Engineering Quantum States, Nonlinear Measurements, and Anomalous Diffusion by Imaging

We show that well-separated quantum superposition states, measurements of strongly nonlinear observables, and quantum dynamics driven by anomalous diffusion can all be achieved for single atoms or molecules by imaging spontaneous photons that they emit via resonance florescence. To generate anomalous diffusion we introduce continuous measurements driven by L\'evy processes, and prove a number of results regarding their properties. In particular we present strong evidence that the only stable L\'evy density that can realize a strictly continuous measurement is the Gaussian.Comment: revtex4-1, 17 pages, 7 eps figure

Feedback cooling of atomic motion in cavity QED

We consider the problem of controlling the motion of an atom trapped in an optical cavity using continuous feedback. In order to realize such a scheme experimentally, one must be able to perform state estimation of the atomic motion in real time. While in theory this estimate may be provided by a stochastic master equation describing the full dynamics of the observed system, integrating this equation in real time is impractical. Here we derive an approximate estimation equation for this purpose, and use it as a drive in a feedback algorithm designed to cool the motion of the atom. We examine the effectiveness of such a procedure using full simulations of the cavity QED system, including the quantized motion of the atom in one dimension.Comment: 22 pages, 17 figure

Estimation of ground reaction forces and ankle moment with multiple, low-cost sensors

Abstract Background Wearable sensor systems can provide data for at-home gait analyses and input to controllers for rehabilitation devices but they often have reduced estimation accuracy compared to laboratory systems. The goal of this study is to evaluate a portable, low-cost system for measuring ground reaction forces and ankle joint torques in treadmill walking and calf raises. Methods To estimate the ground reaction forces and ankle joint torques, we developed a custom instrumented insole and a tissue force sensor. Six healthy subjects completed a collection of movements (calf raises, 1.0 m/s walking, and 1.5 m/s walking) on two separate days. We trained artificial neural networks on the study data and compared the estimates to a multi-camera motion system and an instrumented treadmill. We evaluated the relative strength of each sensor by testing each sensor’s ability to predict the ankle joint torque calculated from a reference inverse kinematics algorithm. We assessed model accuracy through root mean squared error and normalized root mean square error. We hypothesized that the estimation of the models would have normalized root mean square error measures less than 10 %. Results For walking at 1.0 and walking at 1.5 m/s, the single-task, intra-day and multi-task, intra-day predictions had normalized root mean square error less than 10 % for all three force components and both center of pressure components. For the calf raise task, the single-task, intra-day and multi-task, intra-day predictions had normalized root mean square error less than 10 % for only the anterior-posterior center of pressure. The multi-task, intra-day model had similar predictions to the single-task, intra-day model. The normalized root mean square error of predictions from the insole sensor alone were less than 10 % for walking at 1.0 m/s and 1.5 m/s. No sensor was sufficient for the calf raise task. The combination of the insole sensor and the tendon sensor had lower normalized root mean square error than the individual sensors for all three tasks. Conclusions The proposed sensor system provided accurate estimates for five of the six components of the ground reaction kinetics during walking at 1.0 and 1.5 m/s and one of the six components during the calf raise task. The normalized root mean square error of the predictions of the ground reaction forces were similar to published studies using commercial devices. The proposed system of low-cost sensors can provide useful estimations of ankle joint torque for both walking and calf raises for future studies in mobile gait analysis.http://deepblue.lib.umich.edu/bitstream/2027.42/116024/1/12984_2015_Article_81.pd

Quantum feedback control of atomic motion in an optical cavity

We study quantum feedback cooling of atomic motion in an optical cavity. We design a feedback algorithm that can cool the atom to the ground state of the optical potential with high efficiency despite the nonlinear nature of this problem. An important ingredient is a simplified state-estimation algorithm, necessary for a real-time implementation of the feedback loop. We also describe the critical role of parity dynamics in the cooling process and present a simple theory that predicts the achievable steady-state atomic energies

Association of C2, a derivative of the radial artery pressure waveform, with new onset of type 2 diabetes mellitus: the MESA study.

BackgroundAlthough microvascular dysfunction is known to result from diabetes, it might also lead to diabetes. Lower values of C2, a derivative of the radial artery pressure waveform, indicate microvascular dysfunction and predict hypertension and cardiovascular disease (CVD). We studied the association of C2 with incident diabetes in subjects free of overt CVD.MethodsAmong multi-ethnic participants (n = 5214), aged 45-84 years with no diabetes, C2 was derived from the radial artery pressure waveform. Incident diabetes (N = 651) was diagnosed as new fasting glucose ≥ 126 mg/dL or antidiabetic medicine over ~ 10 years. The relative incidence density (RID) for incident diabetes per standard deviation (SD) of C2 was studied during ~ 10 years follow-up using four levels of adjustment.ResultsMean C2 at baseline was 4.58 ± 2.85 mL/mmHg × 100. The RID for incident diabetes per SD of C2 was 0.90 (95% CI 0.82-0.99, P = 0.03). After adjustment for demographics plus body size, the corresponding RID was 0.81 (95% CI 0.73-0.89, P < 0.0001); body mass index (BMI) was the dominant covariate here. After adjustment for demographics plus cardiovascular risk factors, the RID was 0.98 (95% CI 0.89, 1.07, P = 0.63). After adjustment for all the parameters in the previous models, the RID was 0.87 (95% CI 0.78, 0.96, P = 0.006).ConclusionsIn a multi-ethnic sample free of overt CVD and diabetes at baseline, C2 predicted incident diabetes after adjustment for demographics, BMI and CVD risk factors. Differences in arterial blood pressure wave morphology may indicate a long-term risk trajectory for diabetes, independently of body size and the classical risk factors

Associations of body composition measures and C2, a marker for small artery elasticity: The MESA.

ObjectiveLower C2, a continuous blood pressure waveform characteristic asserted to represent small artery elasticity, predicts future cardiovascular disease events. It is hypothesized that the paradoxical positive association between body mass index (BMI) and C2 may reflect muscle instead of excess fat.MethodsIn a multi-ethnic, community-living cohort of 1,960 participants, computed tomography scans of the abdomen were used to measure visceral adipose tissue (VAT) and total abdominal muscle tissue (TAMT), and applanation tonometry of the radial arteries was used to assess C2. The period cross-sectional associations between BMI, TAMT, and VAT with C2 were ascertained.ResultsThe mean age was 62 ± 9 years and 51% were male. After adjustments for age, gender, ethnicity, pack years smoking cigarettes, diabetes, hypertension, and total and HDL cholesterol, higher BMI (standardized beta = 0.09, P-value < 0.01) and more TAMT (standardized beta = 0.12, P-value < 0.01) were significantly associated with higher C2. In contrast, more VAT (standardized beta = -0.09, P-value < 0.01) was associated with lower C2.ConclusionsIn multivariable analysis, VAT, in contrast to TAMT and BMI, was associated with less compliant small arteries. Visceral fat may be a better marker for detrimental excess body fat than BMI

Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton

Abstract Background Robotic ankle exoskeletons can provide assistance to users and reduce metabolic power during walking. Our research group has investigated the use of proportional myoelectric control for controlling robotic ankle exoskeletons. Previously, these controllers have relied on a constant gain to map user’s muscle activity to actuation control signals. A constant gain may act as a constraint on the user, so we designed a controller that dynamically adapts the gain to the user’s myoelectric amplitude. We hypothesized that an adaptive gain proportional myoelectric controller would reduce metabolic energy expenditure compared to walking with the ankle exoskeleton unpowered because users could choose their preferred control gain. Methods We tested eight healthy subjects walking with the adaptive gain proportional myoelectric controller with bilateral ankle exoskeletons. The adaptive gain was updated each stride such that on average the user’s peak muscle activity was mapped to maximal power output of the exoskeleton. All subjects participated in three identical training sessions where they walked on a treadmill for 50 minutes (30 minutes of which the exoskeleton was powered) at 1.2 ms-1. We calculated and analyzed metabolic energy consumption, muscle recruitment, inverse kinematics, inverse dynamics, and exoskeleton mechanics. Results Using our controller, subjects achieved a metabolic reduction similar to that seen in previous work in about a third of the training time. The resulting controller gain was lower than that seen in previous work (β=1.50±0.14 versus a constant β=2). The adapted gain allowed users more total ankle joint power than that of unassisted walking, increasing ankle power in exchange for a decrease in hip power. Conclusions Our findings indicate that humans prefer to walk with greater ankle mechanical power output than their unassisted gait when provided with an ankle exoskeleton using an adaptive controller. This suggests that robotic assistance from an exoskeleton can allow humans to adopt gait patterns different from their normal choices for locomotion. In our specific experiment, subjects increased ankle power and decreased hip power to walk with a reduction in metabolic cost. Future exoskeleton devices that rely on proportional myolectric control are likely to demonstrate improved performance by including an adaptive gain.http://deepblue.lib.umich.edu/bitstream/2027.42/115879/1/12984_2015_Article_86.pd

Lagrangian Liouville models of multiphase flows with randomly forced inertial particles

Eulerian-Lagrangian models of particle-laden (multiphase) flows describe fluid flow and particle dynamics in the Eulerian and Lagrangian frameworks respectively. Regardless of whether the flow is turbulent or laminar, the particle dynamics is stochastic because the suspended particles are subjected to random forces. We use a polynomial chaos expansion (PCE), rather than a postulated constitutive law, to capture structural and parametric uncertainties in the particles' forcing. The stochastic particle dynamics is described by a joint probability density function (PDF) of a particle's position and velocity and random coefficients in the PCE. We deploy the method of distributions (MoD) to derive a deterministic (Liouville-type) partial-differential equation for this PDF. We reformulate this PDF equation in a Lagrangian form, obtaining PDF flow maps and tracing events and their probability in the phase space. That is accomplished via a new high-order spectral scheme, which traces, marginalizes and computes moments of the high-dimensional joint PDF and comports with high-order carrier-phase solvers. Our approach has lower computational cost than either high-order Eulerian solvers or Monte Carlo methods, is not subjected to a CFL condition, does not suffer from Gibbs oscillations and does not require (order-reducing) filtering and regularization techniques. These features are demonstrated on several test cases

Late systolic central hypertension as a predictor of incident heart failure : the Multi-Ethnic Study of Atherosclerosis

Background: Experimental studies demonstrate that high aortic pressure in late systole relative to early systole causes greater myocardial remodeling and dysfunction, for any given absolute peak systolic pressure. Methods and Results: We tested the hypothesis that late systolic hypertension, defined as the ratio of late (last one third of systole) to early (first two thirds of systole) pressure-time integrals (PTI) of the aortic pressure waveform, independently predicts incident heart failure (HF) in the general population. Aortic pressure waveforms were derived from a generalized transfer function applied to the radial pressure waveform recorded noninvasively from 6124 adults. The late/early systolic PTI ratio (L/ESPTI) was assessed as a predictor of incident HF during median 8.5 years of follow-up. The L/ESPTI was predictive of incident HF (hazard ratio per 1% increase= 1.22; 95% CI= 1.15 to 1.29; P58.38%) was more predictive of HF than the presence of hypertension. After adjustment for each other and various predictors of HF, the HR associated with hypertension was 1.39 (95% CI= 0.86 to 2.23; P=0.18), whereas the HR associated with a high L/E was 2.31 (95% CI=1.52 to 3.49; P<0.0001). Conclusions: Independently of the absolute level of peak pressure, late systolic hypertension is strongly associated with incident HF in the general population