Actividad antimicrobiana de cuatro especies del género Piper y elucidación estructural de sus aceites esenciales

Investigación de naturaleza descriptiva, transversal y experimental. Tiene por finalidad determinar la actividad antimicrobiana in vitro de los aceites esenciales y extractos etanólicos de hojas de Piper acutifolium Ruiz & Pav., Piper carpunya Ruiz & Pav., Piper callosum Ruiz & Pav. y Piper amalago L., recolectadas en los departamentos de Cajamarca, Loreto y Amazonas, y la elucidación estructural de los componentes de sus aceites esenciales. La actividad antimicrobiana se evalúa mediante el método de difusión en agar y se determina la Concentración Mínima Inhibitoria (CMI) por el método de microdilución colorimétrica frente a Staphylococcus aureus ATCC 25923, Staphylococcus aureus meticilina resistente ATCC 33591, Staphylococcus epidermidis ATCC 12228, Bacillus subtilis cepa ambiental, Bacillus cereus cepa alimentaria, Pseudomonas aeruginosa ATCC 27853, Escherichia coli ATCC 25922 y Candida albicans ATCC 10231. Los aceites esenciales de P. acutifolium Ruiz & Pav., P. callosum Ruiz & Pav. y P. amalago L. presentan actividad antimicrobiana significativa frente a S. epidermidis y B. cereus, mientras que el extracto etanólico de P. acutifolium Ruiz & Pav. muestra actividad frente a B. subtilis (halos de inhibición > 18 mm). Por el método de microdilución, los aceites esenciales y los extractos etanólicos muestran actividad antimicrobiana con una CMI de 0.12 ± 0.06 a 0.26 ± 0.09 μL/mL y una CMI de 5.86 ± 2.76 a 145.83 ± 95.47 μg/mL solo frente a las bacterias Gram positivas en estudio. Además todos los aceites esenciales y el extracto etanólico de P. callosum Ruiz & Pav. presentan buena actividad frente a C. albicans. La elucidación estructural se realiza mediante Cromatografía de Gases/ Espectrometría de Masas (CG/EM) y revela que los sesquiterpenos son los componentes mayoritarios, seguidos de los monoterpenos y fenilpropanoides.Tesi

Wheat yield prediction in Andalucía using MERIS Terrestrial Chlorophyll Index (MTCI) time series

[EN] There is a relationship between net primary production of wheat and vegetation indices obtained from satellite imaging. Most wheat production studies use the Normalised Difference Vegetation Index (NDVI) to estimate the production and yield of wheat and other crops. On the one hand, few studies use the MERIS Terrestrial Chlorophyll Index (MTCI) to determine crop yield and production on a regional level. This is possibly due to a lack of continuity of MERIS. On the other hand, the emergence of Sentinel 2 open new possibilities for the research and application of MTCI. This study has built two empirical models to estimate wheat production and yield in Andalusia. To this end, the study used the complete times series (weekly images from 2006–2011) of the MTCI vegetation index from the Medium Resolution Imaging Spectrometer (MERIS) sensor associated with the Andalusian yearbook for agricultural and fishing statistics (AEAP—Anuario de estadísticas agrarias y pesqueras de Andalucía). In order to build these models, the optimal development period for the plant needed to be identified, as did the time-based aggregation of MTCI values using said optimal period as a reference, and relation with the index, with direct observations of production and yield through spatial aggregation using coverage from the Geographic Information System for Agricultural Parcels (SIGPAC—Sistema de información geográfica de parcelas agrícolas) and requests for common agricultural policy (CAP) assistance. The obtained results indicate a significant association between the MTCI index and the production and yield data collected by AEAP at the 95% confidence level (R2 =0.81 and R2 =0.57, respectively).[ES] Existe una relación entre la producción primaria neta del trigo y los índices de vegetación obtenidos de imágenes de satélite. Con frecuencia se utiliza el NDVI (Normalized Difference Vegetation Index) para la estimación de producción y rendimiento de trigo y otros cultivos. Sin embargo, hay pocas investigaciones que utilicen el índice MTCI (MERIS Terrestrial Chlorophyll Index) para conocer el rendimiento y la producción de los cultivos a una escala regional posiblemente debido a la falta de continuidad del sensor MERIS. No obstante, la posibilidad del cálculo de MTCI a partir de Sentinel 2 abre nuevas oportunidades para su aplicación e investigación. En esta investigación se han generado dos modelos empíricos de estimación de producción y rendimiento de trigo en Andalucía. Para ello, se ha empleado la serie temporal completa (imágenes semanales de 2006 a 2011) del índice de vegetación MTCI del sensor satelital MERIS (Medium Resolution Imaging Spectrometer) asociada a los datos de producción y rendimiento del Anuario de estadísticas agrarias y pesqueras de Andalucía (AEAP). Para la creación de estos modelos ha sido necesaria la identificación del periodo óptimo del desarrollo de la planta, la agregación temporal de los valores MTCI usando ese momento óptimo como referencia, relacionar ese índice con observaciones directas de producción y rendimiento a través de agregaciones espaciales mediante la utilización de coberturas SIGPAC y las solicitudes de ayudas PAC, caracterizar la variación del índice en función del año de cultivo y relacionarlo con los datos estadísticos. Los resultados obtenidos indican una correlación estadísticamente significativa (p-valor < 0,05) entre el índice MTCI y los datos de producción y rendimiento recogidos por AEAP (R2=0,81 y 0,57, respectivamente).Agradecemos la financiación obtenida de MINECO (Proyectos BIA2013-43462-P, CSO2014-51994-P) y de la Junta de Andalucía (Grupo Investigación RNM177).Egea-Cobrero, V.; Rodriguez-Galiano, V.; Sánchez-Rodríguez, E.; García-Pérez, M. (2018). 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Assimilating remotely sensed information with the wheatgrow model based on the ensemble square root filter for improving regional wheat yield forecasts. Plant Production Science, 16(4), 352-364. https://doi.org/10.1626/pps.16.352ITACyL, AEMET, Consejería de Agricultura y Ganadería de la Junta de Castilla y León. 2016. Boletín de predicción de cosechas de Castilla y León. Recuperado 25 de octubre de 2016, a partir de https://cosechas.itacyl.es/es/inicioJégo, G., Pattey, E., Liu, J. 2012. Using Leaf Area Index, retrieved from optical imagery, in the STICS crop model for predicting yield and biomass of field crops. Field Crops Research, 131, 63-74. https://doi. org/10.1016/j.fcr.2012.02.012Johnson, M.D., Hsieh, W.W., Cannon, A.J., Davidson, A., Bédard, F. 2016. Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods. 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Automated underwriting in life insurance: Predictions and optimisation

© Springer International Publishing AG, part of Springer Nature 2018. Underwriting is an important stage in the life insurance process and is concerned with accepting individuals into an insurance fund and on what terms. It is a tedious and labour-intensive process for both the applicant and the underwriting team. An applicant must fill out a large survey containing thousands of questions about their life. The underwriting team must then process this application and assess the risks posed by the applicant and offer them insurance products as a result. Our work implements and evaluates classical data mining techniques to help automate some aspects of the process to ease the burden on the underwriting team as well as optimise the survey to improve the applicant experience. Logistic Regression, XGBoost and Recursive Feature Elimination are proposed as techniques for the prediction of underwriting outcomes. We conduct experiments on a dataset provided by a leading Australian life insurer and show that our early-stage results are promising and serve as a foundation for further work in this space

Celosía set di Lucidi, juego de transparencias desde nuevas piezas cerámicas: Lattice set di Lucidi, transparency game from new ceramic pieces

In architecture it is necessary to always articulate the guidelines of comfort in the designs, and these can be very delimited according to the comfort one wishes to solve, so to speak of thermal comfort can result from the diverse use of passive and active techniques of bioclimatic Focused on the solution of passive techniques, the lattices are presented, as a technique of ventilation and natural lighting to the architectural spaces, but at the same time it is a technique with little innovation and technological updating, for which reason the present investigation proposes the design of lattices as passive thermal comfort techniques applied to facades from the combination of metal structures that serve as an assembly between the modules. The design starts from a methodology of three phases, which present analysis of the context, documentary research, and design proposal, articulating specialized software such as AutoCAD and Revit for modeling and solar analysis, and applying similar research results in the planimetry of the piece. The result is a design of a lattice without enamel that can be used from non-structural modules such as the skin of the building, which has a particular design that responds to thermal comfort components and technical and technological innovation in the San José de Cúcuta region, in Norte de Santander.En la arquitectura es necesario articular siempre los lineamientos de confort en los diseños, y estos pueden estar muy delimitados según sea el bienestar que se desee resolver, por lo que hablar de confort térmico puede dar como resultado el uso diversas de técnicas pasivas y activas de bioclimática. Enfocado en la solución de técnicas pasivas se presentan las celosías, como método de ventilación e iluminación natural en los espacios arquitectónicos, pero que a su vez es un sistema con poca innovación y actualización tecnológica, por lo que la presente investigación plantea el diseño de celosías como técnicas pasivas para la comodidad térmica aplicado en fachadas desde la combinación de estructuras metálicas que cumplan la función de ensamble entre los módulos. El diseño parte desde una metodología de tres fases, que presentan análisis del contexto, investigación documental, y propuesta de diseño, articulando software especializados como AutoCAD Y Revit para el modelado y análisis solar, aplicando resultados de investigaciones similares en la planimetría de la pieza. El resultado es de diseño de una celosía sin esmalte que puede ser usada desde módulos no estructurales como la piel del edificio, que presenta un desempeño particular que responde a componentes de confort térmico y de innovación técnica y tecnológica en la región de San José de Cúcuta, en Norte de Santander

Celosía set di Lucidi, juego de transparencias desde nuevas piezas cerámicas: Lattice set di Lucidi, transparency game from new ceramic pieces

In architecture it is necessary to always articulate the guidelines of comfort in the designs, and these can be very delimited according to the comfort one wishes to solve, so to speak of thermal comfort can result from the diverse use of passive and active techniques of bioclimatic Focused on the solution of passive techniques, the lattices are presented, as a technique of ventilation and natural lighting to the architectural spaces, but at the same time it is a technique with little innovation and technological updating, for which reason the present investigation proposes the design of lattices as passive thermal comfort techniques applied to facades from the combination of metal structures that serve as an assembly between the modules. The design starts from a methodology of three phases, which present analysis of the context, documentary research, and design proposal, articulating specialized software such as AutoCAD and Revit for modeling and solar analysis, and applying similar research results in the planimetry of the piece. The result is a design of a lattice without enamel that can be used from non-structural modules such as the skin of the building, which has a particular design that responds to thermal comfort components and technical and technological innovation in the San José de Cúcuta region, in Norte de Santander.En la arquitectura es necesario articular siempre los lineamientos de confort en los diseños, y estos pueden estar muy delimitados según sea el bienestar que se desee resolver, por lo que hablar de confort térmico puede dar como resultado el uso diversas de técnicas pasivas y activas de bioclimática. Enfocado en la solución de técnicas pasivas se presentan las celosías, como método de ventilación e iluminación natural en los espacios arquitectónicos, pero que a su vez es un sistema con poca innovación y actualización tecnológica, por lo que la presente investigación plantea el diseño de celosías como técnicas pasivas para la comodidad térmica aplicado en fachadas desde la combinación de estructuras metálicas que cumplan la función de ensamble entre los módulos. El diseño parte desde una metodología de tres fases, que presentan análisis del contexto, investigación documental, y propuesta de diseño, articulando software especializados como AutoCAD Y Revit para el modelado y análisis solar, aplicando resultados de investigaciones similares en la planimetría de la pieza. El resultado es de diseño de una celosía sin esmalte que puede ser usada desde módulos no estructurales como la piel del edificio, que presenta un desempeño particular que responde a componentes de confort térmico y de innovación técnica y tecnológica en la región de San José de Cúcuta, en Norte de Santander

Characterizing degradation of palm swamp peatlands from space and on the ground: an exploratory study in the Peruvian Amazon

Peru has the fourth largest area of peatlands in the Tropics. Its most representative land cover on peat is a Mauritia flexuosa dominated palm swamp (thereafter called dense PS), which has been under human pressure over decades due to the high demand for the M. flexuosa fruit often collected by cutting down the entire palm. Degradation of these carbon dense forests can substantially affect emissions of greenhouse gases and contribute to climate change. The first objective of this research was to assess the impact of dense PS degradation on forest structure and biomass carbon stocks. The second one was to explore the potential of mapping the distribution of dense PS with different degradation levels using remote sensing data and methods. Biomass stocks were measured in 0.25 ha plots established in areas of dense PS with low (n = 2 plots), medium (n = 2) and high degradation (n = 4). We combined field and remote sensing data from the satellites Landsat TM and ALOS/PALSAR to discriminate between areas typifying dense PS with low, medium and high degradation and terra firme, restinga and mixed PS (not M. flexuosa dominated) forests. For this we used a Random Forest machine learning classification algorithm. Results suggest a shift in forest composition from palm to woody tree dominated forest following degradation. We also found that human intervention in dense PS translates into significant reductions in tree carbon stocks with initial (above and below-ground) biomass stocks (135.4 ± 4.8 Mg C ha−1) decreased by 11 and 17% following medium and high degradation. The remote sensing analysis indicates a high separability between dense PS with low degradation from all other categories. Dense PS with medium and high degradation were highly separable from most categories except for restinga forests and mixed PS. Results also showed that data from both active and passive remote sensing sensors are important for the mapping of dense PS degradation. Overall land cover classification accuracy was high (91%). Results from this pilot analysis are encouraging to further explore the use of remote sensing data and methods for monitoring dense PS degradation at broader scales in the Peruvian Amazon. Providing precise estimates on the spatial extent of dense PS degradation and on biomass and peat derived emissions is required for assessing national emissions from forest degradation in Peru and is essential for supporting initiatives aiming at reducing degradation activities

Inter-comparison of satellite sensor land surface phenology and ground phenology in Europe

Land surface phenology (LSP) and ground phenology (GP) are both important sources of information for monitoring terrestrial ecosystem responses to climate changes. Each measures different vegetation phenological stages and has different sources of uncertainties, which make comparison in absolute terms challenging, and therefore, there has been limited attempts to evaluate the complementary nature of both measures. However, both LSP and GP are climate driven and therefore should exhibit similar interannual variation. LSP obtained from the whole time series of Medium-Resolution Imaging Spectrometer data was compared to thousands of deciduous tree ground phenology records of the Pan European Phenology network (PEP725). Correlations observed between the interannual time series of the satellite sensor estimates of phenology and PEP725 records revealed a close agreement (especially for Betula Pendula and Fagus Sylvatica species). In particular, 90% of the statistically significant correlations between LSP and GP were positive (mean R2 = 0.77). A large spatiotemporal correlation was observed between the dates of the start of season (end of season) from space and leaf unfolding (autumn coloring) at the ground (pseudo R2 of 0.70 (0.71)) through the application of nonlinear multivariate models, providing, for the first time, the ability to predict accurately the date of leaf unfolding (autumn coloring) across Europe (root-mean-square error of 5.97 days (6.75 days) over 365 days)

Assessing Visual Attention Using Eye Tracking Sensors in Intelligent Cognitive Therapies Based on Serious Games

This study examines the use of eye tracking sensors as a means to identify children's behavior in attention-enhancement therapies. For this purpose, a set of data collected from 32 children with different attention skills is analyzed during their interaction with a set of puzzle games. The authors of this study hypothesize that participants with better performance may have quantifiably different eye-movement patterns from users with poorer results. The use of eye trackers outside the research community may help to extend their potential with available intelligent therapies, bringing state-of-the-art technologies to users. The use of gaze data constitutes a new information source in intelligent therapies that may help to build new approaches that are fully-customized to final users' needs. This may be achieved by implementing machine learning algorithms for classification. The initial study of the dataset has proven a 0.88 (±0.11) classification accuracy with a random forest classifier, using cross-validation and hierarchical tree-based feature selection. Further approaches need to be examined in order to establish more detailed attention behaviors and patterns among children with and without attention problems

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability

Land surface temperature and vegetation index as a proxy to microclimate

The effect of global climate change on the temperature of urban areas has become more pronounced in the past couple decades, impacting population and quality of life. The United Nations (UN), the National Aeronautics and Space Administration (NASA) and the Intergovernmental Panel on Climate Change (IPCC) have emphasized the impact of urban structures on microclimatic. A better understanding of these effects is important to formulate effective strategies that would contribute to address the impacts of increased urban growth. Here we address a case study of the Vila Rodrigues neighborhood, located in Passo Fundo City in southern Brazil to analyze the variations of emissivity, temperature and vegetation of the terrestrial surface, with influence of buildings. We employ Landsat satellite images, and unpublished data provided by the NASA, interpolated and classified in the QGIS software, using Bands 4, 5 and 10, converted to Gray Level (NC). This procedure allowed the spectral radiance of the reflectance temperature to be obtained. The Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) were used, with correction of emissivity and spectral error, in the identification of the surface temperature of different areas in the Villa Rodrigues. The results showed a total variation of 3.86ºC among the sampled points, which is increased by the difference in significance of the thermal balance in urban areas under open sky with buildings. We suggest that green areas and parks with abundant vegetative cover and the application of new building materials in future constructions would help to improve the urban climate, and such regulation of the local temperature on global scale is an effective step towards addressing the adverse effects from climate change