The Conformal Penrose Limit and the Resolution of the pp-curvature Singularities

We consider the exact solutions of the supergravity theories in various dimensions in which the space-time has the form M_{d} x S^{D-d} where M_{d} is an Einstein space admitting a conformal Killing vector and S^{D-d} is a sphere of an appropriate dimension. We show that, if the cosmological constant of M_{d} is negative and the conformal Killing vector is space-like, then such solutions will have a conformal Penrose limit: M^{(0)}_{d} x S^{D-d} where M^{(0)}_{d} is a generalized d-dimensional AdS plane wave. We study the properties of the limiting solutions and find that M^{(0)}_{d} has 1/4 supersymmetry as well as a Virasoro symmetry. We also describe how the pp-curvature singularity of M^{(0)}_{d} is resolved in the particular case of the D6-branes of D=10 type IIA supergravity theory. This distinguished case provides an interesting generalization of the plane waves in D=11 supergravity theory and suggests a duality between the SU(2) gauged d=8 supergravity of Salam and Sezgin on M^{(0)}_{8} and the d=7 ungauged supergravity theory on its pp-wave boundary.Comment: 20 pages, LaTeX; typos corrected, journal versio

Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?

Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem. Several deep-learning-based methods have been proposed in recent years. However, most methods tend to be static, that is, a single model trained on a large, specialized dataset, which does not generalize well. Instead, the model should learn across datasets arriving sequentially from different hospitals by building upon the characteristics of lesions in a continual manner. In this regard, we explore experience replay, a well-known continual learning method, in the context of MS lesion segmentation across multi-contrast data from 8 different hospitals. Our experiments show that replay is able to achieve positive backward transfer and reduce catastrophic forgetting compared to sequential fine-tuning. Furthermore, replay outperforms the multi-domain training, thereby emerging as a promising solution for the segmentation of MS lesions. The code is available at this link: https://github.com/naga-karthik/continual-learning-msComment: Accepted at the Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop 202

Jacobi structures revisited

Jacobi algebroids, that is graded Lie brackets on the Grassmann algebra associated with a vector bundle which satisfy a property similar to that of the Jacobi brackets, are introduced. They turn out to be equivalent to generalized Lie algebroids in the sense of Iglesias and Marrero and can be viewed also as odd Jacobi brackets on the supermanifolds associated with the vector bundles. Jacobi bialgebroids are defined in the same manner. A lifting procedure of elements of this Grassmann algebra to multivector fields on the total space of the vector bundle which preserves the corresponding brackets is developed. This gives the possibility of associating canonically a Lie algebroid with any local Lie algebra in the sense of Kirillov.Comment: 20 page

The graded Jacobi algebras and (co)homology

Jacobi algebroids (i.e. `Jacobi versions' of Lie algebroids) are studied in the context of graded Jacobi brackets on graded commutative algebras. This unifies varios concepts of graded Lie structures in geometry and physics. A method of describing such structures by classical Lie algebroids via certain gauging (in the spirit of E.Witten's gauging of exterior derivative) is developed. One constructs a corresponding Cartan differential calculus (graded commutative one) in a natural manner. This, in turn, gives canonical generating operators for triangular Jacobi algebroids. One gets, in particular, the Lichnerowicz-Jacobi homology operators associated with classical Jacobi structures. Courant-Jacobi brackets are obtained in a similar way and use to define an abstract notion of a Courant-Jacobi algebroid and Dirac-Jacobi structure. All this offers a new flavour in understanding the Batalin-Vilkovisky formalism.Comment: 20 pages, a few typos corrected; final version to be published in J. Phys. A: Math. Ge

Role of nitric oxide synthases in elastase-induced emphysema

Nitric oxide (NO) in combination with superoxide produces peroxynitrites and induces protein nitration, which participates in a number of chronic degenerative diseases. NO is produced at high levels in the human emphysematous lung, but its role in this disease is unknown. The aim of this study was to determine whether the NO synthases contribute to the development of elastase-induced emphysema in mice. nNOS, iNOS, and eNOS were quantified and immunolocalized in the lung after a tracheal instillation of elastase in mice. To determine whether eNOS or iNOS had a role in the development of emphysema, mice bearing a germline deletion of the eNOS and iNOS genes and mice treated with a pharmacological iNOS inhibitor were exposed to elastase. Protein nitration was determined by immunofluorescence, protein oxidation was determined by ELISA. Inflammation and MMP activity were quantified by cell counts, RT-PCR and zymography in bronchoalveolar lavage fluid. Cell proliferation was determined by Ki67 immunostaining. Emphysema was quantified morphometrically. iNOS and eNOS were diffusely upregulated in the lung of elastase-treated mice and a 12-fold increase in the number of 3-nitrotyrosine-expressing cells was observed. Over 80% of these cells were alveolar type 2 cells. In elastase-instilled mice, iNOS inactivation reduced protein nitration and increased protein oxidation but had no effect on inflammation, MMP activity, cell proliferation or the subsequent development of emphysema. eNOS inactivation had no effect. In conclusion, in the elastase-injured lung, iNOS mediates protein nitration in alveolar type 2 cells and alleviates oxidative injury. Neither eNOS nor iNOS are required for the development of elastase-induced emphysema

Lectura y coherencia textual (análisis de un texto narrativo)

Los autores proponen la Lingüística Textual para un reenfoque de las actividades de análisis de texto en la enseñanza. Como modelo de aplicación de esa propuesta se expone un caso de análisis textual de una nanación en el que se localizan los mecanismos de coherencia y se generan preguntas de control y ejercicios para que el alumno desarrolle estrategias de lectura