Modèle d'état à coefficient aléatoire: filtrage par densités approchées

Le filtrage de Bucy-Kalman s'applique au modèle d'état comprenant des équations linéaires bruitées, décrivant l'évolution de l'état et des équations linéaires bruitées d'observation . Ce filtrage consiste dans le cas gaussien, à calculer de façon récursive, la loi de probabilité, a posteriori, de l'état, au vu de l' observation actuelle et des observations passées . Le filtrage par densités approchées permet de traiter des équations d'état, non linéaires ou à bruits non Gaussiens. Pour un coefficient de rappel aléatoire, cas typique d'une situation de changements de modèles, l'article introduit une famille de lois de probabilité, paramétrées, bimodales servant, par ajustement des paramètres, à approcher les lois a posteriori de l'état aux divers instants . Les paramètres sont recalculés récursivement, lors des mises à jour et des prédictions.

ON THE MINIMUM ABSOLUTE VALUE of THE DISCRIMINANT of ABELIAN FIELDS of DEGREE p(2)

Let p be a prime number. A formula for the minimum absolute value of the discriminant of all Abelian extensions of Q of degree p(2) is given in terms of p.

Identification of species of the Euterpe genus by rare earth elements using inductively coupled plasma mass spectrometry and linear discriminant analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Discriminant analysis of neuromuscular variables in chronic low back pain

Background: Investigation and discrimination of neuromuscular variables related to the complex aetiology of low back pain could contribute to clarifying the factors associated with symptoms. Objective: Analysing the discriminative power of neuromuscular variables in low back pain. Methods: This study compared muscle endurance, proprioception and isometric trunk assessments between women with low back pain (LBP, n=14) and a control group (CG, n=14). Multivariate analysis of variance and discriminant analysis of the data were performed. Results: The muscle endurance time (s) was shorter in the LBP group than in the CG (p=0.004) with values of 85.81 (37.79) and 134.25 (43.88), respectively. The peak torque (Nm/kg) for trunk extension was 2.48 (0.69) in the LBP group and 3.56 (0.88) in the GG (p=0.001); for trunk flexion, the mean torque was 1.49 (0.40) in the LBP group and 1.85 (0.39) in the CG (p=0.023). The repositioning error (degrees) before the endurance test was 2.66 (1.36) in the LBP group and 2.41 (1.46) in the CG (p=0.664), and after the endurance test, it was 2.95 (1.94) in the LBP group and 2.00 (1.16) in the CG (p=0.06). Furthermore, the variables showed discrimination between the groups (p=0.007), with 78.6% of the individuals with low back pain correctly classified in the LBP group. In turn, variables related to muscle activation showed no difference in discrimination between the groups (p=0.369). Conclusion: Based on these findings, the clinical management of low back pain should consist of both resistance and strength training, particularly in the extensor muscles.

Discrimination of production environments of specialty coffees by means of stable isotopes and discriminant model

The south of Minas Gerais, Brazil stands out among various regions through its capacity for production of specialty coffees. Its potential, manifested through being one of the most award-winning Brazilian regions in recent years, has been recognized by the Cup of Excellence (COE). With the evident relationship between product quality and the environment in mind, the need arises for scientific studies to provide a foundation for discrimination of product origin, creating new methods for combating possible fraud. The aim of this study was to evaluate the use of carbon and nitrogen isotopes in discrimination of production environments of specialty coffees from the Serra da Mantiqueira of Minas Gerais by means of the discriminant model. Coffee samples were composed of ripe yellow and red fruits collected manually at altitudes below 1,000 m, from 1,000 to 1,200 m and above 1,200 m. The yellow and red fruits were subjected to dry processing and wet processing, with five replications. A total of 119 samples were used for discrimination of specialty coffee production environments by means of stable isotopes and statistical modeling. The model generated had an accuracy rate of 89% in discrimination of environments and was composed of the isotope variables of δ15N, δ13C, %C, %N, δD, δ18O (meteoric water) and sensory analysis scores. In addition, for the first time, discrimination of environments on a local geographic scale, within a single municipality, was proposed and successfully concluded. This shows that isotope analysis is an effective method in verifying geographic origin for specialty coffees.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Approccio network-based alla discriminant analysis mediante HPC per la ricerca di signature ottimali in dati ad alta dimensionalità

Il presente lavoro di tesi si inserisce nell’ambito della classificazione di dati ad alta dimensionalità, sviluppando un algoritmo basato sul metodo della Discriminant Analysis. Esso classifica i campioni attraverso le variabili prese a coppie formando un network a partire da quelle che hanno una performance sufficientemente elevata. Successivamente, l’algoritmo si avvale di proprietà topologiche dei network (in particolare la ricerca di subnetwork e misure di centralità di singoli nodi) per ottenere varie signature (sottoinsiemi delle variabili iniziali) con performance ottimali di classificazione e caratterizzate da una bassa dimensionalità (dell’ordine di 101, inferiore di almeno un fattore 103 rispetto alle variabili di partenza nei problemi trattati). Per fare ciò, l’algoritmo comprende una parte di definizione del network e un’altra di selezione e riduzione della signature, calcolando ad ogni passaggio la nuova capacità di classificazione operando test di cross-validazione (k-fold o leave- one-out). Considerato l’alto numero di variabili coinvolte nei problemi trattati – dell’ordine di 104 – l’algoritmo è stato necessariamente implementato su High-Performance Computer, con lo sviluppo in parallelo delle parti più onerose del codice C++, nella fattispecie il calcolo vero e proprio del di- scriminante e il sorting finale dei risultati. L’applicazione qui studiata è a dati high-throughput in ambito genetico, riguardanti l’espressione genica a livello cellulare, settore in cui i database frequentemente sono costituiti da un numero elevato di variabili (104 −105) a fronte di un basso numero di campioni (101 −102). In campo medico-clinico, la determinazione di signature a bassa dimensionalità per la discriminazione e classificazione di campioni (e.g. sano/malato, responder/not-responder, ecc.) è un problema di fondamentale importanza, ad esempio per la messa a punto di strategie terapeutiche personalizzate per specifici sottogruppi di pazienti attraverso la realizzazione di kit diagnostici per l’analisi di profili di espressione applicabili su larga scala. L’analisi effettuata in questa tesi su vari tipi di dati reali mostra che il metodo proposto, anche in confronto ad altri metodi esistenti basati o me- no sull’approccio a network, fornisce performance ottime, tenendo conto del fatto che il metodo produce signature con elevate performance di classifica- zione e contemporaneamente mantenendo molto ridotto il numero di variabili utilizzate per questo scopo.

Psychothérapie de la dépression chronique : l’apport du modèle CBASP selon McCullough

Les dépressions chroniques sont fréquentes et souvent traitées par des approches traditionnelles. Cet article vise à présenter la nature spécifique de la psychopathologie et un traitement spécifiquement adapté à ces patients avec dépression chronique. Nous décrirons d’abord les spécificités psychopathologiques de cette population, en nous référant aux travaux de J. Piaget et de D. Kiesler. À partir de ces théories, nous mettrons en avant le modèle Cognitive Behavioral Analysis System of Psychotherapy (CBASP), selon McCullough. Cet auteur propose deux volets d’interventions spécifiquement adaptées aux patients avec dépression chronique : l’analyse situationnelle et les techniques interpersonnelles basées sur la notion de transfert et de contre-transfert. Nous soulignerons la pertinence de cette approche par le résumé de plusieurs études empiriques ayant établi l’efficacité de ce modèle, sous certaines conditions cliniques. Nous terminerons par une réflexion de l’application de ce modèle au-delà du tableau clinique de la dépression chronique en ajoutant ainsi des arguments supplémentaires en faveur de l’apport du modèle CBASP au champ actuel de la psychothérapie des troubles mentaux.

De la presse comme modèle de l’œuvre à la presse dans l’œuvre – et à l’œuvre comme modèle de la presse

De Mallarmé à la fin du xxe siècle, les œuvres d’avant-garde se situent dans un rapport tensionnel et dialectique à la presse. Jusqu’au surréalisme, la littérature emprunte son modèle à la presse, mais en n’en sélectionnant que certaines caractéristiques, et sans oublier la logique du Livre mallarméen : est ainsi visée une synthèse du livre et du journal, dont Le surréalisme au service de la Révolution constitue l’exemple le plus achevé. Si les œuvres d’assemblage de textes de la deuxième moitié du xxe siècle découlent plutôt du collage, elles intègrent des coupures de presse et permettent non seulement de la critiquer, mais surtout de proposer une « pluritextualité » qui fonctionne autrement que les journaux, et qui pourrait être le modèle d’une presse utopique qui demanderait au lecteur non seulement de s’informer, mais surtout de mettre en relation et en perspective les différentes informations qui lui sont proposées.

Un modèle animal simple pour l'apprentissage des techniques de microanastomoses vasculaires de congruences diefférentes

BACKGROUND Since the pioneering work of Jacobson and Suarez, microsurgery has steadily progressed and is now used in all surgical specialities, particularly in plastic surgery. Before performing clinical procedures it is necessary to learn the basic techniques in the laboratory. OBJECTIVE To assess an animal model, thereby circumventing the following issues: ethical rules, cost, anesthesia and training time. METHODS Between July 2012 and September 2012, 182 earthworms were used for 150 microsurgical trainings to simulate discrepancy microanastomoses. Training was undertaken over 10 weekly periods. Each training session included 15 simulations of microanastomoses performed using the Harashina technique (earthworm diameters >1.5 mm [n=5], between 1.0 mm and 1.5 mm [n=5], and <1.0 mm [n=5]). The technique is presented and documented. A linear model with main variable as the number of the week (as a numeric covariate) and the size of the animal (as a factor) was used to determine the trend in time of anastomosis over subsequent weeks as well as differences between the different size groups. RESULTS The linear model showed a significant trend (P<0.001) in time of anastomosis in the course of the training, as well as significant differences (P<0.001) between the groups of animal of different sizes. For diameter >1.5 mm, mean anastomosis time decreased from 19.6±1.9 min to 12.6±0.7 min between the first and last week of training. For training involving smaller diameters, the results showed a reduction in execution time of 36.1% (P<0.01) (diameter between 1.0 mm and 1.5 mm) and 40.6% (P<0.01) (diameter <1.0 mm) between the first and last weeks. The study demonstrates an improvement in the dexterity and speed of nodes' execution. CONCLUSION The earthworm appears to be a reliable experimental model for microsurgical training of discrepancy microanastomoses. Its numerous advantages, as discussed in the present report, show that this model of training will significantly grow and develop in the near future.