Development of a data management tool for investigating multivariate space and free will experiences in virtual reality.

Virtual reality (VR) has become mature enough to be successfully used in clinical applications such as exposure therapy, pain distraction, and neuropsychological assessment. However, we now need to go beyond the outcome data from this research and conduct the detailed scientific investigations required to better understand what factors influence why VR works (or doesn't) in these types of clinical applications. This knowledge is required to guide the development of VR applications in the key areas of education, training, and rehabilitation and to further evolve existing VR approaches. One of the primary assets obtained with the use of VR is the ability to simulate the complexity of real world environments, within which human performance can be tested and trained. But this asset comes with a price in terms of the capture, quantification and analysis of large, multivariate and concurrent data sources that reflect the naturalistic behavioral interaction that is afforded in a virtual world. As well, while achieving realism has been a main goal in making convincing VR environments, just what constitutes realism and how much is needed is still an open question situated firmly in the research domain. Just as in real "reality," such factors in virtual reality are complex and multivariate, and the understanding of this complexity presents exceptional challenges to the VR researcher. For certain research questions, good behavioral science often requires consistent delivery of stimuli within tightly controlled lab-based experimental conditions. However, for other important research questions we do not want to constrain naturalistic behavior and limit VR's ability to replicate real world conditions, simply because it is easier to study human performance with traditional lab-based methodologies. By doing so we may compromise the very qualities that comprise VR's unique capacity to mimic the experiences and challenges that exist in everyday life. What is really needed to address scientific questions that require natural exploration of a simulated environment are more usable and robust tools to instrument, organize, and visualize the complex data generated by measurements of participant behaviors within a virtual world. This paper briefly describes the rationale and methodology of an initial study in an ongoing research program that aims to investigate human performance within a virtual environment where unconstrained "free will" exploratory behavior is essential to research questions that involve the relationships between physiology, emotion, and memory. After a discussion of the research protocol and the types of data that were collected, we describe a novel tool that was borne from our need to more efficiently capture, manage, and explore the complex data that was generated in this research. An example of a research participant's annotated display from this data management and visualization tool is then presented. It is our view that this tool provides the capacity to better visualize and understand the complex data relationships that may arise in VR research that investigates naturalistic free will behavior and its impact on other human performance variables.

Theoretical and experimental investigation of the effect of proton transfer on the (27)al MAS NMR line shapes of zeolite-adsorbate complexes: an independent measure of solid Acid strength.

Assessing the degree of proton transfer from a Brønsted acid site to one or more adsorbed bases is central to arguments regarding the strength of zeolites and other solid acids. In this regard certain solid-state NMR measurements have been fruitful; for example, some (13)C, (15)N, or (31)P resonances of adsorbed bases are sensitive to protonation, and the (1)H chemical shift of the Brønsted site itself reflects hydrogen bonding. We modeled theoretically the structures of adsorption complexes of several bases on zeolite HZSM-5, calculated the quadrupole coupling constants (Q(cc)) and asymmetry parameters (eta) for aluminum in these complexes and then in turn simulated the central transitions of their (27)Al MAS NMR spectra. The theoretical line width decreased monotonically with the degree of proton transfer, reflecting structural relaxation around aluminum as the proton was transferred to a base. We verified this experimentally for a series of adsorbed bases by way of single-pulse MAS and triple quantum MQMAS (27)Al NMR. The combined theoretical and experimental approach described here provides a strategy by which (27)Al data can be applied to resolve disputed interpretations of proton transfer based on other evidence.