Deep Cover HCI

The growing popularity of methodologies that turn "to the wild" for real world data creates new ethical issues for the HCI community. For investigations questioning interactions in public or transient spaces, crowd interaction, or natural behaviour, uncontrolled and uninfluenced (by the experimenter) experiences represent the ideal evaluation environment. We argue that covert research can be completed rigorously and ethically to expand our knowledge of ubiquitous technologies. Our approach, which we call Deep Cover HCI, utilises technology-supported observation in public spaces to stage completely undisturbed experiences for evaluation. We complete studies without informed consent and without intervention from an experimenter in order to gain new insights into how people use technology in public settings. We argue there is clear value in this approach, reflect on the ethical issues of such investigations, and describe our ethical guidelines for completing Deep Cover HCI Research

Regression relation for pure quantum states and its implications for efficient computing

We obtain a modified version of the Onsager regression relation for the expectation values of quantum-mechanical operators in pure quantum states of isolated many-body quantum systems. We use the insights gained from this relation to show that high-temperature time correlation functions in many-body quantum systems can be controllably computed without complete diagonalization of the Hamiltonians, using instead the direct integration of the Schroedinger equation for randomly sampled pure states. This method is also applicable to quantum quenches and other situations describable by time-dependent many-body Hamiltonians. The method implies exponential reduction of the computer memory requirement in comparison with the complete diagonalization. We illustrate the method by numerically computing infinite-temperature correlation functions for translationally invariant Heisenberg chains of up to 29 spins 1/2. Thereby, we also test the spin diffusion hypothesis and find it in a satisfactory agreement with the numerical results. Both the derivation of the modified regression relation and the justification of the computational method are based on the notion of quantum typicality.Comment: 16 pages, 4 figures; minor textual corrections; parts rearrange

Random Variables Recorded under Mutually Exclusive Conditions: Contextuality-by-Default

We present general principles underlying analysis of the dependence of random variables (outputs) on deterministic conditions (inputs). Random outputs recorded under mutually exclusive input values are labeled by these values and considered stochastically unrelated, possessing no joint distribution. An input that does not directly influence an output creates a context for the latter. Any constraint imposed on the dependence of random outputs on inputs can be characterized by considering all possible couplings (joint distributions) imposed on stochastically unrelated outputs. The target application of these principles is a quantum mechanical system of entangled particles, with directions of spin measurements chosen for each particle being inputs and the spins recorded outputs. The sphere of applicability, however, spans systems across physical, biological, and behavioral sciences.Comment: In H. Liljenstr\"om (Ed.) Advances in Cognitive Neurodynamics IV (pp. 405-410) (2015

Lyapunov instabilities in lattices of interacting classical spins at infinite temperature

We numerically investigate Lyapunov instabilities for one-, two- and three-dimensional lattices of interacting classical spins at infinite temperature. We obtain the largest Lyapunov exponents for a very large variety of nearest-neighbor spin-spin interactions and complete Lyapunov spectra in a few selected cases. We investigate the dependence of the largest Lyapunov exponents and whole Lyapunov spectra on the lattice size and find that both quickly become size-independent. Finally, we analyze the dependence of the largest Lyapunov exponents on the anisotropy of spin-spin interaction with the particular focus on the difference between bipartite and nonbipartite lattices

GliomaPredict: A Clinically Useful Tool for Assigning Glioma Patients to Specific Molecular Subtypes

Background: Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine. Results: We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework. Conclusions: GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decisionmaking. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas

The Impact of Right-to-Work Laws on Union Organizing

In contrast to previous studies which have examined the impact of Right-to-Work (RTW) laws on the level or stock of union membership, this paper examines their impact on the most updated flow into membership and the organizing of workers through certified elections. Since detailed annual data are available by state, we are able to estimate an accelerator model of the flow into unionism, and adjust for possible omitted variable and simultaneity bias. The results show dramatic falls in organizing immediately after the passage of a RTW law, with more moderate declines in later years, just as an accelerator model could predict. Overall, the results are consistent with a 5-10 percent reduction in unionism as a result of the passage of RTW laws.