match and close non-match populations

The development of statistical models for forensic fingerprint identification purposes has been the subject of increasing research attention in recent years. This can be partly seen as a response to a number of commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. In addition, key forensic identification bodies such as ENFSI [1] and IAI [2] have recently endorsed and acknowledged the potential benefits of using statistical models as an important tool in support of the fingerprint identification process within the ACE-V framework. In this paper, we introduce a new Likelihood Ratio (LR) model based on Support Vector Machines (SVMs) trained with features discovered via morphometric and spatial analyses of corresponding minutiae configurations for both match and close non-match populations often found in AFIS candidate lists. Computed LR values are derived from a probabilistic framework based on SVMs that discover the intrinsic spatial differences of match and close non-match populations. Lastly, experimentation performed on a set of over 120,000 publicly available fingerprint images (mostly sourced from the National Institute of Standards and Technology (NIST) datasets) and a distortion set of approximately 40,000 images, is presented, illustrating that the proposed LR model is reliably guiding towards the right proposition in the identification assessment of match and close non-match populations. Results further indicate that the proposed model is a promising tool for fingerprint practitioners to use for analysing the spatial consistency of corresponding minutiae configurations.

Cognitive Issues in Fingerprint Analysis: Inter- and Intra-Expert Consistency and the Effect of a "Target" Comparison

Deciding whether two fingerprint marks originate from the same source requires examination and comparison of their features. Many cognitive factors play a major role in such information processing. In this paper we examined the consistency (both between- and within-experts) in the analysis of latent marks, and whether the presence of a 'target' comparison print affects this analysis. Our findings showed that the context of a comparison print affected analysis of the latent mark, possibly influencing allocation of attention, visual search, and threshold for determining a 'signal'. We also found that even without the context of the comparison print there was still a lack of consistency in analysing latent marks. Not only was this reflected by inconsistency between different experts, but the same experts at different times were inconsistent with their own analysis. However, the characterization of these inconsistencies depends on the standard and definition of what constitutes inconsistent. Furthermore, these effects were not uniform; the lack of consistency varied across fingerprints and experts. We propose solutions to mediate variability in the analysis of friction ridge skin.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Toxic substances in blood: an analysis of current recommendations under a Bayesian (decision) approach

This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

The Uncertain generalized probabilistic weighted average and its application in the theory of expertons

A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

Identification of Wax Esters in Latent Print Residues by Gas Chromatography-Mass Spectromertry and Their Potential Use as Aging Parameters

Recent studies show that the composition of fingerprint residue varies significantly from the same donor as well as between donors. This variability is a major drawback in latent print dating issues. This study aimed, therefore, at the definition of a parameter that is less variable from print to print, using a ratio of peak area of a target compound degrading over time divided by the summed area of peaks of more stable compounds also found in latent print residues.Gas chromatography-mass spectrometry (GC/MS) analysis of the initial lipid composition of latent prints identifies four main classes of compounds that can be used in the definition of an aging parameter: fatty acids, sterols, sterol precursors, and wax esters (WEs). Although the entities composing the first three groups are quite well known, those composing WEs are poorly reported. Therefore, the first step of the present work was to identify WE compounds present in latent print residues deposited by different donors. Of 29 WEs recorded in the chromatograms, seven were observed in the majority of samples.The identified WE compounds were subsequently used in the definition of ratios in combination with squalene and cholesterol to reduce the variability of the initial composition between latent print residues from different persons and more particularly from the same person. Finally, the influence of a latent print enhancement process on the initial composition was studied by analyzing traces after treatment with magnetic powder, 1,2-indanedione, and cyanoacrylate.

Intersecciones entre visión artificial y mirada artística. Semantic Intersections between Artificial and Artistic Vision.

En el presente artículo se ha desarrollado un sistema capaz de categorizar de forma automática la base de datos de imágenes que sirven de punto de partida para la ideación y diseño en la producción artística del escultor M. Planas. La metodología utilizada está basada en características locales. Para la construcción de un vocabulario visual se sigue un procedimiento análogo al que se utiliza en el análisis automático de textos (modelo 'Bag-of-Words'-BOW) y en el ámbito de las imágenes nos referiremos a representaciones 'Bag-of-Visual Terms' (BOV). En este enfoque se analizan las imágenes como un conjunto de regiones, describiendo solamente su apariencia e ignorando su estructura espacial. Para superar los inconvenientes de polisemia y sinonimia que lleva asociados esta metodología, se utiliza el análisis probabilístico de aspectos latentes (PLSA) que detecta aspectos subyacentes en las imágenes, patrones formales. Los resultados obtenidos son prometedores y, además de la utilidad intrínseca de la categorización automática de imágenes, este método puede proporcionar al artista un punto de vista auxiliar muy interesante.

Taxometric analysis of DSM-IV and DSM-5 alcohol use disorders.

BACKGROUND: With preparations currently being made for the Diagnostic and Statistical Manual of Mental Disorders-5th Edition (DSM-5), one prominent issue to resolve is whether alcohol use disorders are better represented as discrete categorical entities or as a dimensional construct. The purpose of this study was to investigate the latent structure of DSM-4th edition (DSM-IV) and proposed DSM-5 alcohol use disorders. METHODS: The study used the Wave 2 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) to conduct taxometric analyses of DSM-IV and DSM-5 alcohol use disorders defined by different thresholds to determine the taxonic or dimensional structure underlying the disorders. RESULTS: DSM-IV and DSM-5 alcohol abuse and dependence criteria with 3+ thresholds demonstrated a dimensional structure. Corresponding thresholds with 4+ criteria were clearly taxonic, as were thresholds defined by cut-offs of 5+ and 6+ criteria. CONCLUSIONS: DSM-IV and DSM-5 alcohol use disorders demonstrated a hybrid taxonic-dimensional structure. That is, DSM-IV and DSM-5 alcohol use disorders may be taxonically distinct compared to no disorder if defined by a threshold of 4 or more criteria. However, there may be dimensional variation remaining among non-problematic to subclinical cases. A careful and systematic program of structural research using taxometric and psychometric procedures is warranted.

Identification of promising antigenic components in latent fingermark residues

An analysis of latent fingermark residues by Sodium-Dodecyl-Sulfate PolyAcrylamide Gel Electrophoresis (SDS-PAGE) followed by silver staining allowed the detection of different proteins, from which two major bands, corresponding to proteins of 56 and 64 kDa molecular weight, could be identified. Two other bands, corresponding to proteins of 52 and 48 kDa were also visualizable along with some other weaker bands of lower molecular weights. In order to identify these proteins, three antibodies directed against human proteins were tested on western blots of fingermarks residues: anti-keratin 1 and 10 (K1/10), anti-cathepsin-D (Cat.D) and anti-dermcidin (Derm.). The corresponding antigens are known to be present in the stratum corneum of desquamating stratified epithelium (K1/10, Cat.D) and/or in eccrine sweat (Cat.D, Derm.). The two major bands were identified as consistent with keratin 1 and 10. The pro-form and the active form of the cathepsin-D have also been identified from two other bands. Dermcidin could not be detected in the western blot. In addition, these antibodies have been tested on latent fingermarks left on polyvinylidene fluoride (PVDF) membrane, as well as on whitened and non-whitened paper. The detection of fingermarks was successful with all three antibodies.