Science and Theology: A Working Synthesis

Theologians and scientists, working independently, have provided worldviews that lead to questions about the meaning of existence and human life. When these disciplines interact, opportunity exists for more profound insight. Two individuals, Johannes Kepler in the sixteenth century and Pierre Teilhard de Chardin in the twentieth, attempted theological reconstructions based on revolutionary theories of their eras. Informed by a fierce faith in God and a rigorous pursuit of truth derived from the scientific method, their attempts at synthesizing these fields led to results that were unexpected, even unwanted. Yet they provide lessons in the present age for interpretations of the new discoveries and the responsibility of humankind to play an active role in the modern creation story

Equivalence among different formalisms in the Tsallis entropy framework

In a recent paper [Phys. Lett. A {\bf335}, 351 (2005)] the authors discussed the equivalence among the various probability distribution functions of a system in equilibrium in the Tsallis entropy framework. In the present letter we extend these results to a system which is out of equilibrium and evolves to a stationary state according to a nonlinear Fokker-Planck equation. By means of time-scale conversion, it is shown that there exists a ``correspondence'' among the self-similar solutions of the nonlinear Fokker-Planck equations associated with the different Tsallis formalisms. The time-scale conversion is related to the corresponding Lyapunov functions of the respective nonlinear Fokker-Planck equations.Comment: 20 pages, 1 figure, Elsart macro style, version accepted on Physica

Developments in Qualitative Mindfulness Practice Research: a Pilot Scoping Review

Objectives While scholars are increasingly emphasizing the potential of qualitative mindfulness practice research (QMPR) for advancing the understanding of mindfulness practice, there has been no significant empirical inquiry looking at actual trends and practices of QMPR. Consequently, it has been impossible to direct research practices toward under-researched areas and make methodical suggestions on how to approach them. The aim of the present study was to analyze current trends and practices in QMPR in order to address these areas of need. Methods Based on a scoping review, 229 qualitative studies published between 2000 and 2019 were analyzed in regard to their disciplinary backgrounds, research questions and intentions, type of mindfulness practice, target population, as well as practices of data collection and analysis. Results A strong focus of QMPR lies in the inquiry of mindfulness-based interventions, particularly mindfulness-based stress reduction, mindfulness-based cognitive therapy, and adaptations. Over 10% of the publications do not fully specify the mindfulness practice. The efficacy and subjective experience of mindfulness practices constitute the dominant research interests of QMPR. Data collection is highly concentrated on practice participants and first-person data. Interpretative paradigms are the predominant analytical approach within QMPR. QMPR studies have a strong proclivity toward emphasizing the positive effects of mindfulness practice. Nine percent of all articles considered for our study did not fully disclose their analytical procedure. Adversarial research groups and pluralistic qualitative research remain scarce. Conclusions Future QMPR should (i) include second- and third-person data, (ii) include dropouts and former mindfulness practitioners, (iii) fully disclose details on the mindfulness practice and data analysis, (iv) intensify the application of critical and deconstructivist paradigms, as well as pluralistic qualitative research, and (v) build adversarial research teams.Leuphana Universität Lüneburg (3117)Peer Reviewe

BLADE: Filter Learning for General Purpose Computational Photography

The Rapid and Accurate Image Super Resolution (RAISR) method of Romano, Isidoro, and Milanfar is a computationally efficient image upscaling method using a trained set of filters. We describe a generalization of RAISR, which we name Best Linear Adaptive Enhancement (BLADE). This approach is a trainable edge-adaptive filtering framework that is general, simple, computationally efficient, and useful for a wide range of problems in computational photography. We show applications to operations which may appear in a camera pipeline including denoising, demosaicing, and stylization

Transforming Consumer Behavior: Introducing Self-Inquiry-Based and Self-Experience-Based Learning for Building Personal Competencies for Sustainable Consumption

Despite growing educational efforts in various areas of society and albeit expanding knowledge on the background and consequences of consumption, little has changed about individual consumer behavior and its detrimental impact. Against this backdrop, some scholars called for a stronger focus on personal competencies, especially affective–motivational ones to foster more sustainable consumption. Such competencies, however, are rarely addressed within the context of education for sustainable consumption. Responding to this gap, we suggest two new learning formats that allow students to systematically acquire affective–motivational competencies: self-inquiry-based learning (SIBL) and self-experience-based learning (SEBL). We developed these approaches at Leuphana University Lüneburg, Germany, since 2016, and applied them within the framework of two seminars called Personal Approaches to Sustainable Consumption. Conducting scholarship of teaching and learning, we investigated the potential of SIBL and SEBL for cultivating personal competencies for sustainable development in general and sustainable consumption in particular. Our results indicate that SIBL and SEBL are promising approaches for this purpose

Security and Privacy of Personal Health Records in Cloud Computing Environments – An Experimental Exploration of the Impact of Storage Solutions and Data Breaches

In the course of the digitization in healthcare, the collection and central storage of large health-related datasets in clouds in the form of personal health records is growing. However, the use of cloud services for sensitive data is associated with security and privacy risks. Further, the delegation of control over security and privacy measures to the cloud provider requires trust on the users’ side. In order to investigate the role of security and privacy when storing and processing patient data, we conducted an online experiment, in which third-party cloud services are compared to private on-premise data centers. Additionally, we examine the impact of data breaches on the perceived security, privacy, control and trust in both storage scenarios. Our results indicate that cloud-based personal health records still face concerns regarding perceived security, privacy, control and trust amongst end-users. Nevertheless, after a data breach, no significant differences between both solutions exist

A Survey of Languages for Specifying Dynamics: A Knowledge Engineering Perspective

A number of formal specification languages for knowledge-based systems has been developed. Characteristics for knowledge-based systems are a complex knowledge base and an inference engine which uses this knowledge to solve a given problem. Specification languages for knowledge-based systems have to cover both aspects. They have to provide the means to specify a complex and large amount of knowledge and they have to provide the means to specify the dynamic reasoning behavior of a knowledge-based system. We focus on the second aspect. For this purpose, we survey existing approaches for specifying dynamic behavior in related areas of research. In fact, we have taken approaches for the specification of information systems (Language for Conceptual Modeling and TROLL), approaches for the specification of database updates and logic programming (Transaction Logic and Dynamic Database Logic) and the generic specification framework of abstract state machine