Predicting intention to work with social robots

The growing number of robotic solutions geared to interact socially with humans, social robots, urge the study of the factors that will facilitate or hinder future human robot collaboration. Hence the research question: what are the factors that predict intention to work with a social robot in the near future. To answer this question the following socio-cognitive models were studied, the theory of reasoned action, the theory of planned behavior and the model of goal directed behavior. These models purport that all the other variables will only have an indirect effect on behavior. That is, through the variables of the model. Based on the research on robotics and social perception/ cognition, social robot appearance, belief in human nature uniqueness, perceived warmth, perceived competence, anthropomorphism, negative attitude towards robots with human traits and negative attitudes towards interactions with robots were studied for their effects on attitude towards working with a social robot, perceived behavioral control, positive anticipated emotions and negative anticipated emotions. Study 1 identified the social representation of robot. Studies 2 to 5 investigated the psychometric properties of the Portuguese version of the negative attitude towards robots scale. Study 6 investigated the psychometric properties of the belief in human nature uniqueness scale. Study 7 tested the theory of reasoned action and the theory of planned behavior. Study 8 tested the model of goal directed behavior. Studies 7 and 8 also tested the role of the external variables. Study 9 tested and compared the predictive power of the three socio-cognitive models. Finally conclusion are drawn from the research results, and future research suggestions are offered.

Profiles of ageing in the South of Portugal: education and cognitive functioning in elderly persons living in institutionalized and community contexts

The region of the Algarve shows huge differences between the coastline where population in the urban areas grows, and the inland rural areas, in some cases very isolated, which frequently have high ageing indexes. This general scenario, with an elderly population with very different economic and social conditions, frames the ongoing PhD research designed as a cross-sectional study of an intentional sample of elderly persons. The basic theoretical framework departs from the perspective of developmental psychology of life-span and the model of selection, optimisation and compensation for optimal ageing (Baltes & Baltes, 1990; Freund & Baltes, 2002). The present study is a first step in the analysis of empirical data collected in the PhD sample (N=156; age range 65 to 97 years; M = 80.4 years; SD = 7.2 years). Its purpose is to assess the cognitive functioning of participants, screening for cognitive impairment and examine the relations between the cognitive status of the subjects and a number of selected variables including educational level, age, physical activity and living contexts of the subjects. We accessed the cognitive status of the participants with the Portuguese version of Mini Mental State Examination (MMSE) finding a 10.3% prevalence of positive cases with cognitive impairment. The results also show significant relationships between the cognitive status accessed by the MMSE and educational level, professional qualification, age, living arrangement and activity level of the participants. The relationship verified between educational level and cognitive status of the participants was the largest correlation found in the study with the variability in educational level accounting for 44.8% of the variability in MMSE score. This results points in the same direction of several lines of research that corroborate the strong intercorrelation between education and cognitive functioning in old age.

Cape Verde coastal ecosystem: a study of community structure, trophic interactions and exploitation pattern

Tese de dout., Ciências e Tecnologia das Pescas, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2005

Can we use niche models of indicator species to predict the distribution of endangered communities?

European-wide conservation policies are based on the identification of priority habitats. However, research on conservation biogeography often relies on the results and projections of species distribution models to assess species' vulnerability to global change. We assess whether the distribution and structure of threatened communities can be predicted by the suitability of the environmental conditions for their indicator species. We present some preliminary results elucidating if using species distribution models of indicator species at a regional scale is a valid approach to predict these endangered communities. Dune plant assemblages, affected by severe conditions, are excellent models for studying possible interactions among their integrating species and the environment. We use data from an extensive survey of xerophytic inland sand dune scrub communities from Portugal, one of the most threatened habitat types of Europe. We identify indicator shrub species of different types of communities, model their geographical response to the environment, and evaluate whether the output of these niche models are able to predict the distribution of each type of community in a different region.