Combining statistics: the role of phonotactics on cross-situational word learning

Abstract Language learners can rely on phonological and semantic information to learn novel words. Using a cross-situational word learning paradigm, we explored the role of phonotactic probabilities on word learning in ambiguous contexts. Brazilian-Portuguese speaking adults (N = 30) were exposed to two sets of word-object pairs. Words from one set of labels had slightly higher phonotactic probabilities than words from the other set. By tracking co-occurrences of words and objects, participants were able to learn word-object mappings similarly across both sets. Our findings contrast with studies showing a facilitative effect of phonotactic probability on word learning in non-ambiguous contexts.

Metodología de Análisis de Emociones para Identificar Riesgo de Cometer Suicidio Generado por el COVID-19 / Methodology of Emotion Analysis to Identify Risk of Committing Suicide Generated by COVID-19 / Metodologia de Análise de Emoções para Identificar o Risco de Suicídio Gerada por COVID-19

Resumen Introducción: El comienzo del año 2020 llegó acompañado de una pandemia causada por el virus denominado SARS-CoV-2. Con las medidas de distanciamiento social implementadas para evitar la propagación de este virus, se presentan problemáticas de salud mental, como ansiedad, depresión, etc., trayendo como consecuencia una necesidad de atención a pacientes a distancia. Dadas las cifras alarmantes de incidencias de suicidio en la sociedad actual, aunadas a estas medidas de distanciamiento, son requeridas herramientas de apoyo para identificar individuos en riesgo de cometer suicidio. Objetivo: Proponer y evaluar una nueva metodología para calcular riesgo de suicidio en usuarios de Twitter, apoyándose en el análisis de emociones. Materiales y Métodos: Usando modelos de aprendizaje estadístico (supervisado y no supervisado), la metodología propuesta identifica el nivel de riesgo en el texto analizado de 77 tuits de usuarios regulares y de figuras políticas en México y Latinoamérica. Resultados: Se encontró que, al comparar los métodos utilizados, el porcentaje de coincidencia en clasificación es cercano al 96 %, siendo los métodos supervisado no paramétrico y no supervisado los que detectaron los niveles extremos de riesgo al suicidio. Conclusiones: la metodología propuesta es una herramienta que puede ser de gran apoyo para especialistas del área de salud mental al ayudar a identificar, de manera masiva, la presencia de indicios de enfermedades mentales, para su subsecuente diagnóstico.

Abstract Introduction: The beginning of 2020 was accompanied by a pandemic caused by the virus called SARS-CoV-2. With social distancing measures implemented to prevent the spread of this virus, mental health problems arose, such as anxiety, depression, etc., resulting in a need for telemedicine. Given the alarming numbers of suicide incidences in today's society, coupled with these distancing measures, support tools are required to identify individuals at risk of committing suicide. Objective: To propose and evaluate a new methodology to calculate suicide risk in Twitter users, based on the analysis of emotions. Materials and Methods: Using statistical learning models (supervised and unsupervised), the proposed methodology identifies the level of risk in the analyzed text of 77 tweets from regular users and political figures in Mexico and Latin America. Results: It was found that, when comparing the methods used, the percentage of coincidence in classification is close to 96%, being the supervised non-parametric and unsupervised methods those that detected the extreme levels of suicide risk. Conclusions: the proposed methodology is a tool that can be of great support for specialists in the mental health area by helping to identify, in a massive way, the presence of signs of mental illness, for its subsequent diagnosis.

Resumo Introdução: O início de 2020 foi acompanhado por uma pandemia causada pelo vírus denominado SARS-CoV-2. Com as medidas de distanciamento social implantadas para prevenir a propagação desse vírus, surgem problemas de saúde mental, como ansiedade, depressão, etc., resultando na necessidade de atendimento remoto ao paciente. Dados os números alarmantes de incidentes de suicídio na sociedade atual, juntamente com essas medidas de distanciamento, ferramentas de apoio são necessárias para identificar indivíduos em risco de suicídio. Objetivo: propor e avaliar uma nova metodologia para calcular o risco de suicídio em usuários do Twitter, a partir da análise das emoções. Materiais e Métodos: Usando modelos estatísticos de aprendizagem (supervisionados e não supervisionados), a metodologia proposta identifica o nível de risco no texto analisado de 77 tweets de usuários regulares e figuras políticas no México e na América Latina. Resultados: Verificou-se que, na comparação dos métodos utilizados, o percentual de coincidência na classificação é próximo a 96%, sendo os métodos não paramétricos supervisionados e não supervisionados aqueles que detectaram os níveis extremos de risco de suicídio. Conclusões: A metodologia proposta é uma ferramenta que pode ser de grande apoio aos especialistas da área de saúde mental por ajudar a identificar, de forma massiva, a presença de indícios de doença mental, para seu posterior diagnóstico.

Neurocognitive Correlates of Statistical Learning of Orthographic-Semantic Connections in Chinese Adult Learners / 神经科学通报·英文版

We examined the neural correlates of the statistical learning of orthographic-semantic connections in Chinese adult learners. Visual event-related potentials (ERPs) were recorded while participants were exposed to a sequence of artificial logographic characters containing semantic radicals carrying low, moderate, or high levels of semantic consistency. The behavioral results showed that the mean accuracy of participants' recognition of previously exposed characters was 63.1% that was significantly above chance level (50%), indicating the statistical learning of the regularities of semantic radicals. The ERP data revealed a temporal sequence of the neural process of statistical learning of orthographic-semantic connections, and different brain indexes were found to be associated with this processing, i.e., a clear N170-P200-N400 pattern. For N170, the larger negative amplitudes were evoked by the high and moderate consistency than the low consistency. For P200, the mean amplitudes elicited by the moderate and low consistency were larger than the high consistency. In contrast, a larger N400 amplitude was observed in the low than moderate and high consistency; and more negative amplitude was elicited by the moderate than high consistency. We propose that the initial potential shifts (N170 and P200) may reflect orthographic or graphic form identification, while the later component (N400) may be associated with semantic information analysis.

The extension of the largest generalized-eigenvalue based distance metric D(ij)(γ₁) in arbitrary feature spaces to classify composite data points

Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric D(ij)(γ₁) in any linear and non-linear feature spaces. We prove that D(ij)(γ₁) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule δ(Ξi) (i.e., mean of D(ij)(γ₁)) in classification of heterogeneous sets of biosequences compared with the decision rules min(Ξi) and median(Ξi). We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

Avaliação Psicológica no Século XXI: de Onde Viemos e para Onde Vamos / Psychological Assessment in the 21st Century: Where We Come from and Where We Go / Evaluación Psicológica en el Siglo XXI: de Dónde Venimos y Hacia Dónde Vamos

Na primeira parte, esse artigo fará um enquadramento amplo da avaliação psicológica dentre as atividades profissionais do psicólogo e uma breve descrição reflexiva histórica, dos últimos 18 anos, dos esforços empreendidos pelo Conselho Federal de Psicologia na tentativa de regulamentação da área, focando nas lições aprendidas. Na segunda parte, o artigo irá focar os eventos científicos e históricos ocorridos nos últimos cinco anos, especialmente no âmbito da inteligência artificial, os quais apontam para um novo papel da avaliação psicológica no mundo. O artigo faz uma reflexão sobre as implicações dessas mudanças para o papel do psicólogo e para a regulamentação de sua prática profissional....(AU)

In the first part, this article will provide a broad framework of psychological assessment of the psychologist's professional activities and a brief historical reflective description of the area's regulatory board efforts over the past eighteen years., focusing on the lessons learned. In the second part, the article will focus on scientific and historical events occurring in the last five years, especially in the field of artificial intelligence, which point to a new role of psychological assessment in the world. It presents a reflection on the implications of these changes for the role of psychologists and for the regulation of their professional practice....(AU)

En la primera parte, este artículo hará un encuadramiento amplio de la evaluación psicológica entre las actividades profesionales del psicólogo y una breve descripción reflexiva histórica de los esfuerzos del consejo de reglamentación del área en los últimos dieciocho años, enfocándose en las lecciones aprendidas. En la segunda parte, el artículo se centrará en eventos científicos e históricos ocurridos en los últimos cinco años, especialmente en el ámbito de la inteligencia artificial, que apuntan a un nuevo papel de la evaluación psicológica en el mundo. El artículo hace una reflexión sobre las implicaciones de estos cambios para el papel del psicólogo y para la regulación de su práctica profesional....(AU)