Visualising the South Yorkshire floods of ‘07

This paper describes initial work on developing an information system to gather, process and visualise various multimedia data sources related to the South Yorkshire (UK) floods of 2007. The work is part of the Memoir project which aims to investigate how technology can help people create and manage long-term personal memories. We are using maps to aggregate multimedia data and to stimulate remembering past events. The paper describes an initial prototype; challenges faced so far and planned future work

Integrative analyses of speciation and divergence in Psammodromus hispanicus (Squamata: Lacertidae)

BackgroundGenetic, phenotypic and ecological divergence within a lineage is the result of past and ongoing evolutionary processes, which lead ultimately to diversification and speciation. Integrative analyses allow linking diversification to geological, climatic, and ecological events, and thus disentangling the relative importance of different evolutionary drivers in generating and maintaining current species richness.ResultsHere, we use phylogenetic, phenotypic, geographic, and environmental data to investigate diversification in the Spanish sand racer (Psammodromus hispanicus). Phylogenetic, molecular clock dating, and phenotypic analyses show that P. hispanicus consists of three lineages. One lineage from Western Spain diverged 8.3 (2.9-14.7) Mya from the ancestor of Psammodromus hispanicus edwardsianus and P. hispanicus hispanicus Central lineage. The latter diverged 4.8 (1.5-8.7) Mya. Molecular clock dating, together with population genetic analyses, indicate that the three lineages experienced northward range expansions from southern Iberian refugia during Pleistocene glacial periods. Ecological niche modelling shows that suitable habitat of the Western lineage and P. h. edwardsianus overlap over vast areas, but that a barrier may hinder dispersal and genetic mixing of populations of both lineages. P. h. hispanicus Central lineage inhabits an ecological niche that overlaps marginally with the other two lineages.ConclusionsOur results provide evidence for divergence in allopatry and niche conservatism between the Western lineage and the ancestor of P. h. edwardsianus and P. h. hispanicus Central lineage, whereas they suggest that niche divergence is involved in the origin of the latter two lineages. Both processes were temporally separated and may be responsible for the here documented genetic and phenotypic diversity of P. hispanicus. The temporal pattern is in line with those proposed for other animal lineages. It suggests that geographic isolation and vicariance played an important role in the early diversification of the group, and that lineage diversification was further amplified through ecological divergence

Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors

[EN] We introduce a high performance, multi-threaded realization of the gemm kernel for the ARMv8.2 architecture that operates with 16-bit (half precision)/queryKindly check and confirm whether the corresponding author is correctly identified. floating point operands. Our code is especially designed for efficient machine learning inference (and to a certain extent, also training) with deep neural networks. The results on the NVIDIA Carmel multicore processor, which implements the ARMv8.2 architecture, show considerable performance gains for the gemm kernel, close to the theoretical peak acceleration that could be expected when moving from 32-bit arithmetic/data to 16-bit. Combined with the type of convolution operator arising in convolutional neural networks, the speed-ups are more modest though still relevant.This work was supported by projects TIN2017-82972-R and RTI2018-093684-B-I00 from the Ministerio de Ciencia, Innovacion y Universidades, project S2018/TCS-4423 of the Comunidad de Madrid, project PR65/19-22445 of the UCM, and project Prometeo/2019/109 of the Generalitat Valenciana.San Juan-Sebastian, P.; Rodríguez-Sánchez, R.; Igual, FD.; Alonso-Jordá, P.; Quintana-Ortí, ES. (2021). Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors. The Journal of Supercomputing. 77(10):11257-11269. https://doi.org/10.1007/s11227-021-03636-41125711269771

Monitoring dynamics of human adenovirus disassembly induced by mechanical fatigue

The standard pathway for virus infection of eukaryotic cells requires disassembly of the viral shell to facilitate release of the viral genome into the host cell. Here we use mechanical fatigue, well below rupture strength, to induce stepwise disruption of individual human adenovirus particles under physiological conditions, and simultaneously monitor disassembly in real time. Our data show the sequence of dismantling events in individual mature (infectious) and immature (noninfectious) virions, starting with consecutive release of vertex structures followed by capsid cracking and core exposure. Further, our experiments demonstrate that vertex resilience depends inextricably on maturation, and establish the relevance of penton vacancies as seeding loci for virus shell disruption. The mechanical fatigue disruption route recapitulates the adenovirus disassembly pathway in vivo, as well as the stability differences between mature and immature virionsWe acknowledge funding by grants from the Ministry of Science and Innovation of Spain, PIB2010US-00233, FIS2011-29493, Consolider CSD2010-00024 and CAM project and the Comunidad de Madrid No. S2009/MAT-1467 to P. J. P.; BFU2010-16382/BMC to C.S.M.; and FIS2011-16090-E to C.S.M. and P.J.P. S.J.F acknowledges funding from the National Institutes of Health, USA (GM037705 and AI1058172). A.J.P.-B. holds a Juan de la Cierva postdoctoral contract from the Ministry of Science and Innovation of Spain; A.O.-E. and R.M.-C. are recipients of predoctoral fellowships from the Ministry of Education and the Instituto de Salud Carlos III of Spain, respectivel

Modeling Wildfire Dynamics in Latin America Using the FLAM Framework

The increasing frequency of wildfires caused by climate change poses a significant threat globally, particularly in Latin America – a region known for its critical ecosystems. Its vulnerability to climate change-induced wildfire threats, resulting from increasing temperatures and changing precipitation patterns, is uncertain, highlighting the need for comprehensive strategies such as incorporating advanced modeling and proactive measures to understand, manage, and conserve its ecological state in the face of threats posed by climate change, such as wildfires. This study utilizes the wildFire cLimate impacts and Adaptation Model (FLAM) by IIASA to provide a comprehensive analysis of past and projected wildfire dynamics in Latin America. FLAM is a process-based fire parameterization algorithm used to assess the impacts of climate, fuel availability, topography, and anthropogenic factors on wildfire characteristics. It is highly adjustable and adaptable, making it suitable to analyze past and future wildfire trends in diverse regions such as Latin America. We analyzed spatial and temporal wildfire patterns using MODIS satellite data alongside historical climate and anthropogenic data to calibrate FLAM. We generated projections of burned areas until 2100 under 3 RCP scenarios for Latin American as a whole, as well as for distinct sub-regions to better assess regional wildfire dynamics and climate change impacts. Moreover, we developed a scenario to explore the impacts of increased fire suppression efficiency on projected burned area and highlight the impacts of focusing mitigation and management efforts on areas identified as hotspots (high risk of wildfire). The study shows FLAM’s effectiveness in modeling historical wildfires and its sensitivity to the RCP scenarios in predicting wildfire trends in Latin America. Our analysis and results show how FLAM helps in evaluating the potential future changes in wildfire intensity, and geographic spread under various climatic scenarios. FLAM projected a dramatic rise in burned area until the end of the century across Latin America in line with observed trends, especially under severe climate change scenarios. Regions with the highest temperature rises are also prone to reduced precipitation, which further increase wildfire risks. The spatially-explicit projections highlight areas at higher risk of wildfire, enabling targeted and efficient fire management and mitigation strategies. Our study further showed the potential impact of adaptive measures, such as enhanced fire suppression efficiency in identified hotspots, in reducing annual mean burned area. Overall, this study provides critical insights into the relationship between climate change and wildfire dynamics using a state of the art model. It sets the foundation for further research on fires in Latin America and efficient management strategies which can be modelled by FLAM

Comparación de las percepciones del aprendizaje en dos cohortes de estudiantes de Anatomía normal

Se define a los enfoques de aprendizaje como “los procesos de aprendizaje que emerge de la percepción que tienen los estudiantes de las tareas académicas, influenciadas por sus características personales”. En publicaciones previas, se analizaron las percepciones de los componentes sobre los enfoques del aprendizaje en cohortes de estudiantes de anatomía del año 2015 y 2016.Facultad de Ciencias Médica

Comparación de las percepciones del aprendizaje en dos cohortes de estudiantes de Anatomía normal

Se define a los enfoques de aprendizaje como “los procesos de aprendizaje que emerge de la percepción que tienen los estudiantes de las tareas académicas, influenciadas por sus características personales”. En publicaciones previas, se analizaron las percepciones de los componentes sobre los enfoques del aprendizaje en cohortes de estudiantes de anatomía del año 2015 y 2016.Facultad de Ciencias Médica

Discovering duplicate tasks in transition systems for the simplification of process models

This work presents a set of methods to improve the understandability of process models. Traditionally, simplification methods trade off quality metrics, such as fitness or precision. Conversely, the methods proposed in this paper produce simplified models while preserving or even increasing fidelity metrics. The first problem addressed in the paper is the discovery of duplicate tasks. A new method is proposed that avoids overfitting by working on the transition system generated by the log. The method is able to discover duplicate tasks even in the presence of concurrency and choice. The second problem is the structural simplification of the model by identifying optional and repetitive tasks. The tasks are substituted by annotated events that allow the removal of silent tasks and reduce the complexity of the model. An important feature of the methods proposed in this paper is that they are independent from the actual miner used for process discovery.Peer ReviewedPostprint (author's final draft

Procesos de decisión en la antiagregación (IV): Síndrome Coronario Agudo

El síndrome coronario agudo es la entidad patológica donde los tratamientos de antiagregación o anticoagulación se vuelven más elaborados. Las terapias múltiples, los nuevos antiagregantes y la gran producción científica que genera cambios en las recomendaciones, cambios apoyados por una potente industria farmacéutica, puede complicar la toma de decisiones preoperatorias. En anteriores entradas hemos hablado sobre la profilaxis primaria de la isquemia cardíaca, y vemos como las recomendaciones sobre su tratamiento preventivo han ido evolucionado para ser cada vez más restrictivas. Los descubrimientos de nuevos factores individuales (tanto genéticos como ambientales) que desempeñen un papel fundamental en la incidencia del síndrome coronario son cada vez más estudiados y aclarados. Desde el descubrimiento de los isotipos del gen de la paraoxonasa-1, pasando por la implicación del perímetro abdominal, hasta llegar a la polución ambiental, se vislumbran con fuerza estos y otros nuevos factores individuales implicados en la aparición de un episodio isquémico coronario, lo que condicionará un cambio de recomendación en las guías futuras para prevenir dichos eventos

Anticipating Future Risks of Climate-Driven Wildfires in Boreal Forests

Extreme forest fires have historically been a significant concern in Canada, the Russian Federation, the USA, and now pose an increasing threat in boreal Europe. This paper deals with application of the wildFire cLimate impacts and Adaptation Model (FLAM) in boreal forests. FLAM operates on a daily time step and utilizes mechanistic algorithms to quantify the impact of climate, human activities, and fuel availability on wildfire probabilities, frequencies, and burned areas. In our paper, we calibrate the model using historical remote sensing data and explore future projections of burned areas under different climate change scenarios. The study consists of the following steps: (i) analysis of the historical burned areas over 2001–2020; (ii) analysis of temperature and precipitation changes in the future projections as compared to the historical period; (iii) analysis of the future burned areas projected by FLAM and driven by climate change scenarios until the year 2100; (iv) simulation of adaptation options under the worst-case scenario. The modeling results show an increase in burned areas under all Representative Concentration Pathway (RCP) scenarios. Maintaining current temperatures (RCP 2.6) will still result in an increase in burned area (total and forest), but in the worst-case scenario (RCP 8.5), projected burned forest area will more than triple by 2100. Based on FLAM calibration, we identify hotspots for wildland fires in the boreal forest and suggest adaptation options such as increasing suppression efficiency at the hotspots. We model two scenarios of improved reaction times—stopping a fire within 4 days and within 24 h—which could reduce average burned forest areas by 48.6% and 79.2%, respectively, compared to projected burned areas without adaptation from 2021–2099