1,721,026 research outputs found
Parsing with Polymorphic Categorial Grammars
No full textIn this paper we investigate the use of polymorphic categorial
grammars as a model for parsing natural language. We will show that,
despite the undecidability of the general model, a subclass of polymorphic
categorial grammars, which we call linear, is mildly context-sensitive and
we propose a polynomial parsing algorithm for these grammars
Characterization of GSTM3 polymorphism by Real-Time PCR with LightCycler. Mozzoni P, De Palma G, Scotti E, Capelletti M, Mutti A.
No full textPolymorphic Categorial Grammars: expressivity and computational properties
No full textWe investigate the use of polymorphic categorial grammars as a model for parsing natural language. We will show that, despite the undecidability of the general model, a subclass of polymorphic categorial grammars, which we call linear, is mildly context-sensitive and we propose a polynomial parsing algorithm for them. An interesting aspect of the resulting system is the absence of spurious ambiguity
MET and ALK as targets for the treatment of NSCLC
No full textCell proliferation, survival, differentiation, migration and metabolism are some of the fundamental cellular processes tightly controlled by the activity of tyrosine-kinase receptors (RTKs). The aberrant signaling of RTKs contributes to cancer growth and survival and has become important target for therapeutic approaches. Well-characterized kinase molecular target in lung cancer, in particular in non-small cell lung cancer (NSCLC), is the activated epidermal growth factor receptor (EGFR) pathway. More recently, the oncogenic role of other two tyrosine-kinases, the hepatocyte growth factor receptor (MET) and the anaplastic lymphoma kinase (ALK), has been recognized. Many different therapeutic strategies have been investigated with the goal to inhibit these receptors, subsequent downstream signaling cascades and arrest tumor growth. This review will discuss the MET and ALK pathways, the different strategies of their inhibition and the potential approaches to overcome acquired resistance to kinase inhibitors in these two genes. © 2014 Bentham Science Publishers
The middle house or the middle floor: Bisecting horizontal and vertical mental number lines in neglect
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This study explores the processing of mental number lines and physical lines in five patients with left unilateral neglect. Three tasks were used: mental number bisection (‘report the middle number between two numbers’), physical line bisection (‘mark the middle of a line’), and a landmark task (‘is the mark on the line to the left/right or higher/lower than the middle of the line?’). We manipulated the number line orientation purely by task instruction: neglect patients were told that the number-pairs represented either houses on a street (horizontal condition) or floors in a building (vertical condition). We also manipulated physical line orientation for comparison. All five neglect patients showed a rightward bias for horizontally oriented physical and number lines (e.g. saying ‘five’ is the middle house number between ‘two’ and ‘six’). Only three of these patients also showed an upward bias for vertically oriented number lines. The remaining two patients did not show any bias in processing vertical lines. Our results suggest that: (1) horizontal and vertical neglect can associate or dissociate among different patients; (2) bisecting number lines operates on internal horizontal and vertical representations possibly analogous to horizontal and vertical physical lines; (3) at least partially independent mechanisms may be involved in processing horizontal and vertical number lines
A Refractory pleural small cell carcinoma in never smoker. A case report.
No full textA 47-year-old woman who had never smoked was evaluated for chest wall pain, cough and dyspnea that proved to be due to neoplastic right pleural disease with effusion. Cytological examination of the pleural fluid and histological analysis of a biopsy specimen of the pleural mass obtained during thoracoscopy were consistent with a diagnosis of small cell carcinoma. The patient was treated with two lines of chemotherapy and with octreotide, but without any clinical or radiological benefit. Since there was immunohistochemical overexpression of epidermal growth factor receptor, the patient was treated with gefitinib. Despite an initial clinical improvement she died due to disease progression. This case of a refractory pleural small cell carcinoma, which is an extremely rare disease, is the first reported in a never smoker and the first to be fully characterized for EGFR status
Regression dilution effects in wind power prediction from wind speed forecasts
No full textWhen there exists a cause-effect relationship de-scribed by an input-output structural equation, for instance the power curve of a wind turbine, the effect (generated power) is obviously predicted by feeding the cause (wind speed) into the structural model (the power curve). But what is going to happen if the wind speed is not directly observed and is surrogated by a guess, as happens with meteorological forecasts? Such a kind of errors-in-variables framework is well understood in the linear Gaussian case: the straightforward application of the structural equation does not give optimal predictions, a phenomenon known as regression dilution. In the present work, the practical significance of regression dilution effects in the nonlinear regression of wind power from forecasts of wind speed is assessed through data taken from the Global Energy Forecasting Competition 2012 (GEFCOM2012). It is found that the effect is relevant and some lessons are learned, in particular about the benefit of using regression models tailored to the specific prediction horizon
Wind power curve modeling: A probabilistic Beta regression approach
Full text linkWind turbine power curves play a key role in various aspects during the life of a wind farm. Typical uses range from wind power forecasting to wind turbine condition monitoring. This paper addresses the identification of probabilistic models of wind power curves from observed data. The main challenge is the need to handle a statistical distribution of wind energy whose shape not only may be highly skewed, but can also change with wind speed. To address these issues, we resort to the framework of Generalized Linear Models (GLMs), proposing a Beta regression approach, with constant or variable dispersion and an appropriate preconditioning step. The proposed methodology was tested on three real SCADA measurements retrieved from public datasets, including a comparison with Quantile Regression Forests (QRFs), also in terms of robustness to outliers. The results suggest that Beta regression can be a valuable resource in the development of probabilistic models for wind energy, as it provides a high degree of flexibility while preserving an interpretable structure
Diagnosi di mutazioni ignote nella Neurofibromatosi 2 su proteine ricombinanti prodotte in vitro
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