Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science

UTP2: Higher-Order Equational Reasoning by Pointing

We describe a prototype theorem prover, UTP2, developed to match the style of hand-written proof work in the Unifying Theories of Programming semantical framework. This is based on alphabetised predicates in a 2nd-order logic, with a strong emphasis on equational reasoning. We present here an overview of the user-interface of this prover, which was developed from the outset using a point-and-click approach. We contrast this with the command-line paradigm that continues to dominate the mainstream theorem provers, and raises the question: can we have the best of both worlds?Comment: In Proceedings UITP 2014, arXiv:1410.785

Integrating Information Flow Analysis in Unifying Theories of Programming

This research is supported by the China National R&D Key Research Program (2019YFB1705703) and the In-terdisciplinary Program of SJTU, Shanghai, China (No. YG2019ZDA07).Postprin

From Endings Come Beginnings: Facilitating the Transition from Ending Student to Beginning Practitioner

This presentation was part of the session : Pedagogy: Theories, Approaches24th National Conference on the Beginning Design StudentThe receipt of a degree is momentous; it is at once the end of an academic career and the beginning of practice life. Terminal coursework thus becomes a critical component in successfully preparing students for the classroom-to-office transition. Essential to student preparedness is the ability to critically analyze, synthesize and apply myriad skills and knowledge. Critical thinking and problem solving require an understanding of the intimate relationship between various aspects of theory, research, applied design, and construction methods, materials, and documentation technologies. Equally as important is the development of student confidence and ownership. The lessons offered within a final studio should therefore integrate these elements into a comprehensive process promoting independent exploration, discovery, and application. This approach allows students to make their own connections between design skills and, in turn, transform abstract knowledge into applied understanding. Armed with a holistic comprehension of core fundamentals, emerging practitioners can effectively, efficiently and creatively address the innumerable challenges of professional practice. This paper discusses the application of these ideals into a graduate level, terminal design studio. The exploration of meaning is used to organize the studio around a variety of in-depth urban design projects. Student work is augmented with a reading and discussion seminar that highlights the need for reading, writing and verbal skills in the design process, as well as promotes the continued use of theory and research within professional practice. In total, student design explorations represent successful theory-to-practice applications related to urban landscapes at scales ranging from 1"=40'-0" to 1/8"=1'-0"

Mixed-Integer Convex Nonlinear Optimization with Gradient-Boosted Trees Embedded

Decision trees usefully represent sparse, high dimensional and noisy data. Having learned a function from this data, we may want to thereafter integrate the function into a larger decision-making problem, e.g., for picking the best chemical process catalyst. We study a large-scale, industrially-relevant mixed-integer nonlinear nonconvex optimization problem involving both gradient-boosted trees and penalty functions mitigating risk. This mixed-integer optimization problem with convex penalty terms broadly applies to optimizing pre-trained regression tree models. Decision makers may wish to optimize discrete models to repurpose legacy predictive models, or they may wish to optimize a discrete model that particularly well-represents a data set. We develop several heuristic methods to find feasible solutions, and an exact, branch-and-bound algorithm leveraging structural properties of the gradient-boosted trees and penalty functions. We computationally test our methods on concrete mixture design instance and a chemical catalysis industrial instance