There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

I. the origin of species by means of natural selection

A series of weaknesses in creativity, research design, and quality of writing continue to handicap energy social science. Many studies ask uninteresting research questions, make only marginal contributions, and lack innovative methods or application to theory. Many studies also have no explicit research design, lack rigor, or suffer from mangled structure and poor quality of writing. To help remedy these shortcomings, this Review offers suggestions for how to construct research questions; thoughtfully engage with concepts; state objectives; and appropriately select research methods. Then, the Review offers suggestions for enhancing theoretical, methodological, and empirical novelty. In terms of rigor, codes of practice are presented across seven method categories: experiments, literature reviews, data collection, data analysis, quantitative energy modeling, qualitative analysis, and case studies. We also recommend that researchers beware of hierarchies of evidence utilized in some disciplines, and that researchers place more emphasis on balance and appropriateness in research design. In terms of style, we offer tips regarding macro and microstructure and analysis, as well as coherent writing. Our hope is that this Review will inspire more interesting, robust, multi-method, comparative, interdisciplinary and impactful research that will accelerate the contribution that energy social science can make to both theory and practice.

Promoting novelty, rigor, and style in energy social science: towards codes of practice for appropriate methods and research design

1 July 7, 2010, marks the fifth anniversary of the 2005 terrorist attacks on London’s Metro system. In 2005, terrorists launched a coordinated attack against London’s transportation system, with 3 bombs detonating simultaneously at three different Metro stations and a fourth bomb exploding an hour later on a city bus. In all, there were 52 victims in these bombings with an additional 700 injuries resulting. The four terrorists who executed the attacks were killed in the explosions.

National Consortium for the Study of Terrorism and Responses to Terrorism

A comprehensive survey on support vector machine classification: Applications, challenges and trends

Serious games and gamification to engage consumers in pro-environmental behaviours for energy efficiency are in their infancy To date, despite growing interest and some initial attempts, their potential to engage consumers in energy efficiency behaviours has been understudied To provide an overview of serious games and gamification to engage individuals in pro-environmental behaviours for energy efficiency, a computer-based search for relevant publications was performed in several databases After applying the inclusion criteria and removing duplicates, 10 papers were included in this systematic review Results showed that serious games and gamification have been used in three different areas related to energy efficiency: environmental education, consumption awareness, and pro-environmental behaviours This review also showed that applied gaming interventions can be used in more than one of these three areas (comprehensive interventions) The main observation to be drawn from this review is that both serious games and gamification can foster energy-saving behaviours and vary widely in terms of type of games and of features that might be appealing and motivating

Gaming for Earth: Serious games and gamification to engage consumers in pro-environmental behaviours for energy efficiency

The success of a drug treatment is strongly correlated with the ability of a molecule to reach its target in the patient's organism without inducing toxic effects. Moreover the reduction of cost and time associated with drug discovery and development is becoming a crucial requirement for pharmaceutical industry. Therefore computational methods allowing reliable predictions of newly synthesized compounds properties are of outmost relevance. In this paper we discuss the role of genetic programming in predictive pharmacokinetics, considering the estimation of adsorption, distribution, metabolism, excretion and toxicity processes (ADMET) that a drug undergoes into the patient's organism. We compare genetic programming with other well known machine learning techniques according to their ability to predict oral bioavailability (%F), median oral lethal dose (LD50) and plasma-protein binding levels (%PPB). Since these parameters respectively characterize the percentage of initial drug dose that effectively reaches the systemic blood circulation, the harmful effects and the distribution into the organism of a drug, they are essential for the selection of potentially good molecules. Our results suggest that genetic programming is a valuable technique for predicting pharmacokinetics parameters, both from the point of view of the accuracy and of the generalization ability.

Genetic programming for computational pharmacokinetics in drug discovery and development

Bayesian Optimization and Data Science

Bayesian optimization has become a widely used tool in the optimization and machine learning communities. It is suitable to problems as simulation/optimization and/or with an objective function computationally expensive to evaluate. Bayesian optimization is based on a surrogate probabilistic model of the objective whose mean and variance are sequentially updated using the observations and an “acquisition” function based on the model, which sets the next observation at the most “promising” point. The most used surrogate model is the Gaussian Process which is the basis of well-known Kriging algorithms. In this paper, the authors consider the pump scheduling optimization problem in a Water Distribution Network with both ON/OFF and variable speed pumps. In a global optimization model, accounting for time patterns of demand and energy price allows significant cost savings. Nonlinearities, and binary decisions in the case of ON/OFF pumps, make pump scheduling optimization computationally challenging, even for small Water Distribution Networks. The well-known EPANET simulator is used to compute the energy cost associated to a pump schedule and to verify that hydraulic constraints are not violated and demand is met. Two Bayesian Optimization approaches are proposed in this paper, where the surrogate model is based on a Gaussian Process and a Random Forest, respectively. Both approaches are tested with different acquisition functions on a set of test functions, a benchmark Water Distribution Network from the literature and a large-scale real-life Water Distribution Network in Milan, Italy.

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Bayesian optimization of pump operations in water distribution systems

Several different approaches have been suggested for the numerical solution of the global optimization problem: space covering methods, trajectory methods, random sampling, random search and methods based on a stochastic model of the objective function are considered in this paper and their relative computational effectiveness is discussed. A closer analysis is performed of random sampling methods along with cluster analysis of sampled data and of Bayesian nonparametric stopping rules.

Francesco Archetti

Papers

Gaming for Earth: Serious games and gamification to engage consumers in pro-environmental behaviours for energy efficiency

Genetic programming for computational pharmacokinetics in drug discovery and development

Bayesian Optimization and Data Science

Bayesian optimization of pump operations in water distribution systems

A survey on the global optimization problem: General theory and computational approaches