Focus groups as a knowledge elicitation technique: an exploratorystudy

The authors examine whether one technique for group knowledge elicitation, focus groups, can provide different thoughts and judgments about a problem than individual interviews. The experimental situation was based on the resolution of an ill-structured problem by experienced subjects in a field setting. Videotaped scenarios were used to describe the situation for knowledge acquisition. Ten subjects were used, five for individual interviews and five for the focus groups. It was found that focus groups performed better in generating original responses than individual interviews and that focus groups were at least as good as individual interviews in terms of the quality and acceptability of ideas     

Defining a synthetic pheromone blend attractive to male Heliothis subflexa under wind tunnel conditions

Heliothis subflexa males were flown in a wind tunnel to a variety of combinations of synthetic pheromone components admixed on a filter paper disk. Blends containing (Z)-11-hexadecenal (Z11–16:Ald, 1000 ng), (Z)-9-hexadecenal (Z9–16:Ald, 500 ng) and (Z)-11-hexadecenol (Z11–16:OH, 10–500 ng) elicited upwind flight and source contact in 52–69% of males. All these compounds have previously been isolated and identified from female H. subflexa gland extracts and volatile pheromone emissions. Males were not attracted by blends in which Z9–16:Ald was omitted (0% source contact). Similarly, blends lacking Z11–16:OH were unattractive to male H. subflexa (3% or less source contact). Males were extremely sensitive to the presence of Z11–16:OH; however, responding in high numbers (57–69% source contact) to blends containing a dosage of 1% (10 ng) or greater Z11–16:OH. Males were unresponsive to blends in which Z9–16:Ald was replaced with a variety of dosages of (Z)-9-tetradecenal, a secondary component of a closely-related congeneric species, Heliothis virescens. Another compound present in the blend emitted by conspecific females, (Z)-11-hexadecenyl acetate (Z11–16:Ac), did not inhibit H. subflexa males (69% source contact) when added to the three-component mixture (1:0.5:0.1) at a ratio of 0.1 (100 ng) with respect to Z11–16:Ald. These results indicate that Z9–16:Ald and Z11–16:OH are required in addition to Z11–16:Ald to elicit significant levels of upwind flight in H. subflexa males. The effects of Z11–16:Ac are more subtle, but at the dosage tested in these experiments, this compound does not have an antagonistic effect on upwind flight and source location by H. subflexa males.     

Evolution-in-materio: solving computational problems using carbon nanotube–polymer composites

Evolution-in-materio uses evolutionary algorithms to exploit properties of materials to solve computational problems without requiring a detailed understanding of such properties. We show that using a purpose-built hardware platform called Mecobo, it is possible to solve computational problems by evolving voltages and signals applied to an electrode array covered with a carbon nanotube–polymer composite. We demonstrate for the first time that this methodology can be applied to function optimization and also to the tone discriminator problem (TDP). For function optimization, we evaluate the approach on a suite of optimization benchmarks and obtain results that in some cases come very close to the global optimum or are comparable with those obtained using well-known software-based evolutionary approach. We also obtain good results in comparison with prior work on the tone discriminator problem. In the case of the TDP we also investigated the relative merits of different mixtures of materials and organizations of electrode array.     

Adiabatic quantum optimization with qudits

Most realistic solid state devices considered as qubits are not true two-state systems. If the energy separation of the upper energy levels from the lowest two levels is not large, then these upper states may affect the evolution of the ground state over time and therefore cannot be neglected. In this work, we study the effect of energy levels beyond the lowest two energy levels on adiabatic quantum optimization in a device with a double-well potential as the basic logical element. We show that the extra levels can be modeled by adding additional ancilla qubits coupled to the original logical qubits, and that the presence of upper levels has no effect on the final ground state. We also study the influence of upper energy levels on the minimum gap for a set of 8-qubit spin glass instances.     

Characterisation of flucloxacillin and 5-hydroxymethyl flucloxacillin haptenated HSA in vitro and in vivo

Flucloxacillin is a synthetic penicillin used in the treatment of Staphylococcal infections. Adverse reactions to the drug are believed to arise through covalent modification of proteins, with tissue damage occurring secondary to an immune reaction. Serum proteins have been shown by adduct-specific antibodies to be modified by flucloxacillin, but the nature and sites of modification have not been characterised. Here, in vitro studies on HSA have shown by MS that the modification of protein lysine residues occurs in a dose-, time- and site-dependent manner. Affinity, cation exchange and reversed phase chromatography prior to MS revealed in vivo modification of HSA with flucloxacillin in tolerant patients, with up to nine modified lysine residues being detected in each patient, and with modification of Lys190 and Lys212 being detected in 8/8 patients. It was also revealed for the first time that plasma proteins could be modified with the 5-hydroxymethyl metabolite of flucloxacillin, and that essentially the same Lys residues were targeted by both the parent drug and its metabolite. This study provides a detailed characterisation of sites of chemical modification of an endogenous target and reveals candidate peptides for T-cell and antibody assays of flucloxacillin hypersensitivity.     

Partitioning large networks without breaking communities

The identification of cohesive communities is a key process in social network analysis. However, the algorithms that are effective for finding communities do not scale well to very large problems, as their time complexity is worse than linear in the number of edges in the graph. This is an important issue for those interested in applying social network analysis techniques to very large networks, such as networks of mobile phone subscribers. In this respect, the contributions of this paper are twofold. First, we demonstrate these scaling issues using a prominent community-finding algorithm as a case study. Then, we show that a two-stage process, whereby the network is first decomposed into manageable subnetworks using a multilevel graph partitioning procedure, is effective in finding communities in networks with more than 10⁶ nodes.     

FeynRules - Feynman rules made easy

In this paper we present FeynRules, a new Mathematica package that facilitates the implementation of new particle physics models. After the user implements the basic model information (e.g., particle content, parameters and Lagrangian), FeynRules derives the Feynman rules and stores them in a generic form suitable for translation to any Feynman diagram calculation program. The model can then be translated to the format specific to a particular Feynman diagram calculator via FeynRules translation interfaces. Such interfaces have been written for CalcHEP/CompHEP, FeynArts/FormCalc, MadGraph/MadEvent and Sherpa, making it possible to write a new model once and have it work in all of these programs. In this paper, we describe how to implement a new model, generate the Feynman rules, use a generic translation interface, and write a new translation interface. We also discuss the details of the FeynRules code.

Program summary

Program title: FeynRulesCatalogue identifier: AEDI_v1_0Program summary URL::http://cpc.cs.qub.ac.uk/summaries/AEDI_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 15 980No. of bytes in distributed program, including test data, etc.: 137 383Distribution format: tar.gzProgramming language: MathematicaComputer: Platforms on which Mathematica is availableOperating system: Operating systems on which Mathematica is availableClassification: 11.1, 11.2, 11.6Nature of problem: Automatic derivation of Feynman rules from a Lagrangian. Implementation of new models into Monte Carlo event generators and FeynArts.Solution method: FeynRules works in two steps:

1. derivation of the Feynman rules directly form the Lagrangian using canonical commutation relations among fields and creation operators.

2. implementation of the new physics model into FeynArts as well as various Monte Carlo programs via interfaces.

Full-size table

     

A new representation and associated algorithms for generalized planning

Constructing plans that can handle multiple problem instances is a longstanding open problem in AI. We present a framework for generalized planning that captures the notion of algorithm-like plans and unifies various approaches developed for addressing this problem. Using this framework, and building on the TVLA system for static analysis of programs, we develop a novel approach for computing generalizations of classical plans by identifying sequences of actions that will make measurable progress when placed in a loop. In a wide class of problems that we characterize formally in the paper, these methods allow us to find generalized plans with loops for solving problem instances of unbounded sizes and also to determine the correctness and applicability of the computed generalized plans. We demonstrate the scope and scalability of the proposed approach on a wide range of planning problems.