The effect of the Spanish Law of Political Parties (LPP) on the attitude of the Basque Country population towards ETA: A dynamic modelling approach

In June 2002, the Spanish Government passed the ¿Law of Political Parties¿ (LPP) with the aim, among others, of preventing parties giving political support to terrorist organizations. This law affected the Basque nationalist party ¿Batasuna¿, due to its proved relation with ETA. In this paper, taking data from the Euskobarometro (Basque Country survey) related to the attitude of the Basque population towards ETA, we propose a dynamic model for the pre-LPP scenario. This model will be extrapolated to the future in order to predict what would have happened to the attitude of the Basque population if the law had not been passed. These model predictions will be compared to post-LPP data from the Euskobarometro using a bootstrapping approach in order to quantify the effect of the LPP on the attitude of Basque Country population towards ETA.Peco Yeste, M.; Santonja, F.; Tarazona Tornero, AC.; Villanueva Micó, RJ.; Villanueva Oller, FJ. (2013). The effect of the Spanish Law of Political Parties (LPP) on the attitude of the Basque Country population towards ETA: A dynamic modelling approach. Mathematical and Computer Modelling. 1-7. doi:10.1016/j.mcm.2011.11.007S1

Calibration of an agent-based simulation model to the data of women infected by Human Papillomavirus with uncertainty

[EN] Recently, the transmission dynamics of the Human Papillomavirus (HPV) has been studied. In previous works, we have designed and implemented a computational model (agent-based simulation model) where the contagion of the HPV is described on a network of lifetime sexual partners. The run of a single simulation of this computational model, composed of a network with 500 000 nodes, takes about one hour and a half. In addition to set an adequate model, finding out the model parameters that best fit the proposed model to the available data of prevalence is a crucial goal. Taking into account that the necessary number of simulations to perform the calibration of the model may be very high, the aforementioned goal may become unaffordable. In this paper, we present a procedure to fit the proposed HPV model to the available data and the design of an asynchronous version of the Particle Swarm Optimization (PSO) algorithm adapted to the distributed computing environment. In the process, the number of particles used in PSO should be set carefully looking for a compromise between quality of the solutions and computation time. Another feature of the procedure presented here is that we want to capture the intrinsic uncertainty in the data (data come from a survey) when calibrating the model. To do so, we also propose the design of an algorithm to select the model parameter sets obtained during the calibration that best capture the data uncertainty.This work has been supported by the Spanish Ministerio de Economia y Competitividad grants MTM2017-89664-P, TIN2014-54806-R and RTI2018-095180-B-I00, Grants Y2018/NMT-4668 (Micro-Stres-MAP-CM) and GenObIA-CM (S2017/BMD-3773) financed by the Community of Madrid, Spain and co-financed with EU Structural Funds, Spain, and by GLENO project financed by Fundacion Eugenio Rodriguez Pascual, Spain.Villanueva Micó, RJ.; Hidalgo, J.; Cervigon, C.; Villanueva-Oller, J.; Cortés, J. (2019). Calibration of an agent-based simulation model to the data of women infected by Human Papillomavirus with uncertainty. Applied Soft Computing. 80:546-556. https://doi.org/10.1016/j.asoc.2019.04.015S5465568

Optimizing strategies for meningococcal C disease vaccination in Valencia (Spain)

BackgroundMeningococcal C (MenC) conjugate vaccines have controlled invasive diseases associated with this serogroup in countries where they are included in National Immunization Programs and also in an extensive catch-up program involving subjects up to 20 years of age. Catch-up was important, not only because it prevented disease in adolescents and young adults at risk, but also because it decreased transmission of the bacteria, since it was in this age group where the organism was circulating. Our objective is to develop a new vaccination schedule to achieve maximum seroprotection in these groups.MethodsA recent study has provided detailed age-structured information on the seroprotection levels against MenC in Valencia (Spain), where vaccination is routinely scheduled at 2 months and 6 months, with a booster dose at 18 months of age. A complementary catch-up campaign was also carried out in n for children from 12 months to 19 years of age. Statistical analyses of these data have provided an accurate picture on the evolution of seroprotection in the last few years.ResultsAn agent-based model has been developed to study the future evolution of the seroprotection histogram. We have shown that the optimum strategy for achieving high protection levels in all infants, toddlers and adolescents is a change to a 2 months, 12 months and 12 years of age vaccination pattern. If the new schedule were implemented in January 2014, high-risk subjects between 15-19 years of age would have very low seroprotection for the next 6 years, thereby threatening the program.ConclusionsHigh protection levels and a low incidence of meningococcal C disease can be achieved in the future by means of a cost-free change in vaccination program. However, we recommend a new catch-up program simultaneous to the change in regular vaccination program

Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia

[EN] Seasonal fluctuations in the incidence of several respiratory infections are a feature of epidemiological surveys all around the world. This phenomenon is characteristic of influenza and respiratory syncytial virus pandemics. However, the explanation of the seasonal outbreaks of these diseases remains poorly understood. Many statistical studies have been carried out in order to provide a correlation of the outbreaks with climatic or social factors without achieving a definitive conclusion. Here we show that, in a random social network, self-sustained seasonal epidemics emerge as a process modulated by the infection probability and the immunity period after recovering from the infection. This is a purely endogenous phenomenon that does not require any exogenous forcing. Assuming that this is the dominant mechanism for seasonal epidemics, many implications for public health policies for infectious respiratory diseases could be drawn. (C) 2010 Elsevier Ltd. All rights reserved.Supported by a grant from the Universidad Politecnica de Valencia PAID-06-09 ref: 2588.Acedo Rodríguez, L.; Moraño Fernández, JA.; Villanueva Micó, RJ.; Villanueva Oller, FJ.; Díez Domingo, J. (2011). Using random networks to study the dynamics of respiratory syncytial virus (RSV) in the Spanish region of Valencia. Mathematical and Computer Modelling. 54(7-8):1650-1654. https://doi.org/10.1016/j.mcm.2010.11.068S16501654547-

Random Network Models to Predict the Long-Term Impact of HPV Vaccination on Genital Warts

[EN] The Human papillomaviruses (HPV) vaccine induces a herd immunity effect in genital warts when a large number of the population is vaccinated. This aspect should be taken into account when devising new vaccine strategies, like vaccination at older ages or male vaccination. Therefore, it is important to develop mathematical models with good predictive capacities. We devised a sexual contact network that was calibrated to simulate the Spanish epidemiology of different HPV genotypes. Through this model, we simulated the scenario that occurred in Australia in 2007, where 12¿13 year-old girls were vaccinated with a three-dose schedule of a vaccine containing genotypes 6 and 11, which protect against genital warts, and also a catch-up program in women up to 26 years of age. Vaccine coverage were 73% in girls with three doses and with coverage rates decreasing with age until 52% for 20¿26 year-olds. A fast 59% reduction in the genital warts diagnoses occurred in the model in the first years after the start of the program, similar to what was described in the literature.We are grateful for the support from Sanofi Pasteur. The authors would also like to thank M. Diaz-Sanchis from the Institut Catala d'Oncologia (ICO) for her useful comments and the data provided on HPV prevalence. We would also like to thank the ICO for the HPV information centre at http://hpvcentre.net.Diez-Domingo, J.; Sánchez-Alonso, V.; Villanueva Micó, RJ.; Acedo Rodríguez, L.; Moraño Fernández, JA.; Villanueva-Oller, J. (2017). Random Network Models to Predict the Long-Term Impact of HPV Vaccination on Genital Warts. Viruses. 9(10). doi:10.3390/v9100300S91

Progressive imaging: S-transform order

The paper focuses on progressive transmission of CT or MR images, and introduces two general schemes that are built around information embedded in transforms of images. A direct, a priori ordering of 93, parallel, CT slices of a head is obtained by successively finer sweepings of their natural subscript ordering to give a benchmark illustration. By comparison, an ordering of these CT slices simply by their energies is seen to not provide a viable progressive imaging scheme, at least when an overall, 3D skin level rendering is the gauge employed. To investigate progressive imaging that does not obscure internal detail, two techniques based on transform space information are introduced here, and illustrated in detail with a 128?128 MR slice of a head I(x, y). The first uses decreasing size of the moduli of the elements of the Fourier transform F(k x , k y ) of I(x, y). The second, a one parameter generalization, exploits the localization feature of the recent S-transform and also provides a capability for an observer to outline a region of interest within the progressive transmission process. Both transform based methods are effective for the specific illustrations included, and the latter opens important research questions for application in analysis, handling or interpretation of the massive data sets arising in magnetic resonance imaging

Epidemic Random Network Simulations in a Distributed Computing Environment

We discuss a computational system following the paradigm of distributed computing, which will allow us to simulate the epidemic propagation in random networks with large number of nodes up to one million. This paradigm consists of a server that delivers tasks to be carried out by client computers. When the task is finished, the client sends the obtained results to the server to be stored until all tasks are finished and then ready to be analysed. Finally, we show that this technique allows us to disclose the emergence of seasonal patterns in the respiratory syncytial virus transmission dynamics which do not appear neither in smaller systems nor in continuous systems.This paper has been supported by the Grant from the Universitat Politecnica de Valencia PAID-06-11 ref: 2087 and the Grant FIS PI-10/01433. The authors would like to thank the staff of the Facultad de Administracion de Empresas of the Universidad Politecnica de Valencia, in particular Mara Angeles Herrera, Teresa Solaz, and Jose Luis Real, and the staff of the CES Felipe II of Aranjuez for their help and for letting them use free computer rooms to carry out the Sisifo computations described in this paper. They would also like to acknowledge the BOINC community for its support and the many anonymous volunteers who joined thier project and helped them obtain the results so fast.Villanueva-Oller, J.; Acedo Rodríguez, L.; Moraño Fernández, JA.; Sánchez Sánchez, A. (2013). Epidemic Random Network Simulations in a Distributed Computing Environment. Abstract and Applied Analysis. 2013:1-10. https://doi.org/10.1155/2013/462801S1102013PROULX, S., PROMISLOW, D., & PHILLIPS, P. (2005). Network thinking in ecology and evolution. Trends in Ecology & Evolution, 20(6), 345-353. doi:10.1016/j.tree.2005.04.004Traud, A. L., Mucha, P. 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Molecular portrait of high alpha-fetoprotein in hepatocellular carcinoma: implications for biomarker-driven clinical trials

The clinical utility of serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC) is widely recognised. However, a clear understanding of the mechanisms of AFP overexpression and the molecular traits of patients with AFP-high tumours are not known. We assessed transcriptome data, whole-exome sequencing data and DNA methylome profiling of 520 HCC patients from two independent cohorts to identify distinct molecular traits of patients with AFP-high tumours (serum concentration?>?400?ng/ml), which represents an accepted prognostic cut-off and a predictor of response to ramucirumab. Those AFP-high tumours (18% of resected cases) were characterised by significantly lower AFP promoter methylation (p?<?0.001), significant enrichment of progenitor-cell features (CK19, EPCAM), higher incidence of BAP1 oncogene mutations (8.5% vs 1.6%) and lower mutational rates of CTNNB1 (14% vs 30%). Specifically, AFP-high tumours displayed significant activation of VEGF signalling (p?<?0.001), which might provide the rationale for the reported benefit of ramucirumab in this subgroup of patients

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented