Electroweak Theory and Noncommutative Geometry

The noncommutative generalisation of the standard electroweak model due to Balakrishna, Gursey and Wali is formulated in terms of the derivations Der_2(M_3) of a three dimensional representation of the su(2) Lie algebra of weak isospin. A light Higgs boson of mass about 130 GeV, together with four very heavy scalar bosons are predicted.Comment: 11 pages, LATEX, no figures. Talk given at the 2nd Gursey Memorial Conference, June 2000, Istanbu

Software defect prediction: do different classifiers find the same defects?

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.During the last 10 years, hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. We investigate the individual defects that four classifiers predict and analyse the level of prediction uncertainty produced by these classifiers. We perform a sensitivity analysis to compare the performance of Random Forest, Naïve Bayes, RPart and SVM classifiers when predicting defects in NASA, open source and commercial datasets. The defect predictions that each classifier makes is captured in a confusion matrix and the prediction uncertainty of each classifier is compared. Despite similar predictive performance values for these four classifiers, each detects different sets of defects. Some classifiers are more consistent in predicting defects than others. Our results confirm that a unique subset of defects can be detected by specific classifiers. However, while some classifiers are consistent in the predictions they make, other classifiers vary in their predictions. Given our results, we conclude that classifier ensembles with decision-making strategies not based on majority voting are likely to perform best in defect prediction.Peer reviewedFinal Published versio

Scaling Cosmologies from Duality Twisted Compactifications

Oscillating moduli fields can support a cosmological scaling solution in the presence of a perfect fluid when the scalar field potential satisfies appropriate conditions. We examine when such conditions arise in higher-dimensional, non-linear sigma-models that are reduced to four dimensions under a generalized Scherk-Schwarz compactification. We show explicitly that scaling behaviour is possible when the higher-dimensional action exhibits a global SL(n,R) or O(2,2) symmetry. These underlying symmetries can be exploited to generate non-trivial scaling solutions when the moduli fields have non-canonical kinetic energy. We also consider the compactification of eleven-dimensional vacuum Einstein gravity on an elliptic twisted torus.Comment: 21 pages, 3 figure

On the perturbative chiral ring for marginally deformed N=4 SYM theories

For \cal{N}=1 SU(N) SYM theories obtained as marginal deformations of the \cal{N}=4 parent theory we study perturbatively some sectors of the chiral ring in the weak coupling regime and for finite N. By exploiting the relation between the definition of chiral ring and the effective superpotential we develop a procedure which allows us to easily determine protected chiral operators up to n loops once the superpotential has been computed up to (n-1) order. In particular, for the Lunin-Maldacena beta-deformed theory we determine the quantum structure of a large class of operators up to three loops. We extend our procedure to more general Leigh-Strassler deformations whose chiral ring is not fully understood yet and determine the weight-two and weight-three sectors up to two loops. We use our results to infer general properties of the chiral ring.Comment: LaTex, 40 pages, 4 figures, uses JHEP3; v2: minor correction

Lectures on Nongeometric Flux Compactifications

These notes present a pedagogical review of nongeometric flux compactifications. We begin by reviewing well-known geometric flux compactifications in Type II string theory, and argue that one must include nongeometric "fluxes" in order to have a superpotential which is invariant under T-duality. Additionally, we discuss some elementary aspects of the worldsheet description of nongeometric backgrounds. This review is based on lectures given at the 2007 RTN Winter School at CERN.Comment: 31 pages, JHEP

Long-term performance of a plant microbial fuel cell with Spartina anglica

The plant microbial fuel cell is a sustainable and renewable way of electricity production. The plant is integrated in the anode of the microbial fuel cell which consists of a bed of graphite granules. In the anode, organic compounds deposited by plant roots are oxidized by electrochemically active bacteria. In this research, salt marsh species Spartina anglica generated current for up to 119 days in a plant microbial fuel cell. Maximum power production was 100 mW m−2 geometric anode area, highest reported power output for a plant microbial fuel cell. Cathode overpotential was the main potential loss in the period of oxygen reduction due to slow oxygen reduction kinetics at the cathode. Ferricyanide reduction improved the kinetics at the cathode and increased current generation with a maximum of 254%. In the period of ferricyanide reduction, the main potential loss was transport loss. This research shows potential application of microbial fuel cell technology in salt marshes for bio-energy production with the plant microbial fuel cell

Electroosmotically generated disinfectant from urine as a by-product of electricity in microbial fuel cell for the inactivation of pathogenic species

This work presents a small scale and low cost ceramic based microbial fuel cell, utilising human urine into electricity, while producing clean catholyte into an initially empty cathode chamber through the process of electro-osmostic drag. It is the first time that the catholyte obtained as a by-product of electricity generation from urine was transparent in colour and reached pH>13 with high ionic conductivity values. The catholyte was collected and used ex situ as a killing agent for the inactivation of a pathogenic species such as Salmonella typhimurium, using a luminometer assay. Results showed that the catholyte solutions were efficacious in the inactivation of the pathogen organism even when diluted up to 1:10, resulting in more than 5 log-fold reduction in 4 min. Long-term impact of the catholyte on the pathogen killing was evaluated by plating Salmonella typhimurium on agar plates and showed that the catholyte possesses a long-term killing efficacy and continued to inhibit pathogen growth for 10 days

The Prevalence of Errors in Machine Learning Experiments

Context: Conducting experiments is central to research machine learning research to benchmark, evaluate and compare learning algorithms. Consequently it is important we conduct reliable, trustworthy experiments. Objective: We investigate the incidence of errors in a sample of machine learning experiments in the domain of software defect prediction. Our focus is simple arithmetical and statistical errors. Method: We analyse 49 papers describing 2456 individual experimental results from a previously undertaken systematic review comparing supervised and unsupervised defect prediction classifiers. We extract the confusion matrices and test for relevant constraints, e.g., the marginal probabilities must sum to one. We also check for multiple statistical significance testing errors. Results: We find that a total of 22 out of 49 papers contain demonstrable errors. Of these 7 were statistical and 16 related to confusion matrix inconsistency (one paper contained both classes of error). Conclusions: Whilst some errors may be of a relatively trivial nature, e.g., transcription errors their presence does not engender confidence. We strongly urge researchers to follow open science principles so errors can be more easily be detected and corrected, thus as a community reduce this worryingly high error rate with our computational experiments