Spin-orbit effects on two-electron states in nanowhisker double quantum dots

We investigate theoretically the combined effects of the electron-electron and the Rashba spin-orbit interactions on two electrons confined in quasi-one-dimensional AlInSb-based double quantum dots. We calculate the two-electron wave functions and explore the interplay between these two interactions on the energy levels and the spin of the states. The energy spectrum as a function of an applied magnetic field shows crossings and anticrossings between triplet and singlet states, associated with level mixing induced by the spin-orbit coupling. We find that the fields at which these crossings occur can be naturally controlled by the interdot barrier width, which controls the exchange integral in the structure.Comment: 5 pages, 6 figure

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits

Space Telescope and Optical Reverberation Mapping Project. VII. Understanding the Ultraviolet Anomaly in NGC 5548 with X-Ray Spectroscopy

During the Space Telescope and Optical Reverberation Mapping Project observations of NGC 5548, the continuum and emission-line variability became decorrelated during the second half of the six-month-long observing campaign. Here we present Swift and Chandra X-ray spectra of NGC 5548 obtained as part of the campaign. The Swift spectra show that excess flux (relative to a power-law continuum) in the soft X-ray band appears before the start of the anomalous emission-line behavior, peaks during the period of the anomaly, and then declines. This is a model-independent result suggesting that the soft excess is related to the anomaly. We divide the Swift data into on- and off-anomaly spectra to characterize the soft excess via spectral fitting. The cause of the spectral differences is likely due to a change in the intrinsic spectrum rather than to variable obscuration or partial covering. The Chandra spectra have lower signal-to-noise ratios, but are consistent with the Swift data. Our preferred model of the soft excess is emission from an optically thick, warm Comptonizing corona, the effective optical depth of which increases during the anomaly. This model simultaneously explains all three observations: the UV emission-line flux decrease, the soft-excess increase, and the emission-line anomaly

An optimal strategy for extracting probabilistic rules by combining rough sets and genetic algorithm

This paper proposes an optimal strategy for extracting probabilistic rules from databases. Two inductive learning-based statistic measures and their rough set-based definitions: accuracy and coverage are introduced. The simplicity of a rule emphasized in this paper has previously been ignored in the discovery of probabilistic rules. To avoid the high computational complexity of rough-set approach, some rough-set terminologies rather than the approach itself are applied to represent the probabilistic rules. The genetic algorithm is exploited to find the optimal probabilistic rules that have the highest accuracy and coverage, and shortest length. Some heuristic genetic operators are also utilized in order to make the global searching and evolution of rules more efficiently. Experimental results have revealed that it run more efficiently and generate probabilistic classification rules of the same integrity when compared with traditional classification methods.<br /

Transthoracic Doppler echocardiography assessment of left anterior descending artery flow in patients with previous anterior myocardial infarction

Aim: We tested the hypothesis that shortening of diastolic pressure half time (PHT) of left anterior descending (LAD) coronary flow in patients with old reperfused anterior myocardial infarction (MI) is related to the presence of permanent myocardial damage of the reperfused area. Methods and results: We studied 49 patients divided into: group A: 15 patients with previous anterior MI and evidence of myocardial scar; group B: 10 patients with previous anterior MI and no evidence of myocardial scar and group C: 24 patients without anterior MI. All patients underwent coronary angiography at least 6 months after an index event and any reperfusion procedure. Group A patients had lower PHT (199 ± 62 ms) than group C (377 ± 103 ms, p = 0.0001) and group B (316 ± 154 ms, p = 0.029) patients. No other LAD flow velocity parameter differed among the 3 groups. A PHT value of 265 ms discriminated patients with scarred anteriorwallwith a sensitivity of 79% and a specificity of 94% (0.88, p < 0.001). Conclusion: Shortening of the LAD flow diastolic PHT in patients with remote, reperfused anterior MI reflects scarred myocardial tissue in the anteroapical wall while patients who maintain diastolic wall thickness after an acute coronary syndrome have PHT similar to patients without anterior MI