Automatic data collection for enterprise architecture models

Enterprise Architecture (EA) is an approach used to provide decision support based on organization-wide models. The creation of such models is, however, cumbersome as multiple aspects of an organization need to be considered, making manual efforts time-consuming, and error prone. Thus, the EA approach would be significantly more promising if the data used when creating the models could be collected automatically—a topic not yet properly addressed by either academia or industry. This paper proposes network scanning for automatic data collection and uses an existing software tool for generating EA models (ArchiMate is employed as an example) based on the IT infrastructure of enterprises. While some manual effort is required to make the models fully useful to many practical scenarios (e.g., to detail the actual services provided by IT components), empirical results show that the methodology is accurate and (in its default state) require little effort to carry out.     

Attentional sensitization of unconscious cognition: Task sets modulate subsequent masked semantic priming.

According to classical theories, automatic processes are autonomous and independent of higher level cognitive influence. In contrast, the authors propose that automatic processing depends on attentional sensitization of task-congruent processing pathways. In 3 experiments, the authors tested this hypothesis with a modified masked semantic priming paradigm during a lexical decision task by measuring event-related potentials (ERPs): Before masked prime presentation, participants attended an induction task either to semantic or perceptual stimulus features designed to activate a semantic or perceptual task set, respectively. Semantic priming effects on the N400 ERP component, an electrophysiological index of semantic processing, were obtained when a semantic task set was induced immediately before subliminal prime presentation, whereas a previously induced perceptual task set attenuated N400 priming. Across experiments, comparable results were obtained regardless of the difficulty level and the verbal or nonverbal nature of the induction tasks. In line with the proposed attentional sensitization model, unconscious semantic processing is enhanced by a semantic and attenuated by a perceptual task set. Hence, automatic processing of unconscious stimuli is susceptible to top-down control for optimizing goal-related information processing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimizing wheel profiles and suspensions for railway vehicles operating on specific lines to reduce wheel wear: a case study

Multibody System Dynamics - The selection of a wheel profile is a topic of great interest as it can affect running performances and wheel wear, which needs to be determined based on the actual...     

Coherent interaction of atoms with a beam of light confined in a light cage

Controlling coherent interaction between optical fields and quantum systems in scalable, integrated platforms is essential for quantum technologies. Miniaturise...     

t-Private and t-secure Auctions

In most of the auction systems the values of bids are known to the auctioneer. This allows him to manipulate the outcome of the auction. Hence, one might be interested in hiding these values. Some cryptographically secure protocols for electronic auctions have been presented in the last decade. Our work extends these protocols in several ways. On the basis of garbled circuits, i.e., encrypted circuits, we present protocols for sealed-bid auctions that fulfill the following requirements: 1) protocols are information-theoretically t-private for honest but curious parties; 2) the number of bits that can be learned by malicious adversaries is bounded by the output length of the auction; 3) the computational requirements for participating parties are very low: only random bit choices and bitwise computation of the XOR-function are necessary. Note that one can distinguish between the protocol that generates a garbled circuit for an auction and the protocol to evaluate the auction. In this paper we address both problems. We will present a t-private protocol for the construction of a garbled circuit that reaches the lower bound of 2t 1 parties, and a more randomness effcient protocol for (t 1)2 parties. Finally, we address the problem of bid changes in an auction.     

Automatic classifier selection for non-experts

Choosing a suitable classifier for a given dataset is an important part of developing a pattern recognition system. Since a large variety of classification algorithms are proposed in literature, non-experts do not know which method should be used in order to obtain good classification results on their data. Meta-learning tries to address this problem by recommending promising classifiers based on meta-features computed from a given dataset. In this paper, we empirically evaluate five different categories of state-of-the-art meta-features for their suitability in predicting classification accuracies of several widely used classifiers (including Support Vector Machines, Neural Networks, Random Forests, Decision Trees, and Logistic Regression). Based on the evaluation results, we have developed the first open source meta-learning system that is capable of accurately predicting accuracies of target classifiers. The user provides a dataset as input and gets an automatically created high-performance ready-to-use pattern recognition system in a few simple steps. A user study of the system with non-experts showed that the users were able to develop more accurate pattern recognition systems in significantly less development time when using our system as compared to using a state-of-the-art data mining software.     

BetweenIT: An Interactive Tool for Tight Inbetweening

The generation of inbetween frames that interpolate a given set of key frames is a major component in the production of a 2D feature animation. Our objective is to considerably reduce the cost of the inbetweening phase by offering an intuitive and effective interactive environment that automates inbetweening when possible while allowing the artist to guide, complement, or override the results. Tight inbetweens, which interpolate similar key frames, are particularly time‐consuming and tedious to draw. Therefore, we focus on automating these high‐precision and expensive portions of the process. We have designed a set of user‐guided semi‐automatic techniques that fit well with current practice and minimize the number of required artist‐gestures. We present a novel technique for stroke interpolation from only two keys which combines a stroke motion constructed from logarithmic spiral vertex trajectories with a stroke deformation based on curvature averaging and twisting warps. We discuss our system in the context of a feature animation production environment and evaluate our approach with real production data.     

Intramyocardial Inflammation after COVID-19 Vaccination: An Endomyocardial Biopsy-Proven Case Series

Myocarditis in response to COVID-19 vaccination has been reported since early 2021. In particular, young male individuals have been identified to exhibit an increased risk of myocardial inflammation following the administration of mRNA-based vaccines. Even though the first epidemiological analyses and numerous case reports investigated potential relationships, endomyocardial biopsy (EMB)-proven cases are limited. Here, we present a comprehensive histopathological analysis of EMBs from 15 patients with reduced ejection fraction (LVEF = 30 (14–39)%) and the clinical suspicion of myocarditis following vaccination with Comirnaty^® (Pfizer-BioNTech) (n = 11), Vaxzevria^® (AstraZenica) (n = 2) and Janssen^® (Johnson & Johnson) (n = 2). Immunohistochemical EMB analyses reveal myocardial inflammation in 14 of 15 patients, with the histopathological diagnosis of active myocarditis according the Dallas criteria (n = 2), severe giant cell myocarditis (n = 2) and inflammatory cardiomyopathy (n = 10). Importantly, infectious causes have been excluded in all patients. The SARS-CoV-2 spike protein has been detected sparsely on cardiomyocytes of nine patients, and differential analysis of inflammatory markers such as CD4⁺ and CD8⁺ T cells suggests that the inflammatory response triggered by the vaccine may be of autoimmunological origin. Although a definitive causal relationship between COVID-19 vaccination and the occurrence of myocardial inflammation cannot be demonstrated in this study, data suggest a temporal connection. The expression of SARS-CoV-2 spike protein within the heart and the dominance of CD4⁺ lymphocytic infiltrates indicate an autoimmunological response to the vaccination.     

Long-term effects of dissolved carbonate species on the degradation of trichloroethylene by zerovalent iron

The effect of different concentrations of total inorganic carbon (TIC) and flow rates on the reactivity of iron metal with trichloroethylene (TCE) was studied in column experiments to verify whether concentration or mass flux of TIC is the major key parameter for barrier performance. First-order rate coefficients (kobs) for TCE degradation vary initially between 0.15 and 0.32 h-' and are positively related to TIC influent concentration. Maximal kobs were reached after 164 and 591 PV, varied between 0.55 and 1.1 h(-1), and were positively correlated to the TIC mass flux, followed by a decrease resulting in values similar to the reference system at the end of the experiments. Enhancement of iron corrosion (0.7 to 3.5 mmol kgFe(-1) d(-1) and formation of gas bubbles during the initial experimental phase were observed and were also positively correlated to TIC mass flux. The higher gas bubble formation probably has a more significant effect on porosity than mineral precipitations in Fe0-systems. The results suggest that higher TIC mass fluxes cause a more pronounced acceleration in CHC degradation, but also a faster inhibition in the longer-term. This faster inhibition has serious implication for the design of funnel and gate systems.     

A microarray for monitoring the production of mycotoxins in food

A microarray, which covers most of the known relevant mycotoxin biosynthesis genes, has been developed. The microarray carries oligonucleotides of the fumonisin, the aflatoxin, the ochratoxin, the trichothecene (type A and B) and the patulin biosynthesis pathways. For trichothecene producing Fusaria the biosynthesis cluster of trichothecene producing Fusarium sporotrichioides (type A) and of Gibberrella zeae (type B, teleomorph of F. graminearum) have been spotted. The aflatoxin cluster carries oligonucleotides specific for Aspergillus flavus. The ochratoxin pattern is specific for ochratoxin A producing Penicillia, the fumonisin cluster is specific for G. moniliformis (teleomorph of F. verticillioides) and the patulin genes have been obtained from Penicillium expansum. The microarray is designed in a way that newly identified pathway genes can be added easily at any time. The microarray was used to detect the activation of all gene clusters under conditions conducive for mycotoxin biosynthesis. According to the results the obtained signals were specific under the hybridization conditions used and only insignificant cross-hybridizations occurred. The microarray was used to demonstrate differences in mycotoxin pathway gene expressions after growth on various media for trichothecene and ochratoxin A biosynthesis. It was used further to study and compare the expression kinetics of the trichothecene biosynthesis genes of Fusarium on different trichothecene supporting media. An expression pattern indicative for trichothecene biosynthesis could be identified.