Género e representações sociais: duplo-padrão sexual em função da religião e da posição política

O estudo de natureza não experimental apresentado pretendeu identificar e caracterizar os padrões sexuais pré-matrimoniais aos níveis individual e social e analisá-los em função do sexo, religião e posição política numa amostra de 308 estudantes do ensino superior. Os resultados apontaram para a adesão ao duplo-padrão sexual ao nível individual, mas para uma maior consensualidade na sua forma social, isto é, na percepção dessa duplicidade moral nos julgamentos e nas avaliações dos comportamentos sexuais pela sociedade em geral. Da análise da influência da opção religiosa e da posição política sobre as representações sociais da sexualidade pré-matrimonial, observou-se que os factores religiosidade e conservadorismo político estão negativamente associados à permissividade das atitudes sexuais, apesar da tendência comum dos diferentes grupos religiosos e políticos para a adesão ao duplo-padrão sexual, nas suas duas formas, individual e social. As implicações dos resultados são discutidas no âmbito da teoria das representações sociais e do género

From ''Chastity as a gift'' to ''Doing it as a sign of love'': a longitudinal analysis of the discourses on female sexuality in popular magazines in Portugal

Female sexuality published in six types of magazines between 1965 and 2006 were content analyzed. The results showed that Portuguese media’s discourse on sexuality is not only becoming more liberal but is also characterized by ambiguity and contradiction. Within a “progressive” discursive framework for sexuality, tensions and double standards for women are still noticeable. The media discourse in Portugal continues to reinforce the established gender hierarchy and inequality in heterosexual relationships and maintain traditional gender roles

Attribution-based motivation treatment efficacy in an online learning environment for students who differ in cognitive elaboration

Attribution-based motivation treatments can boost performance in competitive achievement settings (Perry and Hamm 2017), yet their efficacy relative to mediating processes and affect-based treatments remains largely unexamined. In a two-semester, pre-post, randomized treatment study (n = 806), attributional retraining (AR) and stress-reduction (SR) treatments were administered in an online learning environment to first-year college students who differed in cognitive elaboration (low, high). Low elaborators who received AR outperformed their SR peers by nearly a letter grade on a class test assessed 5 months post-treatment. Path analysis revealed this AR-performance linkage was mediated by causal attributions, perceived control, and positive and negative achievement emotions in a hypothesized causal sequence. Results advance the literature by showing AR (vs. SR) improved performance indirectly via cognitive and affective process variables specified by Weiner’s (1985a, 2012) attribution theory of motivation and emotion

Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis

Semantic Web Logic Programming Tools

The last two decades of research in Logic Programming, both at the theoretical and practical levels, have addressed several topics highly relevant for the Semantic Web e#ort, providing very concrete answers to some open questions

An evolvable rule-based e-mail agent

Abstract. The Semantic Web is a “living organism”, which combines autonomously evolving data sources/knowledge repositories. This dynamic character of the Semantic Web requires (declarative) languages and mechanisms for specifying its maintenance and evolution. For example, for changing the behaviour of a data source, so that a new rule becomes into effect, one should not be concerned with the complex, interrelated, and dynamically obtained knowledge, and should have a way to simply specify what knowledge is to be changed. This requires the existence of a language for exacting such changes (or updates), which takes in consideration the addition/deletion and changes of rules, thereby automating the task of dealing with inconsistencies arising from those updates. To address this issue, we resort to recent developments in the field of Logic Programming, and show how the framework of EVOLP can be put to work to model such reactive and updateable rule bases, bringing an important added value to RuleML. We make our case by exhibiting a detailed application example of how EVOLP can be used to express updateable RuleML rule bases, employing it to define an evolving e-mail Personal Assistant Agent.

Logic Programming Techniques for Solving Circuit Diagnosis

Model-based diagnosis is a general technique of Artificial Intelligence that has applications to engineering design, networking, planning, and other domains. These applications have led to the creation of special-purpose systems for model-based diagnosis, based on theories of truth maintenance. In this paper we focus on circuit diagnosis, and consider several logic programming approaches, which in contrast to the special-purpose systems, require very small amounts of code, yet are often quite efficient. As a basis for comparison, we start generate and test algorithms. Next, we model faults as abducibles, and the abductive program is evaluated using tabling. As an alternative to abduction, we use Answer Set Programming to capture each diagnosis as a stable model. The most efficient method resorts to bottom-up dependencies propagation, and annotates each the truth-value of each circuit with a set of faults required in the derivation of that truth-value. All tests are performed on the 6288 ISCAS85 benchmark circuit