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.

A Lentiviral Vector Expressing Japanese Encephalitis Virus-like Particles Elicits Broad Neutralizing Antibody Response in Pigs.

BACKGROUND Japanese encephalitis virus (JEV) is the major cause of viral encephalitis in Southeast Asia. Vaccination of domestic pigs has been suggested as a "one health" strategy to reduce viral disease transmission to humans. The efficiency of two lentiviral TRIP/JEV vectors expressing the JEV envelope prM and E glycoproteins at eliciting protective humoral response was assessed in a mouse model and piglets. METHODOLOGY/PRINCIPAL FINDINGS A gene encoding the envelope proteins prM and E from a genotype 3 JEV strain was inserted into a lentiviral TRIP vector. Two lentiviral vectors TRIP/JEV were generated, each expressing the prM signal peptide followed by the prM protein and the E glycoprotein, the latter being expressed either in its native form or lacking its two C-terminal transmembrane domains. In vitro transduction of cells with the TRIP/JEV vector expressing the native prM and E resulted in the efficient secretion of virus-like particles of Japanese encephalitis virus. Immunization of BALB/c mice with TRIP/JEV vectors resulted in the production of IgGs against Japanese encephalitis virus, and the injection of a second dose one month after the prime injection greatly boosted antibody titers. The TRIP/JEV vectors elicited neutralizing antibodies against JEV strains belonging to genotypes 1, 3, and 5. Immunization of piglets with two doses of the lentiviral vector expressing JEV virus-like particles led to high titers of anti-JEV antibodies, that had efficient neutralizing activity regardless of the JEV genotype tested. CONCLUSIONS/SIGNIFICANCE Immunization of pigs with the lentiviral vector expressing JEV virus-like particles is particularly efficient to prime antigen-specific humoral immunity and trigger neutralizing antibody responses against JEV genotypes 1, 3, and 5. The titers of neutralizing antibodies elicited by the TRIP/JEV vector are sufficient to confer protection in domestic pigs against different genotypes of JEV and this could be of a great utility in endemic regions where more than one genotype is circulating.

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.

Effects of divergent selection for growth on egg quality traits in Japanese quail

The experiment was designed to investigate the impact of selection for increased body mass on external and internal egg quality traits of Japanese quail. Three hundred and sixty Japanese quail, divergently selected over three generations for different body mass at 4 weeks of age, were used. Quail were homogeneously divided into three groups each consisting of 120 birds: high body mass (HBM), low body mass (LBM) and Control. ANOVA was used to detect the effect of selection on egg quality. In addition, correlation between external and internal egg quality traits was measured. Our results revealed thatHBMquail laid heavier eggs (P = 0.03 compared with LBM but not significantly different with Control quail) with a higher external (shell thickness, shell weight, eggshell ratio and eggshell density, P = 0.0001) and internal egg quality score (albumen weight, P = 0.003; albumen ratio, P = 0.01; albumen height, yolk height, yolk index and Haugh unit, P = 0.0001) when compared with both the Control and LBM. The egg surface area and yolk diameter were significantly higher in HBM when compared with the LBM but not with the Control line. Egg weight was positively correlated with albumen weight (r = 0.54, P = 0.0001), albumen ratio (r = 0.14, P = 0.05), yolk height (r = 0.27, P = 0.0001), yolk weight (r = 0.23, P = 0.002), yolk diameter (r = 0.14, P = 0.05) and yolk index (r = 0.21, P = 0.005) but was negatively correlated with yolk ratio (r = –0.16, P = 0.03). Our results indicate that selection for higher body mass might result in heavier eggs and superior egg quality.