Diagnosis of diabetes mellitus: case of different cutoff values: A data mining approach

Objective: An estimation of cut-off points for the diagnosis of diabetes mellitus (DM) based on individual risk factors. Methods: A subset of the 1991 Oman National Diabetes Survey is used, including all patients with a 2h post glucose load >= 200 mg/dl (278 subjects) and a control group of 286 subjects. All subjects previously diagnosed as diabetic and all subjects with missing data values were excluded. The data set was analyzed by use of the SPSS Clementine data mining system. Decision Tree Learners (C5 and CART) and a method for mining association rules (the GRI algorithm) are used. The fasting plasma glucose (FPG), age, sex, family history of diabetes and body mass index (BMI) are input risk factors (independent variables), while diabetes onset (the 2h post glucose load >= 200 mg/dl) is the output (dependent variable). All three techniques used were tested by use of crossvalidation (89.8%). Results: Rules produced for diabetes diagnosis are: A- GRI algorithm (1) FPG>=108.9 mg/dl, (2) FPG>=107.1 and age>39.5 years. B- CART decision trees: FPG >=110.7 mg/dl. C- The C5 decision tree learner: (1) FPG>=95.5 and 54, (2) FPG>=106 and 25.2 kg/m2. (3) FPG>=106 and =133 mg/dl. The three techniques produced rules which cover a significant number of cases (82%), with confidence between 74 and 100%. Conclusion: Our approach supports the suggestion that the present cut-off value of fasting plasma glucose (126 mg/dl) for the diagnosis of diabetes mellitus needs revision, and the individual risk factors such as age and BMI should be considered in defining the new cut-off value.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

Study of the influence of grain size and precipitates on the electromagnetic losses in different grades of non-oriented fully processed electrical steel

The study was performed in the installations of OCAS, a Steel Research Centre of ArcelorMittal. Taking M32 steel (3.25%Si+0.9%Al) as the basis chemical composition and three different thicknesses (0.35, 0.5 and 0.65mm), different annealing conditions (temperature and time) have been applied in the laboratory simulator at St. Chély, France. The aim was to link annealing parameters, grain size and energy loss. It was determined the optimum annealing parameters to reach the lowest power losses for three different grades of non-oriented fully processed electrical steel. In addition, M250-50 samples having different magnetic behaviour (high and low losses) but the same grain size and texture, have been analyzed in terms of TEM observations of their precipitates, in the University of Marseille. The results reveal that a high amount of medium and big precipitates (&10 nm) worsen the magnetic properties of the material. The small precipitates (&10nm) do not have a strong influence on the magnetic properties. The presence of precipitates can have a great influence on the power losses and further work is clearly necessary.

Link between microstructure and properties in new metallurgical concepts for very low loss non-oriented electrical steel

The influence of chemistry and soaking temperature (maximal temperature of the continuous annealing) on the final properties of non-oriented electrical steels has been studied. With this objective two different studies have been performed. First the Mn, Ni and Cr content of a low loss electrical steel composition has been modified. An intermediate content and a high content of each element has been added in order to study the influence of this components on the magnetic looses, grain size and texture. Secondly the influence of the soaking temperature on magnetic properties, grain size and oxidation in four grades of non-oriented electrical steels (Steel A, B, C and D) was studied.

Developing a non-public research software for public use

EasyLEED is a program designed for the extraction of intensity-energy spectra from low-energy electron diffraction patterns. It can be used to get information about the position of individual atoms on a surface of some substance. The goal of this thesis is to make easyLEED useful in LEED-research. It is achieved by adding new features, i.e. plotting intensity-energy spectra, setting tracking parameters and allowing exporting and importing of settings and spot location data, to the program. The detailed description of these added features and how they’re done and how they impact on the usefulness of the program in research are presented in this thesis. Improving the calculational part of the program is not discussed.

Evaluation of sets of oriented and non-oriented receptive fields as local descriptors

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.

Formal linguistic approaches to heritage language acquisition: bridges for pedagogically oriented research

The goal of this chapter is to lay out the central themes of heritage language acquisition research adopting a formal/theoretical linguistic perspective.  Specifically, we aim to provide a detailed discussion of the nature of heritage language grammars. In doing so, we will address the debates on how to explain heritage speaker competence differences from monolingual baselines and more. This chapter will not be limited to discussions of Spanish as a heritage language, but rather will highlight the important role that Spanish has played and will continue to play in the development of heritage language acquisition studies. Finally, we will offer some comments/insights on how the information covered regarding the formal linguistic properties of heritage speaker knowledge should be considered for and implemented in heritage language pedagogies and thus dealing with heritage speakers in the classroom setting.