Induced correlations and rupture of molecular chaos by anisotropic dissipative Janus hard disks

A system of smooth "frozen" Janus-type disks is studied. Such disks cannot rotate and are divided by their diameter into two sides of different inelasticities. Taking as a reference a system of colored elastic disks, we find differences in the behavior of the collisions once the anisotropy is included. A homogeneous state, akin to the homogeneous cooling state of granular gases, is seen to arise and the singular behavior of both the collisions and the precollisional correlations are highlighted

Bosquejo económico político de la isla de Cuba. Tomo II

Tiene el pie de imprenta: Habana : [s.n.], 1853 (Imprenta de Barcelona

Historia de la Revolución hispano-americana

Copia digital. Madrid : Ministerio de Cultura. Subdirección General de Coordinación Bibliotecaria, 2007Imprenta de Moreno en t. II y IIIT. I. (456 p.) -- T. II. (572 p.) -- T. III. (272 [i.e. 632] p.

Cuestion importante sobre la esclavitud

Copia digital. España : Ministerio de Cultura y Deporte. Subdirección General de Coordinación Bibliotecaria, 202

Integrating speculation detection and deep learning to extract lung cancer diagnosis from clinical notes

Despite efforts to develop models for extracting medical concepts from clinical notes, there are still some challenges in particular to be able to relate concepts to dates. The high number of clinical notes written for each single patient, the use of negation, speculation, and different date formats cause ambiguity that has to be solved to reconstruct the patient’s natural history. In this paper, we concentrate on extracting from clinical narratives the cancer diagnosis and relating it to the diagnosis date. To address this challenge, a hybrid approach that combines deep learning-based and rule-based methods is proposed. The approach integrates three steps: (i) lung cancer named entity recognition, (ii) negation and speculation detection, and (iii) relating the cancer diagnosis to a valid date. In particular, we apply the proposed approach to extract the lung cancer diagnosis and its diagnosis date from clinical narratives written in Spanish. Results obtained show an F-score of 90% in the named entity recognition task, and a 89% F-score in the task of relating the cancer diagnosis to the diagnosis date. Our findings suggest that speculation detection is together with negation detection a key component to properly extract cancer diagnosis from clinical notesThis work is supported by the EU Horizon 2020 innovation program under grant agreement No. 780495, project BigMedilytics (Big Data for Medical Analytics). It has been also supported by Fundación AECC and Instituto de Salud Carlos III (grant AC19/00034), under the frame of ERA-NET PerMe

Behavioural insights (BI) for childhood development and effective public policies in Latin America: A survey and a randomised controlled trial

Objectives We developed (a) a survey to investigate the knowledge of childhood health experts on public policies and behavioural insights (BI), as well as its use in Latin American and the Caribbean countries (LACs), and (b) an intervention (randomised controlled trial) to test the influence of nudges on the effect of a simulated public health programme communication. Participants and settings A total of 2003 LACs childhood health professionals participated in the study through a Hispanic online platform. Primary and secondary outcomes We used regression models analysing expertise-related information, individual differences and location. We extracted several outcome variables related to (a) ‘Public Policy Knowledge Index’ based on the participants’ degree of knowledge on childhood health public policies and (b) BI knowledge, perceived effectiveness and usefulness of a simulated public programme communication. We also analysed a ‘Behavioural Insights Knowledge Index’ (BIKI) based on participants’ performance in BI questions. Results In general, health professionals showed low BI knowledge (knowledge of the term BI: χ2 =210.29, df=1 and p<0.001; BIKI: χ2 =160.5, df=1 and p<0.001), and results were modulated by different factors (age, academic formation, public policy knowledge and location). The use of BI principles for the communication of the public programme revealed higher impact and clarity ratings from professionals than control messages. Conclusions Our findings provide relevant knowledge about BI in health professionals to inform governmental and non-governmental organisations’ decision-making processes related with childhood public policies and BI designs.Fil: Tomio, Andrea A.. Universidad de San Andrés; ArgentinaFil: Dottori, Martin. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hesse Rizzi, Eugenia Fátima. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Torrente, Fernando Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Flichtentrei, Daniel. IntraMed; ArgentinaFil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. University Of California at San Francisco; Estados Unidos. Universidad de Dublin; Irlanda. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin