Thermally-induced change in the relaxation behavior of skin tissue.

Skin biothermomechanics is highly interdisciplinary, involving bioheat transfer, burn damage, biomechanics, and physiology. Characterization of the thermomechanical behavior of skin tissue is of great importance and can contribute to a variety of medical applications. However, few quantitative studies have been conducted on the thermally-dependent mechanical properties of skin tissue. The aim of the present study is to experimentally examine the thermally-induced change in the relaxation behavior of skin tissue in both hyperthermal and hypothermic ranges. The results show that temperature has great influence on the stress-relaxation behavior of skin tissue under both hyperthermal and hypothermic temperatures; the quantitative relationship that has been found between temperature and the viscoelastic parameter (the elastic fraction or fractional energy dissipation) was temperature dependent, with greatest dissipation at high temperature levels.

Instability in threshold voltage and subthreshold behavior in Hf-In-Zn-O thin film transistors induced by bias-and light-stress

Electrical bias and light stressing followed by natural recovery of amorphous hafnium-indium-zinc-oxide (HIZO) thin film transistors with a silicon oxide/nitride dielectric stack reveals defect density changes, charge trapping and persistent photoconductivity (PPC). In the absence of light, the polarity of bias stress controls the magnitude and direction of the threshold voltage shift (Δ VT), while under light stress, VT consistently shifts negatively. In all cases, there was no significant change in field-effect mobility. Light stress gives rise to a PPC with wavelength-dependent recovery on time scale of days. We observe that the PPC becomes more pronounced at shorter wavelengths. © 2010 American Institute of Physics.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.

Dynamical behavior of damped driven coupled single electron simple harmonic oscillators

Coherent coupling between a large number of qubits is the goal for scalable approaches to solid state quantum information processing. Prototype systems can be characterized by spectroscopic techniques. Here, we use pulsed-continuous wave microwave spectroscopy to study the behavior of electrons trapped at defects within the gate dielectric of a sol-gel-based high-k silicon MOSFET. Disorder leads to a wide distribution in trap properties, allowing more than 1000 traps to be individually addressed in a single transistor within the accessible frequency domain. Their dynamical behavior is explored by pulsing the microwave excitation over a range of times comparable to the phase coherence time and the lifetime of the electron in the trap. Trap occupancy is limited to a single electron, which can be manipulated by resonant microwave excitation and the resulting change in trap occupancy is detected by the change in the channel current of the transistor. The trap behavior is described by a classical damped driven simple harmonic oscillator model, with the phase coherence, lifetime and coupling strength parameters derived from a continuous wave (CW) measurement only. For pulse times shorter than the phase coherence time, the energy exchange between traps, due to the coupling, strongly modulates the observed drain current change. This effect could be exploited for 2-qubit gate operation. The very large number of resonances observed in this system would allow a complex multi-qubit quantum mechanical circuit to be realized by this mechanism using only a single transistor.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models. © 2010 Nagengast et al.

The Ic behavior of 2G YBCO tapes under DC/AC magnetic fields at various temperatures

In order to design a High Temperature Superconducting (HTS) machine that is able to operate safely and reliably, studies on the characterization of Second Generation (2G) HTS tapes are of paramount importance. This paper presents an experimental setup to measure critical current of 2G HTS tapes in high DC magnetic fields (up to 5 Tesla) with an AC current ripple superimposed, as well as various temperatures ranging from 25 K to 77 K. The 2G tape measured is the SGS12050 coated conductor made by SuperPower. The critical current is measured by a flux vector with reference to the widest sample face from 0 to 90 degrees in 10 degree steps. Smaller steps are required close to 0 . A Variable Temperature Insert (VTI) is utilized to control temperature change. © 2010 IEEE.

Predicting the performance of an office under climate change: A study of metrics, sensitivity and zonal resolution

Climate change is expected to have significant impact on the future thermal performance of buildings. Building simulation and sensitivity analysis can be employed to predict these impacts, guiding interventions to adapt buildings to future conditions. This article explores the use of simulation to study the impact of climate change on a theoretical office building in the UK, employing a probabilistic approach. The work studies (1) appropriate performance metrics and underlying modelling assumptions, (2) sensitivity of computational results to identify key design parameters and (3) the impact of zonal resolution. The conclusions highlight the importance of assumptions in the field of electricity conversion factors, proper management of internal heat gains, and the need to use an appropriately detailed zonal resolution. © 2010 Elsevier B.V. All rights reserved.

Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior

Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers. © 2006 IEEE.

Effects of initial soil fabric and mode of shearing on quasi-steady state line for monotonic undrained behavior

The effects of initial soil fabric and mode of shearing on quasi-steady state line in void ratiostress space are studied by employing the Distinct Element Method numerical analysis. The results show that the initial soil fabric and the mode of shearing have a profound effect on the location of the quasi-steady state line. The evolution of the soil fabric during the course of undrained shearing shows that the specimens with different initial soil fabrics reach quasi-steady state at various soil fabric conditions. At quasi-steady state, the soil fabric has a significant adjustment to change its behavior from contractive to dilative. As the stress state approaches the steady state, the soil fabrics of different initial conditions become similar. The numerical analysis results are compared qualitatively with the published experimental data and the effects of specimen reconstitution methods and mode of shearing found in the experimental studies canbe systematically explained by the numerical analysis. © 2009 Taylor & Francis Group.

Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective.

The tendency to make unhealthy choices is hypothesized to be related to an individual's temporal discount rate, the theoretical rate at which they devalue delayed rewards. Furthermore, a particular form of temporal discounting, hyperbolic discounting, has been proposed to explain why unhealthy behavior can occur despite healthy intentions. We examine these two hypotheses in turn. We first systematically review studies which investigate whether discount rates can predict unhealthy behavior. These studies reveal that high discount rates for money (and in some instances food or drug rewards) are associated with several unhealthy behaviors and markers of health status, establishing discounting as a promising predictive measure. We secondly examine whether intention-incongruent unhealthy actions are consistent with hyperbolic discounting. We conclude that intention-incongruent actions are often triggered by environmental cues or changes in motivational state, whose effects are not parameterized by hyperbolic discounting. We propose a framework for understanding these state-based effects in terms of the interplay of two distinct reinforcement learning mechanisms: a "model-based" (or goal-directed) system and a "model-free" (or habitual) system. Under this framework, while discounting of delayed health may contribute to the initiation of unhealthy behavior, with repetition, many unhealthy behaviors become habitual; if health goals then change, habitual behavior can still arise in response to environmental cues. We propose that the burgeoning development of computational models of these processes will permit further identification of health decision-making phenotypes.