We believe the key to the lO's longevity is its basically simple, clean structure with adequately large (one Mbyte) address space that allows users to get work done. In this way, it has evolved easily with use and with technology. An equally significant factor in its success is a single operating systetn environment enabling user program sharing among all machines. The machine has thus attracted users who have built significant languages and applications in a variety of environments. These user-developers are thus the dominant system architects-implementors.In retrospect, the machine turned out to be larger and further from a minicomputer than we expected. As such it could easily have died or destroyed the tiny DEC organization that started it. We hope that this paper has provided insight into the interactions of its development.Acknowledgments. Dan Siewiorek deserves our greatest thanks for helping with a complete editing of the text. The referees and editors have been especially helpful. The important program contributions by users are too numerous for us to give by name but here are most of them: APL, Basic, BUSS, DOT, LISP, Pascal, Simula, sos, TECO, and Tenex, Likewise, there have been so many contributions to the lO's architecture and implementations within DEC and throughout the user community that we dare not give what would be a partial list.

In 18 batch-fermentation experiments, baker's yeast was grown in an enriched mineral medium, containing 10% by weight glucose, at various pH and temperature levels. The pH and temperature are just two representative engineering variables which can be easily varied at negligible cost. The commercial yeast inoculum, 20% by weight or about .16% viable cells, was selected to represent industrial (nonsterile) conditions. Free L-lysine, ethanol, and cell growth were followed in time for each batch run held at a fixed pH and temperature. The maximum free lysine level reached at either 10 1/2 or 24 hr occurred at a pH of 5 and 32 degrees C. At 24 hr, the peak free lysine level, 120 mg/liter, is three times as great as the uncontrolled pH counterpart. In terms of total L-lysine (free plus protein-bound) the peak represents a 25% improvement over the uncontrolled case, based on an average 3.5% lysine level per cell weight. The greatest measured cell level, .9% by weight in the fermentation broth, or a 5 1/2-fold increase over th inoculum, was reached during the 36 degrees C and pH 3 run, while the largest measured ethanol value (3%, or 30% conversion by weight from glucose) was achieved during the 28 degrees C and pH 6 experiment. The optimal lysine run product, however, no less than 15% of the maximum cell and 30% of the maximum ethanol levels.

Continuous fermentation processes are usually designed from batch experimental data. These data are often described by a Monod growth model which, with the transient phase or with inhibition, gives a unimodal or single peaking growth-substrate relationship. In the batch culture of S. cerevisiae (baker's yeast) grown on glucose limiting media and P. cerevisiae (a bacterium) grown on lysine limiting media, a double peaking or bimodal growthsubstrate relationship has been observed. The bimodal phenomena could be accounted for by either the synchronous growth of microorganisms (a homogeneous culture of cells simultaneously grow and subsequently divide together) or a diauxie effect (one substrate is selected over another in a two substrate medium). This paper deals with the implications of bimodal growth on the design of continuous fermentation processes. From batch culture data for S. cerevisiae grown on chemically defined media both a single and double peaking model were developed. Digital simulation of continuous culture reveals that the unimodal model has one stable operating point, whereas the bimodal model, for residence times below a certain critical value, has two stable operating points. The steady-state operating point achieved in the bimodal model is dependent upon the initial conditions of the cell and substrate concentrations. These results may help explain the occurrence of suboptimal yields in such continuous fermentations as single cell protein production and biological waste treatment processes.

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