Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SARerr model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SARerr model, which led to a trend SARerr model. Overall, BT spread from north-eastern to south-western France. The average trend SARerr-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SARerr-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SARerr models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases

Sex-Specific Linkages Between Taxonomic and Functional Profiles of Tick Gut Microbiomes

Ticks transmit the most diverse array of disease agents and harbor one of the most diverse microbial communities. Major progress has been made in the characterization of the taxonomic profiles of tick microbiota. However, the functional profiles of tick microbiome have been comparatively less studied. In this proof of concept we used state-of-the-art functional metagenomics analytical tools to explore previously reported datasets of bacteria found in male and female Ixodes ovatus, Ixodes persulcatus, and Amblyomma variegatum. Results showed that both taxonomic and functional profiles have differences between sexes of the same species. KEGG pathway analysis revealed that male and female of the same species had major differences in the abundance of genes involved in different metabolic pathways including vitamin B, amino acids, carbohydrates, nucleotides, and antibiotics among others. Partial reconstruction of metabolic pathways using KEGG enzymes suggests that tick microbiome form a complex metabolic network that may increase microbial community resilience and adaptability. Linkage analysis between taxonomic and functional profiles showed that among the KEGG enzymes with differential abundance in male and female ticks only 12% were present in single bacterial genera. The rest of these enzymes were found in more than two bacterial genera, and 27% of them were found in five up to ten bacterial genera. Comparison of bacterial genera contributing to the differences in the taxonomic and functional profiles of males and females revealed that while a small group of bacteria has a dual-role, most of the bacteria contribute only to functional or taxonomic differentiation between sexes. Results suggest that the different life styles of male and female ticks exert sex-specific evolutionary pressures that act independently on the phenomes (set of phenotypes) and genomes of bacteria in tick gut microbiota. We conclude that functional redundancy is a fundamental property of male and female tick microbiota and propose that functional metagenomics should be combined with taxonomic profiling of microbiota because both analyses are complementary

Approche variationnelle pour la cartographie spatio-temporelle du risque en épidémiologie à l'aide de champs de Markov cachés

Session : biostatistiques 2 : épidémiologie National audienceL'analyse spatio-temporelle d'une épidémie permet aux épidémiologistes de comprendre son étiologie et fournit des suggestions pour planifier de nouvelles études pour examiner les causes sous-jacentes. Cette analyse donne lieu à une estimation du risque épidémiologique dans différentes unités géographiques et produit ainsi des cartes de risque permettant la détection de différences de niveau de risque à différents pas de temps. Nous proposons d'adapter une méthode par champs de Markov cachés discrets (issue de l'analyse d'images) dans le cadre spatial, pour permettre une classification intrinsèque des risques en vue du tracé des cartes de niveaux de risque te de l'étendre par la suite à un contexte spatio-temporel. Afin d'estimer les paramètres du modèle et de définir les classes,l'algorithme EM-champ moyen est utilisé

The Circadian Clock Gene BMAL1 Coordinates Intestinal Regeneration

Background & Aims The gastrointestinal syndrome is an illness of the intestine caused by high levels of radiation. It is characterized by extensive loss of epithelial tissue integrity, which initiates a regenerative response by intestinal stem and precursor cells. The intestine has 24-hour rhythms in many physiological functions that are believed to be outputs of the circadian clock: a molecular system that produces 24-hour rhythms in transcription/translation. Certain gastrointestinal illnesses are worsened when the circadian rhythms are disrupted, but the role of the circadian clock in gastrointestinal regeneration has not been studied. Methods: We tested the timing of regeneration in the mouse intestine during the gastrointestinal syndrome. The role of the circadian clock was tested genetically using the BMAL1 loss of function mouse mutant in vivo, and in vitro using intestinal organoid culture. Results: The proliferation of the intestinal epithelium follows a 24-hour rhythm during the gastrointestinal syndrome. The circadian clock runs in the intestinal epithelium during this pathologic state, and the loss of the core clock gene, BMAL1, disrupts both the circadian clock and rhythmic proliferation. Circadian activity in the intestine involves a rhythmic production of inflammatory cytokines and subsequent rhythmic activation of the JNK stress response pathway. Conclusions: Our results show that a circadian rhythm in inflammation and regeneration occurs during the gastrointestinal syndrome. The study and treatment of radiation-induced illnesses, and other gastrointestinal illnesses, should consider 24-hour timing in physiology and pathology

Spatial risk mapping for rare disease with hidden Markov fields and variational EM

We recast the disease mapping issue of automatically classifying geographical units into risk classes as a clustering task using a discrete hidden Markov model and Poisson class-dependent distributions. The designed hidden Markov prior is non standard and consists of a variation of the Potts model where the interaction parameter can depend on the risk classes. The model parameters are estimated using an EM algorithm and the mean field approximation. This provides a way to face the intractability of the standard EM in this spatial context, with a computationally efficient alternative to more intensive simulation based Monte Carlo Markov Chain (MCMC) procedures. We then focus on the issue of dealing with very low risk values and small numbers of observed cases and population sizes. We address the problem of finding good initial parameter values in this context and develop a new initialization strategy appropriate for spatial Poisson mixtures in the case of not so well separated classes as encountered in animal disease risk analysis. Using both simulated and real data, we compare this strategy to other standard strategies and show that it performs well in a lot of situations.Nous abordons la cartographie automatique d' unités géographiques en classes de risque comme un problème de clustering à l'aide de modèles de Markov cachés discrets et de modèles de mélange de Poisson. Le modèle de Markov caché proposé est une variante du modèle de Potts, où le paramètre d'interaction dépend des classes de risque. Afin d'estimer les paramètres du modèle, nous utilisons l'algorithme EM combiné à une approche variationnelle champ-moyen. Cette approche nous permet d'appliquer l'algorithme EM dans un cadre spatial et présente une alternative efficace aux méthodes d'estimation basées sur des simulations intensives de type Markov chain Monte Carlo (MCMC). Nous abordons également les problèmes d'initialisation, spécialement quand les taux de risque sont petits (cas des maladies animales). Nous proposons une nouvelle stratégie d'initialisation appropriée aux modèles de mélange de Poisson quand les classes sont mal séparées. Pour illustrer notre méthodologie, nous présentons des résultats d'application sur des données épidémiologiques réelles et simulées et montrons la performance de la stratégie d'initialisation présentée en comparaison à celles utilisées usuellement

Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model

Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the “second wave” of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained

Evaluation using latent class models of the diagnostic performances of three ELISA tests commercialized for the serological diagnosis of <i>Coxiella burnetii</i> infection in domestic ruminants

International audienceELISA methods are the diagnostic tools recommended for the serological diagnosis of Coxiella burnetii infection in ruminants but their respective diagnostic performances are difficult to assess because of the absence of a gold standard. This study focused on three commercial ELISA tests with the following objectives (1) assess their sensitivity and specificity in sheep, goats and cattle, (2) assess the between-and within-herd seroprevalence distribution in these species, accounting for diagnostic errors, and (3) estimate optimal sample sizes considering sensitivity and specificity at herd level. We comparatively tested 1413 cattle, 1474 goat and 1432 sheep serum samples collected in France. We analyzed the cross-classified test results with a hierarchical zero-inflated beta-binomial latent class model considering each herd as a population and conditional dependence as a fixed effect. Potential biases and coverage probabilities of the model were assessed by simulation. Conditional dependence for truly seropositive animals was high in all species for two of the three ELISA methods. Specificity estimates were high, ranging from 94.8% [92.1; 97.8] to 99.2% [98.5; 99.7], whereas sensitivity estimates were generally low, ranging from 39.3 [30.7; 47.0] to 90.5% [83.3; 93.8]. Betweenand within-herd seroprevalence estimates varied greatly among geographic areas and herds. Overall, goats showed higher within-herd seroprevalence levels than sheep and cattle. The optimal sample size maximizing both herd sensitivity and herd specificity varied from 3 to at least 20 animals depending on the test and ruminant species. This study provides better interpretation of three widely used commercial ELISA tests and will make it possible to optimize their implementation in future studies. The methodology developed may likewise be applied to other human or animal diseases