Generalized descriptive set theory and classification theory

Descriptive set theory is mainly concerned with studying subsets of the space of all countable binary sequences. In this paper we study the generalization where countable is replaced by uncountable. We explore properties of generalized Baire and Cantor spaces, equivalence relations and their Borel reducibility. The study shows that the descriptive set theory looks very different in this generalized setting compared to the classical, countable case. We also draw the connection between the stability theoretic complexity of first-order theories and the descriptive set theoretic complexity of their isomorphism relations. Our results suggest that Borel reducibility on uncountable structures is a model theoretically natural way to compare the complexity of isomorphism relations.

Period-Luminosity-Colour distribution and classification of Galactic oxygen-rich LPVs I. Luminosity calibrations

The absolute K magnitudes and kinematic parameters of about 350 oxygen-rich Long-Period Variable stars are calibrated, by means of an up-to-date maximum-likelihood method, using HIPPARCOS parallaxes and proper motions together with radial velocities and, as additional data, periods and V-K colour indices. Four groups, differing by their kinematics and mean magnitudes, are found. For each of them, we also obtain the distributions of magnitude, period and de-reddened colour of the base population, as well as de-biased period-luminosity-colour relations and their two-dimensional projections. The SRa semiregulars do not seem to constitute a separate class of LPVs. The SRb appear to belong to two populations of different ages. In a PL diagram, they constitute two evolutionary sequences towards the Mira stage. The Miras of the disk appear to pulsate on a lower-order mode. The slopes of their de-biased PL and PC relations are found to be very different from the ones of the Oxygen Miras of the LMC. This suggests that a significant number of so-called Miras of the LMC are misclassified. This also suggests that the Miras of the LMC do not constitute a homogeneous group, but include a significant proportion of metal-deficient stars, suggesting a relatively smooth star formation history. As a consequence, one may not trivially transpose the LMC period-luminosity relation from one galaxy to the other.

Generalized Schmidt decomposition and classification of three-quantum-bit states

We prove for any pure three-quantum-bit state the existence of local bases which allow one to build a set of five orthogonal product states in terms of which the state can be written in a unique form. This leads to a canonical form which generalizes the two-quantum-bit Schmidt decomposition. It is uniquely characterized by the five entanglement parameters. It leads to a complete classification of the three-quantum-bit states. It shows that the right outcome of an adequate local measurement always erases all entanglement between the other two parties.

Prediction of crude protein and classification of the growth stage of wheat plant samples from NIR spectra

Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based on these differences, a classification procedure (SIMCA) showed a very accurate classification of the validation set samples : all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content of these samples was considered in two ways: building up a global model for all the growth stages, and building up local models for each stage, separately. The best prediction results for crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local model for the harvest stage samples.

Feature Selection, Ranking of Each Feature and Classification for the Diagnosis of Community Acquired Legionella Pneumonia

Diagnosis of community acquired legionella pneumonia (CALP) is currently performed by means of laboratory techniques which may delay diagnosis several hours. To determine whether ANN can categorize CALP and non-legionella community-acquired pneumonia (NLCAP) and be standard for use by clinicians, we prospectively studied 203 patients with community-acquired pneumonia (CAP) diagnosed by laboratory tests. Twenty one clinical and analytical variables were recorded to train a neural net with two classes (LCAP or NLCAP class). In this paper we deal with the problem of diagnosis, feature selection, and ranking of the features as a function of their classification importance, and the design of a classifier the criteria of maximizing the ROC (Receiving operating characteristics) area, which gives a good trade-off between true positives and false negatives. In order to guarantee the validity of the statistics; the train-validation-test databases were rotated by the jackknife technique, and a multistarting procedure was done in order to make the system insensitive to local maxima.

Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

Estimation of parametric and nonparametric models for univariate claim severity distributions - an approach using R

This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described

Evaluation of subsidies programs to sell green cars: Impact on prices, quantities and efficiency

During the recent period of economic crisis, many countries have introduced scrappage schemes to boost the sale and production of vehicles, particularly of vehicles designed to pollute less. In this paper, we analyze the impact of a particular scheme in Spain (Plan2000E) on vehicle prices and sales figures as well as on the reduction of polluting emissions from vehicles on the road. We considered the introduction of this scheme an exogenous policy change and because we could distinguish a control group (non-subsidized vehicles) and a treatment group (subsidized vehicles), before and after the introduction of the Plan, we were able to carry out our analysis as a quasi-natural experiment. Our study reveals that manufacturers increased vehicle prices by the same amount they were granted through the Plan (1,000 €). In terms of sales, econometric estimations revealed an increase of almost 5% as a result of the implementation of the Plan. With regard to environmental efficiency, we compared the costs (inverted quantity of money) and the benefits of the program (reductions in polluting emissions and additional fiscal revenues) and found that the Plan would only be beneficial if it boosted demand by at least 30%.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

A distributed environment for virtual and/or real experiments for underwater robots

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments

Nitric oxide synthase (NOS) inhibition for one week improves renal sodium and water excretion in cirrhotic rats with ascites

Normalization of the increased vascular nitric oxide (NO) generation with low doses of NG-nitro-L-arginine methyl ester (L-NAME) corrects the hemodynamic abnormalities of cirrhotic rats with ascites. We have undertaken this study to investigate the effect of the normalization of vascular NO production, as estimated by aortic cyclic guanosine monophosphate (cGMP) concentration and endothelial nitric oxide synthase (eNOS) protein expression in the aorta and mesenteric artery, on sodium and water excretion. Rats with carbon tetrachloride-induced cirrhosis and ascites were investigated using balance studies. The cirrhotic rats were separated into two groups, one receiving 0.5 mg/kg per day of L-NAME (CIR-NAME) during 7 d, whereas the other group (CIR) was administrated the same volume of vehicle. Two other groups of rats were used as controls, one group treated with L-NAME and another group receiving the same volume of vehicle. Sodium and water excretion was measured on days 0 and 7. On day 8, blood samples were collected for electrolyte and hormone measurements, and aorta and mesenteric arteries were harvested for cGMP determination and nitric oxide synthase (NOS) immunoblotting. Aortic cGMP and eNOS protein expression in the aorta and mesenteric artery were increased in CIR as compared with CIR-NAME. Both cirrhotic groups had a similar decrease in sodium excretion on day 0 (0.7 versus 0.6 mmol per day, NS) and a positive sodium balance (+0.9 versus +1.2 mmol per day, NS). On day 7, CIR-NAME rats had an increase in sodium excretion as compared with the CIR rats (sodium excretion: 2.4 versus 0.7 mmol per day, P < 0.001) and a negative sodium balance (-0.5 versus +0.8 mmol per day, P < 0.001). The excretion of a water load was also increased after L-NAME administration (from 28+/-5% to 65+/-7, P < 0.05). Plasma renin activity, aldosterone and arginine vasopressin were also significantly decreased in the CIR-NAME, as compared with the CIR rats. The results thus indicate that normalization of aortic cGMP and eNOS protein expression in vascular tissue is associated with increased sodium and water excretion in cirrhotic rats with ascites.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

A reappraisal of 'International Stratigraphic Lexicon' and the need for the creation named units critical catalogues

Analysis of stratigraphic terminology and classification, shows that time-related stratigraphic units, which by definition have a global extent, are the concern of international cornrnissions and committees of the intemational Union of Geological Sciences (IUGS) . In contrast, lithostratigraphic, and other closely related units, are regional in extent and are catalogued in the International Stratigraphic Lexicon (ISL), the last volume of which, was published in 1987. Tlie intemational Commission on Stratigraphy (ICS) is currently attempting to revitalize the publication of ISL, given that the information contained in published volumes has never been updated, and that there has been a significant increase in stratigraphic research in recent decades. The proliferation of named units in the South Pyrenean and Ebro Basin Paleogene is evaluated to illustrate the extent of the problem. Moreover, new approaches to stratigraphic analysis have led to the naming of genetic units according to similar guidelines followed in the naming of descnptive or lithostratigraphic units. This has led to considerable confusion. The proposal to revitalize the ISL is accepted as part of the solution, that should also include the publication of critica1 catalogues, and the creation of norms for genetic unit terminology.

Eines interactives per l'aprenentatge de la dinàmica i el control dels convertidors de potència

El projecte s'ha centrat en el disseny i desenvolupament de laboratoris virtuals per a la docència del dispositius i mètodes de gestió d’energia. Això s’ha realitzat a dos nivells clarament diferenciats, el primer grup de laboratoris correspon als convertidors electrònics de potencia i el segon grup de laboratoris correspon a un conjunt de casos d’aplicacions concretes. En el primer grup es descriu el detall del funcionament dels diferents elements mentre que en el segon els descriuen les idees i conceptes bàsics de funcionament. Els laboratoris virtuals de convertidors electrònics de potència inclouen el convertidor elevador (boost), el convertidor reductor (buck), i convertidors acobladors magnèticament. Aquestes permeten estudiar el comportament dinàmica des d’un punt de vista commutat o bé promitjat, les aplicacions incorporen també la possibilitat de sintonitzar els controladors. Aquestes aplicacions han estat desenvolupades per ser un complement per les sessions de pràctiques presencials. Els laboratoris virtuals d’aplicacions, inclouen els sistema de transport metropolità, el vehicle híbrid i els sistemes de gestió de talls transitoris en el subministrament d’energia principalment. Aquestes laboratoris permeten introduir els estudiants de forma qualitativa en els diferents conceptes i tècniques emprades en els sistemes de generació, transport i transformació d’energia. Totes les aplicacions han estat desenvolupades emprant Easy JAVA Simulations, aquesta eina permet desenvolupar laboratoris multiplataforma fàcilment distribuïbles a través d’internet.