1,720,974 research outputs found
Relating imperatives to action
Full text linkThe aim of this chapter is to provide an analysis of the use of logically complex imperatives, in particular, imperatives of the form Do A1 or A2 and Do A, if B. We argue for an analysis of imperatives in terms of classical logic which takes into account the influence of background information on imperatives. We show that by doing so one can avoid some counter-intuitive results which have been associated with analyses of imperatives in terms of classical logic. In particular, I address Hamblin's observations concerning rule-like imperatives and Ross' Paradox. The analysis is carried out within an agent-based logical framework. This analysis explicates what it means for an agent to have a successful policy for action with respect to satisfying his or her commitments, where some of these commitments have been introduced as a result of imperative language use
GASICA: Design, validation and use of a system for inducing and controlling physiological stress
No full textStress is a prevalent condition in the Western world. In the Netherlands, a recent study reported the costs of stress to be around 4 billion euro per year, only factoring in work-related stress. In addition, the societal and individual impact of stress is high: the same study estimated that every year 150.000 to 300.000 people are unable to work, and one out of seven people who receive WAO (dispensation for people who are incapacitated for work) is estimated to be in that position due to stress. It is therefore relevant and beneficial to our society to perform research into stress. Research enables us to determine the factors causing stress and the systems underlying our responses to these factors, providing insights for developing prevention and therapies for stress. Therefore, we performed a series of research into the human physiological stress system. Starting point of our research was the recognition of three general requirements that must be fulfilled in stress research, in order to adequately interpret and compare the obtained results. These are: standardization of the methods used, precision of the stressor definition and control of the stress status of the human subject. To aid in fulfilling these requirements, we developed a novel application: the Generic Automated Stress Induction and Control Application (GASICA). In this application we utilized a digital game as a stressor. Moreover, a set of measurements devices and a feedback loop were used to control the stressor characteristics, and in turn the stress status of the subject. Validation of GASICA showed that the application was able to induce both acute and more chronic stress responses and was able to significantly predict the physiological response for the majority of the presented stressors. With respect to control, GASICA was found to correctly predict around 20% of the responses using individually fitted models. We concluded, however, that this is insufficient for an adequate control of the stress status. The application of GASICA as a research tool revealed fundamental insights into the working of physiological stress response system. We found that, in general, the cardiovascular system responds more specific to presented stressors than the sympathetic nervous system. We also found that the acute electrodermal response is significantly higher for non-symbolic stressors compared to symbolic stressors, and that the acute heart rate response for females is higher to visual stressors compared to auditory stressors. Finally, we found indications that the height of the acute response to a stressor combination is a linear function of the amount of stressors presented simultaneously. These insights could provide starting points for further research and potential interventions. To improve our application, we propose several development steps, such as improving the user friendliness of the application, in order to allow GASICA to be adopted as a novel standard for stress induction and control. Future use of GASICA in several fields is envisioned, for example by examining whether the individually fitted models can be used for diagnosing and/or predicting stress related illnesses. Given our findings, we believe that GASICA has potential as a standard for ecological valid research of the human physiological stress system in various research, training and therapeutic situations
GASICA: Design, validation and use of a system for inducing and controlling physiological stress
No full textStress is a prevalent condition in the Western world. In the Netherlands, a recent study reported the costs of stress to be around 4 billion euro per year, only factoring in work-related stress. In addition, the societal and individual impact of stress is high: the same study estimated that every year 150.000 to 300.000 people are unable to work, and one out of seven people who receive WAO (dispensation for people who are incapacitated for work) is estimated to be in that position due to stress. It is therefore relevant and beneficial to our society to perform research into stress. Research enables us to determine the factors causing stress and the systems underlying our responses to these factors, providing insights for developing prevention and therapies for stress. Therefore, we performed a series of research into the human physiological stress system. Starting point of our research was the recognition of three general requirements that must be fulfilled in stress research, in order to adequately interpret and compare the obtained results. These are: standardization of the methods used, precision of the stressor definition and control of the stress status of the human subject. To aid in fulfilling these requirements, we developed a novel application: the Generic Automated Stress Induction and Control Application (GASICA). In this application we utilized a digital game as a stressor. Moreover, a set of measurements devices and a feedback loop were used to control the stressor characteristics, and in turn the stress status of the subject. Validation of GASICA showed that the application was able to induce both acute and more chronic stress responses and was able to significantly predict the physiological response for the majority of the presented stressors. With respect to control, GASICA was found to correctly predict around 20% of the responses using individually fitted models. We concluded, however, that this is insufficient for an adequate control of the stress status. The application of GASICA as a research tool revealed fundamental insights into the working of physiological stress response system. We found that, in general, the cardiovascular system responds more specific to presented stressors than the sympathetic nervous system. We also found that the acute electrodermal response is significantly higher for non-symbolic stressors compared to symbolic stressors, and that the acute heart rate response for females is higher to visual stressors compared to auditory stressors. Finally, we found indications that the height of the acute response to a stressor combination is a linear function of the amount of stressors presented simultaneously. These insights could provide starting points for further research and potential interventions. To improve our application, we propose several development steps, such as improving the user friendliness of the application, in order to allow GASICA to be adopted as a novel standard for stress induction and control. Future use of GASICA in several fields is envisioned, for example by examining whether the individually fitted models can be used for diagnosing and/or predicting stress related illnesses. Given our findings, we believe that GASICA has potential as a standard for ecological valid research of the human physiological stress system in various research, training and therapeutic situations
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dialogue and Instruction: Modeling Interaction in Intelligent Tutoring Systems
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