Recent emergence of nanopore sequencing technology set a challenge for the established assembly methods not optimized for the combination of read lengths and high error rates of nanopore reads. In this work we assessed how existing de novo assembly methods perform on these reads. We benchmarked three non-hybrid (in terms of both error correction and scaffolding) assembly pipelines as well as two hybrid assemblers which use third generation sequencing data to scaffold Illumina assemblies. Tests were performed on several publicly available MinION and Illumina datasets of E. coli K-12, using several sequencing coverages of nanopore data (20x, 30x, 40x and 50x). We attempted to assess the quality of assembly at each of these coverages, to estimate the requirements for closed bacterial genome assembly. Results show that hybrid methods are highly dependent on the quality of NGS data, but much less on the quality and coverage of nanopore data and perform relatively well on lower nanopore coverages. Furthermore, when coverage is above 40x, all nonhybrid methods correctly assemble the E. coli genome, even a non-hybrid method tailored for Pacific Bioscience reads. While it requires higher coverage compared to a method designed particularly for nanopore reads, its running time is significantly lower.

Supplementary data are available at Bioinformatics online.

No abstract

Abstract-The speedup is usually limited by two main laws in high-performance computing, that is, the Amdahl's and Gustafson's laws. However, the speedup sometimes can reach far beyond the limited linear speedup, known as superlinear speedup, which means that the speedup is greater than the number of processors that are used. Although the superlinear speedup is not a new concept and many authors have already reported its existence, most of them reported it as a side effect, without explaining why and how it is happening.In this paper, we analyze several different superlinear speedup types and define a taxonomy for them. Additionally, we present several explanations and cases of superlinearity existence for different types of granular algorithms (tasks), which means that they can be divided into many sub-tasks and scattered to the processors for execution. Apart from frequent explanation that having more cache memory in parallel execution is the main reason, we summarize other different effects that cause the superlinearity, including the superlinear speedup in cloud virtual environment for both vertical and horizontal scaling.

-The concept of the augmented coaching ecosystem for non-obtrusive adaptive personalized elderly care is proposed on the basis of the integration of new and available ICT approaches. They include multimodal user interface (MMUI), augmented reality (AR), machine learning (ML), Internet of Things (IoT), and machine-tomachine (M2M) interactions. The ecosystem is based on the Cloud-Fog-Dew computing paradigm services, providing a full symbiosis by integrating the whole range from low level sensors up to high level services using integration efficiency inherent in synergistic use of applied technologies. Inside of this ecosystem, all of them are encapsulated in the following network layers: Dew, Fog, and Cloud computing layer. Instead of the "spaghetti connections", "mosaic of buttons", "puzzles of output data", etc., the proposed ecosystem provides the strict division in the following dataflow channels: consumer interaction channel, machine interaction channel, and caregiver interaction channel. This concept allows to decrease the physical, cognitive, and mental load on elderly care stakeholders by decreasing the secondary human-to-human (H2H), human-to-machine (H2M), and machine-to-human (M2H) interactions in favor of M2M interactions and distributed Dew Computing services environment. It allows to apply this non-obtrusive augmented reality ecosystem for effective personalized elderly care to preserve their physical, cognitive, mental and social well-being.