Nonstationary increments, scaling distributions, and variable diffusion processes in financial markets

Fat-tailed distributions have been reported in fluctuations of financial markets for more than a decade. Sliding interval techniques used in these studies implicitly assume that the underlying stochastic process has stationary increments. Through an analysis of intraday increments, we explicitly show that this assumption is invalid for the Euro-Dollar exchange rate. We find several time intervals during the day where the standard deviation of increments exhibits power law behavior in time. Stochastic dynamics during these intervals is shown to be given by diffusion processes with a diffusion coefficient that depends on time and the exchange rate. We introduce methods to evaluate the dynamical scaling index and the scaling function empirically. In general, the scaling index is significantly smaller than previously reported values close to 0.5. We show how the latter as well as apparent fat-tailed distributions can occur only as artifacts of the sliding interval analysis.     

Precision, signal-to-noise ratio, and dose optimization of magnitude and phase arterial input functions in dynamic susceptibility contrast MRI

PURPOSE: To determine optimal conditions for precise measurement of arterial input function (AIFs) in dynamic susceptibility contrast (DSC) perfusion MRI. MATERIALS AND METHODS: Magnitude-based (DeltaR(2)*) and phase-based (Deltaphi) AIFs were numerically simulated for several doses and baseline MRI noise levels [SNR(I(0))]. Random noise (1000 realizations) was added to real/imaginary MRI signals (derived from an internal carotid AIF), and AIF signal, noise, and signal-to-noise ratio (SNR) were determined. The optimal dose was defined as the dose that maximizes mean AIF SNR over the first-pass (SNR(mean)), rather than SNR at the AIF peak (SNR(peak)) because, compared to SNR(peak), doses predicted by SNR(mean) reduced the AIF-induced variability in cerebral blood flow (CBF) by 24% to 40%. RESULTS: The AIF SNR is most influenced by choice of AIF signal, then optimal dosing, each with little penalty. Compared to DeltaR(2)*, Deltaphi signal has 4 to 80 times the SNR over all doses and time points, and approximately 10-fold SNR(mean) at respective optimal doses. Optimal doses induce 85% to 90% signal drop for the DeltaR(2)* method, and 70% to 75% for Deltaphi, with two-fold dose errors causing approximately 1.7-fold loss in SNR(mean). Increases in SNR(I(0)) proportionally increase AIF SNR, but at a cost. CONCLUSION: AIF SNR is affected most by signal type, then dosing, and lastly, SNR(I(0)).     

Chemically accurate coarse graining of double-stranded DNA

Coarse-grained (CG) modeling approaches are widely used to simulate many important biological processes involving DNA, including chromatin folding and genomic packaging. The bending propensity of a semiflexible DNA molecule critically influences these processes. However, existing CG DNA models do not retain a sufficient fidelity of the important local chain motions, whose propagation at larger length scales would generate correct DNA persistent lengths, in particular when the solution's ionic strength is widely varied. Here we report on a development of an accurate CG model for the double-stranded DNA chain, with explicit treatment of mobile ions, derived systematically from all-atom molecular dynamics simulations. Our model generates complex local motions of the DNA chain, similar to fully atomistic dynamics, leading also to a quantitative agreement of our simulation results with the experimental data on the dependence of the DNA persistence length on the solution ionic strength. We also predict a structural transition in a torsionally stressed DNA nanocircle as the buffer ionic strength is increased beyond a threshold value.     

Effect of innervation-zone distribution on estimates of average muscle-fiber conduction velocity

Muscle-fiber conduction velocity (MFCV) may be a diagnostic variable, but the factors affecting its estimate from surface electromyographic (SEMG) signals are still not fully understood. We investigated the effect of innervation-zone distribution on estimates of average MFCV from simulated SEMG signals. Single-fiber action potentials were simulated using a computer model that describes an idealized cylindrical volume conductor comprised of bone, muscle, subcutaneous, and skin tissues. A model describing the characteristics and control of a motor-neuron pool was used to simulate 60 s of SEMG. Five innervation-zone distributions, inclined with respect to the fiber direction, were simulated within the muscle tissue, based on data from the literature and an experimental analysis. Two parameters were varied concurrently: (1) excitation level (5%-100%, 5% increments); and (2) subcutaneous tissue thickness (4 and 10 mm). The MFCV estimates were affected by the distribution of innervation zones with bias varying with excitation level and thickness of subcutaneous tissue. The MFCV estimates ranged from 3.95 to 11.67 m/s for single-differential and from 3.99 to 5.23 m/s for double-differential recordings when all simulated motor units were assigned the same conduction velocity of 4 m/s. Amplitude and characteristic spectral frequencies were also influenced by the distribution of innervation zones. The effect of innervation-zone distribution on MFCV estimates is thus substantial and may be a significant confounding factor in experimental and clinical studies on muscles with diffuse innervation zones.     

Ambulant intensiv miljø- og psykoterapi af unge skizofrene patienter: En beskrivelse af behandlingscentret Nordhuset,Helsingør

Orientering Nordhuset er en ambulant behandlingsenhed under psykiatrisk afdeling R, Centralsygehuset i Hillerød.

Behandlingen i Nordhuset påbegyndtes I 1983 udfra ønsket om at give yngre kroniske patienter et relevant ambulant behandlingstilbud som alternativ ti1 døgnindlaeggelse. Personalenormeringen er: 1 sygeplejerske, 1 1/2 ergoterapeut, 1 fysioteråpeut, 1 socialridgiver, 1 psykolog, 2 læger og 1 1/2 sekretaer.     

Importance of Path Planning Variability: A Simulation Study

Individuals vary in the way they navigate through space. Some take novel shortcuts, while others rely on known routes to find their way around. We wondered how and why there is so much variation in the population. To address this, we first compared the trajectories of 368 human subjects navigating a virtual maze with simulated trajectories. The simulated trajectories were generated by strategy-based path planning algorithms from robotics. Based on the similarities between human trajectories and different strategy-based simulated trajectories, we found that there is a variation in the type of strategy individuals apply to navigate space, as well as variation within individuals on a trial-by-trial basis. Moreover, we observed variation within a trial when subjects occasionally switched the navigation strategies halfway through a trajectory. In these cases, subjects started with a route strategy, in which they followed a familiar path, and then switched to a survey strategy, in which they took shortcuts by considering the layout of the environment. Then we simulated a second set of trajectories using five different but comparable artificial maps. These trajectories produced the similar pattern of strategy variation within and between trials. Furthermore, we varied the relative cost, that is, the assumed mental effort or required timesteps to choose a learned route over alternative paths. When the learned route was relatively costly, the simulated agents tended to take shortcuts. Conversely, when the learned route was less costly, the simulated agents showed preference toward a route strategy. We suggest that cost or assumed mental effort may be the reason why in previous studies, subjects used survey knowledge when instructed to take the shortest path. We suggest that this variation we observe in humans may be beneficial for robotic swarms or collections of autonomous agents during information gathering.     

The performance of different propensity-score methods for estimating relative risks

OBJECTIVES: The propensity score is the probability of treatment conditional on observed variables. Conditioning on the propensity-score results in unbiased estimation of the expected difference in observed responses to two treatments. The performance of propensity-score methods for estimating relative risks has not been studied. STUDY DESIGN AND SETTING: Monte Carlo simulations were used to assess the performance of matching, stratification, and covariate adjustment using the propensity score to estimate relative risks. RESULTS: Matching on the propensity score and stratification on the quintiles of the propensity score resulted in estimates of relative risk with similar mean squared error (MSE). Propensity-score matching resulted in estimates with less bias, whereas stratification on the propensity score resulted in estimates of with greater precision. Including only variables associated with the outcome or including only the true confounders in the propensity-score model resulted in estimates with lower MSE than did including all variables associated with treatment or all measured variables in the propensity-score model. CONCLUSIONS: When estimating relative risks, propensity-score matching resulted in estimates with less bias than did stratification on the quintiles of the propensity score, but stratification on the quintiles of the propensity score resulted in estimates with greater precision.     

BOLD background gradient contributions in diffusion‐weighted fMRI—comparison of spin‐echo and twice‐refocused spin‐echo sequences

The interaction (‘cross terms’) between diffusion‐weighting gradients and susceptibility‐induced background gradient fields around vessels has an impact on apparent diffusion coefficient (ADC) measurements and diffusion‐weighted functional magnetic resonance imaging (DFMRI) experiments. Monte‐Carlo (MC) simulations numerically integrating the Bloch equations for a large number of random walks in a vascular model were used to investigate to what extent such interactions would influence the extravascular signal change as well as the ADC change observed in DFMRI experiments. The vascular model consists of a set of independent, randomly oriented, infinite cylinders whose internal magnetic susceptibility varies as the state changes between rest and activation. In such a network, the cross terms result in the observation of a functional increase in ADC accompanied by a descending percent signal change with increasing diffusion weighting. It is shown that the twice‐refocused spin‐echo sequence permits sufficient yet not total suppression of such effects compared to the standard Stejskal‐Tanner spin‐echo diffusion weighting under experimentally relevant conditions. Copyright © 2010 John Wiley & Sons, Ltd.     

Normative comparisons for large neuropsychological test batteries: User-friendly and sensitive solutions to minimize familywise false positives

Introduction. In neuropsychological research and clinical practice, a large battery of tests is often administered to determine whether an individual deviates from the norm. We formulate three criteria for such large battery normative comparisons. First, familywise false-positive error rate (i.e., the complement of specificity) should be controlled at, or below, a prespecified level. Second, sensitivity to detect genuine deviations from the norm should be high. Third, the comparisons should be easy enough for routine application, not only in research, but also in clinical practice. Here we show that these criteria are satisfied for current procedures used to assess an overall deviation from the norm—that is, a deviation given all test results. However, we also show that these criteria are not satisfied for current procedures used to assess test-specific deviations, which are required, for example, to investigate dissociations in a test profile. We therefore propose several new procedures to assess such test-specific deviations. These new procedures are expected to satisfy all three criteria. Method. In Monte Carlo simulations and in an applied example pertaining to Parkinson disease, we compare current procedures to assess test-specific deviations (uncorrected and Bonferroni normative comparisons) to new procedures (Holm, one-step resampling, and step-down resampling normative comparisons). Results. The new procedures are shown to: (a) control familywise false-positive error rate, whereas uncorrected comparisons do not; (b) have higher sensitivity than Bonferroni corrected comparisons, where especially step-down resampling is favorable in this respect; (c) be user-friendly as they are implemented in a user-friendly normative comparisons website, and as the required normative data are provided by a database. Conclusion. These new normative comparisons procedures, especially step-down resampling, are valuable additional tools to assess test-specific deviations from the norm in large test batteries.