Embryogenesis in Oak species. A Review.

Embryogenesis in Oak species. A Review

Propiedades psicométricas del Pain and Sensitivity Reactivity Scales (PSRS) en población neurotípica infantojuvenil

La percepción del dolor y la reactividad sensorial se presenta como una tarea difícil para la ciencia al ser considera una respuesta subjetiva que depende de diferencias individuales. Esta dificultad se incrementa aún más si la población de estudio incluye a niños y a adolescentes. Para la medición de esta respuesta se pueden utilizar medidas neurofisiológicas o escalas estandarizadas que cuantifiquen la información. Esta evaluación es de suma importancia, ya que puede detectar si existe una dificultad para recibir e interpretar los estímulos sensoriales tanto exteroceptivos como interoceptivos. Sin embargo, aún no existe una escala dimensional para población infanto-juvenil que aborde este campo. El objetivo de este estudio es presentar las propiedades psicométricas del Pain and Sensitivity Reactivity Scale (PSRS) en población infanto-juvenil neurotípica. La muestra está formada por más de 1000 niños y adolescentes de 12 a 17 años. La versión infanto-juvenil de la PSRS está formada tres escalas que hacen referencia al dolor, la hiposensibilidad e hipersensibilidad. Los resultados muestran una consistencia interna adecuada tanto para las diferentes escalas y como para el instrumento. Por último, en el análisis factorial exploratorio aparecen las tres dimensiones principales. En conclusión, poder evaluar la percepción del dolor y la reactividad sensorial en población infanto-juvenil puede ayudar a contextualizar problemas conductuales, emocionales e incluso académicos que pueden estar encubiertos por el desconocimiento que tanto el propio individuo muestra sobre su percepción como por el desconocimiento que familiares y profesionales de la educación presentan sobre las diferencias en la reactividad sensorial y la percepción del dolor.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

All-cause mortality in the cohorts of the Spanish AIDS Research Network (RIS) compared with the general population: 1997Ł2010

Abstract Background: Combination antiretroviral therapy (cART) has produced significant changes in mortality of HIVinfected persons. Our objective was to estimate mortality rates, standardized mortality ratios and excess mortality rates of cohorts of the AIDS Research Network (RIS) (CoRIS-MD and CoRIS) compared to the general population. Methods: We analysed data of CoRIS-MD and CoRIS cohorts from 1997 to 2010. We calculated: (i) all-cause mortality rates, (ii) standardized mortality ratio (SMR) and (iii) excess mortality rates for both cohort for 100 personyears (py) of follow-up, comparing all-cause mortality with that of the general population of similar age and gender. Results: Between 1997 and 2010, 8,214 HIV positive subjects were included, 2,453 (29.9%) in CoRIS-MD and 5,761 (70.1%) in CoRIS and 294 deaths were registered. All-cause mortality rate was 1.02 (95% CI 0.91-1.15) per 100 py, SMR was 6.8 (95% CI 5.9-7.9) and excess mortality rate was 0.8 (95% CI 0.7-0.9) per 100 py. Mortality was higher in patients with AIDS, hepatitis C virus (HCV) co-infection, and those from CoRIS-MD cohort (1997. Conclusion: Mortality among HIV-positive persons remains higher than that of the general population of similar age and sex, with significant differences depending on the history of AIDS or HCV coinfection

Stand structure, competition and growth of Scots pine (Pinus sylvestris L.) in a Mediterranean mountainous environment

The relationship between competition and tree growth was studied in four stands of Pinus sylvestris L. occurring in a continental Mediterranean mountain area (in the Guadarrama range, Spain), i.e., an uneven-aged stand, a stand with oak (Quercus pyrenaica Willd.) understorey, a plantation, and a mature even-aged stand. Competition was measured by a simple size-ratio distance-independent index and was negatively associated with tree diameter. This negative association was stronger in the uneven-aged, plantation and mature even-aged stands than in the stand with oak understorey. Competition was also negatively associated with current diameter increment. This relationship was moderately strong in the mature even-aged stand and weak in the uneven-aged stand and the plantation. In the uneven-aged and the mature even-aged stands, a weakly significant relationship was found between diameter growth and tree size, whereas these parameters were not associated in the stand with oak understorey. The competition index provided a better prediction of growth rate than the alternative use of diameter. Both diameter and basal area growth were greater in the uneven-aged than in the even-aged stands.Structure des peuplements, compétition et croissance du pin sylvestre (Pinus sylvestris L.) dans un environnement montagneux méditerranéen. La relation entre compétition et croissance a été étudiée dans quatre peuplements de Pinus sylvestris L. que l'on rencontre dans la zone continentale des montagnes méditerranéennes (dans la région de Guadarrama en Espagne). Ont été pris en compte un peuplement inéquienne, un peuplement avec du chêne (Quercus pyrenaica Willd.) en sous–étage, une plantation, et un peuplement équienne âgé. La compétition a été mesurée par un index indépendant, simple rapport taille/distance, et était corrélée négativement avec le diamètre des arbres. Cette corrélation négative était plus forte dans le peuplement inéquienne, la plantation et le peuplement équienne âgé que dans le peuplement avec sous-étage de chêne. L'index de compétition était aussi corrélé négativement avec l'accroissement courant en diamètre. La relation était modérément forte dans le peuplement équienne âgé et faible dans le peuplement inéquienne et la plantation. Dans le peuplement inéquienne et le peuplement équienne âgé une relation faiblement significative a été trouvée entre croissance en diamètre et taille de l'arbre, alors que ces paramètres n'étaient pas corrélés dans le peuplement avec sous-étage de chêne. L'index de compétition fournit une meilleure prédiction du taux de croissance que le simple diamètre. La croissance en diamètre et en surface terrière était plus importante dans le peuplement inéquienne que dans le peuplement équienne âgé

Employing False Color Infrared Cameras for Biomass Estimation on Natural Grassland

Natural grasslands occupy up to 40.5% of Earth’s terrestrial surface (Monson, 2014) and provide important ecosystem services as well as supporting livestock production systems. Broadly, grazing-management is a fine equilibrium between three parameters: stocking rates, biomass and grazing-period. From these, biomass estimation is the most critical parameter to measure, thus, manage, given that its estimation is part of a complex and dynamic system, made even more difficult by the large spatial heterogeneity, seasonal and inter-annual variability of forage resources. Remote sensing techniques have long been proposed as a solution to such topic (Tucker, 1979). However, it has not become a widely utilized tool given the absence of an accurate, timely and cost-effectivemethods available for end-users, mostly due to inadequate spatial and temporal resolutions of available data. To bridge such gap, remotely piloted aircraft systems (RPAS) have been the subject of intense research in the recent past. In fact, within the past five years, several purposely built RPAS multispectral sensors became commercially available and a large extent of image-processing (mosaicking and radiometric calibration) can now be executed on the cloud (i.e. remotely.) Prior to such developments, however, modified digital cameras (off-the shelf) were commonly employed as false colour-infrared broadband sensors. This study examines the use of a RPAS and modified digital cameras as a tool for instantaneous measurement of forage biomass (dry matter perhectare) utilizing digital number (DN) as a proxy for reflectance values. The ability of automating a mostly manual task (biomass estimation) using a simple method could be worthwhile to end-users

Most similar neighbor imputation of forest attributes using metrics derived from combined airborne LIDAR and multispectral sensors

<p>In the context of predicting forest attributes using a combination of airborne LIDAR and multispectral (MS) sensors, we suggest the inclusion of normalized difference vegetation index (NDVI) metrics along with the more traditional LIDAR height metrics. Here the data fusion method consists of back-projecting LIDAR returns onto original MS images, avoiding co-registration errors. The prediction method is based on non-parametric imputation (the most similar neighbor). Predictor selection and accuracy assessment include hypothesis tests and over-fitting prevention methods. Results show improvements when using combinations of LIDAR and MS compared to using either of them alone. The MS sensor has little explanatory capacity for forest variables dependent on tree height, already well determined from LIDAR alone. However, there is potential for variables dependent on tree diameters and their density. The combination of LIDAR and MS sensors can be very beneficial for predicting variables describing forests structural heterogeneity, which are best described from synergies between LIDAR heights and NDVI dispersion. Results demonstrate the potential of NDVI metrics to increase prediction accuracy of forest attributes. Their inclusion in the predictor dataset may, however, in a few cases be detrimental to accuracy, and therefore we recommend to carefully assess the possible advantages of data fusion on a case-by-case basis.</p

Are We Ready for Bariatric Surgery in a Liver Transplant Program? A Meta-Analysis

Background Obesity-related non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are two main causes of end-stage liver disease requiring a liver transplantation. Studies exploring bariatric surgery in the liver transplantation setting have increased in recent years; however, a systematic analysis of the topic is lacking to date. This meta-analysis was conducted to explore the perioperative and long-term outcomes of bariatric surgery in obese patients undergoing liver transplantation. Methods Electronic databases were systematically searched for studies reporting bariatric surgery in patients undergoing liver transplantation. The primary outcomes were postoperative complications and mortality. We also extracted data about excess weight loss, body mass index, and improvement of comorbidities after bariatric surgery. Results A total of 96 patients from 8 articles were included. Bariatric surgery–related morbidity and mortality rates were 37% (95% CI 0.27–0.47) and 0.6% (95% CI 0.02–0.13), respectively. Body mass index at 24 months was 31.02 (95% CI 25.96–36.09) with a percentage excess weight loss at 12 and 24 months of 44.08 (95% CI 27.90–60.26) and 49.2 (95% CI 31.89–66.66), respectively. After bariatric surgery, rates of improvement of arterial hypertension and diabetes mellitus were 61% (95% CI 0.45–0.75) and 45% (95% CI 0.25–0.66), respectively. In most patients, bariatric surgery was performed after liver transplant and the most frequent technique was sleeve gastrectomy. Conclusions Bariatric surgery can be performed safely in the setting of liver transplantation resulting in improvement of obesity-related comorbidities. The optimal timing and technique require further studies