Inference with interference between units in an fMRI experiment of motor inhibition

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

Strange Quarks Nuggets in Space: Charges in Seven Settings

We have computed the charge that develops on an SQN in space as a result of balance between the rates of ionization by ambient gammas and capture of ambient electrons. We have also computed the times for achieving that equilibrium and binding energy of the least bound SQN electrons. We have done this for seven different settings. We sketch the calculations here and give their results in the Figure and Table II; details are in the Physical Review D.79.023513 (2009).Comment: Six pages, one figure. To appear in proceedings of the 2008 UCLA coference on dark matter and dark energ

Conductivity of Metallic Si:B near the Metal-Insulator Transition: Comparison between Unstressed and Uniaxially Stressed Samples

The low-temperature dc conductivities of barely metallic samples of p-type Si:B are compared for a series of samples with different dopant concentrations, n, in the absence of stress (cubic symmetry), and for a single sample driven from the metallic into the insulating phase by uniaxial compression, S. For all values of temperature and stress, the conductivity of the stressed sample collapses onto a single universal scaling curve. The scaling fit indicates that the conductivity of si:B is proportional to the square-root of T in the critical range. Our data yield a critical conductivity exponent of 1.6, considerably larger than the value reported in earlier experiments where the transition was crossed by varying the dopant concentration. The larger exponent is based on data in a narrow range of stress near the critical value within which scaling holds. We show explicitly that the temperature dependences of the conductivity of stressed and unstressed Si:B are different, suggesting that a direct comparison of the critical behavior and critical exponents for stress- tuned and concentration-tuned transitions may not be warranted

The ⋆\star-value Equation and Wigner Distributions in Noncommutative Heisenberg algebras

We consider the quantum mechanical equivalence of the Seiberg-Witten map in the context of the Weyl-Wigner-Groenewold-Moyal phase-space formalism in order to construct a quantum mechanics over noncommutative Heisenberg algebras. The formalism is then applied to the exactly soluble Landau and harmonic oscillator problems in the 2-dimensional noncommutative phase-space plane, in order to derive their correct energy spectra and corresponding Wigner distributions. We compare our results with others that have previously appeared in the literature.Comment: 19 page

Critical Behavior of the Conductivity of Si:P at the Metal-Insulator Transition under Uniaxial Stress

We report new measurements of the electrical conductivity sigma of the canonical three-dimensional metal-insulator system Si:P under uniaxial stress S. The zero-temperature extrapolation of sigma(S,T -> 0) ~\S - S_c\^mu shows an unprecidentedly sharp onset of finite conductivity at S_c with an exponent mu = 1. The value of mu differs significantly from that of earlier stress-tuning results. Our data show dynamical sigma(S,T) scaling on both metallic and insulating sides, viz. sigma(S,T) = sigma_c(T) F(\S - S_cT^y) where sigma_c(T) is the conductivity at the critical stress S_c. We find y = 1/znu = 0.34 where nu is the correlation-length exponent and z the dynamic critical exponent.Comment: 5 pages, 4 figure

Bimanual grasp planning reflects changing rather than fixed constraint dominance

We studied whether motor-control constraints for grasping objects that are moved to new positions reflect a rigid constraint hierarchy or a flexible constraint hierarchy. In two experiments, we asked participants to move two plungers from the same start locations to different target locations (both high, both low, or one high and one low). We found that participants grasped the plungers symmetrically and at heights that ensured comfortable or easy-to-control end postures when the plungers had the same target heights, but these grasp tendencies were reduced when the plungers had different target heights. In addition, when the plungers had different mass distributions, participants behaved in ways that suggested still-different emphases of the relevant grasp constraints. When the plungers had different mass distributions, participants sacrificed bimanual symmetry for end-state comfort. The results suggest that bimanual grasp planning relies on a flexible rather than static hierarchy. Different constraints take on different degrees of importance depending on the nature of the task and on the level of task experience. The results have implications for the understanding of perceptual-motor skill learning. It may be that one mechanism underlying such learning is changing the priorities of task constraints

IR Kuiper Belt Constraints

We compute the temperature and IR signal of particles of radius $a$ and albedo $\alpha$ at heliocentric distance $R$, taking into account the emissivity effect, and give an interpolating formula for the result. We compare with analyses of COBE DIRBE data by others (including recent detection of the cosmic IR background) for various values of heliocentric distance, $R$, particle radius, $a$, and particle albedo, $\alpha$. We then apply these results to a recently-developed picture of the Kuiper belt as a two-sector disk with a nearby, low-density sector (40<R<50-90 AU) and a more distant sector with a higher density. We consider the case in which passage through a molecular cloud essentially cleans the Solar System of dust. We apply a simple model of dust production by comet collisions and removal by the Poynting-Robertson effect to find limits on total and dust masses in the near and far sectors as a function of time since such a passage. Finally we compare Kuiper belt IR spectra for various parameter values.Comment: 34 pages, LaTeX, uses aasms4.sty, 11 PostScript figures not embedded. A number of substantive comments by a particularly thoughtful referee have been addresse

SPECIFIC TRAINING CAN IMPROVE SENSORIMOTOR CONTROL IN TYPE 2 DIABETIC PATIENTS

Diabetes mellitus often is associated with proprioceptive and sensory deficits as a result of distal diabetic polyneuropathy (DPN). The aim of this prospective controlled longitudinal trial was to evaluate a specific sport intervention program regarding sensorimotor capabilities in type 2 diabetic patients compared to healthy controls. A higher incidence of fall-related injuries is given in the literature (Allet et al.2008; Allet et al 2009)

Interpreting random forest classification models using a feature contribution method

Model interpretation is one of the key aspects of the model evaluation process. The explanation of the relationship between model variables and outputs is relatively easy for statistical models, such as linear regressions, thanks to the availability of model parameters and their statistical significance . For “black box” models, such as random forest, this information is hidden inside the model structure. This work presents an approach for computing feature contributions for random forest classification models. It allows for the determination of the influence of each variable on the model prediction for an individual instance. By analysing feature contributions for a training dataset, the most significant variables can be determined and their typical contribution towards predictions made for individual classes, i.e., class-specific feature contribution “patterns”, are discovered. These patterns represent a standard behaviour of the model and allow for an additional assessment of the model reliability for new data. Interpretation of feature contributions for two UCI benchmark datasets shows the potential of the proposed methodology. The robustness of results is demonstrated through an extensive analysis of feature contributions calculated for a large number of generated random forest models

The Electron Glass in a Switchable Mirror: Relaxation, Aging and Universality

The rare earth hydride YH$_{3-\delta}$ can be tuned through the metal-insulator transition both by changing $\delta$ and by illumination with ultraviolet light. The transition is dominated by strong electron-electron interactions, with transport in the insulator sensitive to both a Coulomb gap and persistent quantum fluctuations. Via a systematic variation of UV illumination time, photon flux, Coulomb gap depth, and temperature, we demonstrate that polycrystalline YH$_{3-\delta}$ serves as a model system for studying the properties of the interacting electron glass. Prominent among its features are logarithmic relaxation, aging, and universal scaling of the conductivity