Relation between vibrotactile perception thresholds and reductions in finger blood flow induced by vibration of the hand at frequencies in the range 8–250 Hz

Purpose: this study investigated how the vasoconstriction induced by vibration depends on the frequency of vibration when the vibration magnitude is defined by individual thresholds for perceiving vibration [i.e. sensation levels (SL)].Methods: fourteen healthy subjects attended the laboratory on seven occasions: for six vibration frequencies (8, 16, 31.5, 63, 125, or 250 Hz) and a static control condition. Finger blood flow (FBF) was measured in the middle fingers of both hands at 30-second intervals during five successive periods: (i) no force or vibration, (ii) 2-N force, no vibration, (iii) 2-N force, vibration, (iv) 2-N force, no vibration, (v) no force or vibration. During period (iii), vibration was applied to the right thenar eminence via a 6-mm diameter probe during ten successive 3-min periods as the vibration magnitude increased in ten steps (?10 to +40 dB SL).Results: with vibration at 63, 125, and 250 Hz, there was vasoconstriction on both hands when the vibration magnitude reached 10 dB SL. With vibration at 8, 16, and 31.5 Hz, there was no significant vasoconstriction until the vibration reached 25 dB SL. At all frequencies, there was greater vasoconstriction with greater magnitudes of vibration.Conclusions: it is concluded that at the higher frequencies (63, 125, and 250 Hz), the Pacinian channel mediates vibrotactile sensations near threshold and vasoconstriction occurs when vibration is perceptible. At lower frequencies (8, 16, and 31.5 Hz), the Pacinian channel does not mediate sensations near threshold and vasoconstriction commences at greater magnitudes when the Pacinian channel is activate

A class of second-order geometric quasilinear hyperbolic PDEs and their application in imaging science

In this paper, we study damped second-order dynamics, which are quasilinear hyperbolic partial differential equations (PDEs). This is inspired by the recent development of second-order damping systems for accelerating energy decay of gradient flows. We concentrate on two equations: one is a damped second-order total variation flow, which is primarily motivated by the application of image denoising; the other is a damped second-order mean curvature flow for level sets of scalar functions, which is related to a non-convex variational model capable of correcting displacement errors in image data (e.g. dejittering). For the former equation, we prove the existence and uniqueness of the solution. For the latter, we draw a connection between the equation and some second-order geometric PDEs evolving the hypersurfaces which are described by level sets of scalar functions, and show the existence and uniqueness of the solution for a regularized version of the equation. The latter is used in our algorithmic development. A general algorithm for numerical discretization of the two nonlinear PDEs is proposed and analyzed. Its efficiency is demonstrated by various numerical examples, where simulations on the behavior of solutions of the new equations and comparisons with first-order flows are also documented

Do Momentum Strategies Work?: - Australian Evidence

This paper investigates the profitability of momentum investment strategy and the predictive power of trading volume for equities listed in the Australian Stock Exchange. Recent research finds that momentum and trading volume appear to predict subsequent returns in U.S. market and past volume helps to reconcile intermediate-horizon “under reaction” and long-horizon “overreaction” effects. However, bulk of the evidence on this important relationship between past returns and future returns is limited to U.S. portfolios. This study provides an out of sample evidence by examining the relationship between “trading volume” (measured by the turnover ratio) and “momentum” strategies in an Australian setting. We document a strong momentum effect for the Australian market during the period 1988 through 2002 and find that momentum plays an important role in providing information about stocks. We also find that past trading volume predicts both the magnitude and persistence of price momentum. In summary, our findings are consistent with the U.S. evidence.

A random forest system combination approach for error detection in digital dictionaries

When digitizing a print bilingual dictionary, whether via optical character recognition or manual entry, it is inevitable that errors are introduced into the electronic version that is created. We investigate automating the process of detecting errors in an XML representation of a digitized print dictionary using a hybrid approach that combines rule-based, feature-based, and language model-based methods. We investigate combining methods and show that using random forests is a promising approach. We find that in isolation, unsupervised methods rival the performance of supervised methods. Random forests typically require training data so we investigate how we can apply random forests to combine individual base methods that are themselves unsupervised without requiring large amounts of training data. Experiments reveal empirically that a relatively small amount of data is sufficient and can potentially be further reduced through specific selection criteria.Comment: 9 pages, 7 figures, 10 tables; appeared in Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data, April 201