Transmission electron microscopy study of a dental gallium alloy

Analytical transmission electron microscopy (TEM) studies of a dental gallium alloy have been carried out. This commercial Ga alloy was made by triturating a Ag-Sn-Cu-rich alloy powder with a liquid Ga alloy containing Ga, In and Sn. Ga alloys are of increasing interest as an alternative to amalgam. The dental material studied in the present work was found to be a composite consisting of remaining, undissolved particles from the Ag-based alloy powder in a matrix of reaction products with the liquid Ga alloy. The phases in the matrix and the remaining Ag-based alloy particles have been identified by electron diffraction, high resolution electron microscopy and energy dispersive X-ray spectroscopy. the following phases were identified: orthorhombic Ag₃Sn, cubic -Cu₉Ga₄, cubic Ag₉In₄, tetragonal -Sn and hexagonal Ag₂Ga. In addition to these well-known phases Ga-rich regions of Cu-Ga were observed consisting of an intergrowth of the tetragonal CuGa₂ and one of the cubic -Cu₉Ga₄ phases.     

Influence of serotonergic neurons and of pineal gland on the development of the neonatal androgen sterilization syndrome in the rat

The effect of the removal of pineal gland, performed in adult age or during perinatal life, was investigated in the neonatal androgen sterility (NA-CEA) syndrome, in combination with drugs acting on serotonergic neurons. Perinatal pinealectomy (Px) was more potent in preventing the development of NA-CEA state than Px performed in the adult age. These data indicate that the masculinized hypothalamus becomes less sensitive to pineal influences during the lifespan. Effect of Px was potentiated by drugs increasing the central serotonergic tone. The results lead to the assumption that pineal hormones are influential on the maturation of serotonergic neurons, which might interfere with the sterilizing property of neonatal androgen treatment during the "critical" period of sexual differentiation.     

ARPO-2: An expert system for legal advice on the breach of building contracts

Although Berman and Hafner [Berman 1989, pp. 928–938] presented the possibility to adapt the model of reasoning of development of an expert system for medical diagnosis to the reasoning of a judge when he/she sentences criminals does not resemble the reasoning found in the decisions of physicians, mathematicians or statisticians.When a lawyer reasons, he/she not only looks for the solution of a case; he/she simultaneously looks for the bases on which his/her reasoning can rest [Galindo 1992, pp. 363–367]. That is to say, he/she not only needs to find the solution but moreover he/she has to find the references (laws, jurisprudence and bibliography) that allow him/her to argue the solution.In many cases, computer solutions to these reasoning processes have been made in a separated way: the solution to the cases using expert systems, and the search of documentation using information retrieval systems.This paper presents the ARPO-2 prototype, a solution integrating the two aspects of legal reasoning: an expert system which is able to simultaneously find the solution to a problem and to give the necessary references so that the lawyer argues the solution. The subject on which the prototype solves problems is the breach of building contracts.In this paper, we describe the process of development of an expert system for solving, justification and documentation of breach of contracts, giving details on the way how the objects that intervene in the case were defined as well as on the reasoning followed.This paper was funded in part by DGICYT, Spanish Civil Law Computerization Project: PB870-632.     

An improved method for voice pathology detection by means of a HMM-based feature space transformation

This paper presents new a feature transformation technique applied to improve the screening accuracy for the automatic detection of pathological voices. The statistical transformation is based on Hidden Markov Models, obtaining a transformation and classification stage simultaneously and adjusting the parameters of the model with a criterion that minimizes the classification error. The original feature vectors are built up using classic short-term noise parameters and mel-frequency cepstral coefficients. With respect to conventional approaches found in the literature of automatic detection of pathological voices, the proposed feature space transformation technique demonstrates a significant improvement of the performance with no addition of new features to the original input space. In view of the results, it is expected that this technique could provide good results in other areas such as speaker verification and/or identification.     

Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values

The additive model of multiattribute value theory is widely used in multicriteria choice problems. But often it is not easy to obtain precise values for the scaling weights or the alternatives’ value in each function. Several decision rules which require weaker information, such as ordinal information, have been proposed to select an alternative under these circumstances. We propose new decision rules and test them using Monte-Carlo simulation, considering that there is ordinal information both on the scaling weights and on the alternatives’ values. Results show the new rules constitute a good approximation. We provide guidelines about how to use these rules in a context of selecting a subset of the most promising alternatives, considering the contradictory objectives of keeping a low number of alternatives yet not excluding the best one.     

An adaptive, real-time, traffic monitoring system

In this paper we describe a computer vision-based traffic monitoring system able to detect individual vehicles in real-time. Our fully integrated system first obtains the main traffic variables: counting, speed and category; and then computes a complete set of statistical variables. The objective is to investigate some of the difficulties impeding existing traffic systems to achieve balanced accuracy in every condition; i.e. day and night transitions, shadows, heavy vehicles, occlusions, slow traffic and congestions. The system we present is autonomous, works for long periods of time without human intervention and adapts automatically to the changing environmental conditions. Several innovations, designed to deal with the above circumstances, are proposed in the paper: an integrated calibration and image rectification step, differentiated methods for day and night, an adaptive segmentation algorithm, a multistage shadow detection method and special considerations for heavy vehicle identification and treatment of slow traffic. A specific methodology has been developed to benchmark the accuracy of the different methods proposed.     

Effect of high-level content organizers on hypertext learning

This study investigates the cognitive abilities involved in hypertext learning and design approaches that can help users. We examined the effects of two types of high-level content organizers - a graphic spatial map and an alphabetical list - on readers’ memory for hypertext structure. In the control condition, a simple “home” page with no navigational aid was offered. Subjects were asked to read the hypertext with the purpose of learning the content, but in the post test phase they also had to recall the layout of nodes and links. Memory for links and page places varied as a function of condition. When a spatial map was available participants reconstructed more accurate formal structure then in the two other conditions. Participants’ memory about page places was the least accurate in the list condition. Results also indicate that participants use the content organizer when it is available in order to orientate during learning from hypertext documents.Our results prove that a content organizer showing the formal structure can facilitate the spatial mapping process. However, an organizer exposing a different structure than the real one would generate a conflict.     

Aerodynamic optimization via multi-objective micro-genetic algorithm with range adaptation,knowledge-based reinitialization,crowding and ε-dominance

In this study, an optimization of the airfoil of a sailplane is carried out by a recently developed multi-objective genetic algorithm based on microevolution, containing crowding, range adaptation, knowledge-based reinitialization and ε-dominance. Its efficiency was tested on a set of test problems. The results are encouraging, suggesting that very small populations can be used effectively to solve real-world multi-objective optimization problems in many cases of interest.     

A Minimal Closed-form Solution for the Perspective Three Orthogonal Angles (P3oA) Problem: Application To Visual Odometry

We provide a simple closed-form solution to the Perspective three orthogonal angles (P3oA) problem: given the projection of three orthogonal lines in a calibrated camera, find their 3D directions. Upon this solution, an algorithm for the estimation of the camera relative rotation between two frames is proposed. The key idea is to detect triplets of orthogonal lines in a hypothesize-and-test framework and use all of them to compute the camera rotation in a robust way. This approach is suitable for human-made environments where numerous groups of orthogonal lines exist. We evaluate the numerical stability of the P3oA solution and the estimation of the relative rotation with synthetic and real data, comparing our results to other state-of-the-art approaches.