1,218 research outputs found

    How Hard Is Deciding Trivial Versus Nontrivial in the Dihedral Coset Problem?

    Get PDF
    We study the hardness of the dihedral hidden subgroup problem. It is known that lattice problems reduce to it, and that it reduces to random subset sum with density > 1 and also to quantum sampling subset sum solutions. We examine a decision version of the problem where the question asks whether the hidden subgroup is trivial or order two. The decision problem essentially asks if a given vector is in the span of all coset states. We approach this by first computing an explicit basis for the coset space and the perpendicular space. We then look at the consequences of having efficient unitaries that use this basis. We show that if a unitary maps the basis to the standard basis in any way, then that unitary can be used to solve random subset sum with constant density >1. We also show that if a unitary can exactly decide membership in the coset subspace, then the collision problem for subset sum can be solved for density >1 but approaching 1 as the problem size increases. This strengthens the previous hardness result that implementing the optimal POVM in a specific way is as hard as quantum sampling subset sum solutions

    Characterizing Question Facets for Complex Answer Retrieval

    Get PDF
    Complex answer retrieval (CAR) is the process of retrieving answers to questions that have multifaceted or nuanced answers. In this work, we present two novel approaches for CAR based on the observation that question facets can vary in utility: from structural (facets that can apply to many similar topics, such as 'History') to topical (facets that are specific to the question's topic, such as the 'Westward expansion' of the United States). We first explore a way to incorporate facet utility into ranking models during query term score combination. We then explore a general approach to reform the structure of ranking models to aid in learning of facet utility in the query-document term matching phase. When we use our techniques with a leading neural ranker on the TREC CAR dataset, our methods rank first in the 2017 TREC CAR benchmark, and yield up to 26% higher performance than the next best method.Comment: 4 pages; SIGIR 2018 Short Pape

    Root foraging capacity in bambara groundnut (Vigna subterranea (L.) Verdc.) core parental lines depends on the root system architecture during the pre-flowering stage

    Get PDF
    © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Characterizing the morphological variability in root system architecture (RSA) during the sensitive pre-flowering growth stage is important for crop performance. To assess this variation, eight bambara groundnut single genotypes derived from landraces of contrasting geographic origin were selected for root system architecture and rooting distribution studies. Plants were grown in a polyvinyl chloride (PVC) column system under controlled water and nutrient availability in a rainout shelter. Days to 50% plant emergence was characterized during the first two weeks after sowing, while taproot length (TRL), root length (RL), root length density (RLD), branching number (BN), branching density (BD) and intensity (BI), surface area (SA), root volume (RV), root diameter (RDia), root dry weight (RDW), shoot dry weight (SDW), and shoot height (SH) were determined at the end of the experiment, i.e., 35 days after emergence. Genotypes S19-3 and DipC1 sourced from drier regions of sub-Saharan Africa generally had longer taproots and greater root length distribution in deeper (60 to 90 cm) soil depths. In contrast, bambara groundnut genotypes from wetter regions (i.e., Gresik, Lunt, and IITA-686) in Southeast Asia and West Africa exhibited relatively shallow and highly branched root growth closer to the soil surface. Genotypes at the pre-flowering growth stage showed differential root foraging patterns and branching habits with two extremes, i.e., deep-cheap rooting in the genotypes sourced from dry regions and a shallow-costly rooting system in genotypes adapted to higher rainfall areas with shallow soils. We propose specific bambara groundnut genotype as donors in root trait driven breeding programs to improve water capture and use efficiency

    A high-throughput microfluidic approach for 1000-fold leukocyte reduction of platelet-rich plasma

    Get PDF
    Leukocyte reduction of donated blood products substantially reduces the risk of a number of transfusion-related complications. Current ‘leukoreduction’ filters operate by trapping leukocytes within specialized filtration material, while allowing desired blood components to pass through. However, the continuous release of inflammatory cytokines from the retained leukocytes, as well as the potential for platelet activation and clogging, are significant drawbacks of conventional ‘dead end’ filtration. To address these limitations, here we demonstrate our newly-developed ‘controlled incremental filtration’ (CIF) approach to perform high-throughput microfluidic removal of leukocytes from platelet-rich plasma (PRP) in a continuous flow regime. Leukocytes are separated from platelets within the PRP by progressively syphoning clarified PRP away from the concentrated leukocyte flowstream. Filtrate PRP collected from an optimally-designed CIF device typically showed a ~1000-fold (i.e. 99.9%) reduction in leukocyte concentration, while recovering >80% of the original platelets, at volumetric throughputs of ~1?mL/min. These results suggest that the CIF approach will enable users in many fields to now apply the advantages of microfluidic devices to particle separation, even for applications requiring macroscale flowrates

    A cross-species gene expression marker-based genetic map and QTL analysis in bambara groundnut

    Get PDF
    Bambara groundnut (Vigna subterranea (L.) Verdc.) is an underutilised legume crop, which has long been recognised as a protein-rich and drought-tolerant crop, used extensively in Sub-Saharan Africa. The aim of the study was to identify quantitative trait loci (QTL) involved in agronomic and drought-related traits using an expression marker-based genetic map based on major crop resources developed in soybean. The gene expression markers (GEMs) were generated at the (unmasked) probe-pair level after cross-hybridisation of bambara groundnut leaf RNA to the Affymetrix Soybean Genome GeneChip. A total of 753 markers grouped at an LOD (Logarithm of odds) of three, with 527 markers mapped into linkage groups. From this initial map, a spaced expression marker-based genetic map consisting of 13 linkage groups containing 218 GEMs, spanning 982.7 cM (centimorgan) of the bambara groundnut genome, was developed. Of the QTL detected, 46% were detected in both control and drought treatment populations, suggesting that they are the result of intrinsic trait differences between the parental lines used to construct the cross, with 31% detected in only one of the conditions. The present GEM map in bambara groundnut provides one technically feasible route for the translation of information and resources from major and model plant species to underutilised and resource-poor crops

    Applying molecular genetics to underutilised species – problems and opportunities

    Get PDF
    Molecular markers represent an important tool for marker-assisted breeding in major crop plant breeding programmes. Applying molecular genetics to underutilised and minor crop species is more challenging as the funds available to research and develop such crops are often severely limited. Bambara groundnut is an underutilised African legume crop with good drought tolerance. It is also grown at low levels in Southeast Asia. In this review we examine some of the applications of DNA markers and illustrate their value in bambara groundnut
    • …
    corecore