Universal ontology: attentive tracking of objects and substances across languages and over development

Previous research has demonstrated that adults are successful at visually tracking rigidly moving items, but experience great difficulties when tracking substance-like ‘‘pouring’’ items. Using a comparative approach, we investigated whether the presence/absence of the grammatical count–mass distinction influences adults and children’s ability to attentively track objects versus substances. More specifically, we aimed to explore whether the higher success at tracking rigid over substance-like items appears universally or whether speakers of classifier languages (like Japanese, not marking the object–substance distinction) are advantaged at tracking substances as compared to speakers of non-classifier languages (like Swiss German, marking the object–substance distinction). Our results supported the idea that language has no effect on low-level cognitive processes such as the attentive visual processing of objects and substances. We concluded arguing that the tendency to prioritize objects is universal and independent of specific characteristics of the language spoken.

A note on adding objects to an existing twoway graph

In Stata, graphs are usually generated by one call to the graph command. Sometimes, however, it would be convenient to be able to add objects to a graph after the graph has been created. In this article, I provide a command called addplot that offers such functionality for twoway graphs, capitalizing on an undocumented feature of Stata's graphics system.

A Genetic Algorithm to associate optical measurements and estimate orbits of geocentric objects

Cataloging geocentric objects can be put in the framework of Multiple Target Tracking (MTT). Current work tends to focus on the S = 2 MTT problem because of its favorable computational complexity of O(n²). The MTT problem becomes NP-hard for a dimension of S˃3. The challenge is to find an approximation to the solution within a reasonable computation time. To effciently approximate this solution a Genetic Algorithm is used. The algorithm is applied to a simulated test case. These results represent the first steps towards a method that can treat the S˃3 problem effciently and with minimal manual intervention.

Associating optical measurements and estimating orbits of geocentric objects through population-based meta-heuristic methods

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both, the correct associations among the observations and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. The number S corresponds to the number of fences involved in the problem. Each fence consists of a set of observations where each observation belongs to a different object. The S ≥ 3 MTT problem is an NP-hard combinatorial optimization problem. There are two general ways to solve this. One way is to seek the optimum solution, this can be achieved by applying a branch-and- bound algorithm. When using these algorithms the problem has to be greatly simplified to keep the computational cost at a reasonable level. Another option is to approximate the solution by using meta-heuristic methods. These methods aim to efficiently explore the different possible combinations so that a reasonable result can be obtained with a reasonable computational effort. To this end several population-based meta-heuristic methods are implemented and tested on simulated optical measurements. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

Polar Nature of Biomimetic Fluorapatite/Gelatin Composites: A Comparison of Bipolar Objects and the Polar State of Natural Tissue

The correspondence of the state of alignment of macromolecules in biomimetic materials and natural tissues is demonstrated by investigating a mechanism of electrical polarity formation: An in vitro grown biomimetic FAp/gelatin composite is investigated for its polar properties by second harmonic (SHGM) and scanning pyroelectric microscopy (SPEM). Hexagonal prismatic seed crystals formed in gelatin gels represent a monodomain polar state, due to aligned mineralized gelatin molecules. Later growth stages, showing dumbbell morphologies, develop into a bipolar state because of surface recognition by gelatin functionality: A reversal of the polar alignment of macromolecules, thus, takes place close to that basal plane of the seed. In natural hard tissues (teeth and bone investigated by SPEM) and the biomimetic FAp/gelatin composite, we find a surprising analogy in view of growth-induced states of polarity: The development of polarity in vivo and in vitro can be explained by a Markov-type mechanism of molecular recognition during the attachment of macromolecules.

Context Aware e-Learning Objects and their Types from the Perspective of the Object-Oriented Paradigm

The contribution of this article demonstrates how to identify context-aware types of e-Learning objects (eLOs) derived from the subject domains. This perspective is taken from an engineering point of view and is applied during requirements elicitation and analysis relating to present work in constructing an object-oriented (OO), dynamic, and adaptive model to build and deliver packaged e-Learning courses. Consequently, three preliminary subject domains are presented and, as a result, three primitive types of eLOs are posited. These types educed from the subject domains are of structural, conceptual, and granular nature. Structural objects are responsible for the course itself, conceptual objects incorporate adaptive and logical interoperability, while granular objects congregate granular assets. Their differences, interrelationships, and responsibilities are discussed. A major design challenge relates to adaptive behaviour. Future research addresses refinement on the subject domains and adaptive hypermedia systems.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

Transforming growth factor beta signaling is essential for the autonomous formation of cartilage-like tissue by expanded chondrocytes.

Cartilage is a tissue with limited self-healing potential. Hence, cartilage defects require surgical attention to prevent or postpone the development of osteoarthritis. For cell-based cartilage repair strategies, in particular autologous chondrocyte implantation, articular chondrocytes are isolated from cartilage and expanded in vitro to increase the number of cells required for therapy. During expansion, the cells lose the competence to autonomously form a cartilage-like tissue, that is in the absence of exogenously added chondrogenic growth factors, such as TGF-βs. We hypothesized that signaling elicited by autocrine and/or paracrine TGF-β is essential for the formation of cartilage-like tissue and that alterations within the TGF-β signaling pathway during expansion interfere with this process. Primary bovine articular chondrocytes were harvested and expanded in monolayer culture up to passage six and the formation of cartilage tissue was investigated in high density pellet cultures grown for three weeks. Chondrocytes expanded for up to three passages maintained the potential for autonomous cartilage-like tissue formation. After three passages, however, exogenous TGF-β1 was required to induce the formation of cartilage-like tissue. When TGF-β signaling was blocked by inhibiting the TGF-β receptor 1 kinase, the autonomous formation of cartilage-like tissue was abrogated. At the initiation of pellet culture, chondrocytes from passage three and later showed levels of transcripts coding for TGF-β receptors 1 and 2 and TGF-β2 to be three-, five- and five-fold decreased, respectively, as compared to primary chondrocytes. In conclusion, the autonomous formation of cartilage-like tissue by expanded chondrocytes is dependent on signaling induced by autocrine and/or paracrine TGF-β. We propose that a decrease in the expression of the chondrogenic growth factor TGF-β2 and of the TGF-β receptors in expanded chondrocytes accounts for a decrease in the activity of the TGF-β signaling pathway and hence for the loss of the potential for autonomous cartilage-like tissue formation.