Object oriented databases in software development for structural analysis

A technique for using object-oriented technologies to write structural analysis software has been developed. The structural design information of an individual building is stored in an object-oriented database. A global database provides general design values as material data and safety factors. A class library for load elements has been evolved to model the transfer of loads in a building. This class library is the basis for the development of further classes for other structural elements such as beams, columns or slabs. A software has been developed to monitor the forces transferred from one structural member to another in a building for load cases and combinations according to Eurocode 1. The results of the analysis are stored in the projects database from which a structural design report may be generated. The software was developed under Microsoft Visual C++. The Microsoft Foundation Class Library (MFC) was used to program the Graphical User Interface (GUI). Object Linking and Embedding (OLE) technology is useful to include any type of OLE server objects for example texts written with a word processor or CAD drawings in the structural design report. The Object-Oriented Database Management System (OODBMS) ObjectStore provides services to store the large amount of objects

The influence of prior knowledge on memory: A developmental cognitive neuroscience perspective

Across ontogenetic development, individuals gather manifold experiences during which they detect regularities in their environment and thereby accumulate knowledge. This knowledge is used to guide behavior, make predictions, and acquire further new knowledge. In this review, we discuss the influence of prior knowledge on memory from both the psychology and the emerging cognitive neuroscience literature and provide a developmental perspective on this topic. Recent neuroscience findings point to a prominent role of the medial prefrontal cortex (mPFC) and of the hippocampus (HC) in the emergence of prior knowledge and in its application during the processes of successful memory encoding, consolidation, and retrieval. We take the lateral PFC into consideration as well and discuss changes in both medial and lateral PFC and HC across development and postulate how these may be related to the development of the use of prior knowledge for remembering. For future direction, we argue that, to measure age differential effects of prior knowledge on memory, it is necessary to distinguish the availability of prior knowledge from its accessibility and use

On the estimation of brain signal entropy from sparse neuroimaging data

Multi-scale entropy (MSE) has been recently established as a promising tool for the analysis of the moment-to-moment variability of neural signals. Appealingly, MSE provides a measure of the predictability of neural operations across the multiple time scales on which the brain operates. An important limitation in the application of the MSE to some classes of neural signals is MSE’s apparent reliance on long time series. However, this sparse-data limitation in MSE computation could potentially be overcome via MSE estimation across shorter time series that are not necessarily acquired continuously (e.g., in fMRI block-designs). In the present study, using simulated, EEG, and fMRI data, we examined the dependence of the accuracy and precision of MSE estimates on the number of data points per segment and the total number of data segments. As hypothesized, MSE estimation across discontinuous segments was comparably accurate and precise, despite segment length. A key advance of our approach is that it allows the calculation of MSE scales not previously accessible from the native segment lengths. Consequently, our results may permit a far broader range of applications of MSE when gauging moment-to- moment dynamics in sparse and/or discontinuous neurophysiological data typical of many modern cognitive neuroscience study designs