Cytosolic Calcium Concentration Changes in Neuronal Cells Under Clinorotation and in Parabolic Flight Missions

All life on earth has been established under conditions of stable gravity of 1g. Nevertheless, in numerous experiments the direct gravity dependence of biological processes has been shown on all levels of organization, from single molecules to humans. To study the effects especially of microgravity on biological systems, a variety of platforms are available, from drop towers to the ISS. Due to the costs of these platforms and their limited availability, as an alternative, numerous simulators have been developed for so called “simulated” microgravity. A classical systems is a clinostat, basically rotating a sample around one axis, and by integration of the gravity vector for 360° arguing that thus the effects of gravity are depleted. Indeed, a variety of studies has shown that taking out the direction of gravity from a biological system often results in consequences similar to the exposure of the system to real microgravity. Nevertheless, the opposite has been shown, too, and as a consequence the relevance of clinostats in microgravity research is still under discussion. To get some more insight into this problem we have constructed a small fluorescence clinostat and have studied the effects of clinorotation on the cytosolic calcium concentration of neuroglioma cells. The results have been compared to experiments with identical cells in real microgravity, utilizing parabolic flight missions. Our results show that in case of a cell suspension used in a small florescence clinostat within a tube diameter of 2mm, the effects of clinorotation are comparable to those under real microgravity, both showing a significant increase in intracellular calcium concentration.     

Efficient indexing algorithms for one-dimensional discretely-scaled strings

The discretely-scaled string indexing problem asks one to preprocess a given text string T, so that for a queried pattern P, the matched positions in T that P appears with some discrete scale can be reported efficiently. For solving this problem, Wang et al. first show that with an O(|T|log|T|)-time preprocessing on T, all matched positions can be reported in O(|P|+Ud) time, where |T|, |P|, and Ud denote the length of T, the length of P, and the number of matched positions for discretely-scaled P in T, respectively. In this paper, for fixed alphabets we propose the first-known optimal indexing algorithm that takes O(|T|) and O(|P|+Ud) time in its preprocessing and query phases, respectively. For integer and unbounded alphabets, our new algorithm can also be extended to obtain the best-known results.     

The pragmatic quality of Resources‐ Events‐Agents diagrams: an experimental evaluation

The Resources‐Events‐Agents (REA) model is a semantic data model for the development of enterprise information systems. Although this model has been proposed as a benchmark for enterprise information modelling, only few studies have attempted to empirically validate the claimed benefits of REA modelling. Moreover, these studies focused on the evaluation of REA‐based system implementations rather than directly assessing the REA‐modelled conceptual schemas that these systems are based on. This paper presents a laboratory experiment that measured the user understanding of diagrammatic conceptual schemas developed using the REA model. The theoretical foundation for the hypotheses are cognitive theories that explain pattern recognition phenomena and the resulting reduction in cognitive effort for understanding conceptual schemas. The results of the experiment indicate a more accurate understanding of the business processes and policies modelled when users recognize the REA model’s core pattern of enterprise information in the diagram. The implication for modelling practice is that the use of the REA model improves the requirements engineering process by facilitating the user validation of conceptual schemas produced by analysts, and thus helps ensuring the quality of the enterprise information system that is developed or implemented.     

Promoting metacognitive skills through peer scaffolding in a CSCL environment

This paper aims to better understand the development of students’ metacognitive learning processes when participating actively in a CSCL system called KnowCat. To this end, a longitudinal case study was designed, in which 18 university students took part in a 12-month (two semesters) learning project. The students followed an instructional process, using specific features of the KnowCat design to support and improve their interaction processes, especially peer-learning processes. Our research involved both supervising the students’ collaborative learning processes throughout the learning project and focusing our analysis on the qualitative evolution of their interaction processes and of their metacognitive learning processes. The results of the current research suggest that the pedagogical use of the KnowCat system may favour and improve the development of the students’ metacognitive learning processes. In addition, the implications of the design of CSCL networks and related pedagogical issues are discussed.     

Automatic detection of breast cancers in mammograms using structured support vector machines

Breast cancer is one of the most common cancers diagnosed in women. Large margin classifiers like the support vector machine (SVM) have been reported effective in computer-assisted diagnosis systems for breast cancers. However, since the separating hyperplane determination exclusively relies on support vectors, the SVM is essentially a local classifier and its performance can be further improved. In this work, we introduce a structured SVM model to determine if each mammographic region is normal or cancerous by considering the cluster structures in the training set. The optimization problem in this new model can be solved efficiently by being formulated as one second order cone programming problem. Experimental evaluation is performed on the Digital Database for Screening Mammography (DDSM) dataset. Various types of features, including curvilinear features, texture features, Gabor features, and multi-resolution features, are extracted from the sample images. We then select the salient features using the recursive feature elimination algorithm. The structured SVM achieves better detection performance compared with a well-tested SVM classifier in terms of the area under the ROC curve.     

Fuzzy clustering of time series in the frequency domain

Traditional and fuzzy cluster analyses are applicable to variables whose values are uncorrelated. Hence, in order to cluster time series data which are usually serially correlated, one needs to extract features from the time series, the values of which are uncorrelated. The periodogram which is an estimator of the spectral density function of a time series is a feature that can be used in the cluster analysis of time series because its ordinates are uncorrelated. Additionally, the normalized periodogram and the logarithm of the normalized periodogram are also features that can be used. In this paper, we consider a fuzzy clustering approach for time series based on the estimated cepstrum. The cepstrum is the spectrum of the logarithm of the spectral density function. We show in our simulation studies for the typical generating processes that have been considered, fuzzy clustering based on the cepstral coefficients performs very well compared to when it is based on other features.     

DynaMICs: Comprehensive Support for Run-Time Monitoring

Software engineering strives to enable the economic construction of software systems that behave reliably, predictably, and safely. In other engineering disciplines, safety is assured in part by detailed monitoring of processes. In software, we may achieve some level of confidence in the operation of programs by monitoring their execution. DynaMICs is a software tool that facilitates the collection and use of constraints for software systems. In addition, it supports traceability by mapping constraints to system artifacts. Constraint specifications are stored separately from code; constraint-monitoring code is automatically generated from the specifications and inserted into the program at appropriate places; and constraints are verified at execution time. These constraint checks are triggered by changes made to variable values. We describe the architecture of DynaMICs, discuss alternative verification techniques, and outline research directions for the DynaMICs project.     

New driving scheme for intelligent power‐efficient high‐voltage display drivers

Abstract— A new bistable‐display driver is presented. The innovation in the developed driver is the addition of a new logical block that calculates the most energy‐efficient driving waveforms. In this paper, the algorithms being applied to the row and column waveforms in order to reduce the power consumption are discussed. Some theoretical as well as experimental results are shown, proving a reduction in the power consumption by about 50%. The proposed algorithms are especially important for battery‐powered applications.