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The current definition of the hardware-program implementation defining mathematical models for cognitive-process domains, in other words, announced as the trading-based name "Artificial Intelligence", could raise serious arguments. The main reason for this issue is rooted in the entirely non-engineering aspect in which such models are being presented to the public with an intentional incarnation of non-existent functionality. There is a rising trend of user access and usage of such technology, which reaches nearly 1.8 billion visits per month. Rapidly spreading boundaries of potential application of the trading-based name “аrtificial intelligence” covers vast areas of human activity. It should be denoted that in certain cases a parallel could be made between discoveries made in the exact sciences and the consequences of their incomplete understanding and application – for example, the underestimated risk of radium-226 application, which consequences were wrongly ignored. It is important for humanity not to repeat the same mistake and despite the euphoria of "artificial intelligence", it is necessary to refine the concepts and pay attention to the semantic, generative, and anthropological problems that the invasion of this technology poses. [ABSTRACT FROM AUTHOR]

The article addresses how to improve the professional training of specialists in the transport industry using information and cognitive technologies. The article aims to study and explain the problems, opportunities, and prospects of implementing and using information and cognitive technologies in the educational environment, as well as the specifics of their implementation for teaching and learning in educational and professional programs for the transport specialists’ training. The following methods of semantic and comparative analysis, classification, generalization, and systematization, as well as competency-based, technological, and creative development approaches were used in the research. It has been found that cognitive technologies in the context of teaching and learning involve the use of methods and tools, which are based on understanding and activating cognitive processes such as thinking, memory, and attention. In cognitive learning, the educational process focuses not on absorbing information but on understanding the internal connections of the studied subjects, which encourages students to engage in dialogical, exploratory thinking, and increases mental activity concentration. By complementing information technologies with cognitive ones, which take into account the individual and general cognitive students’ abilities, it is possible not only to encourage professional training but also to enhance the overall cognitive efficiency of future specialists. For educators, these technologies facilitate the use of ICT as cognitive tools for transitioning from traditional teacher-centred methods to constructivist student-centred approaches. It has been established that information-cognitive technologies combine methods and algorithms based on insights into the cognition processes, learning, communication, and information processing, grounded in the achievements of neuroscience, digital and information technologies, and the mathematical modelling of consciousness. In the educational process, they are designed to support students in setting and solving creative tasks that are difficult to formalize, as well as to reveal and effectively operate their cognitive potential. In the professional training of students, certain information-cognitive technologies can be applied both with and without the use of computer systems. These include technologies for developing critical thinking, creatively developmental technologies, project technologies, foresight methodologies, problem-based learning technologies, mastery learning technologies, mental activity activation technologies, case studies, gaming technologies, visualization and data representation technologies, and learning through practice. Additionally, the use of multimedia technologies, scribing, virtual and augmented reality, project technologies based on networking, gamification, interactive technologies, primarily group work technologies, open, distance, and blended learning technologies, and also the Internet of Things, Blockchain, Big Data, expert systems, SMART technologies, and artificial intelligence significantly enhances the quality of training students in proficiency transport area. It has been concluded that information and cognitive technologies provide interactive, personalized, and practically oriented learning, contribute to the development of student’s critical thinking, and for future transport specialists can optimize logistics processes, automate diagnostics, repair, and operation of vehicles, in addition, increase the specialist’s adaptability to the complex conditions of the modern and future professional environment.

Psychology-oriented research extensively studied how affect influences human decision making. Particularly, the cognitive tuning assumption suggests that mood can serve to regulate between shallow and deliberative decisions – a more negative mood means higher deliberation. This work proposes a model that mimics the cognitive tuning assumption. To that end, the Collective Risk Dilemma (CRD) game For the Planet was designed and created, a process allowing for distinct levels of reasoning was defined and tested in that game, and mood was integrated to control the level of reasoning of such a process. Several distinct Artificial Intelligence (AI) profiles were created to verify that the developed model was able to dynamically change the level of reasoning and adjust the resulting AI behavior in our CRD game. Results revealed that the distinct AI profiles were influenced by their affective states and experienced circumstances, and that the emergent behaviors were consistent with the cognitive tuning assumption, thus demonstrating that we managed to construct an innovative and flexible model that can use mood to dynamically adjust the level of reasoning of an AI agent. [ABSTRACT FROM AUTHOR]

Objective: Auditory hallucinations (hearing voices) have been associated with a range of altered cognitive functions, pertaining to signal detection, source-monitoring, memory, inhibition and language processes. Yet, empirical results are inconsistent. Despite this, several theoretical models of auditory hallucinations persist, alongside increasing emphasis on the utility of a multidimensional framework. Thus, clarification of current evidence across the broad scope of proposed mechanisms is warranted. Method: A systematic search of the Web of Science, PubMed and Scopus databases was conducted. Records were screened to confirm the use of an objective behavioural cognitive task, and valid measurement of hallucinations specific to the auditory modality. Results: Auditory hallucinations were primarily associated with difficulties in perceptual decision-making (i.e. reduced sensitivity/accuracy for signal-noise discrimination; liberal responding to ambiguity), source-monitoring (i.e. self–other and temporal context confusion), working memory and language function (i.e. reduced verbal fluency). Mixed or limited support was observed for perceptual feature discrimination, imagery vividness/illusion susceptibility, source-monitoring for stimulus form and spatial context, recognition and recall memory, executive functions (e.g. attention, inhibition), emotion processing and language comprehension/hemispheric organisation. Conclusions: Findings were considered within predictive coding and self-monitoring frameworks. Of concern was the portion of studies which – despite offering auditory-hallucination-specific aims and inferences – employed modality-general measures, and/or diagnostic-based contrasts with psychologically healthy individuals. This review highlights disparities within the literature between theoretical conceptualisations of auditory hallucinations and the body of rigorous empirical evidence supporting such inferences. Future cognitive investigations, beyond the schizophrenia-spectrum, which explicitly define and measure the timeframe and sensory modality of hallucinations, are recommended. [ABSTRACT FROM AUTHOR]

Objective: The present study examines the cognitive effects of placing icons in unexpected spatial locations within websites. Background: Prior research has revealed evidence for cognitive conflict when web icons occur in unexpected locations (e.g., cart, top left), generally consistent with a dynamical systems models. Here, we compare the relative strength of evidence for both dual and dynamical systems models. Methods: Participants clicked on icons located in either expected (e.g., cart, top right) or unexpected (e.g., cart, top left) locations while mouse trajectories were continuously recorded. Trajectories were classified according to prototypes associated with each cognitive model. The dynamical systems model predicts curved trajectories, while the dual-systems model predicts straight and change of mind trajectories. Results: Trajectory classification revealed that curved trajectories increased (+11%), while straight and change of mind trajectories decreased (−12%) when target icons occurred in unexpected locations (p <.001). Conclusion: Rather than employing a single cognitive strategy, users shift from a primarily dual-systems to dynamical systems strategy when icons occur in unexpected locations. Application: Potential applications of this work include the assessment of cognitive impacts such as mental workload and cognitive conflict during real-time interaction with websites and other screen-based interfaces, personalization and adaptive interfaces based on an individual's cognitive strategy, and data-driven A/B testing of alternative interface designs. [ABSTRACT FROM AUTHOR]

Cognitive Linguistics, as an expanding discipline in language study, delves into language as a mental phenomenon, presenting a holistic approach that integrates linguistic and cognitive elements. Unlike traditional linguistics, which scrutinizes syntactical patterns, word structures, grammar rules, phonology, semantics, and lexical meanings, Cognitive Linguistics offers a comprehensive model that interweaves various closely connected theories. This study seeks to elucidate the manifestations of Cognitive Linguistics in language, providing scholars with a discerning analysis of existing theories. Furthermore, employing methods of descriptive and comparative analysis, this study aims to demonstrate the impact of Cognitive Linguistics on language processing and acquisition. It highlights its significance in second language acquisition while elucidating the underlying mental processes involved. The paper offers a succinct overview of this evolving discipline, encapsulating its unique characteristics within the encompassing term Cognitive Linguistics. [ABSTRACT FROM AUTHOR]

Humans are universally good in providing stable and accurate judgments about what forms part of their language and what not. Large Language Models (LMs) are claimed to possess human-like language abilities; hence, they are expected to emulate this behavior by providing both stable and accurate answers, when asked whether a string of words complies with or deviates from their next-word predictions. This work tests whether stability and accuracy are showcased by GPT-3/text-davinci- 002, GPT-3/text-davinci- 003, and ChatGPT, using a series of judgment tasks that tap on 8 linguistic phenomena: plural attraction, anaphora, center embedding, comparatives, intrusive resumption, negative polarity items, order of adjectives, and order of adverbs. For every phenomenon, 10 sentences (5 grammatical and 5 ungrammatical) are tested, each randomly repeated 10 times, totaling 800 elicited judgments per LM (total n = 2,400). Our results reveal variable above-chance accuracy in the grammatical condition, below-chance accuracy in the ungrammatical condition, a significant instability of answers across phenomena, and a yes-response bias for all the tested LMs. Furthermore, we found no evidence that repetition aids the Models to converge on a processing strategy that culminates in stable answers, either accurate or inaccurate. We demonstrate that the LMs’ performance in identifying (un)grammatical word patterns is in stark contrast to what is observed in humans (n = 80, tested on the same tasks) and argue that adopting LMs as theories of human language is not motivated at their current stage of development. [ABSTRACT FROM AUTHOR]

With this manuscript we aim to initiate a discussion specific to educational actions around ultrasonics sonochemistry. The importance of these actions does not just derive from a mere pedagogical significance, but they can be an exceptional tool for illustrating various concepts in other disciplines, such as process intensification and microfluidics. Sonochemistry is currently a far-reaching discipline extending across different scales of applicability, from the fundamental physics of tiny bubbles and molecules, up to process plants. This review is part of a special issue in Ultrasonics Sonochemistry, where several scholars have shared their experiences and highlighted opportunities regarding ultrasound as an education tool. The main outcome of our work is that teaching and mentorship in sonochemistry are highly needed, with a balanced technical and scientific knowledge to foster skills and implement safe protocols. Applied research typically features the use of ultrasound as ancillary, to merely enhance a given process and often leading to poorly conceived experiments and misunderstanding of the actual effects. Thus, our scientific community must build a consistent culture and monitor reproducible practices to rigorously generate new knowledge on sonochemistry. These practices can be implemented in teaching sonochemistry in classrooms and research laboratories. We highlight ways to collectively provide a potentially better training for scientists, invigorating academic and industry-oriented careers. A salient benefit for education efforts is that sonochemistry-based projects can serve multidisciplinary training, potentially gathering students from different disciplines, such as physics, chemistry and bioengineering. Herein, we discuss challenges, opportunities, and future avenues to assist in designing courses and research programs based on sonochemistry. Additionally, we suggest simple experiments suitable for teaching basic physicochemical principles at the undergraduatelevel. We also provide arguments and recommendations oriented towards graduate and postdoctoral students, in academia or industry to be more entrepreneurial. We have identified that sonochemistry is consistently seen as a ‘green’ or sustainable tool, which particular appeal to process intensification approaches, including microfluidics and materials science. We conclude that a globally aligned pedagogical initiative and constantly updated educational tools will help to sustain a virtuous cycle in STEM and industrial applications of sonochemistry.

The article deals with the role and impact of advanced technologies on literary education. In the beginning, the author emphasizes fundamentally different cognitive objectives of empirical science and humanities. In the authors' opinion, the current scientification of the humanities leads to the domination of a single type of knowledge based on empiricism promoted in schools as a part of the so-called STEM education. A visible manifestation of this process is the labification of school learning methods. The laboratory metaphor may, however, be destructive for the non-science studies. Thereafter, the author outlines how advanced technologies can be used to teach literature according to the specificity of the cognitive model of philological studies. Through the example of an ongoing research project he shows how using cultural heritage sites and embedded education can enhance the process of studying literature, and thus help students develop new interpretative pathways and cognitive skills based on elements typical for digital environments and augmented reality. [ABSTRACT FROM AUTHOR]

Spatial navigation is an important aspect of everyday life but may be negatively impacted by both cognitive and affective load. Cognitive and affective load may be measured via autonomic arousal and increased load may lead to reduced navigational abilities. 53 college students (64.0% female; M age = 19.62) participated in the Virtual Reality Paced Serial Auditory Addition Task (VR-PASAT). Participants followed guides through different areas of the virtual environment (VE). In some areas participants completed the PASAT, high load, and in other areas they simply followed the guides, low load. Some participants were instructed beforehand they would perform a navigate task, increasing load. Results suggested that several psychophysiological measures including skin conductance and inter-beat intervals were impacted by increased load while others were related to the interactions between load and zone order. Awareness of the navigation task led to worse performance on the VR-PASAT, and high load decreased navigational performance. The VR-PASAT was used to implement a VE to manipulate cognitive load. This study may be useful for the creation of adaptive systems because it demonstrates that psychophysiological metrics can assess cognitive and affective load, which may impact navigation within a VE, and navigational task awareness may interact with load. [ABSTRACT FROM AUTHOR]

The scientific task, which is solved in the research, is the analysis of knowledge representation methods in intelligent decision-making support systems. The problem is explained by the fact that the form of knowledge representation significantly affects the characteristics and properties of the system. In order to operate all kinds of knowledge from the real world with the help of a computer, it is necessary to carry out their simulation. In such cases, it is necessary to distinguish knowledge intended for processing by computational devices from knowledge used by humans. In addition, with a large amount of knowledge, it is desirable to simplify the sequential management of individual elements of knowledge. A homogeneous representation leads to a simplification of the logic management mechanism and a simplification of knowledge management. The research is aimed at the analysis of knowledge representation methods in intelligent decision-making support systems. Currently, many models of knowledge representation have been developed. The main models include: logical models; frame model; network models (or semantic networks); production models. Therefore, the object of research is the intelligent decision-making support system. The subject of research is an intelligent decision-making support system. The following is set: – the methods (models, approaches) presented in the research for presenting knowledge in intelligent decision-making support systems in a canonical form are not advisable to use for a number of objective reasons given in subsection 3.1 of the research; – it is necessary to develop new (improvement of existing) representations of knowledge in intelligent decision-making support systems, which will have the advantages of these approaches without their disadvantages. Further improvement of these approaches to reduce the number of shortcomings and limitations of their application should be considered as the direction of further research. [ABSTRACT FROM AUTHOR]

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The construction of cognitive models is the basis for cognitive diagnosis, and the cognitive models will change based on the purpose of the study. According to the purpose of mathematical education, the cognitive factorization model is constructed based on the competence and knowledge dimensions. The factorization cognitive model was preliminarily constructed using expert-defined and literature surveys, and a small-scale test was subsequently carried out. The rationality of the cognitive model was tested through verbal reports and the regression of the item's difficulty through the cognitive attributes. The study included a sample of 72 students from two eighth-grade classes in a junior high school located in Wuhan. A diagnosis was made based on the mastery of factorization knowledge and the level of mathematical operation ability of the eighth graders in the cognitive model. Research 1 demonstrates that the construction of the cognitive factorization model is reasonable. Research 2 shows that approximately 79% of students' mathematics operation ability can reach the level of knowledge understanding, 71% of students can reach the level of knowledge transfer, and only 28% of students can reach the level of knowledge innovation. [ABSTRACT FROM AUTHOR]

Background: This review provides an overview of obsessive‐compulsive disorder (OCD) symptoms, including the four partially distinct subtypes of the disorder, current diagnostic criteria, and common comorbidities. Critically, it focuses on the etiology of OCD, including its underlying neuropathology, and examines cognitive dysfunction in OCD. Methods: This review study was conducted by library method. Results: We show how dysfunction in cortico‐striato‐thalamo‐cortical (CSTC) circuits may underpin symptoms; and shed light on the putative neurochemistry within these loops such as the role of serotonin, dopamine, and glutamate systems. We also show how OCD is characterized by cognitive dysfunction including problems in cognitive flexibility, visuospatial memory, response inhibition, and goal‐directed behavior, linked to aberrant activity within CSTC circuits. Conclusions: In brief, research questions we shed light on include (1) what are the symptoms in OCD; (2) what is the etiology of the disorder and do existing models explain OCD; and (3) what are key cognitive deficits in OCD and do these improve with treatment? [ABSTRACT FROM AUTHOR]

Instance-based learning theory (IBLT) is a comprehensive account of how humans make decisions from experience during dynamic tasks. Since it was first proposed almost two decades ago, multiple computational models have been constructed based on IBLT (i.e., IBL models). These models have been demonstrated to be very successful in explaining and predicting human decisions in multiple decision-making contexts. However, as IBLT has evolved, the initial description of the theory has become less precise, and it is unclear how its demonstration can be expanded to more complex, dynamic, and multi-agent environments. This paper presents an updated version of the current theoretical components of IBLT in a comprehensive and precise form. It also provides an advanced implementation of the full set of theoretical mechanisms, SpeedyIBL, to unlock the capabilities of IBLT to handle a diverse taxonomy of individual and multi-agent decision-making problems. SpeedyIBL addresses a practical computational issue in past implementations of IBL models, the curse of exponential growth, that emerges from memory-based tabular computations. When more observations accumulate over time, there is an exponential growth of the memory of instances that leads directly to an exponential slowdown of the computational time. Thus, SpeedyIBL leverages parallel computation with vectorization to speed up the execution time of IBL models. We evaluate the robustness of SpeedyIBL over an existing implementation of IBLT in decision games of increased complexity. The results not only demonstrate the applicability of IBLT through a wide range of decision-making tasks, but also highlight the improvement of SpeedyIBL over its prior implementation as the complexity of decision features the of agents increase. The library is open sourced for the use of the broad research community. [ABSTRACT FROM AUTHOR]

Years and Centuries are the measurement units used to quantify a longer time duration, while subtraction is the operation required to determine the duration based on two given time points. However, subtraction of time is a difficult skill to be mastered by many elementary students. To identify the root cause of the student's failure in performing subtraction involving the unit of time, we developed and validated the three cognitive models related to this skill by conducting a descriptive study which involved 119 Grade Five students from three Malaysian elementary schools. The cognitive diagnostic assessment developed based on the three cognitive models was used to elicit the participants' responses. Then, Attribute Hierarchy Method and Classical Test Theory were employed to analyse the data. The findings indicated that the hierarchical structures of all cognitive models are supported by the student's responses. The three student-based cognitive models were also highly consistent with the corresponding expert-based cognitive models. The cognitive models developed could guide diagnostic assessment development and diagnostic inference making. [ABSTRACT FROM AUTHOR]

This study aims to determine the effectiveness of the application of the project-based learning model to football learning outcomes. The research method used is a True experiment with a randomized posttest-only control group design. The research sample was 60 grade IX students of SMPN 4 Ciawigebang, Kuningan Regency, divided into two groups an experimental class of 30 students and 30 students for a control group. The sampling technique uses random cluster sampling. Research instruments to measure student football learning outcomes with passing-stoping tests (skills), attitude scales (affective), and knowledge tests in the form of questions (cognitive). The data analysis technique used is the independent sample test. The results showed that the application of the project-based learning model positively influenced student football learning outcomes in both psychomotor, affective, and cognitive aspects.

Abstract This paper explored entrepreneurial intentions in the Caribbean adult population using a social cognitive approach. It used the Global Entrepreneurship Monitor (GEM) Adult Population Survey (APS), which includes questions about entrepreneurial intentions of potential business owners and entrepreneurial perceptions, namely individual, entrepreneurial opportunities and socio-cultural, along with demographic and socio-economic variables. The effect of perceptions along with socio-economic control variables on entrepreneurial intentions was investigated using probit regression models. The results confirm that even after controlling for demographic and socio-economic and country fixed effects, social cognitive perceptions were indeed relevant in explaining entrepreneurial intentions in the region. This study therefore provides insights into understanding entrepreneurship in particular the decision to form a new business through the individual’s perceptions and intentions.

User models that can directly use and learn how to do tasks with unmodified interfaces would be helpful in system design to compare task knowledge and times between interfaces. Including user errors can be helpful because users will always make mistakes and generate errors. We compare three user models: an existing validated model that simulates users' behavior in the Dismal spreadsheet in Emacs, a newly developed model that interacts with an Excel spreadsheet, and a new model that generates and fixes user errors. These models are implemented using a set of simulated eyes and hands extensions. All the models completed a 14-step task without modifying the system that participants used. These models predict that the task in Excel is approximately 20% faster than in Dismal, including suggesting why, where, and how much Excel is a better design. The Excel model predictions were compared to newly collected human data (N = 23). The model's predictions of subtask times correlate well with the human data (r2 =.71). We also present a preliminary model of human error and correction based on user keypress errors, including 25 slips. The predictions to data comparison suggest that this interactive model that includes errors moves us closer to having a complete user model that can directly test interface design by predicting human behavior and performing the task on the same interface as users. The errors from the model's hands also allow further exploration of error detection, error correction, and different knowledge types in user models. [ABSTRACT FROM AUTHOR]

Abstract Background This review provides an overview of obsessive‐compulsive disorder (OCD) symptoms, including the four partially distinct subtypes of the disorder, current diagnostic criteria, and common comorbidities. Critically, it focuses on the etiology of OCD, including its underlying neuropathology, and examines cognitive dysfunction in OCD. Methods This review study was conducted by library method. Results We show how dysfunction in cortico‐striato‐thalamo‐cortical (CSTC) circuits may underpin symptoms; and shed light on the putative neurochemistry within these loops such as the role of serotonin, dopamine, and glutamate systems. We also show how OCD is characterized by cognitive dysfunction including problems in cognitive flexibility, visuospatial memory, response inhibition, and goal‐directed behavior, linked to aberrant activity within CSTC circuits. Conclusions In brief, research questions we shed light on include (1) what are the symptoms in OCD; (2) what is the etiology of the disorder and do existing models explain OCD; and (3) what are key cognitive deficits in OCD and do these improve with treatment?

Given identical informational content, the order in which youreceive spatial information may heavily influence the correct-ness of your mental representation. This can reveal importantinsights into the specifics of human spatial cognition and theway we integrate information. Despite its importance in ev-eryday life, its causes and the mental processes involved stillremain an open question. Most cognitive models so far havefocused on modeling only answer distributions or just the mostfrequent answer given by all participants.In this paper we take a rather radical approach: We turn tothe individual spatial reasoner and focus our analyses on thestream of spatial information and related reaction times, i.e.,how the spatial information is represented and cognitively pro-cessed. By spanning a space of 243 cognitive spatial models,some of which outperform the current state-of-the art models,it is possible to test the goodness of general principles under-lying such models.

The present article engages with multidimensional analysis of autointertextuality, putting forward a cognitive approach based on V. Evans' Cognitive Model and Lexical Concepts (LCCM) Theory. Taking into consideration a variety of viewpoints introduced in the current article, reference is made to traditional and most recent approaches provided by both Russian and European scholars for the purpose of analyzing intertextuality from the cognitive point of view, putting the imperative on the mental processes occurring in the literary text. The current article explores Roald Dahl's perception of the concept of "crime" through the prism of cognitive intertextuality. The subject matter of the article is the comprehensive analysis of the techniques employed in the literary text which can serve as prerequisites for the study of autointertextual relations. The topicality is determined by the current tendency of cognitive linguistics to interpret the literary text through the lens of semantic intertextual frames. Eventually, our research is devoted to the study of the concept of "crime" in R. Dahl's stories in the view of intertextual domain with reference to autointertextuality. [ABSTRACT FROM AUTHOR]

Background and hypothesis A plausible cause of distress for voice hearers is listening to and believing the threats and criticisms heard. Qualitative research indicates that patients have understandable reasons to listen. This study aimed to develop the understanding of distress using this listening and believing framework. Measures were developed of listening and believing voices and the reasons, and associations with distress tested. Study design A cross-sectional study of patients hearing derogatory and threatening voices (N  = 591). Listening and Believing–Assessment and Listening and Believing–Reasons item pools were completed, and assessments of distress. Exploratory and confirmatory factor analyses and structural equation modeling (SEM) were conducted. Study results 52% (n  = 307) of participants believed their voices most or all the time. Listening and believing had 4 factors: active listening, passive listening, believing, and disregarding. Higher levels of believing, active listening, and particularly passive listening were associated with higher levels of anxiety, depression, and voice distress. Reasons for listening and believing formed 7 factors: to better understand the threat; being too worn down to resist; to learn something insightful; being alone with time to listen; voices trying to capture attention; voices sounding like real people; and voices sounding like known people. Each type of reason was associated with active listening, passive listening, and believing. SEM showed that feeling worn down in particular accounted for listening and believing. Test–retest reliability of measures was excellent. Conclusions A framework of listening and believing negative voices has the potential to inform the understanding and treatment of voice distress. [ABSTRACT FROM AUTHOR]

This paper analyzes metaphorical conceptualizations of happiness in the historical corpus of Classical Malay and in the corpus of present-day Indonesian, the national variety of Malay used in Indonesia. The aim is to explore the idea of diachronic salience and universal/variation in metaphorical conceptualizations between diachronic varieties of the same language. Token and type frequencies are used as measures of salience of the metaphors. Seven of the top-10 metaphors in Classical Malay with high token and type frequencies also make into the top-10 metaphors ranked by these measures in Indonesian, suggesting a relatively stable diachronic salience of the metaphoric cognitive models of happiness in these two Malay varieties. The shared metaphors are parts of larger networks of semantic domains, namely possession, location, motion, containment, and quantity. The metaphors are discussed in relation to themes reported in earlier cross-cultural psychological studies of the cultural folk models of happiness. [ABSTRACT FROM AUTHOR]

Human body experience is remarkably flexible, which enables us to integrate passive tools as well as intelligent robotic devices into our body representation. Accordingly, it can serve as a role model to make (assistive) robots interact seamlessly with their users or to provide (humanoid) robots with a human-like self-perception and behavior generation. This article discusses the potential of understanding human body experience and applying it to robotics. Particular focus is set on how to use artificial intelligence techniques and create intelligent artificial agents from insights about human body experience. The discussion is based on a summary of the author's habilitation thesis and combines theoretical and experimental perspectives from psychology, cognitive science and neuroscience as well as computer science, engineering, and artificial intelligence. From this, it derives directions for future developments towards creating artificial body intelligence with human-like capabilities. [ABSTRACT FROM AUTHOR]

The language of emotions is culturally conditioned and a conceptualization of emotions is determined by the value systems adopted in given cultures, as well as by personal experiences in recognizing, valuing, and communicating those emotions. It is believed that sometimes certain emotions have no lexical equivalents in particular languages. Even within one culture and one language, we can observe a gray area in the meaning of terms from this field. This is not surprising, given the subjective perception of the world by each member of a specific community, as well as the multitude of emotions themselves. Although most information about other people's emotions comes to the recipients through language, talking or writing about them is not simple. Emotions are among the concepts that are not very clearly delineated in our experience and therefore other, more comprehensible concepts, such as spatial orientations or objects, should be used when referring to them. In the novel The Slynx by Tatyana Tolstaya, emotions are conceptualized and represented for instance by liquids, small animals, natural forces, and substances with some specific taste (sour, bitter, etc.). Our goal was to figure out which emotions and their linguistic instantiations are only typical for the Russian language and which ones would fall in the universal category. The paper will focus on the description and the way emotions are conceptualized from a cognitive linguistic perspective, drawing on CMT (Conceptual Metaphor Theory), conceptual metonymies, and cognitive models. [ABSTRACT FROM AUTHOR]

This paper explored entrepreneurial intentions in the Caribbean adult population using a social cognitive approach. It used the Global Entrepreneurship Monitor (GEM) Adult Population Survey (APS), which includes questions about entrepreneurial intentions of potential business owners and entrepreneurial perceptions, namely individual, entrepreneurial opportunities and socio-cultural, along with demographic and socio-economic variables. The effect of perceptions along with socio-economic control variables on entrepreneurial intentions was investigated using probit regression models. The results confirm that even after controlling for demographic and socio-economic and country fixed effects, social cognitive perceptions were indeed relevant in explaining entrepreneurial intentions in the region. This study therefore provides insights into understanding entrepreneurship in particular the decision to form a new business through the individual's perceptions and intentions. [ABSTRACT FROM AUTHOR]