Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series

A Bayesian classifier mapped the Burned Area (BA) in the Northeastern Siberian boreal forest (70°N 120°E–60°N 170°E) from 1982 to 2015. The algorithm selected the 0.05° (~5 km) Long-Term Data Record (LTDR) version 3 and 4 data sets to generate 10-day BA composites. Landsat-TM scenes of the entire study site in 2002, 2010, and 2011 assessed the spatial accuracy of this LTDR-BA product, in comparison to Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD45A1 and MCD64A1 BA products. The LTDR-BA algorithm proves a reliable source to quantify BA in this part of Siberia, where comprehensive BA remote sensing products since the 1980s are lacking. Once grouped by year and decade, this study explored the trends in fire activity. The LTDR-BA estimates contained a high interannual variability with a maximum of 2.42 million ha in 2002, an average of 0.78 million ha/year, and a standard deviation of 0.61 million ha. Going from 6.36 in the 1980s to 10.21 million ha BA in the 2010s, there was a positive linear BA trend of approximately 1.28 million ha/decade during these last four decades in the Northeastern Siberian boreal forest

Mapping Chestnut Stands Using Bi-Temporal VHR Data

This study analyzes the potential of very high resolution (VHR) remote sensing images and extended morphological profiles for mapping Chestnut stands on Tenerife Island (Canary Islands, Spain). Regarding their relevance for ecosystem services in the region (cultural and provisioning services) the public sector demand up-to-date information on chestnut and a simple straight-forward approach is presented in this study. We used two VHR WorldView images (March and May 2015) to cover different phenological phases. Moreover, we included spatial information in the classification process by extended morphological profiles (EMPs). Random forest is used for the classification process and we analyzed the impact of the bi-temporal information as well as of the spatial information on the classification accuracies. The detailed accuracy assessment clearly reveals the benefit of bi-temporal VHR WorldView images and spatial information, derived by EMPs, in terms of the mapping accuracy. The bi-temporal classification outperforms or at least performs equally well when compared to the classification accuracies achieved by the mono-temporal data. The inclusion of spatial information by EMPs further increases the classification accuracy by 5% and reduces the quantity and allocation disagreements on the final map. Overall the new proposed classification strategy proves useful for mapping chestnut stands in a heterogeneous and complex landscape, such as the municipality of La Orotava, Tenerife

RanBP2-Mediated SUMOylation Promotes Human DNA Polymerase Lambda Nuclear Localization and DNA Repair

Cellular DNA is under constant attack by a wide variety of agents, both endogenous and exogenous. To counteract DNA damage, human cells have a large collection of DNA repair factors. Among them, DNA polymerase lambda (Polλ) stands out for its versatility, as it participates in different DNA repair and damage tolerance pathways in which gap-filling DNA synthesis is required. In this work we show that human Polλ is conjugated with Small Ubiquitin-like MOdifier (SUMO) proteins both in vitro and in vivo, with Lys27 being the main target of this covalent modification. Polλ SUMOylation takes place in the nuclear pore complex and is mediated by the E3 ligase RanBP2. This post-translational modification promotes Polλ entry into the nucleus, which is required for its recruitment to DNA lesions and stimulated by DNA damage induction. Our work represents an advance in the knowledge of molecular pathways that regulate cellular localization of human Polλ, which are essential to be able to perform its functions during repair of nuclear DNA, and that might constitute an important point for the modulation of its activity in human cells

Evaluation of a Bayesian Algorithm to Detect Burned Areas in the Canary Islands’ Dry Woodlands and Forests Ecoregion Using MODIS Data

Burned Area (BA) is deemed as a primary variable to understand the Earth’s climate system. Satellite remote sensing data have allowed for the development of various burned area detection algorithms that have been globally applied to and assessed in diverse ecosystems, ranging from tropical to boreal. In this paper, we present a Bayesian algorithm (BY-MODIS) that detects burned areas in a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2002 to 2012 of the Canary Islands’ dry woodlands and forests ecoregion (Spain). Based on daily image products MODIS, MOD09GQ (250 m), and MOD11A1 (1 km), the surface spectral reflectance and the land surface temperature, respectively, 10 day composites were built using the maximum temperature criterion. Variables used in BY-MODIS were the Global Environment Monitoring Index (GEMI) and Burn Boreal Forest Index (BBFI), alongside the NIR spectral band, all of which refer to the previous year and the year the fire took place in. Reference polygons for the 14 fires exceeding 100 hectares and identified within the period under analysis were developed using both post-fire LANDSAT images and official information from the forest fires national database by the Ministry of Agriculture and Fisheries, Food and Environment of Spain (MAPAMA). The results obtained by BY-MODIS can be compared to those by official burned area products, MCD45A1 and MCD64A1. Despite that the best overall results correspond to MCD64A1, BY-MODIS proved to be an alternative for burned area mapping in the Canary Islands, a region with a great topographic complexity and diverse types of ecosystems. The total burned area detected by the BY-MODIS classifier was 64.9% of the MAPAMA reference data, and 78.6% according to data obtained from the LANDSAT images, with the lowest average commission error (11%) out of the three products and a correlation (R2) of 0.82. The Bayesian algorithm—originally developed to detect burned areas in North American boreal forests using AVHRR archival data Long-Term Data Record—can be successfully applied to a lower latitude forest ecosystem totally different from the boreal ecosystem and using daily time series of satellite images from MODIS with a 250 m spatial resolution, as long as a set of training areas adequately characterising the dynamics of the forest canopy affected by the fire is defined

Regulation of human Polλ by ATM-mediated phosphorylation during Non-Homologous End Joining

DNA double strand breaks (DSBs) trigger a variety of cellular signaling processes, collectively termed the DNA-damage response (DDR), that are primarily regulated by protein kinase ataxia-telangiectasia mutated (ATM). Among DDR activated processes, the repair of DSBs by non-homologous end joining (NHEJ) is essential. The proper coordination of NHEJ factors is mainly achieved through phosphorylation by an ATM-related kinase, the DNA-dependent protein kinase catalytic subunit (DNA-PKcs), although the molecular basis for this regulation has yet to be fully elucidated. In this study we identify the major NHEJ DNA polymerase, DNA polymerase lambda (Polλ), as a target for both ATM and DNA-PKcs in human cells. We show that Polλ is efficiently phosphorylated by DNA-PKcs in vitro and predominantly by ATM after DSB induction with ionizing radiation (IR) in vivo. We identify threonine 204 (T204) as a main target for ATM/DNA-PKcs phosphorylation on human Polλ, and establish that its phosphorylation may facilitate the repair of a subset of IR-induced DSBs and the efficient Polλ-mediated gap-filling during NHEJ. Molecular evidence suggests that Polλ phosphorylation might favor Polλ interaction with the DNA-PK complex at DSBs. Altogether, our work provides the first demonstration of how Polλ is regulated by phosphorylation to connect with the NHEJ core machinery during DSB repair in human cells.España MINECO y la Comisión Europea (European Regional Development Fund) to J.F.R. RYC-2011-08752, BFU2013-44343-P) and to F.C-L. (SAF2014-55532-R)

Evaluación de un algoritmo para detección de áreas quemadas en bosques de Canarias

Se aplicó un clasificador bayesiano, inicialmente desarrollado y validado con éxito para la detección de áreas quemadas en regiones de bosque boreal usando el conjunto de datos LTDR (Long-Term Data Record) de 0,05º (~ 5 km) de resolución espacial, a una serie temporal de imágenes diarias Terra-MODIS de zonas forestales de Monteverde y Pinar de las Islas Canarias para el periodo 2002-2012. A partir de los dos productos MODIS, MOD09GQ (250 m) y MOD11A1 (1 km), que representan las imágenes diarias de reflectancia y temperatura de superficie respectivamente, se construyeron compuestos de 10 días mediante el criterio de máxima temperatura. Las variables estadísticas utilizadas en el clasificador bayesiano fueron los índices de vegetación GEMI y BBFI, junto con la banda espectral NIR, todos ellos relativos al año anterior y al año de ocurrencia del incendio. Se crearon polígonos de referencia de los 14 incendios mayores de 100 hectáreas identificados en el periodo analizado, utilizando conjuntamente imágenes LANDSAT post-fuego e información oficial de la base de datos nacional de incendios forestales del Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA). El algoritmo de detección se entrenó usando un incendio producido en el sur de Tenerife en julio de 2012 que afectó a más de 6000 ha. Los resultados muestran que 13 de los 14 incendios registrados en ese periodo en el conjunto de las Islas Canarias, fueron detectados. El área total quemada detectada supone un 64,9% de los datos de referencia del MAGRAMA y un 78,6% según los datos obtenidos a partir de las imágenes LANDSAT. La aplicación de la metodología propuesta podría mejorar estos resultados considerando otros criterios de composición, índices de vegetación, variables estadísticas y/o región de entrenamiento, que mejor caractericen la respuesta espectral de la dinámica de la cobertura forestal de las Islas Canarias afectada por el fueg

A Multiple Stakeholder Multicriteria Decision Analysis in Diabetic Macular Edema Management: The MULTIDEX‑EMD Study

Background The clinical and economic management of retinal diseases has become more complex following the introduction of new intravitreal treatments. Multicriteria decision analysis (MCDA) offers the potential to overcome the challenges associated with traditional decision-making tools. Objectives A MCDA to determine the most relevant criteria to decision-making in the management of diabetic macular edema (DME) based on the perspectives of multiple stakeholders in Spain was developed. This MCDA was termed the MULTIDEX-EMD study. Methods Nineteen stakeholders (7 physicians, 4 pharmacists, 5 health authorities and health management experts, 1 psychologist, and 2 patient representatives) participated in this three-phase project. In phase A, an advisory board defined all of the criteria that could influence DME treatment decision-making. These criteria were then screened using a discrete choice experiment (DCE) (phase B). Next, a multinomial logit model was fitted by applying the backward elimination algorithm (relevant criteria: p value = 15 letters (p value < 0.001), effect duration per administration (p value = 0.008), retinal detachment (p value < 0.001), endophthalmitis (p value = 0.012), myocardial infarction (p value < 0.001), intravitreal hemorrhage (p value = 0.021), annual treatment cost per patient (p value = 0.001), health-related quality of life (HRQoL) (p value = 0.004), and disability level (p value = 0.021). Conclusions From a multi-stakeholder perspective, the selection of an appropriate treatment for DME patients should guarantee patient safety and maximize the visual acuity improvement and treatment effect duration. It should also contribute to system sustainability by being affordable, it should have a positive impact on HRQoL, and it should prevent disability

LSP Influence on Mechanical Properties of Thin Dissimilar Laser Welded Joints

Assessment of laser shock processing effects on mechanical resistance of thin dissimilar laser welded joint

Implementación de Servicios en Nethserver: Un Enfoque IEEE

todas las imágenes fueron tomadas haciendo uso de los aplicativos mencionados en las referencias y de acuerdo al desarrollo d la actividad se hizo captura de estas como fuentes propias.Este documento IEEE presenta una implementación integral de servicios de infraestructura IT en Nethserver. Incluye la instalación inicial del sistema en un entorno virtualizado, seguida de la configuración detallada de DHCP, DNS, Controlador de Dominio, Proxy y Cortafuegos. Se abordan temáticas adicionales, como File Server, Print Server y VPN, destacando la gestión eficiente de recursos y la seguridad de la red. Cada sección proporciona pasos detallados para configurar y validar servicios clave. En resumen, el documento sirve como guía completa para administradores de sistemas que buscan establecer una infraestructura robusta y segura en Nethserver, promoviendo la eficiencia operativa y la facilidad de administración. Se referencian fuentes oficiales de Nethserver y comunidades para respaldar la implementaciónThis IEEE document presents a comprehensive implementation of IT infrastructure services on Nethserver. It includes the initial installation of the system in a virtualized environment, followed by detailed configuration of DHCP, DNS, Domain Controller, Proxy and Firewall. Additional topics are covered, such as File Server, Print Server and VPN, highlighting efficient resource management and network security. Each section provides steps details to configure and validate key services. In summary, the document serves as a comprehensive guide for system administrators seeking to establish a robust and secure Nethserver infrastructure, promoting operational efficiency and ease of management. Official Nethserver sources and communities are referenced to support implementatio