KnAC: an approach for enhancing cluster analysis with background knowledge and explanations

Pattern discovery in multidimensional data sets has been the subject of research for decades. There exists a wide spectrum of clustering algorithms that can be used for this purpose. However, their practical applications share a common post-clustering phase, which concerns expert-based interpretation and analysis of the obtained results. We argue that this can be the bottleneck in the process, especially in cases where domain knowledge exists prior to clustering. Such a situation requires not only a proper analysis of automatically discovered clusters but also conformance checking with existing knowledge. In this work, we present Knowledge Augmented Clustering (KnAC). Its main goal is to confront expert-based labelling with automated clustering for the sake of updating and refining the former. Our solution is not restricted to any existing clustering algorithm. Instead, KnAC can serve as an augmentation of an arbitrary clustering algorithm, making the approach robust and a model-agnostic improvement of any state-of-the-art clustering method. We demonstrate the feasibility of our method on artificially, reproducible examples and in a real life use case scenario. In both cases, we achieved better results than classic clustering algorithms without augmentation.Comment: Accepted to Applied Intelligenc

The application of multiplex PCR to detect seven different DNA targets in group B streptococci

Group B Streptococcus (GBS) causes severe infections in infants and in immunocompromised adults. GBS pathogenicity varies between and within serotypes, with considerable variation in genetic content between strains. For this reason, it is important to be able to carry out immediate and comprehensive diagnostics of these infections. Seven genes important for screening of GBS infection were detected: cfb gene encoding the CAMP factor presented in every GBS; the cps operon genes such as cps1aH, cps1a/2/3IJ, and cps5O specific for capsular polysaccharide types Ia, III, and V, respectively; macrolide resistance genes ermB and mefA/E; and the gbs2018 S10 region specific for ST17 hypervirulent clone. Standardization of multiplex PCR with the use of seven primer pairs was performed on 81 bacterial strains representing different GBS isolates (n = 75) and other Gram-positive cocci (n = 10). Multiplex PCR can be used as an effective screening method to detect different sequences important for the screening of GBS infection

Collective behaviour of partons could be a source of energetic hadrons

We discuss the idea that collective behaviour of the quarks/partons, which has been intensely discussed for the last 40 years in relativistic hadron-nuclear and nuclear-nuclear interactions and confirmed by new data coming from the ultrarelativistic heavy ion collisions, can lead to energetic particle production. Created from hadronization of the quark/parton (or quarks/partons), energetic particles could get the energy of grouped partons from coherent interactions. Therefore, we think that in the centre of some massive stars, a medium with high density, close to Quantum Chromodynamic one could be a source of the super high-energy cosmic rays.Comment: 8 pages, 8 figure

Systematic review of Group B Streptococcal capsular types, sequence types and surface proteins as potential vaccine candidates.

BACKGROUND: 21 million pregnant women worldwide (18%) are estimated to carry Group B Streptococcus (GBS), which is a risk for invasive disease in newborns, pregnant women, and stillbirths. Adults ≥ 60 years or with underlying health conditions are also vulnerable to invasive GBS disease. We undertook systematic reviews on GBS organism characteristics including: capsular polysaccharide (serotype), sequence type (multi-locus sequence types (MLST)), and virulence proteins. We synthesised data by at-risk populations, to inform vaccine development. METHODS: We conducted systematic reviews and meta-analyses to estimate proportions of GBS serotypes for at risk populations: maternal colonisation, invasive disease in pregnant women, stillbirths, infants 0-90 days age, and older adults (≥60 years). We considered regional variation and time trends (2001-2018). For these at-risk population groups, we summarised reported MLST and surface proteins. RESULTS: Based on 198 studies (29247isolates), 93-99% of GBS isolates were serotypes Ia, Ib, II, III, IV and V. Regional variation is likely, but data gaps are apparent, even for maternal colonisation which has most data. Serotype III dominates for infant invasive disease (60%) and GBS-associated stillbirths (41%). ST17 accounted for a high proportion of infant invasive disease (41%; 95%CI: 35-47) and was found almost exclusively in serotype III strains, less present in maternal colonisation (9%; 95%CI:6-13),(4%; 95%CI:0-11) infant colonisation, and adult invasive disease (4%, 95%CI:2-6). Percentages of strains with at least one of alp 1, alp2/3, alpha C or Rib surface protein targets were 87% of maternal colonisation, 97% infant colonisation, 93% infant disease and 99% adult invasive disease. At least one of three pilus islands proteins were reported in all strains. DISCUSSION: A hexavalent vaccine (serotypes Ia, Ib, II, III, IV and V) might provide comprehensive cover for all at-risk populations. Surveillance of circulating, disease-causing target proteins is useful to inform vaccines not targeting capsular polysaccharide. Addressing data gaps especially by world region and some at-risk populations (notably stillbirths) is fundamental to evidence-based decision-making during vaccine design

Imperative vs. Declarative Modeling of Industrial Process. The Case Study of the Longwall Shearer Operation

Process modeling is an important and necessary step for further analysis and monitoring of industrial processes. In the process modeling two main paradigms exist, namely imperative and declarative ones. In our work, we analyzed information potential of these model paradigms regarding to conformance checking task of real life industrial process – longwall shearer operation carried out in an underground coal mine. The objective of our work was an analysis of selected imperative and declarative models to discover which approach is more appropriate from a practical point of view, taking into consideration criteria formulated by the domain expert. The first novelty of our work rely on real life industrial sensor data analysis and creation of event log with heuristic approach for case ID identification and labeling with expert rules. In parallel, we created prescribed process models. As representatives of imperative and declarative languages, we have selected the Petri nets and Declare models, respectively. We created two Petri nets (with Inductive and Heuristic Miner) and seven declarative models differ in restriction power. Due to the better description of the ideal cycle, to the further analysis and conformance checking task, we selected the Petri net created by Heuristic Miner. After the process model creation, we compared selected Petri net with Declare models using the natural language approach and constraints hierarchy. Based on created similarity measures, we choose one declarative model to conformance checking task and comparison with Petri net due to formulated quantitative and qualitative criteria. As main artifact in the conformance checking task, we used obtained real event log. Evaluation of the created models indicates that in the case of the longwall shearer operation monitoring, the declarative model better captures the necessary information to decision-makers than the Petri net, thus being more appropriate for practical use