La larga lucha por la tierra en Andalucía

Cuando estamos hablando, como en este número de la revista, de concentración y acaparamiento de tierras, es necesario atender el caso concreto de Andalucía, donde la fotografía del latifundio no es más que el resultado histórico y actual de muchos e injustos "acaparamientos". Y este artículo (extracto de uno más extenso que estará disponible en la web), además de ofrecer un pequeño recuerdo histórico, nos sitúa en las luchas actuales

Chaotic asymptotic behaviour of the solutions of the Lighthill Whitham Richards equation

[EN] The phenomenon of chaos has been exhibited in mathematical nonlinear models that describe traffic flows, see, for instance (Li and Gao in Modern Phys Lett B 18(26-27):1395-1402, 2004; Li in Phys. D Nonlinear Phenom 207(1-2):41-51, 2005). At microscopic level, Devaney chaos and distributional chaos have been exhibited for some car-following models, such as the quick-thinking-driver model and the forward and backward control model (Barrachina et al. in 2015; Conejero et al. in Semigroup Forum, 2015). We present here the existence of chaos for the macroscopic model given by the Lighthill Whitham Richards equation.The authors are supported by MEC Project MTM2013-47093-P. The second and third authors are supported by GVA, Project PROMETEOII/2013/013Conejero, JA.; Martínez Jiménez, F.; Peris Manguillot, A.; Ródenas Escribá, FDA. (2016). Chaotic asymptotic behaviour of the solutions of the Lighthill Whitham Richards equation. 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Syst. 29(1), 67–79 (2011)Barrachina, X., Conejero, J.A.: Devaney chaos and distributional chaos in the solution of certain partial differential equations. Abstr. Appl. Anal. Art. ID 457019, 11 (2012)Barrachina, X., Conejero, J.A., Murillo-Arcila, M., Seoane-Sepúlveda, J.B.: Distributional chaos for the forward and backward control traffic model (2015, preprint)Bayart, F., Matheron, É.: Dynamics of Linear Operators, Cambridge Tracts in Mathematics, vol. 179. Cambridge University Press, Cambridge (2009)Bayart, F., Matheron, É.: Mixing operators and small subsets of the circle. J Reine Angew. Math. (2015, to appear)Bermúdez, T., Bonilla, A., Conejero, J.A., Peris, A.: Hypercyclic, topologically mixing and chaotic semigroups on Banach spaces. Stud. Math. 170(1), 57–75 (2005)Bermúdez, T., Bonilla, A., Martínez-Giménez, F., Peris, A.: Li-Yorke and distributionally chaotic operators. J. Math. Anal. 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Differential medial temporal lobe morphometric predictors of item- and relational-encoded memories in healthy individuals and in individuals with mild cognitive impairment and Alzheimer's disease.

INTRODUCTION:Episodic memory processes are supported by different subregions of the medial temporal lobe (MTL). In contrast to a unitary model of memory recognition supported solely by the hippocampus, a current model suggests that item encoding engages perirhinal cortex, whereas relational encoding engages parahippocampal cortex and the hippocampus. However, this model has not been examined in the context of aging, neurodegeneration, and MTL morphometrics. METHODS:Forty-four healthy subjects (HSs) and 18 cognitively impaired subjects (nine mild cognitive impairment [MCI] and nine Alzheimer's disease [AD] patients) were assessed with the relational and item-specific encoding task (RISE) and underwent 3T magnetic resonance imaging. The RISE assessed the differential contribution of relational and item-specific memory. FreeSurfer was used to obtain measures of cortical thickness of MTL regions and hippocampus volume. RESULTS:Memory accuracies for both item and relational memory were significantly better in the HS group than in the MCI/AD group. In MCI/AD group, relational memory was disproportionately impaired. In HSs, hierarchical regressions demonstrated that memory was predicted by perirhinal thickness after item encoding, and by hippocampus volume after relational encoding (both at trend level) and significantly by parahippocampal thickness at associative recognition. The same brain morphometry profiles predicted memory accuracy in MCI/AD, although more robustly perirhinal thickness for item encoding (R2 = 0.31) and hippocampal volume and parahippocampal thickness for relational encoding (R2 = 0.31). DISCUSSION:Our results supported a model of episodic memory in which item-specific encoding was associated with greater perirhinal cortical thickness, while relational encoding was associated with parahippocampal thickness and hippocampus volume. We identified these relationships not only in HSs but also in individuals with MCI and AD. In the subjects with cognitive impairment, reductions in hippocampal volume and impairments in relational memory were especially prominent

Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset

[EN] Objective: The lack of representative coronavirus disease 2019 (COVID-19) data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, in which source variability plays an important role. We showcase and discuss potential biases from data source variability for COVID-19 machine learning. Materials and Methods: We used the publicly available nCov2019 dataset, including patient-level data from several countries. We aimed to the discovery and classification of severity subgroups using symptoms and comorbidities. Results: Cases from the 2 countries with the highest prevalence were divided into separate subgroups with distinct severity manifestations. This variability can reduce the representativeness of training data with respect the model target populations and increase model complexity at risk of overfitting. Conclusions: Data source variability is a potential contributor to bias in distributed research networks. We call for systematic assessment and reporting of data source variability and data quality in COVID-19 data sharing, as key information for reliable and generalizable machine learning.This work was supported by Universitat Politecnica de Valencia contract no. UPV-SUB.2-1302 and FONDO SUPERA COVID-19 by CRUE-Santander Bank grant "Severity Subgroup Discovery and Classification on COVID-19 Real World Data through Machine Learning and Data Quality assessment (SUBCOVERWD-19)."Sáez Silvestre, C.; Romero, N.; Conejero, JA.; Garcia-Gomez, JM. (2021). Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset. Journal of the American Medical Informatics Association. 28(2):360-364. https://doi.org/10.1093/jamia/ocaa25836036428

Cognitive processes and performance in the serve action in volleyball

El saque es una de las acciones de juego en voleibol a la que los equipos han dado gran importancia, definiéndose como la acción de poner el balón en juego por el jugador zaguero derecho, situado en la zona de saque. Ésta es la única acción en la que el jugador tiene el 100% del control de la pelota, teniendo tiempo suficiente para elegir el tipo, la fuerza y el área donde irá dirigido. Además, es considerado acción finalista ya que se puede conseguir punto a través de él, pudiendo afectar al rendimiento del equipo. El objetivo de este estudio fue analizar la relación entre la toma de decisiones y el rendimiento en la acción de saque, en voleibol de categoría Juvenil Masculino. Se analizaron mediante la observación sistemática 1555 acciones de saque, correspondientes a los 21 equipos participantes en el Campeonato de España Juvenil Masculino, celebrado en 2012. Los resultados mostraron una asociación significativa entre la toma de decisiones y el rendimiento, en la acción de saque (.337**). Además, existe una asociación alta entre ambas variables (Gamma = .533), y un nivel de dependencia moderado entre las mismas (D de Somers = .315). Estos resultados muestran la importancia de poseer adecuadas capacidades decisionales para obtener un óptimo rendimiento en la acción de saque, y contribuir así a mejorar el rendimiento del equipo. Por tanto, en el proceso de entrenamiento de jugadores de categoría juvenil sería apropiado considerar la posibilidad de empleo de actividades que contribuyan a la mejora de la capacidad decisional de los deportistas.The serve is one of the game actions in volleyball to which teams have given great importance. It is defined as the action to start the rally by the right back player, located in the serve zone. The serve is a single action in which the player has 100% control of the ball, having enough time to choose the type, strength and area where it will be directed. In addition, it is considered a finalist action as a direct point can be achieved through it, affecting the team performance. The objective of this study was to analyze the relationship between decision-making and performance in the serve action, in volleyball U-19 category. 1555 serve actions were analyzed through the systematic observation of the 21 teams participating in the U-19 Male Spanish Championship in 2012. The results showed a significant association between decision-making and performance in the serve action (.337 **). In addition, there is a high association between both variables (Gamma = .533), and a moderate dependency level between them (Somers' D = .315). These results show the importance of having adequate decision-making abilities to obtain optimum performance in the serve action, improving team performance. Therefore, in the training process of youth volleyball players it would be appropriate to use activities to improve the players’ decision-making abilities.• Junta de Extremadura y Fondo Europeo de Desarrollo Regional. AyudapeerReviewe

EST2uni: an open, parallel tool for automated EST analysis and database creation, with a data mining web interface and microarray expression data integration

This article is available from: http://www.biomedcentral.com/1471-2105/9/5[Background] Expressed sequence tag (EST) collections are composed of a high number of single-pass, redundant, partial sequences, which need to be processed, clustered, and annotated to remove low-quality and vector regions, eliminate redundancy and sequencing errors, and provide biologically relevant information. In order to provide a suitable way of performing the different steps in the analysis of the ESTs, flexible computation pipelines adapted to the local needs of specific EST projects have to be developed. Furthermore, EST collections must be stored in highly structured relational databases available to researchers through user-friendly interfaces which allow efficient and complex data mining, thus offering maximum capabilities for their full exploitation.[Results] We have created EST2uni, an integrated, highly-configurable EST analysis pipeline and data mining software package that automates the pre-processing, clustering, annotation, database creation, and data mining of EST collections. The pipeline uses standard EST analysis tools and the software has a modular design to facilitate the addition of new analytical methods and their configuration. Currently implemented analyses include functional and structural annotation, SNP and microsatellite discovery, integration of previously known genetic marker data and gene expression results, and assistance in cDNA microarray design. It can be run in parallel in a PC cluster in order to reduce the time necessary for the analysis. It also creates a web site linked to the database, showing collection statistics, with complex query capabilities and tools for data mining and retrieval.[Conclusion] The software package presented here provides an efficient and complete bioinformatics tool for the management of EST collections which is very easy to adapt to the local needs of different EST projects. The code is freely available under the GPL license and can be obtained at http:// bioinf.comav.upv.es/est2uni. This site also provides detailed instructions for installation and configuration of the software package. The code is under active development to incorporate new analyses, methods, and algorithms as they are released by the bioinformatics community.Partially funded by "Conselleria de Agricultura, Pesca y Alimentacion de la Comunidad Valenciana" and Spanish "Ministerio de Ciencia y Tecnologia" (research grants GEN2001-4885-C05 and GEN2003-20237-C06).Peer reviewe

Root and aerial growth in early-maturing peach trees under two crop load treatments

 The objectives of the paper were to study the pattern of root growth (measured by minirhizotrons) in relation to trunk, fruit and shoot growth and the effects of crop load on tree growth and yield in peach trees. Two crop load (commercial and low) treatments were applied in a mature early-maturing peach tree orchard growing in Mediterranean conditions. Root growth dynamics were measured using minirhizotrons during one growing season. Shoot, trunk and fruit growth were also measured. At harvest, all fruits were weighed, counted and sized. Roots grew throughout the year but at lower rates during the active fruit growth phase. Root growth was asynchronous with shoot growth, while root and trunk growth rates were highest after harvest, when the canopy was big enough to allocate the photo-assimilates to organs that would ensure the following season’s yield. Shoot and fruit growth was greater in the low crop load treatment and was accompanied by a non-significant increase in root growth. High level of fruit thinning decreased the current yield but the fruits were more marketable because of their greater size

Enabling System Wide Shared Memory for Performance Improvement in PyCOMPSs Applications

Python has been gaining some traction for years in the world of scientific applications. However, the high-level abstraction it provides may not allow the developer to use the machines to their peak performance. To address this, multiple strategies, sometimes complementary, have been developed to enrich the software ecosystem either by relying on additional libraries dedicated to efficient computation (e.g., NumPy) or by providing a framework to better use HPC scale infrastructures (e.g., PyCOMPSs).In this paper, we present a Python extension based on SharedArray that enables the support of system-provided shared memory and its integration into the PyCOMPSs programming model as an example of integration to a complex Python environment. We also evaluate the impact such a tool may have on performance in two types of distributed execution-flows, one for linear algebra with a blocked matrix multiplication application and the other in the context of data-clustering with a k-means application. We show that with very little modification of the original decorator (3 lines of code to be modified) of the task-based application the gain in performance can rise above 40% for tasks relying heavily on data reuse on a distributed environment, especially when loading the data is prominent in the execution time.This work was partly funded by the EXPERTISE project (http://www.msca-expertise.eu/), which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 721865. BSC authors have also been supported by the Spanish Government through contracts SEV2015-0493 and TIN2015-65316-P, and by Generalitat de Catalunya through contract 2014-SGR-1051.Peer ReviewedPostprint (author's final draft