Validating Sample Average Approximation Solutions with Negatively Dependent Batches

Sample-average approximations (SAA) are a practical means of finding approximate solutions of stochastic programming problems involving an extremely large (or infinite) number of scenarios. SAA can also be used to find estimates of a lower bound on the optimal objective value of the true problem which, when coupled with an upper bound, provides confidence intervals for the true optimal objective value and valuable information about the quality of the approximate solutions. Specifically, the lower bound can be estimated by solving multiple SAA problems (each obtained using a particular sampling method) and averaging the obtained objective values. State-of-the-art methods for lower-bound estimation generate batches of scenarios for the SAA problems independently. In this paper, we describe sampling methods that produce negatively dependent batches, thus reducing the variance of the sample-averaged lower bound estimator and increasing its usefulness in defining a confidence interval for the optimal objective value. We provide conditions under which the new sampling methods can reduce the variance of the lower bound estimator, and present computational results to verify that our scheme can reduce the variance significantly, by comparison with the traditional Latin hypercube approach

The Flexible Group Spatial Keyword Query

We present a new class of service for location based social networks, called the Flexible Group Spatial Keyword Query, which enables a group of users to collectively find a point of interest (POI) that optimizes an aggregate cost function combining both spatial distances and keyword similarities. In addition, our query service allows users to consider the tradeoffs between obtaining a sub-optimal solution for the entire group and obtaining an optimimized solution but only for a subgroup. We propose algorithms to process three variants of the query: (i) the group nearest neighbor with keywords query, which finds a POI that optimizes the aggregate cost function for the whole group of size n, (ii) the subgroup nearest neighbor with keywords query, which finds the optimal subgroup and a POI that optimizes the aggregate cost function for a given subgroup size m (m <= n), and (iii) the multiple subgroup nearest neighbor with keywords query, which finds optimal subgroups and corresponding POIs for each of the subgroup sizes in the range [m, n]. We design query processing algorithms based on branch-and-bound and best-first paradigms. Finally, we provide theoretical bounds and conduct extensive experiments with two real datasets which verify the effectiveness and efficiency of the proposed algorithms.Comment: 12 page

Fully Gapped Superconducting State Based on a High Normal State Quasiparticle Density of States in Ba0.6_{0.6}K0.4_{0.4}Fe2_2As2_2 Single Crystals

We report the specific heat (SH) measurements on single crystals of hole doped $FeAs$-based superconductor $Ba_{0.6}K_{0.4}Fe_2As_2$. It is found that the electronic SH coefficient $\gamma_e(T)$ is not temperature dependent and increases almost linearly with the magnetic field in low temperature region. These point to a fully gapped superconducting state. Surprisingly the sharp SH anomaly $\Delta C/T|_{T_c}$ reaches a value of 98 $mJ/mol K^2$ suggesting a very high normal state quasiparticle density of states ($\gamma_n \approx 63 mJ/mol K^2$). A detailed analysis reveals that the $\gamma_e(T)$ cannot be fitted with a single gap of s-wave symmetry due to the presence of a hump in the middle temperature region. However, our data indicate that the dominant part of the superconducting condensate is induced by an s-wave gap with the magnitude of about 6 meV.Comment: 5 pages, 5 figure

Combining SNP discovery from next-generation sequencing data with bulked segregant analysis (BSA) to fine-map genes in polyploid wheat

<p>Abstract</p> <p>Background</p> <p>Next generation sequencing (NGS) technologies are providing new ways to accelerate fine-mapping and gene isolation in many species. To date, the majority of these efforts have focused on diploid organisms with readily available whole genome sequence information. In this study, as a proof of concept, we tested the use of NGS for SNP discovery in tetraploid wheat lines differing for the previously cloned grain protein content (GPC) gene <it>GPC-B1</it>. Bulked segregant analysis (BSA) was used to define a subset of putative SNPs within the candidate gene region, which were then used to fine-map <it>GPC-B1</it>.</p> <p>Results</p> <p>We used Illumina paired end technology to sequence mRNA (RNAseq) from near isogenic lines differing across a ~30-cM interval including the <it>GPC-B1 </it>locus. After discriminating for SNPs between the two homoeologous wheat genomes and additional quality filtering, we identified inter-varietal SNPs in wheat unigenes between the parental lines. The relative frequency of these SNPs was examined by RNAseq in two bulked samples made up of homozygous recombinant lines differing for their GPC phenotype. SNPs that were enriched at least 3-fold in the corresponding pool (6.5% of all SNPs) were further evaluated. Marker assays were designed for a subset of the enriched SNPs and mapped using DNA from individuals of each bulk. Thirty nine new SNP markers, corresponding to 67% of the validated SNPs, mapped across a 12.2-cM interval including <it>GPC-B1</it>. This translated to 1 SNP marker per 0.31 cM defining the <it>GPC-B1 </it>gene to within 13-18 genes in syntenic cereal genomes and to a 0.4 cM interval in wheat.</p> <p>Conclusions</p> <p>This study exemplifies the use of RNAseq for SNP discovery in polyploid species and supports the use of BSA as an effective way to target SNPs to specific genetic intervals to fine-map genes in unsequenced genomes.</p

Colonial legacies: shaping African cities

Differential institutions imposed during colonial rule continue to affect the spatial structure and urban interactions in African cities. Based on a sample of 318 cities across 28 countries using satellite data on built cover over time, Anglophone origin cities sprawl compared to Francophone ones. Anglophone cities have less intense land use and more irregular layout in the older colonial portions of cities, and more leapfrog development at the extensive margin. Results are impervious to a border experiment, many robustness tests, measures of sprawl, and sub-samples. Why would colonial origins matter? The British operated under indirect rule and a dual mandate within cities, allowing colonial and native sections to develop without an overall plan and coordination. In contrast, integrated city planning and land allocation mechanisms were a feature of French colonial rule, which was inclined to direct rule. The results also have public policy relevance. From the Demographic and Health Survey, similar households, which are located in areas of the city with more leapfrog development, have poorer connections to piped water, electricity, and landlines, presumably because of higher costs of providing infrastructure with urban sprawl