Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps

In many real world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable sensible comparison between observations. Kohonen's Self-Organizing Map (SOM) has been adapted to data described only through their dissimilarity matrix. This algorithm provides both non linear projection and clustering of non vector data. Unfortunately, the algorithm suffers from a high cost that makes it quite difficult to use with voluminous data sets. In this paper, we propose a new algorithm that provides an important reduction of the theoretical cost of the dissimilarity SOM without changing its outcome (the results are exactly the same as the ones obtained with the original algorithm). Moreover, we introduce implementation methods that result in very short running times. Improvements deduced from the theoretical cost model are validated on simulated and real world data (a word list clustering problem). We also demonstrate that the proposed implementation methods reduce by a factor up to 3 the running time of the fast algorithm over a standard implementation

Self-organizing maps and symbolic data

International audienceIn data analysis new forms of complex data have to be considered like for example (symbolic data, functional data, web data, trees, SQL query and multimedia data, ...). In this context classical data analysis for knowledge discovery based on calculating the center of gravity can not be used because input are not $\mathbb{R}^p$ vectors. In this paper, we present an application on real world symbolic data using the self-organizing map. To this end, we propose an extension of the self-organizing map that can handle symbolic data

Une adaptation des cartes auto-organisatrices pour des données décrites par un tableau de dissimilarités

National audienceMany data analysis methods cannot be applied to data that are not represented by a fixed number of real values, whereas most of real world observations are not readily available in such a format. Vector based data analysis methods have therefore to be adapted in order to be used with non standard complex data. A flexible and general solution for this adaptation is to use a (dis)similarity measure. Indeed, thanks to expert knowledge on the studied data, it is generally possible to define a measure that can be used to make pairwise comparison between observations. General data analysis methods are then obtained by adapting existing methods to (dis)similarity matrices. In this article, we propose an adaptation of Kohonen's Self Organizing Map (SOM) to (dis)similarity data. The proposed algorithm is an adapted version of the vector based batch SOM. The method is validated on real world data: we provide an analysis of the usage patterns of the web site of the Institut National de Recherche en Informatique et Automatique, constructed thanks to web log mining method

Cholesteatome Congenital De L’oreille Moyenne A Propos De Deux Cas

But :Le cholesteatome congenital de l’oreille moyenne est une entite rare. L’objectif de ce travail est de discuter les particularites cliniques et therapeutiques de cette pathologie a travers deux observations de malades presentant un cholesteatome congenital operes et suivis au service d’ORL et de chirurgie cervico-faciale Fattouma Bourguiba Monastir, entre 2002 et 2008. Résultats : Il s’agissait de deux garcons, ages de 5 et 7 ans. La symptomatologie etait dominee par l’apparition d’une hypoacousie et l’examen otologique a revele un tympan complet dans les deux cas. La TDM des rochers a permis d’evoquer le diagnostic du cholesteatome congenital et d’apprecier les extensions locales des lesions. Les deux malades ont eu une tympanoplastie en technique fermee. Conclusion : L’evolution du cholesteatome congenital est insidieuse et le diagnostic est souvent tardif. Le traitement est chirurgical, domine par la tympanoplastie en technique fermee. Mots clès : Chlolesteatome congenital, hypoacousie, tympan complet, tympanoplastie en technique fermee, technique ouverte

T-2 Toxin-induced Toxicity in Pregnant Mice and Rats

T-2 toxin is a cytotoxic secondary fungal metabolite that belongs to the trichothecene mycotoxin family. This mycotoxin is a well known inhibitor of protein synthesis through its high binding affinity to peptidyl transferase, which is an integral part of the ribosomal 60s subunit, and it also inhibits the synthesis of DNA and RNA, probably secondary to the inhibition of protein synthesis. In addition, T-2 toxin is said to induce apoptosis in many types of cells bearing high proliferating activity. T-2 toxin readily passes the placenta and is distributed to embryo/fetal tissues, which include many component cells bearing high proliferating activity. This paper reviews the reported data related to T-2 toxin-induced maternal and fetal toxicities in pregnant mice and rats. The mechanisms of T-2 toxin-induced apoptosis in maternal and fetal tissues are also discussed in this paper

Toksikološka svojstva citrinina

Citrinin (CTN) is a nephrotoxic mycotoxin produced by several fungal strains belonging to the genera Penicillium, Aspergillus, and Monascus. It contaminates various commodities of plant origin, cereals in particular, and is usually found together with another nephrotoxic mycotoxin, ochratoxin A (OTA). These two mycotoxins are believed to be involved in the aetiology of endemic nephropathy. In addition to nephrotoxicity, CTN is also embryocidal and fetotoxic. The genotoxic properties of CTN have been demonstrated with the micronuleus test (MN), but not with single-cell gel electrophoresis. The mechanism of CTN toxicity is not fully understood, especially not whether CTN toxicity and genotoxicity are the consequence of oxidative stress or of increased permeability of mitochondrial membranes. CTN requires complex cellular biotransformation to exert mutagenicity. Compared with other mycotoxins, CTN contamination of food and feed is rather scarce. However, it is reasonable to believe that humans are much more frequently exposed to CTN than generally accepted, because it is produced by the same moulds as OTA, which is a common contaminant of human food all over the world. At present, there are no specifi c regulations either in Croatia or in the European Union concerning CTN in any kind of commodity.Citrinin (CTN) nefrotoksičan je mikotoksin koji proizvode različiti sojevi plijesni iz rodova Penicillium, Aspergillus i Monascus. CTN se može naći u različitim namirnicama biljnog podrijetla, osobito u žitaricama i obično se nalazi zajedno s drugim nefrotoksičnim mikotoksinom, okratoksinom A (OTA). Pretpostavlja se da je izloženost ovim mikotoksinima povezana s nastankom endemske nefropatije. Osim što je nefrotoksičan, CTN je još i embricidan i fetotoksičan. Na genotoksičnost citrinina upućuje pozitivan mikronukleusni test na različitim vrstama staničnih kultura, iako je kometski test negativan. Mutagenost CTN-a očituje se na različitim vrstama stanica samo ako se pridodaju stanični aktivatori kao npr. S9-mix. Mehanizam toksičnosti CTN-a nije potpuno razjašnjen pa još uvijek traje znanstvena rasprava je li njegova toksičnost i genotoksičnost posljedica oksidacijskog stresa ili povećane permeabilnosti mitohondrijskih membrana. U dostupnoj literaturi podaci o kontaminiranosti hrane i krmiva ovim mikotoksinom mnogo su rjeđi od onih za druge mikotoksine. Može se pretpostaviti da su ljudi često izloženi ovom mikotoksinu zato što ga proizvode iste plijesni koje proizvode i OTA, a one kontaminiraju hranu po cijelom svijetu. U Hrvatskoj i u zemljama Europske Unije ne postoje zakonske odredbe o dopuštenim granicama CTN-a u bilo kojoj vrsti hrane