Future publication success in science is better predicted by traditional measures than by the <Emphasis Type="Italic">h</Emphasis> index

Although the use of bibliometric indicators for evaluations in science is becoming more and more ubiquitous, little is known about how future publication success can be predicted from past publication success. Here, we investigated how the post-2000 publication success of 85 researchers in oncology could be predicted from their previous publication record. Our main findings are: (i) Rates of past achievement were better predictors than measures of cumulative achievement. (ii) A combination of authors’ past productivity and the past citation rate of their average paper was most successful in predicting future publication success (R ² ≈ 0.60). (iii) This combination of traditional bibliographic indicators clearly outperformed predictions based on the rate of the h index (R ² between 0.37 and 0.52). We discuss implications of our findings for views on creativity and for science evaluation.     

The Flexible Rare Event Sampling Harness System (FRESHS)

We present the software package FRESHS (http://www.freshs.org) for parallel simulation of rare events using sampling techniques from the ‘splitting’ family of methods. Initially, Forward Flux Sampling (FFS) and Stochastic Process Rare Event Sampling (SPRES) have been implemented. These two methods together make rare event sampling available for both quasi-static and full non-equilibrium regimes. Our framework provides a plugin system for software implementing the underlying physics of the system of interest. At present, example plugins exist for our framework to steer the popular MD packages GROMACS, LAMMPS and ESPResSo, but due to the simple interface of our plugin system, it is also easy to attach other simulation software or self-written code. Use of our framework does not require recompilation of the simulation program. The modular structure allows the flexible implementation of further sampling methods or physics engines and creates a basis for objective comparison of different sampling algorithms.     

Surface ageing at drop scale

Surface ageing of a micro-drop populated by surfactants below the critical micellar concentration and subject to evaporation is considered, motivated by our interest in the transport of biomolecules in digital microfluidics. The classical approach based on diffusion–sorption processes is reviewed in order to address a finite-sized system of digital microfluidics. Short-time and long-time asymptotic approximations for a diffusion-limited regime, as well as full analytical expressions for adsorption- and evaporation-limited regimes, are constructed, which help to validate numerical calculations of full coupling between all these kinetics. The impact of the small drop size and the continuous lack of equilibrium induced by evaporation are described by introducing specific dimensionless numbers. By taking into account evaporative mass transfer in the mass balance, the boundary condition for surfactant transport to and from the interface is modified. Furthermore, the small size of the geometry suggests allowing a novel non-dimensionalisation for surface concentration, following from the mass balance of surfactant molecules in thermo-dynamic equilibrium. This order of magnitude quantifies the equilibrium surface concentration for small-sized geometries.     

Ein Konzept zur Wirkungsgradoptimierung von Einzylinder-Dieselgeneratoren mittels Optimalsteuerung und Extremum-Seeking

In this contribution the problem of maximizing the efficiency of a hybrid power unit at a specified output power level by optimizing the generator current trajectory as well as the design variables that can be chosen during the machine design process is investigated. The concept is demonstrated based on a hybrid single-cylinder diesel engine that is coupled to an electric generator. By developing a model of the system and using open-loop optimal control the optimal operating strategy and the optimal machine design are determined. Besides that, the problems occurring in the application of this strategy to a test rig are discussed. For this purpose, a model-free real-time optimization concept based on extremum seeking control is presented. The effectiveness of both the model-based and the model-free concept are demonstrated by simulation and experimental results.