Search results for "PLIF"
showing 10 items of 835 documents
Guidelines Have a Key Role in Driving HCV Elimination by Advocating for Simple HCV Care Pathways.
2021
The availability of pangenotypic direct-acting antivirals for treatment of hepatitis C (HCV) has provided an opportunity to simplify patient pathways. Recent clinical practice guidelines have recognised the need for simplification to ensure that elimination of HCV as a public health concern remains a priority. Despite the move towards simplified treatment algorithms, there remains some complexity in the recommendations for the management of genotype 3 patients with compensated cirrhosis. In an era where additional clinical trial data are not anticipated, clinical guidance should consider experience gained in real-world settings. Although more experience is required for some pangenotypic the…
Attention-based Model for Evaluating the Complexity of Sentences in English Language
2020
The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…
Deep neural attention-based model for the evaluation of italian sentences complexity
2020
In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.
Multi-class Text Complexity Evaluation via Deep Neural Networks
2019
Automatic Text Complexity Evaluation (ATE) is a natural language processing task which aims to assess texts difficulty taking into account many facets related to complexity. A large number of papers tackle the problem of ATE by means of machine learning algorithms in order to classify texts into complex or simple classes. In this paper, we try to go beyond the methodologies presented so far by introducing a preliminary system based on a deep neural network model whose objective is to classify sentences into more of two classes. Experiments have been carried out on a manually annotated corpus which has been preprocessed in order to make it suitable for the scope of the paper. The results sho…
A posteriori modelling-discretization error estimate for elliptic problems with L ∞-Coefficients
2017
We consider elliptic problems with complicated, discontinuous diffusion tensor A0. One of the standard approaches to numerically treat such problems is to simplify the coefficient by some approximation, say Aϵ, and to use standard finite elements. In [19] a combined modelling-discretization strategy has been proposed which estimates the discretization and modelling errors by a posteriori estimates of functional type. This strategy allows to balance these two errors in a problem adapted way. However, the estimate of the modelling error was derived under the assumption that the difference A0 - Aϵ becomes small with respect to the L∞-norm. This implies in particular that interfaces/discontinui…
Molecular characterization of Treponema pallidum subsp. pallidum in Switzerland and France with a new multilocus sequence typing scheme
2018
Syphilis is an important public health problem and an increasing incidence has been noted in recent years. Characterization of strain diversity through molecular data plays a critical role in the epidemiological understanding of this re-emergence. We here propose a new high-resolution multilocus sequence typing (MLST) scheme for Treponema pallidum subsp. pallidum (TPA). We analyzed 30 complete and draft TPA genomes obtained directly from clinical samples or from rabbit propagated strains to identify suitable typing loci and tested the new scheme on 120 clinical samples collected in Switzerland and France. Our analyses yielded three loci with high discriminatory power: TP0136, TP0548, and TP…
16S rDNA analysis for characterization of denitrifying bacteria isolated from three agricultural soils
2000
Bacteria capable of denitrification are spread among phylogenetically diverse groups. In the present investigation, molecular methods (amplified ribosomal DNA restriction analysis (ARDRA) and partial 16S rDNA gene sequencing) were used to determine the genetic diversity of culturable denitrifying soil bacteria. The purpose of this work was to study the microbial density and diversity of denitrifying communities isolated from two luvisols and a rendosol. The denitrifying bacterial density was significantly higher in the two luvisols (3x10(6) and 4x10(6) bacteria g(-1) dry soil) than in the rendosol (4x10(5) bacteria g(-1) dry soil). Denitrifying isolates from soils were grouped according to …
A coarse to fine 3D acquisition system
2015
International audience; The 3D chain (acquisition-processing-compression) is , most of the time , sequenced into several steps. Such approaches result into an one-dense acquisition of 3D points. In large scope of applications , the first processing step consists in simplifying the data. In this paper , we propose a coarse to fine acquisition system which permits to obtain simplified data directly from the acquisition. By calculating some complementary information from 2D images , such as 3D normals , multiple homogeneous regions will be segmented and affected to a given primitive class. Contrary to other studies , the whole process is not based on a mesh. The obtained model is simplified di…
Identificación de TRIM29 localizado en la región cromosómica 11q23.3 como biomarcador de resistencia a Doxorubicina y proliferación celular en cáncer…
2018
El cáncer de mama es una enfermedad compleja y heterogénea en la que los pacientes pueden presentar síntomas similares y padecer la misma enfermedad por razones genéticas completamente diferentes. Los factores que contribuyen a esta heterogeneidad incluyen la variación en el genoma de cada paciente, las diferencias en el origen y la naturaleza de la célula tumoral y los eventos genéticos que contribuyen a la progresión del tumor. La recaída en cáncer de mama es una de las mayores causas de morbilidad en pacientes que desarrollan la enfermedad y, entre ellas, entre un 15-20% poseerán tumores de mama triple negativo (TN). La mortalidad de pacientes con cáncer de mama TN es considerablemente m…
Hacia la ley europea del clima: las evaluaciones científicas y el futuro papel de las respuestas jurídicas de los estados miembros
2021
Los problemas climáticos son temas persistentes y omnipresentes dentro de las políticas y legislaciones contemporáneas, que exigen un enfoque interdisciplinario para promover soluciones jurídicas adecuadas para la complejidad del tema. Paradójicamente, las propagandas negacionistas, lejos de bloquear las acciones climáticas, las han propiciado, lo que ha llevado al establecimiento de un organismo científico super partes que reconociese las cuestiones climáticas a través de informes científicos avanzados: el Grupo Intergubernamental de Expertos sobre el Cambio Climático de la ONU (IPCC). Desde entonces, muchos países han usado los hallazgos del IPCC como base científica para desarrollar polí…