This report summarizes ten levels of abstraction that together span the continuum from the most elementary to the most general levels when modeling biological systems. It is shown how the neocybernetic principles can be seen as the key to reaching a holistic view of complex processes in general. Preface Concrete examples help to understand complex systems. In this report, the key point is to illustrate the basic mechanisms and properties of neocybernetic system models. Good visualizations are certainly needed. It is biological systems, or living systems, that are perhaps the most characteristic examples of cybernetic systems. This intuition is extended here to natural systems in general — indeed, it is all other than man-made ones that seem to be cybernetic. The word “biological ” in the title should be interpreted as “bio-logical ” — referring to general studies of any living systems, independent of the phenosphere. Starting from the concrete examples, connections to more abstract systems are found, and the discussions become more and more all-embracing in this text. However, the neocybernetic model framework still makes it possible to conceptually master the complexity. There is more information about neocybernetics available in Internet — also this report is available there in electronic form:

Abstract: The properties of our star may be associated with special prerequisites for life. By comparing our Sun to other stars in our galaxy, we may be able to identify such prerequisites. If our star is typical, stellar conditions appropriate for life, and life itself may be common in the Universe. On the other hand, if the Sun is atypical, conditions appropriate for life may be uncommon. Here we describe a method to quantify how typical or atypical the Sun is compared with other stars

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In this work, I have shown that current parity-based RAID levels are nearing the end of their usefulness. Further, the widely used parity-based hierarchical RAID levels are not capable of significantly improving reliability over their component parity-based levels without requiring massively increased hardware investment. In response, I have proposed k + m RAID, a family of RAID levels that allow m, the number of parity blocks per stripe, to vary based on the desired reliability of the volume. I have compared its failure rates to those of RAIDs 5 and 6, and RAIDs 1+0, 5+0, and 6+0 with varying numbers of sets. I have described how GPUs are architecturally well-suited to RAID computations, and have demonstrated the Gibraltar RAID library, a prototype library that performs RAID computations on GPUs. I have provided analyses of the library that show how evolutionary changes to GPU architecture, including the merge of GPUs and CPUs, can change the efficiency of coding operations. I have introduced a new memory layout and dispersal matrix arrangement, improving the efficiency of decoding to match that