We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length (~300bp) and fast runs times (<20hrs) with high base accuracy (Q30 > 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data.

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Three types of guidance systems are studied. The first type is a separated two-loop autopilot guidance law that assumes spectral separation between the guidance and the flight control. However, separation may not hold close to interception, requiring possibly an integrated design of guidance and control. Using the integrated approach, two different guidance law types can be used to improve the end-game performance. The first one is the integrated single-loop guidance law, where the coupling between flight control and guidance loops is taken into account in the derivation process. The second type is the integrated two-loop autopilot guidance law. In this case, the autopilot loop is designed separately from the guidance one, but all the states are fed-back into the guidance loop. The performance of the three guidance laws is evaluated and compared via a single-input single-output test case. It is shown that the integrated two-loop autopilot-guidance law can manipulate the inner autopilot dynamics, resulting in the same performance as the integrated single-loop guidance law. In addition, it is shown that the performance of the separated guidance law is inferior to that of the integrated laws.

Mutually Uncorrelated (MU) codes are a class of codes in which no proper prefix of one codeword is a suffix of another codeword. These codes were originally studied for synchronization purposes and recently, Yazdi et al. showed their applicability to enable random access in DNA storage. In this work we follow the research of Yazdi et al. and study MU codes along with their extensions to correct errors and balanced codes. We first review a well known construction of MU codes and study the asymptotic behavior of its cardinality. This task is accomplished by studying a special class of run-length limited codes that impose the longest run of zeros to be at most some function of the codewords length. We also present an efficient algorithm for this class of constrained codes and show how to use this analysis for MU codes. Next, we extend the results on the runlength limited codes in order to study (d h , dm)-MU codes that impose a minimum Hamming distance of d h between different codewords and dm between prefixes and suffixes. In particular, we show an efficient construction of these codes with nearly optimal redundancy. We also provide similar results for the edit distance and balanced MU codes. Lastly, we draw connections to the problems of comma-free and prefix synchronized codes.

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