The use of PLANS and NetworkX in modeling power grid system failures.

The theoretical and practical aspects and results of simulations based on a specialized tool that is used in the energy industry were adressed. The previously discussed cases in the literature by taking into account the worst case and critical states of networks in terms of complex networks were extended. Using the Monte-Carlo method, the vulnerability of the power grid to node failures was investigated, both in terms of the use of specialized software, which is used in the power industry, and a tool for the analysis of complex networks graphs. We present the results obtained and the observed analogy between the results of the analysis performed in specialized software and the complex network graph analysis tool. It has been shown that the results obtained coincide for both software packages, even though their application focuses on slightly different aspects of system operation. Moreover, further possibilities of extending the research in this direction are proposed, taking into account not only the improvement of the method used, but also a significant increase in the size of the tested structure model.

On the Monte Carlo weights in multiple criteria decision analysis.

In multiple-criteria decision making/aiding/analysis (MCDM/MCDA) weights of criteria constitute a crucial input for finding an optimal solution (alternative). A large number of methods were proposed for criteria weights derivation including direct ranking, point allocation, pairwise comparisons, entropy method, standard deviation method, and so on. However, the problem of correct criteria weights setting persists, especially when the number of criteria is relatively high. The aim of this paper is to approach the problem of determining criteria weights from a different perspective: we examine what weights' values have to be for a given alternative to be ranked the best. We consider a space of all feasible weights from which a large number of weights in the form of n-tuples is drawn randomly via Monte Carlo method. Then, we use predefined dominance relations for comparison and ranking of alternatives, which are based on the set of generated cases. Further on, we provide the estimates for a sample size so the results could be considered robust enough. At last, but not least, we introduce the concept of central weights and the measure of its robustness (stability) as well as the concept of alternatives' multi-dominance, and show their application to a real-world problem of the selection of the best wind turbine.

NanoForms: an integrated server for processing, analysis and assembly of raw sequencing data of microbial genomes, from Oxford Nanopore technology.

Background: Next Generation Sequencing (NGS) techniques dominate today's landscape of genetics and genomics research. Though Illumina still dominates worldwide sequencing, Oxford Nanopore is one of the leading technologies currently being used by biologists, medics and geneticists across various applications. Oxford Nanopore is automated and relatively simple for conducting experiments, but generates gigabytes of raw data, to be processed by often ambiguous set of alternative bioinformatics command-line tools, and genomics frameworks which require a knowledge of bioinformatics to run. Results: We established an inter-collegiate collaboration across experimentalists and bioinformaticians in order to provide a novel bioinformatics tool, free for academics. This tool allows people without extensive bioinformatics knowledge to simply process their raw genome sequencing data. Currently, due to ICT resources' maintenance reasons, our server is only capable of handling small genomes (up to 15 Mb). In this paper, we introduce our tool, NanoForms: an intuitive and integrated web server for the processing and analysis of raw prokaryotic genome data, coming from Oxford Nanopore. NanoForms is freely available for academics at the following locations: http://nanoforms.tech (webserver) and https://github.com/czmilanna/nanoforms (GitHub source repository).

Influence of the geometry of extra column volumes on band broadening in a chromatographic system. Predictions by computational fluid dynamics.

A computational fluid dynamics method was used for prediction of flow behavior and band profiles of small- and macro-molecule compounds eluting in extra-column volumes (ECV) of an Äkta chromatographic system. The model compounds were: acetone, bovine serum albumin and an antibody. The construction of ECV was approximated by different types of geometries, starting from the simplest two-dimensional (2D) arrangement consisting of a straight capillary tube, and ending with a three-dimensional system (3D), which accounted for the flow path curvature of individual elements of ECV, including: injection loop capillary, multi-way valve, connecting capillary and detector cell. The accuracy of the model predictions depended on the flow path length and the eluent flowrate. 2D-geometry models reproduced pretty well the shapes of band profiles recorded at the lowest eluent flowrate used, but they failed for increased flowrates. The 3D-geometry model was found to be sufficiently accurate for all conditions investigated. It was exploited to analyze band broadening in the individual ECV elements. The simulation results revealed that the flow behavior in the injection loop capillaries strongly influenced the shape of band profiles, particularly at higher eluent velocities. This was attributed to the formation of Dean vertices triggered by centrifugal forces in curved parts of the eluent flow path.

Massive Health Record Breaches Evidenced by the Office for Civil Rights Data.

BACKGROUND: Using data collected by the Office for Civil Rights, Department of Health and Human Services (HHS), over half of the population in the USA might have been affected by security breaches since Oct 2009. This study provided analysis of the data, presenting the numbers of individuals affected in one breach and the number of breaches. METHODS: Statistical analysis has been conducted with visualizations. Visualizations include categorized histograms and tables. Histograms are presented as bar charts with categories: location and breach type. Tables show case counts (across top 10 breaches and those with more than one million stolen records) in successive years and covered entity types. All statistics were calculated with the use of package R. Analyzed data were collected from Oct 2009 till Jun 2017. RESULTS: This study presents evidence of health data breaches taking place at an unprecedented level. Medical records of at least 173 million of people, gathered since Oct 2009, have been breached and might have adversely influenced over half of the population in the USA. CONCLUSION: Results of this study are expected to motivate public care authorities to develop similar laws and regulations as the USA while striving for better law enforcement. It takes a considerable amount of time to educate public and it takes substantial financial resources to prevent data breaches.