'The time where the British took the lead is over': ethical aspects of writing in complex research partnerships

Writing reflects some of the different characteristics of the language being used and of the people who are communicating. The present paper focusses on the internal written communication in international and inter-disciplinary research projects. Using a case study of an international public health research project, it argues that the authorship and the languages used in internal project communication are not neutral but help to generate or reinforce power hierarchies. Within research partnerships, language thus raises ethical issues that have so far been neglected. Current ethics guidelines often focus on interactions between scientists and participants of social research and clinical trials, with less attention paid to the interactions among the scientists themselves. Describing all the different project phases based on writing within a research project, the paper distinguishes different influences on the distribution of power that emerge through a focus on written communication. The focus of the present paper is to illuminate the issues of ethics, power and the dimensions of hierarchy, physical location and native versus non-native English speakers that arise from paying attention to such communications

Denoising Autoencoders for fast Combinatorial Black Box Optimization

Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Autoencoders (AE) are generative stochastic networks with these desired properties. We integrate a special type of AE, the Denoising Autoencoder (DAE), into an EDA and evaluate the performance of DAE-EDA on several combinatorial optimization problems with a single objective. We asses the number of fitness evaluations as well as the required CPU times. We compare the results to the performance to the Bayesian Optimization Algorithm (BOA) and RBM-EDA, another EDA which is based on a generative neural network which has proven competitive with BOA. For the considered problem instances, DAE-EDA is considerably faster than BOA and RBM-EDA, sometimes by orders of magnitude. The number of fitness evaluations is higher than for BOA, but competitive with RBM-EDA. These results show that DAEs can be useful tools for problems with low but non-negligible fitness evaluation costs.Comment: corrected typos and small inconsistencie

A Study on Multimemetic Estimation of Distribution Algorithms

PPSN 2014, LNCS 8672, pp. 322-331Multimemetic algorithms (MMAs) are memetic algorithms in which memes (interpreted as non-genetic expressions of problem solving strategies) are explicitly represented and evolved alongside genotypes. This process is commonly approached using the standard genetic procedures of recombination and mutation to manipulate directly information at the memetic level. We consider an alternative approach based on the use of estimation of distribution algorithms to carry on this self-adaptive memetic optimization process. We study the application of different EDAs to this end, and provide an extensive experimental evaluation. It is shown that elitism is essential to achieve top performance, and that elitist versions of multimemetic EDAs using bivariate probabilistic models are capable of outperforming genetic MMAs.This work is partially supported by MICINN project ANYSELF (TIN2011-28627-C04-01), by Junta de Andalucía project DNEMESIS (P10-TIC-6083) and by Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech

Dependency structure matrix, genetic algorithms, and effective recombination

In many different fields, researchers are often confronted by problems arising from complex systems. Simple heuristics or even enumeration works quite well on small and easy problems; however, to efficiently solve large and difficult problems, proper decomposition is the key. In this paper, investigating and analyzing interactions between components of complex systems shed some light on problem decomposition. By recognizing three bare-bones interactions-modularity, hierarchy, and overlap, facet-wise models arc developed to dissect and inspect problem decomposition in the context of genetic algorithms. The proposed genetic algorithm design utilizes a matrix representation of an interaction graph to analyze and explicitly decompose the problem. The results from this paper should benefit research both technically and scientifically. Technically, this paper develops an automated dependency structure matrix clustering technique and utilizes it to design a model-building genetic algorithm that learns and delivers the problem structure. Scientifically, the explicit interaction model describes the problem structure very well and helps researchers gain important insights through the explicitness of the procedure.This work was sponsored by Taiwan National Science Council under grant NSC97- 2218-E-002-020-MY3, U.S. Air Force Office of Scientific Research, Air Force Material Command, USAF, under grants FA9550-06-1-0370 and FA9550-06-1-0096, U.S. National Science Foundation under CAREER grant ECS-0547013, ITR grant DMR-03-25939 at Materials Computation Center, grant ISS-02-09199 at US National Center for Supercomputing Applications, UIUC, and the Portuguese Foundation for Science and Technology under grants SFRH/BD/16980/2004 and PTDC/EIA/67776/2006

The promotion and development of One Health at Swiss TPH and its greater potential

One Health, an integrated health concept, is now an integral part of health research and development. One Health overlaps with other integrated approaches to health such as EcoHealth or Planetary Health, which not only consider the patient or population groups but include them in the social-ecological context. One Health has gained the widest foothold politically, institutionally, and in operational implementation. Increasingly, One Health is becoming part of reporting under the International Health Legislation (IHR 2005). The Swiss Tropical and Public Health Institute (Swiss TPH) has played a part in these developments with one of the first mentions of One Health in the biomedical literature. Here, we summarise the history of ideas and processes that led to the development of One Health research and development at the Swiss TPH, clarify its theoretical and methodological foundations, and explore its larger societal potential as an integrated approach to thinking. The history of ideas and processes leading to the development of One Health research at the Swiss TPH were inspired by far-sighted and open ideas of the directors and heads of departments, without exerting too much influence. They followed the progressing work and supported it with further ideas. These in turn were taken up and further developed by a growing number of individual scientists. These ideas were related to other strands of knowledge from economics, molecular biology, anthropology, sociology, theology, and linguistics. We endeavour to relate Western biomedical forms of knowledge generation with other forms, such as Mayan medicine. One Health, in its present form, has been influenced by African mobile pastoralists' integrated thinking that have been taken up into Western epistemologies. The intercultural nature of global and regional One Health approaches will inevitably undergo further scrutiny of successful ways fostering inter-epistemic interaction. Now theoretically well grounded, the One Health approach of seeking benefits for all through better and more equitable cooperation can clearly be applied to engagement in solving major societal problems such as social inequality, animal protection and welfare, environmental protection, climate change mitigation, biodiversity conservation, and conflict transformation

Symmetry breaking perturbations and strange attractors

The asymmetrically forced, damped Duffing oscillator is introduced as a prototype model for analyzing the homoclinic tangle of symmetric dissipative systems with \textit{symmetry breaking} disturbances. Even a slight fixed asymmetry in the perturbation may cause a substantial change in the asymptotic behavior of the system, e.g. transitions from two sided to one sided strange attractors as the other parameters are varied. Moreover, slight asymmetries may cause substantial asymmetries in the relative size of the basins of attraction of the unforced nearly symmetric attracting regions. These changes seems to be associated with homoclinic bifurcations. Numerical evidence indicates that \textit{strange attractors} appear near curves corresponding to specific secondary homoclinic bifurcations. These curves are found using analytical perturbational tools

A review on probabilistic graphical models in evolutionary computation

Thanks to their inherent properties, probabilistic graphical models are one of the prime candidates for machine learning and decision making tasks especially in uncertain domains. Their capabilities, like representation, inference and learning, if used effectively, can greatly help to build intelligent systems that are able to act accordingly in different problem domains. Evolutionary algorithms is one such discipline that has employed probabilistic graphical models to improve the search for optimal solutions in complex problems. This paper shows how probabilistic graphical models have been used in evolutionary algorithms to improve their performance in solving complex problems. Specifically, we give a survey of probabilistic model building-based evolutionary algorithms, called estimation of distribution algorithms, and compare different methods for probabilistic modeling in these algorithms

High Order Multistep Methods with Improved Phase-Lag Characteristics for the Integration of the Schr\"odinger Equation

In this work we introduce a new family of twelve-step linear multistep methods for the integration of the Schr\"odinger equation. The new methods are constructed by adopting a new methodology which improves the phase lag characteristics by vanishing both the phase lag function and its first derivatives at a specific frequency. This results in decreasing the sensitivity of the integration method on the estimated frequency of the problem. The efficiency of the new family of methods is proved via error analysis and numerical applications.Comment: 36 pages, 6 figure