Eine allgemeine Berechnungsmethode für Wärmeübertragerschaltungen

A general method for calculating any heat exchanger network is presented. As heat exchanger networks can be considered as coupled heat exchangers, that are supplied in a predetermined order, it is convenient to consider even a single heat exchanger with complicated flow patterns as a network composed of several ideally-supplied, coupled devices. The advantage of this method lies in its higher accuracy and the use of a simpler calculation formula for an ideal device model. These advantages far outweigh the disadvantages of the arduous iterative type of calculation used to establish the temperature between ideal devices. The presented method allows, for the first time, without using the iterative method, a calculation of heat exchanger networks based upon the principle of coupled matrix equations. These equations are for any given heat exchanger network simply allocated parameters, and therefore this method is especially suited for the calculation of any network modification. For the application of this method is no special software necessary. The solution of the model equations is obtained very easy and clear with mathematical standard software, e.g. Mathcad or Maple.     

Biologically active secondary metabolites of barley. IV. Hordenine production by different barley lines

Forty-three lines of barley, including ancestral (wild), landraces, Middle Eastern lines, and modern cultivars, were grown under two different sets of environmental conditions. Hordenine production in barley roots was determined at the one-leaf stage by HPLC analysis and, in two lines only, over a period of 35 days. Forty-two of the 43 lines produced significant amounts of hordenine, although there was no variation among groups. Middle Eastern lines had the highest production with 327 µg/g on a dry weight basis. Production was, however, determined more by environmental conditions during growth than by genetic factors. Hordenine production was up to seven times higher in plants grown under lower light intensities.     

Forced intercalation probes (FIT Probes): thiazole orange as a fluorescent base in peptide nucleic acids for homogeneous single-nucleotide-polymorphism detection

Fluorescent base analogues in DNA are versatile probes of nucleic acid-nucleic acid and nucleic acid-protein interactions. New peptide nucleic acid (PNA) based probes are described in which the intercalator dye thiazole orange (TO) serves as a base surrogate. The investigation of six TO derivatives revealed that the linker length and the conjugation site decided whether a base surrogate conveys sequence-selective DNA binding and whether fluorescence is increased or decreased upon single-mismatched hybridization. One TO derivative conferred universal PNA-DNA base pairing while maintaining duplex stability and hybridization selectivity. TO fluorescence increased up to 26-fold upon hybridization. In contrast to most other probes, in which fluorescence is invariant once hybridization had occurred, the emission of TO-containing PNA probes is attenuated when forced to intercalate next to a mismatched base pair. The specificity of DNA detection is therefore not limited by the selectivity of probe-target binding and a DNA target can be distinguished from its single-base mutant under nonstringent hybridization conditions. This property should be of advantage for real-time quantitative PCR and nucleic acid detection within living cells.     

Critical mass in the emergence of collective intelligence: a parallelized simulation of swarms in noisy environments

We extend an abstract agent-based swarming model based on the evolution of neural network controllers, to explore further the emergence of swarming. Our model is grounded in the ecological situation, in which agents can access some information from the environment about the resource location, but through a noisy channel. Swarming critically improves the efficiency of group foraging, by allowing agents to reach resource areas much more easily by correcting individual mistakes in group dynamics. As high levels of noise may make the emergence of collective behavior depend on a critical mass of agents, it is crucial to reach sufficient computing power to allow for the evolution of the whole set of dynamics in simulation. Since simulating neural controllers and information exchanges between agents are computationally intensive, to scale up simulations to model critical masses of individuals, the implementation requires careful optimization. We apply techniques from astrophysics known as treecodes to compute the signal propagation, and efficiently parallelize for multi-core architectures. Our results open up future research on signal-based emergent collective behavior as a valid collective strategy for uninformed search over a domain space.     

A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.