Reference Data For Calibration Research Articles

X‐Ray Fluorescence Determination of FeII/Fetotal Ratios in Sediments and Soils

The two most common oxidation states of iron can be determined by wavelength‐dispersive X‐ray fluorescence spectrometry relatively fast with an accuracy comparable to that of alternative methods. Main advantages for the analysis of sediments and soils are that organic matter does not interfere and solid samples can be analysed directly with minimal preparation effort. The limited availability of appropriate reference materials with certified data on their ferrous iron content turned out to be the major obstacle to implementing the method. For this reason and because no influence of the analysed geological materials on the intensity ratios of the closely adjacent Fe Kβ5 / Fe Kβ1,3 lines became evident, several rock types were selected in addition to sediments and soils to broaden and improve the calibration. Nevertheless, most reference data for calibration had to be determined by 57Fe Mössbauer spectroscopy. Plotting Fe Kβ5/Fe Kβ1,3 intensity ratios versus w FeO/w Fe2O3total ratios resulted in a correlation with R2 = 0.962 for the linear regression of all calibration data.

Geometric distortion and astrometric calibration of the JWST MIRI Medium Resolution Spectrometer

Context. The Medium Resolution integral field Spectrometer (MRS) of the Mid-Infrared Instrument (MIRI) on board the James Webb Space Telescope (JWST) performs spectroscopy between 5 and 28 µm, with a field of view varying from ~13 to ~56 sq. arcsec. The optics of the MRS introduce substantial distortion and this needs to be rectified in order to reconstruct the observed astrophysical scenario. Aims. We aim to use data from the JWST/MIRI commissioning and cycle 1 calibration phase to derive the MRS geometric distortion and astrometric solution, a critical step in the calibration of MRS data. These solutions come in the form of transform matrices that map the detector pixels to spatial coordinates of a local MRS coordinate system called α/β, to the global JWST observatory coordinates V2 and V3 (V2+V3). Methods. For every MRS spectral band and each slice dispersed on the detector, we fit the transform of detector pixels to α/β by a two-dimensional (2D) polynomial, using a raster of point source observations. The dispersed trace of the point source on the detector was initially estimated by fitting a one-dimensional (1D) empirical function and then iterating on the first distortion solution using forward modelling of the point spread function model based on the webbpsf python package. A polynomial transform was used to map the coordinates from α/β to V2+V3. Results. We calibrated the distortion of all 198 discrete slices of the MIRI/MRS integral field units and derived an updated field of view (FoV) for each MRS spectral band. The precision of the distortion solution is estimated to be better than one-tenth of a spatial resolution element, with a root mean square (rms) of 10 milli-arc-second (mas) at 5 µm, to 23 mas at 27 µm. Finally, we found that the wheel positioning repeatability causes an additional astrometric rms error of 30 mas. Conclusions. We demonstrate the application of the MRS astrometric calibration strategy and analysis for all four integral field units and all spectral bands of the MRS that enable the calibration of MRS spectra. This is a critical step in the data pipeline of every MRS observation. The distortion calibration was folded into the JWST pipeline in the Calibration Reference Data System (CRDS) context (jwst_1094.pmap), meeting the pre-launch requirement, with an estimated total astrometric uncertainty of 50 mas.

In-line monitoring of the application weight of an adhesion promoter and the residual moisture content in textile finishing by hyperspectral imaging using a NIR camera

Hyperspectral imaging was used for monitoring of both the application weight of an adhesion promoter for rubber applied to a polyester fabric by impregnation and the residual moisture in the fabric after drying at the end of the finishing process. A NIR camera with a spectral range from 1320 to 1900 nm was used for imaging. Quantitative data were derived from the spectra by chemometric methods using partial least squares (PLS) regression. Reference data for calibration and validation were determined by gravimetry. The root mean square errors of prediction (RMSEP) for the application weight and the moisture content were found to be 1.2 g/m² (for a probed range up to 25 g/m²) and 0.34 wt% (for water contents up to 10 wt%), respectively. Moreover, nonuniformities in both application weight and drying could be clearly uncovered. Mean values for application weight and moisture content obtained by averaging of the individual predictions from all pixels of each spectral image were found to show excellent correlation with the corresponding reference values from gravimetry. The results reveal that hyperspectral imaging with a NIR camera in combination with the PLS algorithm and adequate calibration is able to provide data with sufficient precision for in-line monitoring of both technical parameters and confirm the efficiency of this analytical approach for process control in technical textile converting.

Improved description of ligand polarization enhances transferability of ion-ligand interactions.

The reliability of molecular mechanics (MM) simulations in describing biomolecular ion-driven processes depends on their ability to accurately model interactions of ions simultaneously with water and other biochemical groups. In these models, ion descriptors are calibrated against reference data on ion-water interactions, and it is then assumed that these descriptors will also satisfactorily describe interactions of ions with other biochemical ligands. The comparison against the experiment and high-level quantum mechanical data show that this transferability assumption can break down severely. One approach to improve transferability is to assign cross terms or separate sets of non-bonded descriptors for every distinct pair of ion type and its coordinating ligand. Here, we propose an alternative solution that targets an error-source directly and corrects misrepresented physics. In standard model development, ligand descriptors are never calibrated or benchmarked in the high electric fields present near ions. We demonstrate for a representative MM model that when the polarization descriptors of its ligands are improved to respond to both low and high fields, ligand interactions with ions also improve, and transferability errors reduce substantially. In our case, the overall transferability error reduces from 3.3 kcal/mol to 1.8 kcal/mol. These improvements are observed without compromising on the accuracy of low-field interactions of ligands in gas and condensed phases. Reference data for calibration and performance evaluation are taken from the experiment and also obtained systematically from "gold-standard" CCSD(T) in the complete basis set limit, followed by benchmarked vdW-inclusive density functional theory.

Monitoring of the residual moisture content in finished textiles during converting by NIR hyperspectral imaging

Hyperspectral imaging was used for large-scale monitoring of the residual moisture in wide textile webs at the end of the drying process that follows their washing or finishing by impregnation in aqueous solutions or dispersions. Such data are essential for optimizing the energy efficiency and the precise control of the drying process. Quantitative analysis of the recorded spectral data was carried out with multivariate regression methods such as the partial least squares (PLS) algorithm. Reference data for calibration of the prediction models were determined by gravimetry. The drying of textile materials from both natural or synthetic fibers possessing different water absorption capacities (cotton, polyamide, polyester), which were partially finished with an optical brightener, was investigated. Moisture contents in the range from 0 to about 12 wt% were considered in the calibration models. For all systems, the root mean square error of prediction (RMSEP) for the residual moisture was found to be about 0.5 wt%, that is, about 1 g/m2. In addition to the quantitative determination of the water content, hyperspectral imaging provides detailed information about its spatial distribution across the textile web, which may help to improve the control of the drying process. In particular, it was demonstrated that the developed methods were capable of detecting and visualizing inhomogeneous moisture distributions. Averaging of the individual values of the moisture content predicted from all spectra across the surface of the textile samples resulted in a very close correlation with the corresponding gravimetric reference values. Due to the averaging process, the difference between both values is generally lower than RMSEP even in case of samples with inhomogeneous distribution of the moisture. The high precision and the broad capabilities of the developed analytic methods for in-line monitoring of the moisture content hold the potential for an efficient process control in technical textile converting processes.

A Large Eddy Simulation Study on the Effect of Devolatilization Modelling and Char Combustion Mode Modelling on the Structure of a Large-Scale, Biomass and Coal Co-Fired Flame

This work focuses on the impact of the devolatilization and char combustion mode modelling on the structure of a large-scale, biomass and coal co-fired flame using large eddy simulations. The coal modelling framework previously developed for the simulation of combustion in large-scale facilities is extended for biomass capabilities. An iterative procedure is used to obtain devolatilization kinetics of coal and biomass for the test-case specific fuels and heating conditions. This is achieved by calibrating the model constants of two empirical models: the single first-order model and the distributed activation energy model. The reference data for calibration are devolatilization yields obtained with predictive coal and biomass multistep kinetic mechanisms. The variation of both particle density and diameter during char combustion is governed by the conversion mode, which is modelled using two approaches: the power law using a constant parameter that assumes a constant mode during char combustion and a constant-free model that considers a variable mode during combustion. Three numerical cases are considered: single first-order reaction with constant char combustion mode, distributed activation energy with constant char combustion mode, and single first-order reaction with variable char combustion mode. The numerical predictions from the large eddy simulations are compared with experimental results of a high co-firing rate large-scale laboratory flame of coal and biomass. Furthermore, results from single particle conversion under idealised conditions, isolating the effects of turbulence, are presented to assist the interpretation of the predictions obtained with large eddy simulations. The effects of the devolatilization and conversion mode modelling on the flame lift-off, flame length, and spatial distribution and radial profiles of O2 and CO2 are presented and discussed. Both the devolatilization and conversion mode modelling have a significant effect on the conversion of particles under idealised conditions. The large eddy simulations results show that the devolatilization model has a strong impact on the flame structure, but not on the flame lift-off. On the other hand, for the tested numerical conditions, the char combustion mode model has a marginal impact on the predicted results.

Applying terrestrial lidar for evaluation and calibration of airborne lidar-derived shrub biomass estimates in Arctic tundra

ABSTRACTMonitoring of climate-driven expansion of low-stature shrubs in Arctic tundra can be improved through application of high-resolution remote sensing. However, the destructive nature of harvest sampling that is usually performed for validation of these data is resource intensive and can limit future comparisons by destroying benchmark measurements. We compared aboveground shrub biomass estimates derived from terrestrial laser scanning (TLS) and airborne laser scanning (ALS) with the goal of determining whether TLS data can be used to accurately calibrate ALS estimates of shrub biomass in Arctic tundra. We used a leave-one-out cross-validation calibration of canopy volume against harvested shrub biomass to establish predictive relationships between TLS canopy volume and harvested shrub biomass, and between ALS canopy volume and TLS-derived shrub biomass estimates. TLS produced more accurate predictions of shrub biomass (R2 = 0.78; root mean square deviation [RMSD] = 102 g) than did ALS, but the accuracy of ALS-derived shrub biomass predictions was the same whether they were calibrated directly against harvest biomass or against TLS-derived estimates of biomass (R2 = 0.62; RMSD = 140 g). Our results suggest that once the initial TLS-harvest relationship is known, TLS can provide valid ground reference data for calibration of ALS-derived estimates of shrub biomass without the need for additional destructive harvest.

The Calibration Reference Data System

Abstract We describe a software architecture and implementation for using rules to determine which calibration files are appropriate for calibrating a given observation. This new system, the Calibration Reference Data System (CRDS), replaces what had been previously used for the Hubble Space Telescope (HST) calibration pipelines, the Calibration Database System (CDBS). CRDS will be used for the James Webb Space Telescope (JWST) calibration pipelines, and is currently being used for HST calibration pipelines. CRDS can be easily generalized for use in similar applications that need a rules-based system for selecting the appropriate item for a given dataset; we give some examples of such generalizations that will likely be used for JWST. The core functionality of the Calibration Reference Data System is available under an Open Source license. CRDS is briefly contrasted with a sampling of other similar systems used at other observatories.

Can airborne laser scanning assist in mapping and monitoring natural forests?

Old-growth boreal forests display high within-stand structural variation, with large variation in tree sizes and age structure, a heterogeneous horizontal spatial pattern with gaps of different sizes and multi-layered canopies. Old managed forests, on the other hand, are characterized by more homogeneous structural patterns. In many parts of Europe, no true ‘virgin forests’ remains. Still, in many places forests previously influenced by selective logging have been abandoned, and is now developing towards a more natural forest structure. Such near-natural forest areas can be of special importance for forest biodiversity and related ecosystem services, and it is therefore important to map and monitor such forests. Recently, airborne laser scanning (ALS) has been applied to provide ecologically relevant information on forest structure. The advantage of ALS is that it can characterize three-dimensional forest structure in fine detail across broad areas, replacing more labour-intensive field-based measurements.In this study, we use ALS to compare the structural characteristics of 89 near-natural and 280 managed old forest stands in a 17,000ha boreal forest study site in southeastern Norway. For the study area, both maps of logging history separating old near-natural and old managed forests, and high-resolution ALS data was available.Our aim was to investigate if ALS data could be used to separate vertical and horizontal forest structure in old near natural versus old managed forests. We also wanted to compare different methods for classification, and to describe the potential for use of ALS in classification of forest naturalness for future mapping and monitoring purposes.We found that ALS data had a strong potential in separating stands of old near-natural forests from old managed stands. The most important metrics for classification were those reflecting canopy height, canopy density, variation in canopy height, number of trees per area and gap patterns. This fits well with ecological knowledge of relevant structural differences between forests of different degree of naturalness. Both vertical and horizontal metrics provided useful input to the classification, but the horizontal metrics performed slightly better on accuracy and were easier to interpret. Although the method has a good potential for wider use in boreal forest landscapes, the need for local reference data for calibration as well as the importance of ALS pulse density for precision of classification should be further investigated.Large-scale spatial information on remaining source areas of natural and near-natural forests will be essential in order to manage forests in a way that safeguards biodiversity and ecosystem services. We suggest that classification of forest naturalness based on ALS data can be a helpful tool in future forest mapping and monitoring.

Waveform Calibration of Ground Penetrating Radars for Identification of Buried Objects

This brief paper proposes a method for calibration of GPR pulse waveforms that is effective for identification of buried objects in the ground and/or in concrete structures. This approach is based on the inverse filtering operation that eliminates the influence of GPR antenna characteristics, and a response from a flat metal plate is employed as a reference data for calibration. In order to evaluate the effectiveness of this approach, it is applied to actual experimental data measured by the UWB-GPR antennas. The results show the validity of the method and importance of the waveform calibration for target identification.

A global poverty map derived from satellite data

A global poverty map has been produced at 30 arcsec resolution using a poverty index calculated by dividing population count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.

Calibration of Infrared Prism Spectrometers*

The dependence of frequency ν on the setting T of an infrared prism spectrometer can be given by the formula ν(T) = A(T) + B/(C − T) with a small variation of the parameter A. For prisms in their lowest octave of transmission the variation in A is 10 cm−1 for NaCl, and 2.5 cm−1 for KBr and CsI. For a KBr prism in a double-pass instrument enough atmospheric absorption lines are resolved to give adequate reference data for calibration without using any other gas. Frequencies for this purpose are given.