Multiplex PCR system to track authorized and unauthorized genetically modified soybean events in food and feed

A diverse range of genetic elements has been used to develop genetically modified organisms (GMOs) over the last 18 years. Screening methods that target few elements, such as the Cauliflower Mosaic Virus 35S promoter (P-35S) and Agrobacterium tumefaciens nopaline terminator (T-nos), are not sufficient to screen GMOs. In the present study, a multiplex PCR system for all globally commercialized GM soybean events was developed to easily trace the events. For this purpose, screening elements of 24 GM soybean events were investigated and 9 screening targets were selected and divided into three individual triplex PCR systems: P-35S, ribulose-1,5-bisphosphate carboxylase small subunit promoter of Arabidopsis thaliana, T-nos, T-35S, pea E9 terminator, open reading frame 23 terminator of A. tumefaciens, proteinase inhibitor II terminator of potato, acetohydroxy acid synthase large subunit terminator of A. thaliana, and the revealed 3′ flanking sequences of DP-305423-1. The specificity of the assays was confirmed using thirteen GM soybean events as the respective positive/negative controls. The limit of detection of each multiplex set, as determined using certified reference materials of specific GM events, ranged from 0.03 to 0.5%, depending upon target. Furthermore, 26 food samples that contained soybean ingredients, which were purchased from the USA, China, Japan, and Korea, were analyzed, 17 of which contained one or more GM soybean events. These results suggest that the developed screening method can be used to efficiently track and identify 24 GM soybean events in food and feed.     

Anti-virtual machines and emulations

Virtual Machines are important infrastructural tools for malware analysis. They provide safe yet accurate way of evaluating real life behavior and impact of any executable code, thus providing a better understanding of obfuscated or non conventional portions of code within a binary file. Many virtual machines, such as VMware, Qemu, VirtualBox and SandBoxes, are available and are widely adopted by malware researchers and analysts. Moreover, many antivirus scanners have their own implementation of emulators to achieve comparable results by running malicious code within a controlled environment in order to decrypt obfuscated code. Virus writers have always responded to these technologies. Most malware today uses anti-debug techniques to counter analysis and evade antivirus detection. Lately, malware like Zeus/SpyEye and associated families such as Smoaler, Dromedan, Kazy, Yakes, and other malware such as Spyrat or W32.Pilleuz, have deployed techniques to disrupt the use of virtual machines and emulators. These malware families are able to implement different variations of disruption techniques within single samples or within related groups of malware before propagation. This paper will present a study of these anti-emulation and anti-virtual machine techniques.     

Improving active Mealy machine learning for protocol conformance testing

Using a well-known industrial case study from the verification literature, the bounded retransmission protocol, we show how active learning can be used to establish the correctness of protocol implementation I relative to a given reference implementation R. Using active learning, we learn a model M _R of reference implementation R, which serves as input for a model-based testing tool that checks conformance of implementation I to M _R . In addition, we also explore an alternative approach in which we learn a model M _I of implementation I, which is compared to model M _R using an equivalence checker. Our work uses a unique combination of software tools for model construction (Uppaal), active learning (LearnLib, Tomte), model-based testing (JTorX, TorXakis) and verification (CADP, MRMC). We show how these tools can be used for learning models of and revealing errors in implementations, present the new notion of a conformance oracle, and demonstrate how conformance oracles can be used to speed up conformance checking.     

Identification of straight-chain fatty acids in coal extracts and their geochemical relation with straight-chain alkanes

Mono-carboxylic, straight-chain fatty acids are present in extracts of lignite and subbituminous coal (0.4–1.0 wt%, daf basis), but not in those of a bituminous coal. They are removed with nearly equal ease by both solvent and supercritical gas (SCG) extraction. Octacosanoic acid is the major constituent, and values of the carbon preference index (even over odd) lie between 2 and 6. Solvent extraction of the coals also removes small quantities (< 0.08 wt%) of straight-chain alkanes which are closely related in composition to the straight-chain fatty acids and are probably derived from them during maturation. However, previous SCG extraction of the coals yielded much larger quantities of straight-chain alkanes (0.3–0.7 wt%). Pyrolysis experiments with a lignite fatty acid fraction and with tetracosanoic acid show that these acids largely survive SCG extraction and, therefore, are not the main source of the relatively large quantity of straight-chain alkanes in these extracts.     

Bridging value modelling to ArchiMate via transaction modelling

The ArchiMate modelling language provides a coherent and a holistic view of an enterprise in terms of its products, services, business processes, actors, business units, software applications and more. Yet, ArchiMate currently lacks (1) expressivity in modelling an enterprise from a value exchange perspective, and (2) rigour and guidelines in modelling business processes that realize the transactions relevant from a value perspective. To address these issues, we show how to connect e \(^{3}\) value, a technique for value modelling, to ArchiMate via transaction patterns from the DEMO methodology. Using ontology alignment techniques, we show a transformation between the meta models underlying e \(^{3}\) value, DEMO and ArchiMate. Furthermore, we present a step-wise approach that shows how this model transformation is achieved and, in doing so, we also show the of such a transformation. We exemplify the transformation of DEMO and e \(^{3}\) value into ArchiMate by means of a case study in the insurance industry. As a proof of concept, we present a software tool supporting our transformation approach. Finally, we discuss the functionalities and limitations of our approach; thereby, we analyze its and practical applicability.     

Structural Induction and Coinduction in a Fibrational Setting

We present a categorical logic formulation of induction and coinduction principles for reasoning about inductively and coinductively defined types. Our main results provide sufficient criteria for the validity of such principles: in the presence of comprehension, the induction principle for initial algebras is admissible, and dually, in the presence of quotient types, the coinduction principle for terminal coalgebras is admissible. After giving an alternative formulation of induction in terms of binary relations, we combine both principles and obtain a mixed induction/coinduction principle which allows us to reason about minimal solutionsX≅σ(X) whereXmay occur both positively and negatively in the type constructor σ. We further strengthen these logical principles to deal with contexts and prove that such strengthening is valid when the (abstract) logic we consider is contextually/functionally complete. All the main results follow from a basic result about adjunctions between “categories of algebras” (inserters).     

Influences of mesh density and transformation behavior on the result quality of numerical calculation of welding induced distortion

Welding simulation is a powerful, cost-efficient tool to predict welding induced distortion. Nevertheless, effects on calculation result quality are often unknown, thus, sensitivity analyses should be performed to evaluate the influences of certain parameters on distortion development.In the present paper, a single-layer gas metal arc (GMA) weld of 5 mm thick structural steel S355J2+N is experimentally and numerically investigated. Subsequent to welding, the numerical modeling begins with a mesh analysis based on modal analyses. Hereby, the influence of different coarsening methods and element edge length (EEL) in welding direction on the deformation behavior or the stiffness of the discrete geometry is the focus of the analysis. Secondly, phase transformations in structural steels such as S355J2+N are decisive for final product properties. The sensitivity of welding-induced distortion is examined regarding different continuous cooling transformation (CCT) diagrams for S355J2+N.The present investigations deal with different relevant influences on numerical calculation of welding-induced distortion. The quality and quantity of these effects are clarified based on the experimental and numerical set-up employed. Consequently, prediction of welding-induced distortion is possible and potential for pre-production optimization is present.