Temperature dependence of the electron spin g factor in GaAs

The temperature dependence of the electron spin $g$ factor in GaAs is investigated experimentally and theoretically. Experimentally, the $g$ factor was measured using time-resolved Faraday rotation due to Larmor precession of electron spins in the temperature range between 4.5 K and 190 K. The experiment shows an almost linear increase of the $g$ value with the temperature. This result is in good agreement with other measurements based on photoluminescence quantum beats and time-resolved Kerr rotation up to room temperature. The experimental data are described theoretically taking into account a diminishing fundamental energy gap in GaAs due to lattice thermal dilatation and nonparabolicity of the conduction band calculated using a five-level kp model. At higher temperatures electrons populate higher Landau levels and the average $g$ factor is obtained from a summation over many levels. A very good description of the experimental data is obtained indicating that the observed increase of the spin $g$ factor with the temperature is predominantly due to band's nonparabolicity.Comment: 6 pages 4 figure

Turing instabilities in a mathematical model for signaling networks

GTPase molecules are important regulators in cells that continuously run through an activation/deactivation and membrane-attachment/membrane-detachment cycle. Activated GTPase is able to localize in parts of the membranes and to induce cell polarity. As feedback loops contribute to the GTPase cycle and as the coupling between membrane-bound and cytoplasmic processes introduces different diffusion coefficients a Turing mechanism is a natural candidate for this symmetry breaking. We formulate a mathematical model that couples a reaction-diffusion system in the inner volume to a reaction-diffusion system on the membrane via a flux condition and an attachment/detachment law at the membrane. We present a reduction to a simpler non-local reaction-diffusion model and perform a stability analysis and numerical simulations for this reduction. Our model in principle does support Turing instabilities but only if the lateral diffusion of inactivated GTPase is much faster than the diffusion of activated GTPase.Comment: 23 pages, 5 figures; The final publication is available at http://www.springerlink.com http://dx.doi.org/10.1007/s00285-011-0495-

Prevalence of prediabetes and undiagnosed diabetes in patients with HFpEF and HFrEF and associated clinical outcomes

Purpose: The prevalence and consequences of prediabetic dysglycemia and undiagnosed diabetes is unknown in patients with heart failure (HF) and preserved ejection fraction (HFpEF) and has not been compared to heart failure and reduced ejection fraction (HFrEF). Methods: We examined the prevalence and outcomes associated with normoglycemia, prediabetic dysglycemia and diabetes (diagnosed and undiagnosed) among individuals with a baseline glycated hemoglobin (hemoglobin A1c, HbA1c) measurement stratified by HFrEF or HFpEF in the Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity programme (CHARM). We studied the primary outcome of HF hospitalization or cardiovascular (CV) death, and all-cause death, and estimated hazard ratios (HR) by use of multivariable Cox regression models. Results: HbA1c was measured at baseline in CHARM patients enrolled in the USA and Canada and was available in 1072/3023 (35%) of patients with HFpEF and 1578/4576 (34%) patients with HFrEF. 18 and 16% had normoglycemia (HbA1c < 6.0), 20 and 22% had prediabetes (HbA1c 6.0–6.4), respectively. Finally among patients with HFpEF 22% had undiagnosed diabetes (HbA1c > 6.4), and 40% had known diabetes (any HbA1c), with corresponding prevalence among HFrEF patients being 26 and 35%. The rates of both clinical outcomes of interest were higher in patients with undiagnosed diabetes and prediabetes, compared to normoglycemic patients, irrespective of HF subtype, and in general higher among HFrEF patients. For the primary composite outcome among HFpEF patients, the HRs were 1.02 (95% CI 0.63–1.65) for prediabetes, HR 1.18 (0.75–1.86) for undiagnosed diabetes and 2.75 (1.83–4.11) for known diabetes, respectively, p value for trend across groups < 0.001. Dysglycemia was also associated with worse outcomes in HFrEF. Conclusions: These findings confirm the remarkably high prevalence of dysglycemia in heart failure irrespective of ejection fraction phenotype, and demonstrate that dysglycemia is associated with a higher risk of adverse clinical outcomes, even before the diagnosis of diabetes and institution of glucose lowering therapy in patients with HFpEF as well as HFrEF

Global/Local Dynamic Models

Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering

Practical probabilistic programming with monads

The machine learning community has recently shown a lot of interest in practical probabilistic programming systems that target the problem of Bayesian inference. Such systems come in different forms, but they all express probabilistic models as computational processes using syntax resembling programming languages. In the functional programming community monads are known to offer a convenient and elegant abstraction for programming with probability distributions, but their use is often limited to very simple inference problems. We show that it is possible to use the monad abstraction to construct probabilistic models for machine learning, while still offering good performance of inference in challenging models. We use a GADT as an underlying representation of a probability distribution and apply Sequential Monte Carlo-based methods to achieve efficient inference. We define a formal semantics via measure theory. We demonstrate a clean and elegant implementation that achieves performance comparable with Anglican, a state-of-the-art probabilistic programming system.The first author is supported by EPSRC and the Cambridge Trust.This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2804302.280431

Radiation-induced oscillatory magnetoresistance as a sensitive probe of the zero-field spin splitting in high mobility GaAs/AlGaAs devices

We suggest an approach for characterizing the zero-field spin splitting of high mobility two-dimensional electron systems, when beats are not readily observable in the Shubnikov-de Haas effect. The zero-field spin splitting and the effective magnetic field seen in the reference frame of the electron is evaluated from a quantitative study of beats observed in radiation-induced magnetoresistance oscillations.Comment: 4 pages, 4 color figure

Electron and Hole Spin Splitting and Photogalvanic Effect in Quantum Wells

A theory of the circular photogalvanic effect caused by spin splitting in quantum wells is developed. Direct interband transitions between the hole and electron size-quantized subbands are considered. It is shown that the photocurrent value and direction depend strongly on the form of the spin-orbit interaction. The currents induced by structure-, bulk-, and interface-inversion asymmetry are investigated. The photocurrent excitation spectra caused by spin splittings in both conduction and valence bands are calculated.Comment: 7 pages, 3 figure