Description of three new arctic bramble cultivars and proposal for cultivar identification

Selostus: Kolmen uuden mesimarjalajikkeen kuvaukset ja lajikekuvausohjeet mesimarjalle ja jalomaaraimelle

Molecular epidemiology of methicillin-resistant Staphylococcus aureus in Switzerland: sampling only invasive isolates does not allow a representative description of the local diversity of clones.

We conducted a molecular study of MRSA isolated in Swiss hospitals, including the first five consecutive isolates recovered from blood cultures and the first ten isolates recovered from other sites in newly identified carriers. Among 73 MRSA isolates, 44 different double locus sequence typing (DLST) types and 32 spa types were observed. Most isolates belonged to the NewYork/Japan, the UK-EMRSA-15, the South German and the Berlin clones. In a country with a low to moderate MRSA incidence, inclusion of non-invasive isolates allowed a more accurate description of the diversity.

Statistical description of rotating Kaluza-Klein black holes

We extend the recent microscopic analysis of extremal dyonic Kaluza-Klein (D0-D6) black holes to cover the regime of fast rotation in addition to slow rotation. Fastly rotating black holes, in contrast to slow ones, have nonzero angular velocity and possess ergospheres, so they are more similar to the Kerr black hole. The D-brane model reproduces their entropy exactly, but the mass gets renormalized from weak to strong coupling, in agreement with recent macroscopic analyses of rotating attractors. We discuss how the existence of the ergosphere and superradiance manifest themselves within the microscopic model. In addition, we show in full generality how Myers-Perry black holes are obtained as a limit of Kaluza-Klein black holes, and discuss the slow and fast rotation regimes and superradiance in this context.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

Towards and ab initio description of magnetism in ionic solids

The physical contributions to the KNiF3 magnetic exchange coupling integral have been obtained from specially designed ab initio cluster model calculations. Three important mechanisms have been identified. These are the delocalization of the magnetic orbitals into the anion p band, the variational contribution of the second-order interactions, and the many-body terms hidden in the two-body operator and the Heisenberg Hamiltonian.

A Qualitative Exploration of the Psychological Contents and Dynamics of Momentum in Sport

While studies on triggers and outcomes of Psychological Momentum (PM) exist, little is known about the dynamics by which PM emerges and develops over time. Based on video-assisted recalls of PM experiences in table tennis and swimming competitions, this research qualitatively explored the triggering processes, contents, and the development of PM over time. PM was found to be triggered by mechanisms of dissonance, consonance, or fear of not winning. During the PM experience, participants reported a variety of perceptions, affects and emotions, cognitions, and behaviors, and PM was found to develop through processes of amplification that sometimes ended with a reduction of efforts when the victory or defeat was perceived as certain. These findings are discussed in light of theories on self-regulation and reactance-helplessness. From a practical standpoint, achievement goal-based strategies are suggested, since mastery-approach goals were found to be endorsed to maintain positive PM and overcome negative PM

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Resonating-valence-bond theory for the square-planar lattice

The short-range resonating-valence-bond (RVB) wave function with nearest-neighbor (NN) spin pairings only is investigated as a possible description for the Heisenberg model on a square-planar lattice. A type of long-range order associated to this RVB Ansatz is identified along with some qualitative consequences involving lattice distortions, excitations, and their coupling.

A review of the Tripterygion tripteronotus (Risso, 1810) complex, with a description of a new species from the Mediterranean Sea (Teleostei: Tripterygiidae)

We compared specimens of Tripterygion tripteronotus from 52 localities of the Mediterranean Sea and adjacent waters, using four gene sequences (12S rRNA, tRNA-valine, 16S rRNA and COI) and morphological characters. Two well-differentiated clades with a mean genetic divergence of 6.89±0.73% were found with molecular data, indicating the existence of two different species. These two species have disjunctive geographic distribution areas without any molecular hybrid populations. Subtle but diagnostic morphological differences were also present between the two species. T. tripteronotus is restricted to the northern Mediterranean basin, from the NE coast of Spain to Greece and Turkey, including the islands of Malta and Cyprus. T. tartessicum n. sp. is geographically distributed along the southern coast of Spain, from Cape of La Nao to the Gulf of Cadiz, the Balearic Islands and northern Africa, from Morocco to Tunisia. According to molecular data, these two species could have diverged during the Pliocene glaciations 2.7-3.6 Mya.

Qualitative analysis of barriers and facilitators encountered by HIV patients in an ART adherence programme.

Background Medication adherence is a complex, dynamic and changing behaviour that is affected by a variety of factors, including the patient's beliefs and life circumstances. Studies have highlighted barriers to medication adherence (e.g., unmanaged side effects or a lack of social support), as well as facilitators of medication adherence (e.g., technical simplicity of treatment and psychological acceptance of the disease). Since August 2004, in Lausanne (Switzerland), physicians have referred patients who are either experiencing or are at risk of experiencing problems with their HIV antiretroviral treatment (ART) to a routine interdisciplinary ART adherence programme. This programme consists of multifactorial intervention including electronic drug monitoring (MEMS(TM)). Objective This study's objective was to identify the barriers and facilitators encountered by HIV patients with suboptimal medication adherence (≤90 % adherence over the study period). Setting The community pharmacy of the Department of Ambulatory Care and Community Medicine in Lausanne (Switzerland). Method The study consisted of a retrospective, qualitative, thematic content analysis of pharmacists' notes that were taken during semi-structured interviews with patients and conducted as part of the ART adherence programme between August 2004 and May 2008. Main outcome measure Barriers and facilitators encountered by HIV patients. Results Barriers to and facilitators of adherence were identified for the 17 included patients. These factors fell into three main categories: (1) cognitive, emotional and motivational; (2) environmental, organisational and social; and (3) treatment and disease. Conclusion The pharmacists' notes revealed that diverse barriers and facilitators were discussed during medication adherence interviews. Indeed, the results showed that the 17 non-adherent patients encountered barriers and benefited from facilitators. Therefore, pharmacists should inquire about all factors, regardless of whether they have a negative or a positive impact on medication adherence, and should consider all dimensions of patient adherence. The simultaneous strengthening of facilitators and better management of barriers may allow healthcare providers to tailor care to a patient's specific needs and support each individual patient in improving his medication-related behaviour.

International periodic fever, aphthous stomatitis, pharyngitis, cervical adenitis syndrome cohort: description of distinct phenotypes in 301 patients.

OBJECTIVES: The aims of this study were to describe the clinical features of periodic fever, aphthous stomatitis, pharyngitis and cervical adenitis (PFAPA) and identify distinct phenotypes in a large cohort of patients from different countries. METHODS: We established a web-based multicentre cohort through an international collaboration within the periodic fevers working party of the Pediatric Rheumatology European Society (PReS). The inclusion criterion was a diagnosis of PFAPA given by an experienced paediatric rheumatologist participating in an international working group on periodic fever syndromes. RESULTS: Of the 301 patients included from the 15 centres, 271 had pharyngitis, 236 cervical adenitis, 171 oral aphthosis and 132 with all three clinical features. A total of 228 patients presented with additional symptoms (131 gastrointestinal symptoms, 86 arthralgias and/or myalgias, 36 skin rashes, 8 neurological symptoms). Thirty-one patients had disease onset after 5 years and they reported more additional symptoms. A positive family history for recurrent fever or recurrent tonsillitis was found in 81 patients (26.9%). Genetic testing for monogenic periodic fever syndromes was performed on 111 patients, who reported fewer occurrences of oral aphthosis or additional symptoms. Twenty-four patients reported symptoms (oral aphthosis and malaise) outside the flares. The CRP was >50 mg/l in the majority (131/190) of the patients tested during the fever. CONCLUSION: We describe the largest cohort of PFAPA patients presented so far. We confirm that PFAPA may present with varied clinical manifestations and we show the limitations of the commonly used diagnostic criteria. Based on detailed analysis of this cohort, a consensus definition of PFAPA with better-defined criteria should be proposed.

Staphylococcus lugdunensis infective endocarditis. Description of 10 cases and analysis of native valve, prosthetic valve and pacemaker lead endocarditis clinical profiles

bolism. Surgery was needed in 51% of cases and mortality was 42%. Prosthetic valve endocarditis (nine of 60, 13%) predominated in the aortic position and was associated with abscess formation, required surgery, and high mortality (78%). Pacemaker lead IE (seven of 69, 10%) is associated with a better prognosis when antibiotic treatment is combined with surgery. Conclusions:S lugdunensis IE is an uncommon cause of IE, involving mainly native left sided valves, and it is characterised by an aggressive clinical course. Mortality in left sided native valve IE is high but the prognosis has improved in recent years. Surgery has improved survival in left sided IE and, therefore, early surgery should always be considered. Prosthetic valve S lugdunensis IE carries an ominous prognosis.