A Raman-Heterodyne Study of the Hyperfine Interaction of the Optically-Excited State 5^5D0_0 of Eu3+^{3+}:Y2_2SiO5_5

The spin coherence time of $^{151}$Eu$^{3+}$ which substitutes the yttrium at site 1 in Y$_2$SiO$_5$ crystal has been extended to 6 hours in a recent work [\textit{Nature} \textbf{517}, 177 (2015)]. To make this long-lived spin coherence useful for optical quantum memory applications, we experimentally characterize the hyperfine interaction of the optically-excited state $^5$D$_0$ using Raman-heterodyne-detected nuclear magnetic resonance. The effective spin Hamiltonians for excited and ground state are fitted based on the experimental spectra obtained in 200 magnetic fields with various orientations. To show the correctness of the fitted parameters and potential application in quantum memory protocols, we also characterize the ground-state hyperfine interaction and predict the critical magnetic field which produces the 6-hour-long coherence time. The complete energy level structure for both the $^7$F$_0$ ground state and $^5$D$_0$ excited state at the critical magnetic field are obtained. These results enable the design of quantum memory protocols and the optimization of optical pumping strategy for realization of photonic quantum memory with hour-long lifetime

Integrating PPC and Flat Fee Pricing Schemes to Optimize the Internal Search Engine Revenue in the Electronic Market

Currently, the predominant pricing plan for the search engine (SE) advertising services in a proprietary electronic market is a flat fee (FF) pricing. These services have faced the challenge of customer attrition recently since FF pricing results in the inequality of service surplus among subscribers. A more sustainable and profitable pricing model would be to distinguish advertising resources by providing an additional usage-based pricing for certain user groups to transfer the service surplus among subscribers. We conceive a hybrid model integrating Pay-Per-Click (PPC) pricing into FF pricing. This proposed scheme can offer an incentive-compatible mechanism to attract more subscribers by relieving the inequity of service surplus, and eventually result in the increasing revenue of service providers

Automatic Prediction of Rheumatoid Arthritis Disease Activity from the Electronic Medical Records

Objective: We aimed to mine the data in the Electronic Medical Record to automatically discover patients' Rheumatoid Arthritis disease activity at discrete rheumatology clinic visits. We cast the problem as a document classification task where the feature space includes concepts from the clinical narrative and lab values as stored in the Electronic Medical Record. Materials and Methods The Training Set consisted of 2792 clinical notes and associated lab values. Test Set 1 included 1749 clinical notes and associated lab values. Test Set 2 included 344 clinical notes for which there were no associated lab values. The Apache clinical Text Analysis and Knowledge Extraction System was used to analyze the text and transform it into informative features to be combined with relevant lab values. Results: Experiments over a range of machine learning algorithms and features were conducted. The best performing combination was linear kernel Support Vector Machines with Unified Medical Language System Concept Unique Identifier features with feature selection and lab values. The Area Under the Receiver Operating Characteristic Curve (AUC) is 0.831 (σ = 0.0317), statistically significant as compared to two baselines (AUC = 0.758, σ = 0.0291). Algorithms demonstrated superior performance on cases clinically defined as extreme categories of disease activity (Remission and High) compared to those defined as intermediate categories (Moderate and Low) and included laboratory data on inflammatory markers. Conclusion: Automatic Rheumatoid Arthritis disease activity discovery from Electronic Medical Record data is a learnable task approximating human performance. As a result, this approach might have several research applications, such as the identification of patients for genome-wide pharmacogenetic studies that require large sample sizes with precise definitions of disease activity and response to therapies

The Impact of Social Context on Preschoolers’ Flexibility

The current study investigates whether social interaction without communication between partners may influence preschoolers’ flexibility. Fifty-three 5 year old Singaporean children were randomly assigned to three conditions of a block sorting task (Fawcett & Garton, 2005): playing individually, cooperating with another player, and competing against another player. To control for individual differences, before the block sorting task children were given four cognitive tasks testing vocabulary, short-term memory, and executive function, as well as two affective scales on mood and motivation. Separate one-way Analysis of Variance (ANOVA) showed that although they performed the same on the cognitive tasks and the affective measures, children in the competition condition sorted blocks along significantly more dimensions compared to children in the individual condition. These results suggest that preschoolers’ flexibility is sensitive to social contexts

A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms

We describe a genetic variation map for the chicken genome containing 2.8 million single-nucleotide polymorphisms ( SNPs). This map is based on a comparison of the sequences of three domestic chicken breeds ( a broiler, a layer and a Chinese silkie) with that of their wild ancestor, red jungle fowl. Subsequent experiments indicate that at least 90% of the variant sites are true SNPs, and at least 70% are common SNPs that segregate in many domestic breeds. Mean nucleotide diversity is about five SNPs per kilobase for almost every possible comparison between red jungle fowl and domestic lines, between two different domestic lines, and within domestic lines - in contrast to the notion that domestic animals are highly inbred relative to their wild ancestors. In fact, most of the SNPs originated before domestication, and there is little evidence of selective sweeps for adaptive alleles on length scales greater than 100 kilobases

PSR J1926-0652: A Pulsar with Interesting Emission Properties Discovered at FAST

We describe PSR J1926-0652, a pulsar recently discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Using sensitive single-pulse detections from FAST and long-term timing observations from the Parkes 64-m radio telescope, we probed phenomena on both long and short time scales. The FAST observations covered a wide frequency range from 270 to 800 MHz, enabling individual pulses to be studied in detail. The pulsar exhibits at least four profile components, short-term nulling lasting from 4 to 450 pulses, complex subpulse drifting behaviours and intermittency on scales of tens of minutes. While the average band spacing P3 is relatively constant across different bursts and components, significant variations in the separation of adjacent bands are seen, especially near the beginning and end of a burst. Band shapes and slopes are quite variable, especially for the trailing components and for the shorter bursts. We show that for each burst the last detectable pulse prior to emission ceasing has different properties compared to other pulses. These complexities pose challenges for the classic carousel-type models.Comment: 13pages with 12 figure