Visualizing transport structures of time-dependent flow fields

This article focuses on the transport characteristics of physical properties in fluids-in particular, visualizing the finite-time transport structure of property advection. Applied to a well-chosen set of property fields, the proposed approach yields structures giving insights into the underlying flow's dynamic processes.     

TORC: test plan optimization by requirements clustering

Acceptance testing is a time-consuming task for complex software systems that have to fulfill a large number of requirements. To reduce this effort, we have developed a widely automated method for deriving test plans from requirements that are expressed in natural language. It consists of three stages: annotation, clustering, and test plan specification. The general idea is to exploit redundancies and implicit relationships in requirements specifications. Multi-viewpoint techniques based on RM-ODP (Reference Model for Open Distributed Processing) are employed for specifying the requirements. We then use linguistic analysis techniques, requirements clustering algorithms, and pattern-based requirements collection to reduce the total effort of testing against the requirements specification. In particular, we use linguistic analysis for extracting and annotating the actor, process and object of a requirements statement. During clustering, a similarity function is computed as a measure for the overlap of requirements. In the test plan specification stage, our approach provides capabilities for semi-automatically deriving test plans and acceptance criteria from the clustered informal textual requirements. Two patterns are applied to compute a suitable order of test activities. The generated test plans consist of a sequence of test steps and asserts that are executed or checked in the given order. We also present the supporting prototype tool TORC, which is available open source. For the evaluation of the approach, we have conducted a case study in the field of acceptance testing of a national electronic identification system. In summary, we report on lessons learned how linguistic analysis and clustering techniques can help testers in understanding the relations between requirements and for improving test planning.     

Radiomics and Machine Learning in Oral Healthcare

The increasing storage of information, data, and forms of knowledge has led to the development of new technologies that can help to accomplish complex tasks in different areas, such as in dentistry. In this context, the role of computational methods, such as radiomics and Artificial Intelligence (AI) applications, has been progressing remarkably for dentomaxillofacial radiology (DMFR). These tools bring new perspectives for diagnosis, classification, and prediction of oral diseases, treatment planning, and for the evaluation and prediction of outcomes, minimizing the possibilities of human errors. A comprehensive review of the state‐of‐the‐art of using radiomics and machine learning (ML) for imaging in oral healthcare is presented in this paper. Although the number of published studies is still relatively low, the preliminary results are very promising and in a near future, an augmented dentomaxillofacial radiology (ADMFR) will combine the use of radiomics‐based and AI‐based analyses with the radiologist's evaluation. In addition to the opportunities and possibilities, some challenges and limitations have also been discussed for further investigations.     

Frequency of correctness versus average polynomial time

We prove that every distributional problem solvable in polynomial time on the average with respect to the uniform distribution has a frequently self-knowingly correct polynomial-time algorithm.     

Gezielte Manipulation von Mikropartikeln in einem Plasma. Manipulation of micro‐disperse particles in a process plasma

An optimal treatment (surface modification, coating) of micro‐disperse materials (powder, granulate, fibres etc.) by a process plasma requires the understanding of plasma‐particle interaction. For this purpose, related experimental investigations in a novel set‐up PULVA‐INP will be presented.     

Aromatic amino acids as latent,bio-based curing agents and toughening agents for epoxy resins

In the realm of bio-based curing agents, recent investigations have focused on amino acids owing to their distinctive attributes. Nevertheless, the suitability of thermosets cured with aromatic amino acids as latent matrix materials for fiber-reinforced composites remains to be empirically established. Consequently, this study is oriented toward assessing the mechanical properties of diglycidyl ether of bisphenol A when cured with either L-tryptophan or L-tyrosine, in the presence of a latent, urea-based accelerator. The investigated properties include glass transition temperatures, tensile, flexural, compression, and fracture toughness properties. The predominant variations in the mechanical characteristics of these thermosets are confined to their Young's moduli and fracture toughness properties. This divergence is attributed to the greater presence of crystals in the L-tyrosine-cured thermoset, resulting in enhanced reinforcement and toughening effects compared to the L-tryptophan-cured thermoset.     

Eye Movements and Behavioral Responses to Threatening and Nonthreatening Stimuli During Visual Search in Phobic and Nonphobic Subjects.

Spider-phobic and nonphobic subjects searched for a feared/fear-relevant (spider) or neutral target (mushroom) presented in visual matrices of neutral objects (flowers). In half of the displays, the mushroom target was paired with a spider distractor, or a spider target was paired with a mushroom distractor. Although all subjects responded faster to the neutral target than to the feared/fear-relevant target, phobics were slower to respond than nonphobics when a mushroom target was presented with a spider distractor. Their eyes appeared to be drawn to the feared distractor before fixating neutral targets. A further experiment indicated no group differences when subjects merely judged the homogeneity of matrices. Thus, threat seems to capture the attention of phobics only when it is part of a background that subjects are explicitly instructed to ignore. (PsycINFO Database Record (c) 2010 APA, all rights reserved)