Source conductance scaling for high frequency superconducting quasiparticle receivers

It has been suggested that the optimum source conductance G(sub s) for the superconductor-insulator-superconductor (SIS) quasiparticle mixer should have a l/f dependence. This would imply that the critical current density of SIS junctions used for mixing should increase as frequency squared, a stringent constraint on the design of submillimeter SIS mixers, rather than in simple proportion to frequency as previously believed. We have used Tucker's quantum theory of mixing for extensive numerical calculations to determine G(sub s) for an optimized SIS receiver. We find that G(sub s) is very roughly independent of frequency (except for the best junctions at low frequency), and discuss the implications of our results for the design of submillimeter SIS mixers

Plasma q-plate for generation and manipulation of intense optical vortices

An optical vortex is a light wave with a twisting wavefront around its propagation axis and null intensity in the beam center. Its unique spatial structure of field lends itself to a broad range of applications, including optical communication, quantum information, superresolution microscopy, and multi-dimensional manipulation of particles. However, accessible intensity of optical vortices have been limited to material ionization threshold. This limitation might be removed by using the plasma medium. Here we propose the design of suitably magnetized plasmas which, functioning as a q-plate, leads to a direct convertion from a high-intensity Gaussian beam into a twisted beam. A circularly polarized laser beam in the plasma accumulates an azimuthal-angle-dependent phase shift and hence forms a twisting wavefront. Our three-dimensional particle-in-cell simulations demonstrate extremely high power conversion efficiency. The plasma q-plate can work in a large range of frequencies spanning from terahertz to the optical domain

Limited Contribution of Health Behaviours to Expanding Income-Related Chronic Disease Disparities Based on a Nationwide Cross-Sectional Study in China

This study estimated the association of income and prevalence of cardiovascular diseases (CVD) and hypertension, and then quantified the contribution of health behaviors to the association in China. Using the 2013 survey of the China Health and Retirement Longitudinal Study (CHARLS), a logit model was applied to examine income-related health disparities in relation to CVD and hypertension. A four-step regression method was then constructed to measure the role of health behaviors in income-related health disparities. Using indirect effects, mediation by health behaviors was examined. Income-related health disparities in chronic diseases were found to exist in China. Specifically, individuals in the high-income group had a 14% (OR = 0.86; 95% CI 0.73–1.02) and 14% (OR = 0.86; 95% CI 0.76–0.97) lower odds of suffering from CVD and hypertension than those in the low-income group. However, limited evidence shows this association was mediated by health behaviors. The Heaviness of Smoking Index (HSI), heavy drinking, irregular eating, and nap time did not significantly mediate the association of income and prevalence of CVD and hypertension. To curb the rising prevalence of CVD and hypertension in China, policies should focus on the low-income subpopulation. However, healthy behaviors interventions targeting smoking, heavy drinking, unhealthy napping and irregular eating habits among low-income people may be ineffective in reduction of income-related disparities in prevalence of CVD and hypertension

Efficient Gender Classification Using a Deep LDA-Pruned Net

Many real-time tasks, such as human-computer interaction, require fast and efficient facial gender classification. Although deep CNN nets have been very effective for a multitude of classification tasks, their high space and time demands make them impractical for personal computers and mobile devices without a powerful GPU. In this paper, we develop a 16-layer, yet lightweight, neural network which boosts efficiency while maintaining high accuracy. Our net is pruned from the VGG-16 model starting from the last convolutional (conv) layer where we find neuron activations are highly uncorrelated given the gender. Through Fisher's Linear Discriminant Analysis (LDA), we show that this high decorrelation makes it safe to discard directly last conv layer neurons with high within-class variance and low between-class variance. Combined with either Support Vector Machines (SVM) or Bayesian classification, the reduced CNNs are capable of achieving comparable (or even higher) accuracies on the LFW and CelebA datasets than the original net with fully connected layers. On LFW, only four Conv5_3 neurons are able to maintain a comparably high recognition accuracy, which results in a reduction of total network size by a factor of 70X with a 11 fold speedup. Comparisons with a state-of-the-art pruning method as well as two smaller nets in terms of accuracy loss and convolutional layers pruning rate are also provided.Comment: The only difference with the previous version v2 is the title on the arxiv page. I am changing it back to the original title in v1 because otherwise google scholar cannot track the citations to this arxiv paper correctly. You could cite either the conference version or this arxiv version. They are equivalen

Flux-lattice melting in LaO1−x_{1-x}Fx_{x}FeAs: first-principles prediction

We report the theoretical study of the flux-lattice melting in the novel iron-based superconductor $LaO_{0.9}F_{0.1}FeAs$ and $LaO_{0.925}F_{0.075}FeAs$. Using the Hypernetted-Chain closure and an efficient algorithm, we calculate the two-dimensional one-component plasma pair distribution functions, static structure factors and direct correlation functions at various temperatures. The Hansen-Verlet freezing criterion is shown to be valid for vortex-liquid freezing in type-II superconductors. Flux-lattice meting lines for $LaO_{0.9}F_{0.1}FeAs$ and $LaO_{0.925}F_{0.075}FeAs$ are predicted through the combination of the density functional theory and the mean-field substrate approach.Comment: 5 pages, 4 figures, to appear in Phys. Rev.

Field-Induced Ferromagnetic Order and Colossal Magnetoresistance in La_{1.2}Sr_{1.8}Mn_2O_7: a ^{139}La NMR study

In order to gain insights into the origin of colossal magneto-resistance (CMR) in manganese oxides, we performed a ^{139}La NMR study in the double-layered compound La_{1.2}Sr_{1.8}Mn_2O_7. We find that above the Curie temperature T_C=126 K, applying a magnetic field induces a long-range ferromagnetic order that persists up to T=330 K. The critical field at which the induced magnetic moment is saturated coincides with the field at which the CMR effect reaches to a maximum. Our results therefore indicate that the CMR observed above T_C in this compound is due to the field-induced ferromagnetism that produces a metallic state via the double exchange interaction