Either or neither, but not both : locating the effects of masked primes

Execution of a response that has been primed by a backward-masked stimulus is inhibited (negative compatibility effect; NCE). Three experiments investigated the locus of this inhibition. Masked primes (left- or right-pointing arrows) were followed either by an arrow or a circle target. Arrow targets always required a left- or right-hand response, but the experiments differed in the response required to circles: press neither, either or both response keys (i.e. nogo, free choice and bimanual, respectively). Arrow targets showed the usual NCEs. Circle targets showed NCEs in the form of a response bias away from the primed response in the nogo and free-choice tasks; primes and targets differed on these trials, ruling out a perceptual explanation of the NCE. The bimanual task showed no such bias, suggesting that the NCE is located at a level of abstract response codes rather than specific muscle commands

The Effect of a Reduced-Calorie Diet on alpha-2 Adrenergic Receptor Responsiveness in Abdominal Adipose Tissue in Obese Men During Exercise

There is at present an imperfect understanding of the effect of diet on availability of inhibitory receptors in fat cells during exercise among obese men. 

*Objective:* The purpose of this study was to determine whether diet results in downregulation of alpha-2 adrenergic receptor ([alpha]~2-AR~) messenger RNA (mRNA), improving metabolism in exercise in obese men. 

*Design:* One group, pre-test, post-test design.

*Measurements:* Subcutaneous abdominal adipose tissue was tested for physiologic response, such as changes in catecholamines and other markers of lipolysis measured during periods of exercise, before and after a 12-week diet. Plasma markers of lipolysis/antilipolytic activity (catecholamines [adrenaline and noradrenaline], NEFA, lactate, glucose, hematocrit, or insulin levels) were analyzed at four points in time in order to determine the effect of exercise on [alpha]~2-AR~ and [beta]-AR responsiveness to sympathetic stimulation.

*Subjects:* Otherwise healthy 18 to 45 year old obese men (defined as a body mass index (BMI) over 33 kg/m^2^).

*Results:* The 12-week reduced calorie diet did not result in improved metabolism. Instead, upregulation of alpha-2 adrenergic receptor ([alpha]~2-AR~) messenger RNA (mRNA) was observed. On average, [alpha]~2-AR~ mRNA levels (ratio of [alpha]~2-AR~ to cyclophilin) in subjects increased by 0.022-0.023 after the diet. The average differences in of [alpha]~2-AR~ mRNA and [beta]-AR mRNA measured before and after diet were both insignificant (M = 0.015) t(4) = -0.911; _P_ > 0.05; (M = 0.0139; t(4) = 0.077; _P_ > 0.05). 

*Conclusion:* The observed direction of change in [alpha]~2-AR~ mRNA levels, when viewed together with the stability of [beta]-AR mRNA levels, suggests that upregulation of [alpha]~2-AR~ rather than downregulation occurred. Downregulation would account for decreased lipolytic activity during exercise, future study is needed

First-principles phase diagram calculations for the HfC–TiC, ZrC–TiC, and HfC–ZrC solid solutions

We report first-principles phase diagram calculations for the binary systems HfC–TiC, TiC–ZrC, and HfC–ZrC. Formation energies for superstructures of various bulk compositions were computed with a plane-wave pseudopotential method. They in turn were used as a basis for fitting cluster expansion Hamiltonians, both with and without approximations for excess vibrational free energies. Significant miscibility gaps are predicted for the systems TiC–ZrC and HfC–TiC, with consolute temperatures in excess of 2000 K. The HfC–ZrC system is predicted to be completely miscibile down to 185 K. Reductions in consolute temperature due to excess vibrational free energy are estimated to be ~7%, ~20%, and ~0%, for HfC–TiC, TiC–ZrC, and HfC–ZrC, respectively. Predicted miscibility gaps are symmetric for HfC–ZrC, almost symmetric for HfC–TiC and asymmetric for TiC–ZrC

Enhanced spin accumulation at room temperature in graphene spin valves with amorphous carbon interfacial layers

We demonstrate a large enhancement of the spin accumulation in monolayer graphene following electron-beam induced deposition of an amorphous carbon layer at the ferromagnet-graphene interface. The enhancement is 10^4-fold when graphene is deposited onto poly(methyl metacrylate) (PMMA) and exposed with sufficient electron-beam dose to cross-link the PMMA, and 10^3-fold when graphene is deposited directly onto SiO2 and exposed with identical dose. We attribute the difference to a more efficient carbon deposition in the former case due to an increase in the presence of compounds containing carbon, which are released by the PMMA. The amorphous carbon interface can sustain very large current densities without degrading, which leads to very large spin accumulations exceeding 500 microeVs at room temperature

Resonance parameters of the first 1/2+ state in 9Be and astrophysical implications

Spectra of the 9Be(e,e') reaction have been measured at the S-DALINAC at an electron energy E_0 = 73 MeV and scattering angles of 93{\deg} and 141{\deg} with high energy resolution up to excitation energies E_x = 8 MeV. The astrophysically relevant resonance parameters of the first excited 1/2+ state of 9Be have been extracted in a one-level approximation of R-matrix theory resulting in a resonance energy E_R = 1.748(6) MeV and width Gamma_R = 274(8) keV in good agreement with the latest 9Be(gamma,n) experiment but with considerably improved uncertainties. However, the reduced B(E1) transition strength deduced from an extrapolation of the (e,e') data to the photon point is a factor of two smaller. Implications of the new results for a possible production of 12C in neutron-rich astrophysical scenarios are discussed.Comment: 8 pages, 7 figures, accepted for publication in Phys. Rev.

Optimal control and inverse optimal control by distribution matching

Optimal control is a powerful approach to achieve optimal behavior. However, it typically requires a manual specification of a cost function which often contains several objectives, such as reaching goal positions at different time steps or energy efficiency. Manually trading-off these objectives is often difficult and requires a high engineering effort. In this paper, we present a new approach to specify optimal behavior. We directly specify the desired behavior by a distribution over future states or features of the states. For example, the experimenter could choose to reach certain mean positions with given accuracy/variance at specified time steps. Our approach also unifies optimal control and inverse optimal control in one framework. Given a desired state distribution, we estimate a cost function such that the optimal controller matches the desired distribution. If the desired distribution is estimated from expert demonstrations, our approach performs inverse optimal control. We evaluate our approach on several optimal and inverse optimal control tasks on non-linear systems using incremental linearizations similar to differential dynamic programming approaches

The second law, Maxwell's daemon and work derivable from quantum heat engines

With a class of quantum heat engines which consists of two-energy-eigenstate systems undergoing, respectively, quantum adiabatic processes and energy exchanges with heat baths at different stages of a cycle, we are able to clarify some important aspects of the second law of thermodynamics. The quantum heat engines also offer a practical way, as an alternative to Szilard's engine, to physically realise Maxwell's daemon. While respecting the second law on the average, they are also capable of extracting more work from the heat baths than is otherwise possible in thermal equilibrium

Trust-Region Variational Inference with Gaussian Mixture Models

Many methods for machine learning rely on approximate inference from intractable probability distributions. Variational inference approximates such distributions by tractable models that can be subsequently used for approximate inference. Learning sufficiently accurate approximations requires a rich model family and careful exploration of the relevant modes of the target distribution. We propose a method for learning accurate GMM approximations of intractable probability distributions based on insights from policy search by using information-geometric trust regions for principled exploration. For efficient improvement of the GMM approximation, we derive a lower bound on the corresponding optimization objective enabling us to update the components independently. Our use of the lower bound ensures convergence to a stationary point of the original objective. The number of components is adapted online by adding new components in promising regions and by deleting components with negligible weight. We demonstrate on several domains that we can learn approximations of complex, multimodal distributions with a quality that is unmet by previous variational inference methods, and that the GMM approximation can be used for drawing samples that are on par with samples created by state-of-theart MCMC samplers while requiring up to three orders of magnitude less computational resources