P. H. Patel

People make errors when forecasting future negative affect possibly due to immune neglect, the failure to account for the activity of the psychological immune system that regulates negative affect. This study examined the effect of emotion regulation (ER) on affective forecasting (AF) errors due to immune neglect during an everyday, navigation task. Participants (N = 173) were randomly assigned to use ER strategies that typically vary in their effectiveness (cognitive reappraisal, suppression, or no strategy) prior to forecasting. We reasoned that if we found smaller AF errors for participants who were assigned to use ER strategies versus those who were not, this would indicate that the underlying mechanism of forecasting errors was immune neglect in a control condition. Presumably, participants in the reappraisal and suppression conditions would not ignore their psychological immune systems and, thus, make smaller forecasting errors than those in the control condition. Contrary to the hypothesis, participants showed similar levels of AF errors across all three ER conditions. Overall, this study suggests that ER does not always contribute to AF errors via immune neglect in everyday situations.

Cognitive scientists often represent theories of cognitive behavior in the form of computer programs which simulate and model the performance of humans in experimental settings. Earlier work has demonstrated that evolutionary techniques, specifically genetic programming (GP), can be used to generate a pool of candidate models in the form of executable computer programs. However, previous work has not considered the impact of changes to hyper-parameter values, such as those controlling the behavior and timing of operators or those controlling the operation of the GP process. In this paper, we develop and use a cluster analysis technique based around the Silhouette index to investigate the impact of hyper-parameter changes on the composition of evolved populations of programs. Our metrics support visualizations and enable a user to assess both qualitatively and quantitatively the diversity of candidates from different populations. In this way, a cognitive scientist can analyze the output of the evolutionary system in order to uncover or inspire potentially novel theories of human behavior.

Ethical awareness is fundamental to maintaining integrity in medical research. In the current study, we assess the knowledge of Indian Council of Medical Research (ICMR) ethical guidelines among nursing professionals and examine the association between their demographic characteristics and knowledge levels. Participants (N = 150) completed a structured questionnaire comprising demographic items and a knowledge assessment based on ICMR guidelines. The results showed that approximately 45.0% of participants demonstrated good knowledge of ethical guidelines. Although educational attainment initially appeared to be associated with higher knowledge scores (p = 0.044), this effect did not remain significant after Bonferroni correction for multiple testing (adjusted α = 0.006). No other demographic variables were significantly associated with knowledge. These findings suggest that while a portion of nursing professionals possess adequate ethical awareness, broader and more structured educational efforts are needed to strengthen knowledge and ensure consistent adherence to research ethics in clinical practice.

Ethical awareness is fundamental to maintaining integrity in medical research. In the current study, we assess the knowledge of Indian Council of Medical Research (ICMR) ethical guidelines among nursing professionals and examine the association between their demographic characteristics and knowledge levels. Participants (N = 150) completed a structured questionnaire comprising demographic items and a knowledge assessment based on ICMR guidelines. The results showed that approximately 45.0% of participants demonstrated good knowledge of ethical guidelines. Although educational attainment initially appeared to be associated with higher knowledge scores (p = 0.044), this effect did not remain significant after Bonferroni correction for multiple testing (adjusted α = 0.006). No other demographic variables were significantly associated with knowledge. These findings suggest that while a portion of nursing professionals possess adequate ethical awareness, broader and more structured educational efforts are needed to strengthen knowledge and ensure consistent adherence to research ethics in clinical practice.

In natural language processing (NLP), named entity recognition (NER) and semantic classification are essential tasks. NER is a fundamental task, that identify named entities in text such as people, organizations, and locations. In Legal domain, NER is particularly important due to the variety of named entities that appear in legal documents and are important for legal analysis whereas Semantic classification is the process of giving each sentence in a text a semantic label, such as ”fact,””arguments,” or”judgement”. Both NER and Semantic classi- fication are critical component of many NLP applications such as Knowledge base construction and semantic search. Semantic searching of legal documents is a powerful technique that can be used to quickly find the information that you need. By combining NER and semantic classification, one can identify the key elements of a legal document and search for documents that are related to a particular topic or contain a particular type of information. This paper proposes a novel approach to NER and Semantic classification in legal domain using Long short-term memory (LSTM) model. The proposed approach is evaluated on a corpus of legal text and the result of this study suggest that LSTM models are a promising approach for NER and Semantic classification in legal domain and can be used to improve the performance of semantic searching of legal documents.

So far, most ethical consumerism research has been contained within Western countries, thus limiting our understanding of the concept in emerging markets. Given the call for extending empirical-based knowledge for a better understanding of peculiarities, dynamics and country-level variations (i.e. social, cultural) in the context of ethical consumerism in emerging markets, this research cross-examines the interactive nature of individual- and country-level predictors of ethical consumerism in emerging and developed markets, employing a multilevel approach. At the individual level, we posit that ethical consumerism is motivated by social and cultural capital. In contrast, at the contextual level, we choose country-level affluence as an influential factor that might impact the relationship between socio-cultural capital and ethical consumerism. The study uses the International Social Survey Programme’s (ISSP) 2014 citizenship module data set (including 34 countries) for investigating individual-level predictors (of social and cultural capital). The GDP per capita data from the International Monetary Fund’s (IMF) Economic Outlook database was used to examine the cross-level interactions between individual-level predictors and country-level affluence. The findings suggest that social and cultural capitals positively influence ethical consumerism in emerging and developed markets. Further, country-level affluence moderates the relationship between socio-cultural capital and ethical consumerism for both markets. However, cultural capital proved to be a stronger predictor of ethical consumerism as country-level affluence increases. The research findings highlight meaningful cross-country-level interactions that help further understand the basis of ethical consumerism from a global perspective.