998 resultados para first legume height


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Long paper notebook with a handwritten inventory of Gannett's estate arranged by house location with price estimates. The inventory appears to correspond with the "Sales at auction" document. The verso of the last page contains the note: "Inventory of Personal Estate (copy)."

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Five loose pages of handwritten lists of personal property and calculations.

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Two pages with calculations and notes relating to the differences between the Estate Book and the account rendered by the Judge of Probate.

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Four-page handwritten account statement with the note on the verso: "Thomas B. Gannett's first account as executor to C. Gannett February 1820 copy."

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One-page handwritten accounting document with the note on the verso: "changes of from which items in 1st account of administration are formed." The document is undated.

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LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

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Spin coating polymer blend thin films provides a method to produce multiphase functional layers of high uniformity covering large surface areas. Applications for such layers include photovoltaics and light-emitting diodes where performance relies upon the nanoscale phase separation morphology of the spun film. Furthermore, at micrometer scales, phase separation provides a route to produce self-organized structures for templating applications. Understanding the factors that determine the final phase-separated morphology in these systems is consequently an important goal. However, it has to date proved problematic to fully test theoretical models for phase separation during spin coating, due to the high spin speeds, which has limited the spatial resolution of experimental data obtained during the coating process. Without this fundamental understanding, production of optimized micro- and nanoscale structures is hampered. Here, we have employed synchronized stroboscopic illumination together with the high light gathering sensitivity of an electron-multiplying charge-coupled device camera to optically observe structure evolution in such blends during spin coating. Furthermore the use of monochromatic illumination has allowed interference reconstruction of three-dimensional topographies of the spin-coated film as it dries and phase separates with nanometer precision. We have used this new method to directly observe the phase separation process during spinning for a polymer blend (PS-PI) for the first time, providing new insights into the spin-coating process and opening up a route to understand and control phase separation structures. © 2011 American Chemical Society.

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We report the discovery, tracking, and detection circumstances for 85 trans-Neptunian objects (TNOs) from the first 42 deg2 of the Outer Solar System Origins Survey. This ongoing r-band solar system survey uses the 0.9 deg2 field of view MegaPrime camera on the 3.6 m Canada–France–Hawaii Telescope. Our orbital elements for these TNOs are precise to a fractional semimajor axis uncertainty <0.1%. We achieve this precision in just two oppositions, as compared to the normal three to five oppositions, via a dense observing cadence and innovative astrometric technique. These discoveries are free of ephemeris bias, a first for large trans-Neptunian surveys. We also provide the necessary information to enable models of TNO orbital distributions to be tested against our TNO sample. We confirm the existence of a cold "kernel" of objects within the main cold classical Kuiper Belt and infer the existence of an extension of the "stirred" cold classical Kuiper Belt to at least several au beyond the 2:1 mean motion resonance with Neptune. We find that the population model of Petit et al. remains a plausible representation of the Kuiper Belt. The full survey, to be completed in 2017, will provide an exquisitely characterized sample of important resonant TNO populations, ideal for testing models of giant planet migration during the early history of the solar system.

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Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment

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Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.

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The In Situ Analysis System (ISAS) was developed to produce gridded fields of temperature and salinity that preserve as much as possible the time and space sampling capabilities of the Argo network of profiling floats. Since the first global re-analysis performed in 2009, the system has evolved and a careful delayed mode processing of the 2002-2012 dataset has been carried out using version 6 of ISAS and updating the statistics to produce the ISAS13 analysis. This last version is now implemented as the operational analysis tool at the Coriolis data centre. The robustness of the results with respect to the system evolution is explored through global quantities of climatological interest: the Ocean Heat Content and the Steric Height. Estimates of errors consistent with the methodology are computed. This study shows that building reliable statistics on the fields is fundamental to improve the monthly estimates and to determine the absolute error bars. The new mean fields and variances deduced from the ISAS13 re-analysis and dataset show significant changes relative to the previous ISAS estimates, in particular in the southern ocean, justifying the iterative procedure. During the decade covered by Argo, the intermediate waters appear warmer and saltier in the North Atlantic and fresher in the Southern Ocean than in WOA05 long term mean. At inter-annual scale, the impact of ENSO on the Ocean Heat Content and Steric Height is observed during the 2006-2007 and 2009-2010 events captured by the network.

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Background: Expressed Sequence Tags (ESTs) are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings: Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis), expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions: MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants.

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In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

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Background: Indices predictive of central obesity include waist circumference (WC) and waist-to-height ratio (WHtR). The aims of this study were 1) to establish a Colombian youth smoothed centile charts and LMS tables for WC and WHtR and 2) to evaluate the utility of these parameters as predictors of overweight and obesity. Method: A cross-sectional study whose sample population comprised 7954 healthy Colombian schoolchildren [boys n=3460 and girls n=4494, mean (standard deviation) age 12.8 (2.3) years old]. Weight, height, body mass index (BMI), WC and WHtR and its percentiles were calculated. Appropriate cut-offs point of WC and WHtR for overweight and obesity, as defined by the International Obesity Task Force (IOTF) definitions, were selected using receiver operating characteristic (ROC) analysis. The discriminating power of WC and WHtR was expressed as area under the curve (AUC). Results: Reference values for WC and WHtR are presented. Mean WC increased and WHtR decreased with age for both genders. We found a moderate positive correlation between WC and BMI (r= 0.756, P < 0.01) and WHtR and BMI (r= 0.604, P < 0.01). The ROC analysis showed a high discrimination power in the identification of overweight and obesity for both measures in our sample population. Overall, WHtR was slightly a better predictor for overweight/obesity (AUC 95% CI 0.868-0.916) than the WC (AUC 95% CI 0.862-0.904). Conclusion: This paper presents the first sex- and age-specific WC and WHtR percentiles for both measures among Colombian children and adolescents aged 9–17.9 years. By providing LMS tables for Latin-American people based on Colombian reference data, we hope to provide quantitative tools for the study of obesity and its comorbidities.