Cahiers du bolchévisme : organe théorique du Parti communiste français (S.F.I.C.)

1932/12/15 (A7,N24).

La Calotte

1911/12/15 (A6,N275).

Le Capitaliste : journal de la banque parisienne

1910/12/15 (A33,N50).

Le Capitaliste : journal de la banque parisienne

1904/12/15 (A27,N50).

Le Capitaliste : journal de la banque parisienne

1880/12/15 (A3,N50).

Le Capitaliste : journal de la banque parisienne

1886/12/15 (A9,N50).

Les Chantiers de l'Exposition universelle de 1889 : revue bi-mensuelle du commerce et des industries se rattachant à l'Exposition

1887/12/15 (A1,N17).

Convergència mediàtica digital: el consum de continguts i l'ús de nous mitjans per dones a Catalunya

Des de fa 20 anys, el sector audiovisual viu una important transformació, tant de l’oferta com del consum, en el marc de la convergència digital. La convergència anuncia la coexistència dels nous mitjans digitals amb l’apogeu d’una cultura participativa, protagonitzada per comunitats d’usuaris amb una activitat quasi frenètica (Jenkins,2008). Noves modalitats de treball cooperatiu que permeten la creació i recreació grupal de continguts, i la creació de comunitats d’usuaris que utilitzen i reutilitzen les noves modalitats de serveis. En aquest context, augmenta la segmentació, la fragmentació i l’abonament dels usuaris (Tous, 2009), perquè la tipologia de les plataformes de continguts ha variat de manera significativa, s’han incorporat els dispositius mòbils i s’han diversificat i sofisticat les ofertes a Internet.

Cinéa

1926/12/15 (N75).

Cinéa

1929/12/15 (N146).

Cinéa

1924/12/15 (N27).

Cinéa

1927/12/01 (N98)-1927/12/15 (N99).

Cinéa

1923/12/15 (N3).

Characterizing Propionibacterium freudenreichii ssp. shermanii JS and Lactobacillus rhamnosus LC705 as a new probiotic combination: basic properties of JS and pilot in vivo assessment of the combination

Characterizing Propionibacterium freudenreichii ssp. shermanii JS and Lactobacillus rhamnosus LC705 as a new probiotic combination: basic properties of JS and pilot in vivo assessment of the combination Each candidate probiotic strain has to have the documentation for the proper identification with current molecular tools, for the biological properties, for the safety aspects and for the health benefits in human trials if the intention is to apply the strain as health promoting culture in the commercial applications. No generalization based on species properties of an existing probiotic are valid for any novel strain, as strain specific differences appear e.g. in the resistance to GI tract conditions and in health promoting benefits (Madsen, 2006). The strain evaluation based on individual strain specific probiotic characteristics is therefore the first key action for the selection of the new probiotic candidate. The ultimate goal in the selection of the probiotic strain is to provide adequate amounts of active, living cells for the application and to guarantee that the cells are physiologically strong enough to survive and be biologically active in the adverse environmental conditions in the product and in GI tract of the host. The in vivo intervention studies are expensive and time consuming; therefore it is not rational to test all the possible candidates in vivo. Thus, the proper in vitro studies are helping to eliminate strains which are unlikely to perform well in vivo. The aims of this study were to characterize the strains of Propionibacterium freudenreichii ssp. shermanii JS and Lactobacillus rhamnosus LC705, both used for decades as cheese starter cultures, for their technological and possible probiotic functionality applied in a combined culture. The in vitro studies of Propionibacterium freudenreichii ssp. shermanii JS focused on the monitoring of the viability rates during the acid and bile treatments and on the safety aspects such as antibiotic susceptibility and adhesion. The studies with the combination of the strains JS and LC705 administered in fruit juices monitored the survival of the strains JS and LC705 during the GI transit and their effect on gut wellbeing properties measured as relief of constipation. In addition, safety parameters such as side effects and some peripheral immune parameters were assessed. Separately, the combination of P. freudenreichii ssp. shermanii JS and Lactobacillus rhamnosus LC705 was evaluated from the technological point of view as a bioprotective culture in fermented foods and wheat bread applications. In this study, the role ofP. freudenreichii ssp. shermanii JS as a candidate probiotic culture alone and in a combination with L. rhamnosus LC705 was demonstrated. Both strains were transiently recovered in high numbers in fecal samples of healthy adults during the consumption period. The good survival through the GI transit was proven for both strains with a recovery rate from 70 to 80% for the JS strain and from 40 to 60% for the LC705 strain from the daily dose of 10 log10 CFU. The good survival was shown from the consumption of fruit juices which do not provide similar matrix protection for the cells as milk based products. The strain JS did not pose

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.