Approximating total citation counts from first author counts and from total papers

This paper is an attempt to improve on the approximation. First author citations (C_f)≈Total citations (C_t) of an author's publications without the work of making the complete citation count under the author and all co-author names. Using the bibliographies of all faculty from each of four large departments: Physics, Chemistry, Materials Sciences, and Biosciences, in the same university, both first author and complete citation counts were made, care being taken to avoid the most common errors in such counts. It is shown that the function C_f·T/F (where T and F are the total number of papers and F those with subject author's name first) correlates strongly (>90%) with C_t. We find also that C_t correlates strongly with T. The data also may be used as one more line of evidence to obtain normalizing ratios for possible comparisons of productivityacross different disciplinary universes. A very tentative ratio from different studies would be 8 (Chem.)=4 (Physics)=2.5 (Mat. Sci.)=2 (Mathematics)=4.5 (Biophysics-Biochemistry).     

Ink-Jet Printing System?An Analytical Computer Model

An analytical computer model of an ink jet printing system was created. Based upon the values of 13 input parameters, the program delivers predictions of the forces acting on individual drops and their resulting dynamic behavior. Predictions of drop displacements and flight times were used to infer drop pattern appearance resulting from a given input signal. The computer model was based upon theoretical work plus extensive empirical measurements. Drop behavior was predicted with modest accuracy. An improved understanding of ink jet printing systems and numerous recommendations for their use were also derived in this study.     

Learning from designing the RoboFesta—Blue Peter robots

Can children and adults learn anything from building robots? In 2001 we ran a robot design competition with the BBC TelevisionBlue Peter, program. Some 32 000 children, aged between 5 and 16 years, submitted paper designs. We built prototypes of the four winners' robots for a Robot Design MasterClass at the London Science Museum. It is widely believed that across the curriculum, robotics is a powerful force in motivating education. We ask what the children learned from the robot design process. Our answer is that they learned many things, both inside and outside the science and technology curriculum.