Optical pumping via incoherent Raman transitions

A new optical pumping scheme is presented that uses incoherent Raman transitions to prepare a trapped Cesium atom in a specific Zeeman state within the 6S_{1/2}, F=3 hyperfine manifold. An important advantage of this scheme over existing optical pumping schemes is that the atom can be prepared in any of the F=3 Zeeman states. We demonstrate the scheme in the context of cavity quantum electrodynamics, but the technique is equally applicable to a wide variety of atomic systems with hyperfine ground-state structure.Comment: 8 pages, 4 figure

Age-Related Success with Elective Single versus Double Blastocyst Transfer

Background. Although the optimal outcome of assisted reproductive technology (ART) is a healthy singleton pregnancy, the rate of twin gestation from ART in women over the age of 35 is persistently high. Methods/Findings. We compared clinical pregnancy rates (PRs), ongoing pregnancy/live birth rates, and multiple gestation rates (MGRs) in 108 women who chose elective single blastocyst transfer (eSBT) to 415 women who chose elective double blastocyst transfer (eDBT) at a hospital-based IVF center. There was no significant difference in PR between eSBT and eDBT (57.4% versus 50.2%, P = 0.47) nor between eSBT and eDBT within each age group: <35, 35–37, 38–40, and >40. The risk of multiple gestations, however, was greatly increased between eSBT and eDBT (1.6 versus 32.4%, P < 0.00005), and this difference did not vary across age groups. Conclusion(s). Women undergoing eDBT are at uniformly high risk of multiple gestation regardless of age. eSBT appears to significantly lower the risk of multiple gestation without compromising PR

Frequency Tracking and Parameter Estimation for Robust Quantum State-Estimation

In this paper we consider the problem of tracking the state of a quantum system via a continuous measurement. If the system Hamiltonian is known precisely, this merely requires integrating the appropriate stochastic master equation. However, even a small error in the assumed Hamiltonian can render this approach useless. The natural answer to this problem is to include the parameters of the Hamiltonian as part of the estimation problem, and the full Bayesian solution to this task provides a state-estimate that is robust against uncertainties. However, this approach requires considerable computational overhead. Here we consider a single qubit in which the Hamiltonian contains a single unknown parameter. We show that classical frequency estimation techniques greatly reduce the computational overhead associated with Bayesian estimation and provide accurate estimates for the qubit frequencyComment: 6 figures, 13 page

Microrheology with optical tweezers: data analysis

We present a data analysis procedure that provides the solution to a long-standing issue in microrheology studies, i.e. the evaluation of the fluids' linear viscoelastic properties from the analysis of a finite set of experimental data, describing (for instance) the time-dependent mean-square displacement of suspended probe particles experiencing Brownian fluctuations. We report, for the first time in the literature, the linear viscoelastic response of an optically trapped bead suspended in a Newtonian fluid, over the entire range of experimentally accessible frequencies. The general validity of the proposed method makes it transferable to the majority of microrheology and rheology techniques

Effective Stimuli for Constructing Reliable Neuron Models

The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose

Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses