605 research outputs found
Effective String Theory of Vortices and Regge Trajectories
Starting from a field theory containing classical vortex solutions, we obtain
an effective string theory of these vortices as a path integral over the two
transverse degrees of freedom of the string. We carry out a semiclassical
expansion of this effective theory, and use it to obtain corrections to Regge
trajectories due to string fluctuations.Comment: 27 pages, revtex, 3 figures, corrected an error with the cutoff in
appendix E (was previously D), added more discussion of Fig. 3, moved some
material in section 9 to a new appendi
Neutron matter with a model interaction
An infinite system of neutrons interacting by a model pair potential is
considered. We investigate a case when this potential is sufficiently strong
attractive, so that its scattering length tends to infinity. It appeared, that
if the structure of the potential is simple enough, including no finite
parameters, reliable evidences can be presented that such a system is
completely unstable at any finite density. The incompressibility as a function
of the density is negative, reaching zero value when the density tends to zero.
If the potential contains a sufficiently strong repulsive core then the system
possesses an equilibrium density. The main features of a theory describing such
systems are considered.Comment: 8 pages, LaTeX. In press, Eur. Phys. J.
Quantum Phase Transitions and the Extended Coupled Cluster Method
We discuss the application of an extended version of the coupled cluster
method to systems exhibiting a quantum phase transition. We use the lattice
O(4) non-linear sigma model in (1+1)- and (3+1)-dimensions as an example. We
show how simple predictions get modified, leading to the absence of a phase
transition in (1+1) dimensions, and strong indications for a phase transition
in (3+1) dimensions
EFFICHRONIC study protocol: A non-controlled, multicentre European prospective study to measure the efficiency of a chronic disease self-management programme in socioeconomically vulnerable populations
Introduction More than 70% of world mortality is due to chronic conditions. Furthermore, it has been proven that social determinants have an enormous impact on both health-related behaviour and on the received attention from healthcare services. These determinants cause h
Investigating Predictors of Preserved Cognitive Function in Older Women Using Machine Learning: Women's Health Initiative Memory Study
Background: Identification of factors that may help to preserve cognitive function in late life could elucidate mechanisms and facilitate interventions to improve the lives of millions of people. However, the large number of potential factors associated with cognitive function poses an analytical challenge. Objective: We used data from the longitudinal Women's Health Initiative Memory Study (WHIMS) and machine learning to investigate 50 demographic, biomedical, behavioral, social, and psychological predictors of preserved cognitive function in later life. Methods: Participants in WHIMS and two consecutive follow up studies who were at least 80 years old and had at least one cognitive assessment following their 80th birthday were classified as cognitively preserved. Preserved cognitive function was defined as having a score ≥39 on the most recent administration of the modified Telephone Interview for Cognitive Status (TICSm) and a mean score across all assessments ≥39. Cognitively impaired participants were those adjudicated by experts to have probable dementia or at least two adjudications of mild cognitive impairment within the 14 years of follow-up and a last TICSm score < 31. Random Forests was used to rank the predictors of preserved cognitive function. Results: Discrimination between groups based on area under the curve was 0.80 (95%-CI-0.76-0.85). Women with preserved cognitive function were younger, better educated, and less forgetful, less depressed, and more optimistic at study enrollment. They also reported better physical function and less sleep disturbance, and had lower systolic blood pressure, hemoglobin, and blood glucose levels. Conclusion: The predictors of preserved cognitive function include demographic, psychological, physical, metabolic, and vascular factors suggesting a complex mix of potential contributors
Critical behavior of the two-dimensional N-component Landau-Ginzburg Hamiltonian with cubic anisotropy
We study the two-dimensional N-component Landau-Ginzburg Hamiltonian with
cubic anisotropy. We compute and analyze the fixed-dimension perturbative
expansion of the renormalization-group functions to four loops. The relations
of these models with N-color Ashkin-Teller models, discrete cubic models,
planar model with fourth order anisotropy, and structural phase transition in
adsorbed monolayers are discussed. Our results for N=2 (XY model with cubic
anisotropy) are compatible with the existence of a line of fixed points joining
the Ising and the O(2) fixed points. Along this line the exponent has
the constant value 1/4, while the exponent runs in a continuous and
monotonic way from 1 to (from Ising to O(2)). For N\geq 3 we find a
cubic fixed point in the region , which is marginally stable or
unstable according to the sign of the perturbation. For the physical relevant
case of N=3 we find the exponents and at the cubic
transition.Comment: 14 pages, 9 figure
Machine Learning in Automated Text Categorization
The automated categorization (or classification) of texts into predefined
categories has witnessed a booming interest in the last ten years, due to the
increased availability of documents in digital form and the ensuing need to
organize them. In the research community the dominant approach to this problem
is based on machine learning techniques: a general inductive process
automatically builds a classifier by learning, from a set of preclassified
documents, the characteristics of the categories. The advantages of this
approach over the knowledge engineering approach (consisting in the manual
definition of a classifier by domain experts) are a very good effectiveness,
considerable savings in terms of expert manpower, and straightforward
portability to different domains. This survey discusses the main approaches to
text categorization that fall within the machine learning paradigm. We will
discuss in detail issues pertaining to three different problems, namely
document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey
The use of orthogonal similarity relations in the prediction of authorship
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-37256-8_38Recent work on Authorship Attribution (AA) proposes the use of meta characteristics to train author models. The meta characteristics are orthogonal sets of similarity relations between the features from the different candidate authors. In that approach, the features are grouped and processed separately according to the type of information they encode, the so called linguistic modalities. For instance, the syntactic, stylistic and semantic features are each considered different modalities as they represent different aspects of the texts. The assumption is that the independent extraction of meta characteristics results in more informative feature vectors, that in turn result in higher accuracies. In this paper we set out to the task of studying the empirical value of this modality specific process. We experimented with different ways of generating the meta characteristics on different data sets with different numbers of authors and genres. Our results show that by extracting the meta characteristics from splitting features by their linguistic dimension we achieve consistent improvement of prediction accuracy.This research was partially supported by ONR grant N00014-12-1-0217 and by NSF award 1254108. It was also supported in part by the CONACYT grant 134186 and by the European Commission as part of the WIQ-EI project (project no. 269180) within the FP7 People Programme.Sapkota, U.; Solorio, T.; Montes Gómez, M.; Rosso, P. (2013). The use of orthogonal similarity relations in the prediction of authorship. En Computational Linguistics and Intelligent Text Processing. Springer Verlag (Germany). 463-475. https://doi.org/10.1007/978-3-642-37256-8_38S463475Baker, L.D., McCallum, A.: Distributional clustering of words for text classification. In: SIGIR 1998: Proceedings of the 21st Annual International ACM SIGIR, pp. 96–103. ACM, Melbourne (1998)Biber, D.: The multi-dimensional approach to linguistic analyses of genre variation: An overview of methodology and findings. Computers and the Humanities 26, 331–345 (1993)Blum, A., Mitchell, T.: Combining labeled and unlabeled data with co-training. In: Proceedings of the 1998 Conference on Computational Learning Theory (1998)Dhillon, I.S., Mallela, S., Kumar, R.: A divisive information-theoretic feature clsutering algorithm for text classification. Journal of Machine Learning Research 3, 1265–1287 (2003)Escalante, H.J., Montes-y-Gómez, M., Solorio, T.: A weighted profile intersection measure for profile-based authorship attribution. In: Batyrshin, I., Sidorov, G. (eds.) MICAI 2011, Part I. LNCS, vol. 7094, pp. 232–243. Springer, Heidelberg (2011)Escalante, H.J., Solorio, T., Montes-y-Gomez, M.: Local histograms of character n-grams for authorship attribution. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp. 288–298. Association for Computational Linguistics, Portland (2011)Hayes, J.H.: Authorship attribution: A principal component and linear discriminant analysis of the consistent programmer hypothesis. I. J. Comput. Appl., 79–99 (2008)Houvardas, J., Stamatatos, E.: N-gram feature selection for authorship identification. In: Euzenat, J., Domingue, J. (eds.) AIMSA 2006. LNCS (LNAI), vol. 4183, pp. 77–86. Springer, Heidelberg (2006)Karypis, G.: CLUTO - a clustering toolkit. Tech. Rep. #02-017 (November 2003)Keselj, V., Peng, F., Cercone, N., Thomas, C.: N-gram based author profiles for authorship attribution. In: Proceedings of the Pacific Association for Computational Linguistics, pp. 255–264 (2003)Koppel, M., Schler, J., Argamon, S.: Authorship attribution in the wild. Language Resources and Evaluation 45, 83–94 (2011)Lewis, D.D., Yang, Y., Rose, T.G., Li, F.: Rcv1: A new benchmark collection for text categorization research. Journal of Machine Learning Research 5, 361–397 (2004)Luyckx, K., Daelemans, W.: Authorship attribution and verification with many authors and limited data. In: Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008), Manchester, UK, pp. 513–520 (August 2008)Luyckx, K., Daelemans, W.: The effect of author set size and data size in authorship attribution. In: Literary and Linguistic Computing, pp. 1–21 (August 2010)Marneffe, M.D., MacCartney, B., Manning, C.D.: Generating typed dependency parses from phrase structure parses. In: LREC 2006 (2006)Plakias, S., Stamatatos, E.: Tensor space models for authorship identification. In: Darzentas, J., Vouros, G.A., Vosinakis, S., Arnellos, A. (eds.) SETN 2008. LNCS (LNAI), vol. 5138, pp. 239–249. Springer, Heidelberg (2008)Raghavan, S., Kovashka, A., Mooney, R.: Authorship attribution using probabilistic context-free grammars. In: Proceedings of the ACL 2010 Conference Short Papers, pp. 38–42. Association for Computational Linguistics, Uppsala (2010)Slonim, N., Tishby, N.: The power of word clusters for text classification. In: 23rd European Colloquium on Information Retrieval Research, ECIR (2001)Solorio, T., Pillay, S., Raghavan, S., Montes-y-Gómez: Generating metafeatures for authorship attribution on web forum posts. In: Proceedings of the 5th International Joint Conference on Natural Language Processing, IJCNLP 2011, pp. 156–164. AFNLP, Chiang Mai (2011)Stamatatos, E.: Author identification using imbalanced and limited training texts. In: 18th International Workshop on Database and Expert Systems Applications, DEXA 2007, pp. 237–241 (September 2007)Stamatatos, E.: Author identification: Using text sampling to handle the class imbalance problem. Information Processing and Managemement 44, 790–799 (2008)Stamatatos, E.: Plagiarism detection using stopword n-grams. Journal of the American Society for Information Science and Technology 62(12), 2512–2527 (2011)Stamatatos, E.: A survey on modern authorship attribution methods. Journal of the American Society for Information Science and Technology 60(3), 538–556 (2009)Stolcke, A.: SRILM - an extensible language modeling toolkit, pp. 901–904 (2002)Toutanova, K., Klein, D., Manning, C.D., Singer, Y.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, NAACL 2003, vol. 1, pp. 173–180 (2003)de Vel, O., Anderson, A., Corney, M., Mohay, G.: Multi-topic e-mail authorship attribution forensics. In: Proceedings of the Workshop on Data Mining for Security Applications, 8th ACM Conference on Computer Security (2001)Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann (2005
A re-interpretation of the concept of mass and of the relativistic mass-energy relation
For over a century the definitions of mass and derivations of its relation
with energy continue to be elaborated, demonstrating that the concept of mass
is still not satisfactorily understood. The aim of this study is to show that,
starting from the properties of Minkowski spacetime and from the principle of
least action, energy expresses the property of inertia of a body. This implies
that inertial mass can only be the object of a definition - the so called
mass-energy relation - aimed at measuring energy in different units, more
suitable to describe the huge amount of it enclosed in what we call the
"rest-energy" of a body. Likewise, the concept of gravitational mass becomes
unnecessary, being replaceable by energy, thus making the weak equivalence
principle intrinsically verified. In dealing with mass, a new unit of
measurement is foretold for it, which relies on the de Broglie frequency of
atoms, the value of which can today be measured with an accuracy of a few parts
in 10^9
Nonequilibrium Quantum Dynamics Of Disoriented Chiral Condensates
The nonequilibrium dynamics of the chiral phase transition expected during
the expansion of the quark-qluon plasma produced in a high energy hadron or
heavy ion collision is studied in the O(4) linear sigma model to leading order
in a large expansion. Starting from an approximate equilibrium
configuration at an initial proper time in the disordered phase we study
the transition to the ordered broken symmetry phase as the system expands and
cools. We give results for the proper time evolution of the effective pion
mass, the order parameter as well as for the pion two point
correlation function expressed in terms of a time dependent phase space number
density and pair correlation density. We determine the phase space of initial
conditions that lead to instabilities (exponentially growing long wave length
modes) as the system evolves in time. These instabilities are what eventually
lead to disoriented chiral condensates. In our simulations,we found that
instabilities that are formed during the initial phases of the expansion exist
for proper times that are at most and lead to condensate regions that
do not contain large numbers of particles. The damping of instabilities is a
consequence of strong coupling.Comment: 49 pages, figures available by reques
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