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Institution

University of Trento

EducationTrento, Italy
About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.


Papers
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Journal ArticleDOI
TL;DR: Several kernel functions to model parse tree properties in kernel-based machines, for example, perceptrons or support vector machines are proposed and tree kernels allow for a general and easily portable feature engineering method which is applicable to a large family of natural language processing tasks.
Abstract: The availability of large scale data sets of manually annotated predicate-argument structures has recently favored the use of machine learning approaches to the design of automated semantic role labeling (SRL) systems. The main research in this area relates to the design choices for feature representation and for effective decompositions of the task in different learning models. Regarding the former choice, structural properties of full syntactic parses are largely employed as they represent ways to encode different principles suggested by the linking theory between syntax and semantics. The latter choice relates to several learning schemes over global views of the parses. For example, re-ranking stages operating over alternative predicate-argument sequences of the same sentence have shown to be very effective. In this article, we propose several kernel functions to model parse tree properties in kernel-based machines, for example, perceptrons or support vector machines. In particular, we define different kinds of tree kernels as general approaches to feature engineering in SRL. Moreover, we extensively experiment with such kernels to investigate their contribution to individual stages of an SRL architecture both in isolation and in combination with other traditional manually coded features. The results for boundary recognition, classification, and re-ranking stages provide systematic evidence about the significant impact of tree kernels on the overall accuracy, especially when the amount of training data is small. As a conclusive result, tree kernels allow for a general and easily portable feature engineering method which is applicable to a large family of natural language processing tasks.

171 citations

Journal ArticleDOI
TL;DR: It is possible to communicate with event-related potentials using the mixed filter feedback method, and wavelet transformed data cannot be fed back on-line before the end of a trial, they are applicable only if immediate feedback is not necessary for a brain-computer interface (BCI).

171 citations

Journal ArticleDOI
TL;DR: In this article, the exact solution of the linearized form of the mathematical problem of river morphodynamics was derived, which applies to channels with constant width and arbitrary curvature distribution.
Abstract: Perturbations of channel geometry (like variations of channel curvature or channel width) in meandering rivers give rise to morphodynamic effects which display themselves through the development of large-scale perturbations of bottom topography in the form of stationary bars developing in the longitudinal direction. The latter may then drive the lateral migration of the channel by enhancing bank erosion at bar pools: through this mechanism local perturbations of channel geometry may affect the planimetric development of meandering rivers on large timescales. The problem tackled herein is whether such morphodynamic influence is invariably felt downstream as the commonly employed model of river meandering would suggest.In order to solve this problem, we derive the exact solution of the linearized form of the mathematical problem of river morphodynamics. Linear analysis had pointed out the existence of a resonance phenomenon: in a linear (hence ideal) context, resonance occurs when the meander wavenumber and the width ratio of the channel take values (λR and βR, respectively) such as to force free spatial modes of the system consisting of free bars which neither grow nor decay either in time or in space. Channels characterized by values of the width ratio β larger (smaller) than βR are called super- (sub-)resonant. The present solution, which applies to channels with constant width and arbitrary curvature distribution, shows that two distinct scenarios may occur: downstream influence is associated with sub-resonant channels and vice versa dominant upstream influence occurs in super-resonant channels. Small-amplitude waves of bottom topography are shown to migrate downstream in the former case and may migrate upstream in the latter, as resonance also defines the threshold conditions below (above) which small-amplitude alternate bar perturbations (may) migrate downstream (upstream).These results have several implications. In the present paper we examine the overdeepening phenomenon whereby abrupt variations of channel curvature, as in sequences of straight and constant curvature reaches, lead to sequences of stationary alternate bars with amplitude decaying in the longitudinal direction. We show that, along with downstream overdeepening, an upstream overdeepening scenario is predicted in the super-resonant regime.Implications of the upstream influence on planimetric development of meandering rivers are investigated in Part 2.

171 citations

Journal ArticleDOI
TL;DR: In this paper, the density-density correlation function of an atomic Bose-Einstein condensate in the presence of an acoustic black hole was calculated using the analogy between gravitational systems and nonhomogeneous fluid flows.
Abstract: We have used the analogy between gravitational systems and nonhomogeneous fluid flows to calculate the density-density correlation function of an atomic Bose-Einstein condensate in the presence of an acoustic black hole The emission of correlated pairs of phonons by Hawking-like process results into a peculiar long-range density correlation Quantitative estimations of the effect are provided for realistic experimental configurations

171 citations

Journal ArticleDOI
TL;DR: A Hamilton-Jacobi variational principle is derived from the solution of the Fokker-Planck equation in terms of a path integral that is able to compute the most probable pathway of folding.
Abstract: We present a method to investigate the kinetics of protein folding and the dynamics underlying the formation of secondary and tertiary structures during the entire reaction. By writing the solution of the Fokker-Planck equation in terms of a path integral, we derive a Hamilton-Jacobi variational principle from which we are able to compute the most probable pathway of folding. The method is applied to the folding of the Villin headpiece subdomain simulated using a Go model. An initial collapsing phase driven by the initial configuration is followed by a rearrangement phase, in which secondary structures are formed and all computed paths display strong similarities. This completely general method does not require the prior knowledge of any reaction coordinate and is an efficient tool to perform simulations of the entire folding process with available computers.

170 citations


Authors

Showing all 10758 results

NameH-indexPapersCitations
Yi Chen2174342293080
Jie Zhang1784857221720
Richard B. Lipton1762110140776
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
Andrea Bocci1722402176461
P. Chang1702154151783
Bradley Cox1692150156200
Marc Weber1672716153502
Guenakh Mitselmakher1651951164435
Brian L Winer1621832128850
J. S. Lange1602083145919
Ralph A. DeFronzo160759132993
Darien Wood1602174136596
Robert Stone1601756167901
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023158
2022340
20212,399
20202,286
20192,129
20181,943