Attribute Interactions in Medical Data Analysis

There is much empirical evidence about the success of naive Bayesian classification (NBC) in medical applications of attribute-based machine learning. NBC assumes conditional independence between attributes. In classification, such classifiers sum up the pieces of class-related evidence from individual attributes, independently of other attributes. The performance, however, deteriorates significantly when the “interactions” between attributes become critical. We propose an approach to handling attribute interactions within the framework of “voting” classifiers, such as NBC. We propose an operational test for detecting interactions in learning data and a procedure that takes the detected interactions into account while learning. This approach induces a structuring of the domain of attributes, it may lead to improved classifier’s performance and may provide useful novel information for the domain expert when interpreting the results of learning. We report on its application in data analysis and model construction for the prediction of clinical outcome in hip arthroplasty

GenePath: a System for Automated Construction of Genetic Networks from Mutant Data

Motivation: Genetic pathways are often used in the analysis of biological phenomena. In classical genetics, they are constructed manually from experimental data on mutants. The field lacks formalism to guide such analysis, and accounting for all the data becomes complicated when large amounts of data are considered. Results: We have developed GenePath, an intelligent assistant that mimics expert geneticists in the analysis of genetic data. GenePath employs expert-defined patterns to uncover gene relations from the data, and uses these relations as constraints that guide the search for a plausible genetic network. GenePath provides formalism to genetic data analysis, facilitates the consideration of all the available data in a consistent and systematic manner, and aids in the examination of the large number of possible consequences of a planned experiment. It also provides an explanation mechanism that traces back every finding to the pertinent data. GenePath was successfully tested on several genetic problems. Availability: GenePath can be accessed at http://genepath.org. Supplementary information: Supplementary material is available at http://genepath.org/bi-supp

Web-enabled knowledge-based analysis of genetic data

We present a web-based implementation of GenePath, an intelligent assistant tool for data analysis in functional genomics. GenePath considers mutant data and uses expert-defined patterns to find gene-to-gene or gene-to-outcome relations. It presents the results of analysis as genetic networks, wherein a set of genes has various influence on one another and on a biological outcome. In the paper, we particularly focus on its web-based interface and explanation mechanisms

A Mathematical Model and Numerical Simulation of the Static Stability of a Tractor

Tractor overturning remains a serious problem in agricultural activities. A detailed analysis of problems and causes leading to a tractor overturn have revealed that by improving tractor’s static stability we can positively influence the safety as early as during the concept phase. We designed a mathematical model and a numerical simulation of the static stability of a tractor with an oscillating front axle in relation to its position on a slope. It was followed by analysing the changes of individual parameters, such as the position of the centre of gravity, the wheelbase, the wheel track width and the height of the oscillating axle mounting point, and their impact on tractor’s static stability in relation to its position on a slope. Results show that manipulating these parameters can significantly increase tractor’s static stability. A better static stability is directly proportional to improved dynamic stability, resulting in a better safety in a view of the tractor overturn, particularly while working on a sloping terrain

Flame retardant effectiveness of nanodispersed organophosphorus-derivative in polyamide 6 textile filament yarns

The halogen-free flame retardant (FR) polyamide 6 (PA6) composite textile filament yarns fabricated via melt-compounding have never achieved effective flame retardancy. The main reason for that is related to the agglomeration of FR additives due to their poor compatibility with PA6 polymer chains. The formed FR agglomerates substantially reduce the flame retardant effectiveness, disable continuous melt-spinning process due to clogging of the filters and spinnerets, and significantly impair fibre tensile properties. Therefore, the goal of this study was to investigate how lowering of the FR additive size to the nanoscopic level affects melt-spinning process and flame retardancy of the nanocomposite PA6 filament yarns. To this aim, we established a new scalable approach for the production of new-generation PA6/FR nanocomposite filament yarns with uniformly distributed nano-dispersed halogen-free FR. So, instead of mixing FR additive with PA6 melt, we rather chose a step back, i.e. mixing of FR additive with ε-caprolactam melt and performing the in situ polymerization

In situ prepared polyamide 6/DOPO-derivative nanocomposite for melt-spinning of flame retardant textile filaments

Abstract A novel flame retardant polyamide 6 (PA6)/bridged 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO)-derivative (PHED) nanocomposite textile filament yarns were developed. The scalable production approach includes in situ water-catalyzed ring-opening polymerization of e-caprolactam in the presence of the flame retardant PHED followed by melt-spinning of nanocomposite filament yarns and production of knitted fabrics. The specific chemical structure of the PHED additive enabled its excellent miscibility with molten e-caprolactam and the uninterrupted polymerization of e-caprolactam. The produced PA6/PHED nanocomposite was characterized by the preserved molecular structure of the polyamide 6 and uniformly distributed nano-dispersed FR at concentrations of 10 and 15 wt %. The PA6/PHED nanocomposite structure was successfully preserved after the melt-spinning processing. The PA6 nanocomposite filament yarns at the applied 15 wt %. loading of PHED showed (a) increased thermo-oxidative stability compared to neat PA6 up to 500 °C, with a 43% higher residue at 500 °C and (b) self-extinguishment of fiber strand and knitted samples within 1 s in standard vertical flame spread tests (ASTM D6413), followed by the significant reduction of the melt-dripping and the melt-drop flammability. Additionally, 1.2 mm-tick PA6/PHED bar samples achieved a V0 rating in UL94 vertical burning test at the applied 10 wt % concentration of PHED. This innovative and scalable approach could pave the way for the production of new-generation nanocomposite PA6 filament yarns with self-extinguishing properties at the macro-scale, which would be highly beneficial for increasing fire safety, whilst maintaining the use of a DOPO derivative at the minimum level

Agile Development of Polymer Power Transmission Systems for e-Mobility—A Novel Methodology Based on an e-Bike Drive Case Study

The market for electric bicycles has grown extremely and developed rapidly in recent years. To enter such a market with a new product, the development process has to be fast, and throughout the process, feedback from future potential customer(s) should be sought in order to achieve the best possible market acceptance. The article presents the design process of a pedelec e-bike central drive system. The authors were members of the development team and the designers of the mechanical transmission, and therefore had a good overview of the whole project. The development process and the set-up of production require a certain amount of time, during which design changes are inevitable due to changes in customer expectations and demands. The development team should respond to these changes and take them into account during development. Only the ability to react to changes and constant communication with the customer will ultimately lead to a product that can be commercially successful. Based on a critical review of the successfully completed project, general guidelines were established for the development of mechatronic products that consider the principles of Agile methodology. Particular attention was paid to the development of polymer gears, as these were the most demanding components in the system. The presented guidelines were based on an overview of the e-bike R&D process presented, but they can be generalized and used in the development process of any technical physical product. Agile methods were developed in the field of software development and therefore cannot be directly transferred to the field of physical product development. The article highlights and discusses individual special features that distinguish agile development of physical products from software development

An investigation on the potential of bio-based polymers for use in polymer gear transmissions

The potential for replacing the fossil-based Polyoxymethylene (POM) and Polyamide 66 (PA 66) in polymer gear applications with a bio-based Polyamide 6.10 (PA 6.10) was studied and is presented in the article. The use of bio-based plastics is increasing but mostly in undemanding applications like packaging. High-performance plastics are needed in polymer gear transmissions since their operational conditions are far more severe. The potential of bio-based PA 6.10 was studied by means of gear lifespan testing. Additional insights into the process of polymer gear meshing were garnered by simulating all the tested cases with a FEM model of meshing gears. Test gears were manufactured from commercially available materials, making the results useful for gear designers. Encouraging results were observed since the PA 6.10 gears exhibited a 3.5-times longer lifespan than POM gears and a 10-times longer lifespan than PA 66 gears when tested under identical test conditions. The results indicate great potential for replacing fossil-based plastics in polymer gear applications with bio-based polymer materials. The fatigue strength, coefficient of friction, and wear coefficient were determined and compared for the tested materials, facilitating the reliable design of polymer gears