Destillation im Fein- und Hochvakuum

The distillation in the fine and high vacuum range requires not only appropriate vacuum pumps but also special apparatus and machines. The principle and the design of laboratory and industrial plants are explained. New mathematical methods are supporting laboratory and pilot testing required for process development and plant layout. An example was chosen for demonstration purposes.     

A SONET STS-3c user network interface integrated circuit

Two different design implementation techniques were used to produce a functionally complex high performance synchronous optical network (SONET) synchronous transmission signal (STS)-3c (155.52 Mb/s) user network interface (UNI) chip in cost-effective 1 μm CMOS technology. The CMOS chip functions as an STS-3c transmitter and receiver and can interface to the STS-3c line in either bit-serial or byte-parallel data format. The transmitter creates a SONET STS-3c frame structure including the necessary framing and control bytes. The receiver performs frame detection, several performance monitoring functions, and payload processor interpretation. In addition to SONET overheads, both the transmitter and receiver provide payload asynchronous transfer mode (ATM) mapping signals to the user. The user can choose between serial operation at 155.52 Mb/s or parallel operation at 19.44 Mbyte/s. Test results show that the experimental integrated circuit performs successfully at serial data rates of up to 300 Mb/s     

The Road to Next-Generation Broadband

Next-generation broadband promises to usher in a digital future in which it will be possible, for instance, to have a high-definition videoconference examination with your doctor from the comfort of your own home. Japan and Korea in particular are much closer to this sort of digital future than most countries, including the US. Public policy must play an important role in making tomorrow's broadband a reality in America.     

Isolation of single yeast cells by optical trapping

Individual yeast cells can be successfully isolated and recultured on plates with a new isolation method making use of optical trapping with infrared laser light. The cells can be selected on morphological criteria by high resolution microscopy. The isolation device is constructed from two coverslips separated by spacers, in which selected cells are transferred to a plastic capillary, using the optical trap. To test the procedure, selection experiments were done with a mixture of two Saccharomyces cerevisiae strains, distinguishable both in fluorescence microscopy and on agar plates. These experiments showed that only selected cells were isolated, and close to 100% of the isolated stationary-phase cells formed colonies on agar plates, indicating a high recovery. A lower recovery was obtained with exponential-phase cells, possibly because of a higher sensitivity to laser irradiation. Applications for this method may include the isolation of mutants with altered morphology and the isolation of subpopulations of yeast cultures, for their separate investigation or for the initiation of pure cultures.     

Single machine scheduling with simple linear deterioration to minimize total absolute deviation of completion times

We consider a single machine scheduling problem with simple linear deterioration. Job processing times are assumed to be a simple linear function of a job-dependent growth rate and the job's starting time. We seek an optimal schedule, so as to minimize the total absolute deviation of completion times (TADC). We prove several interesting properties of an optimal schedule, and introduce two efficient heuristics which are tested against a lower bound.     

Prediction of urban stormwater quality using artificial neural networks

There are a vast number of complex, interrelated processes influencing urban stormwater quality. However, the lack of measured fundamental variables prevents the construction of process-based models. Furthermore, hybrid models such as the buildup-washoff models are generally crude simplifications of reality. This has created the need for statistical models, capable of making use of the readily accessible data. In this paper, artificial neural networks (ANN) were used to predict stormwater quality at urbanized catchments located throughout the United States. Five constituents were analysed: chemical oxygen demand (COD), lead (Pb), suspended solids (SS), total Kjeldhal nitrogen (TKN) and total phosphorus (TP). Multiple linear regression equations were initially constructed upon logarithmically transformed data. Input variables were primarily selected using a stepwise regression approach, combined with process knowledge. Variables found significant in the regression models were then used to construct ANN models. Other important network parameters such as learning rate, momentum and the number of hidden nodes were optimized using a trial and error approach. The final ANN models were then compared with the multiple linear regression models. In summary, ANN models were generally less accurate than the regression models and more time consuming to construct. This infers that ANN models are not more applicable than regression models when predicting urban stormwater quality.