The Neron-Severi group of a proper seminormal complex variety

We prove a Lefschetz (1,1)-Theorem for proper seminormal varieties over the complex numbers. The proof is a non-trivial geometric argument applied to the isogeny class of the Lefschetz 1-motive associated to the mixed Hodge structure on H^2.Comment: 16 pages; Mathematische Zeitschrift (2008

Autism and the U.K. secondary school experience

This research investigated the self-reported mainstream school experiences of those diagnosed on the autistic spectrum compared with the typically developing school population. Existing literature identifies four key areas that affect the quality of the school experience for students with autism: social skills, perceived relationships with teaching staff, general school functioning, and interpersonal strengths of the young person. These areas were explored in a mainstream U.K. secondary school with 14 students with autism and 14 age and gender matched students without autism, using self-report questionnaires and semi-structured interviews. Quantitative analyses showed consistent school experiences for both groups, although content analysis of interview data highlighted some differences in the ways in which the groups perceive group work, peers, and teaching staff within school. Implications for school inclusion are discussed, drawing attention to how staff awareness of autism could improve school experience and success for students with autism attending mainstream schools

Standard monomial theory for wonderful varieties

A general setting for a standard monomial theory on a multiset is introduced and applied to the Cox ring of a wonderful variety. This gives a degeneration result of the Cox ring to a multicone over a partial flag variety. Further, we deduce that the Cox ring has rational singularities.Comment: v3: 20 pages, final version to appear on Algebras and Representation Theory. The final publication is available at Springer via http://dx.doi.org/10.1007/s10468-015-9586-z. v2: 20 pages, examples added in Section 3 and in Section

Latest developments in data analysis tools for disruption prediction and for the exploration of multimachine operational spaces.

In the last years significant efforts have been devoted to the development of advanced data analysis tools to both predict the occurrence of disruptions and to investigate the operational spaces of devices, with the long term goal of advancing the understanding of the physics of these events and to prepare for ITER. On JET the latest generation of the disruption predictor called APODIS has been deployed in the real time network during the last campaigns with the new metallic wall. Even if it was trained only with discharges with the carbon wall, it has reached very good performance, with both missed alarms and false alarms in the order of a few percent (and strategies to improve the performance have already been identified). Since for the optimisation of the mitigation measures, predicting also the type of disruption is considered to be also very important, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been developed. This technique allows automatic classification of an incoming disruption with a success rate of better than 85%. Various other manifold learning tools, particularly Principal Component Analysis and Self Organised Maps, are also producing very interesting results in the comparative analysis of JET and ASDEX Upgrade (AUG) operational spaces, on the route to developing predictors capable of extrapolating from one device to another

Uniformizing the Stacks of Abelian Sheaves

Elliptic sheaves (which are related to Drinfeld modules) were introduced by Drinfeld and further studied by Laumon--Rapoport--Stuhler and others. They can be viewed as function field analogues of elliptic curves and hence are objects "of dimension 1". Their higher dimensional generalisations are called abelian sheaves. In the analogy between function fields and number fields, abelian sheaves are counterparts of abelian varieties. In this article we study the moduli spaces of abelian sheaves and prove that they are algebraic stacks. We further transfer results of Cerednik--Drinfeld and Rapoport--Zink on the uniformization of Shimura varieties to the setting of abelian sheaves. Actually the analogy of the Cerednik--Drinfeld uniformization is nothing but the uniformization of the moduli schemes of Drinfeld modules by the Drinfeld upper half space. Our results generalise this uniformization. The proof closely follows the ideas of Rapoport--Zink. In particular, analogies of $p$-divisible groups play an important role. As a crucial intermediate step we prove that in a family of abelian sheaves with good reduction at infinity, the set of points where the abelian sheaf is uniformizable in the sense of Anderson, is formally closed.Comment: Final version, appears in "Number Fields and Function Fields - Two Parallel Worlds", Papers from the 4th Conference held on Texel Island, April 2004, edited by G. van der Geer, B. Moonen, R. Schoo

Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions

Over the last few years progress has been made on the front of disruption prediction in tokamaks. The less forgiving character of the new metallic walls at JET emphasized the importance of disruption prediction and mitigation. Being able not only to predict but also classify the type of disruption will enable one to better choose the appropriate mitigation strategy. From this perspective, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been applied to the JET disruption database. This approach allows the error bars of the measurements to be taken into account and has proved to clearly outperform the more traditional classification methods based on the Euclidean distance. The developed technique with the highest success rate manages to identify the type of disruption with 85% confidence, several hundreds of ms before the thermal quench. Therefore, the combined use of this method and the more traditional disruption predictors would significantly improve the mitigation strategy on JET and could contribute to the definition of an optimized approach for ITER

Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions

Over the last few years progress has been made on the front of disruption prediction in tokamaks. The less forgiving character of the new metallic walls at JET emphasized the importance of disruption prediction and mitigation. Being able not only to predict but also classify the type of disruption will enable one to better choose the appropriate mitigation strategy. From this perspective, a new clustering method, based on the geodesic distance on a probabilistic manifold, has been applied to the JET disruption database. This approach allows the error bars of the measurements to be taken into account and has proved to clearly outperform the more traditional classification methods based on the Euclidean distance. The developed technique with the highest success rate manages to identify the type of disruption with 85% confidence, several hundreds of ms before the thermal quench. Therefore, the combined use of this method and the more traditional disruption predictors would significantly improve the mitigation strategy on JET and could contribute to the definition of an optimized approach for ITER.</p

[Age and management decisions in patients with primary lung cancer].

ERMAInternational audienceINTRODUCTION: Therapeutic decisions are difficult in elderly patients because of the heterogeneity of this population. Our objective was to evaluate the role of age in the management of patients suffering from primary lung cancer seen in the department of respiratory diseases of the Limoges regional teaching hospital between 2002 and 2004. METHODS: A cross sectional study analysed the management of 363 patients suffering from primary lung cancer. The patients were divided into two groups according to their age (less than seventy or seventy and over). A comparison was made between the management of the two groups. RESULTS: The comparisons according to age produced evidence of reduced activity, greater dependence, an increased Charlson score, less frequently administered radiotherapy and chemotherapy, and more frequent symptomatic treatment in the elderly group (p<0.001). CONCLUSIONS: The geriatric assessment of patients suffering from primary lung cancer should make allowance for the physiological age of the patient and adapt the management to ensure the best quality of life