Estimation of the top of the saturated zone from airborne electromagnetic data

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. EN63-EN76 ◽  
Author(s):  
Noah Dewar ◽  
Rosemary Knight
Keyword(s):  
Data Acquisition ◽  
Central Valley ◽  
Saturated Zone ◽  
Data Set ◽  
Northern Portion ◽  
Airborne Electromagnetic ◽  
Rms Error ◽  
The Difference ◽  
Using Data ◽  
Airborne Electromagnetic Data

In an airborne electromagnetic (AEM) data set acquired in unsaturated and saturated zones, the depth of the top of the saturated zone (TSZ) at the time of data acquisition should be accounted for in the resistivity-to-lithology transform. We have developed and tested a methodology for estimating the TSZ from AEM data, using data collected in three survey areas in the Central Valley of California and water-table elevation (WTE) measurements from nearby wells. The methodology is based on the difference in the distribution of resistivity values above and below the TSZ, using the WTE measurements to optimize two components of the general workflow. From the AEM data acquired in Tulare County, in the southern portion of the Central Valley, where the WTE measurements were acquired two to four weeks before the AEM data acquisition, we have found estimates of the TSZ with a root-mean-square (rms) error of 10.6 m when compared to the WTE measurements. From the two survey areas in Butte and Glenn counties, in the northern portion of the Central Valley, where WTE measurements were available at the time of, and closer to the locations of, AEM data acquisition, we have found estimates of the TSZ with an rms error ranging from 3.8 to 5.3 m, depending on the form of inversion. The level of error found in the three survey areas is comparable to the thickness of the layers in the resistivity models at the depths of the TSZ. Because the intended use of these estimates is to locate the TSZ for use in developing and applying the resistivity-to-lithology transform, the level of error associated with this new methodology is acceptable.

scholarly journals Cattle stratified on genetic merit segregate on carcass characteristics, but there is scope for improvement1

2019 ◽  
Vol 3 (2) ◽  
pp. 893-902 ◽  
Author(s):  
Donagh P Berry ◽  
Thierry Pabiou ◽  
Denis Brennan ◽  
Patrick J Hegarthy ◽  
Michelle M Judge
Keyword(s):  
Carcass Weight ◽  
Data Set ◽  
Study Objective ◽  
Positive Weight ◽  
Association Analyses ◽  
Genetic Merit ◽  
The Difference ◽  
Fat Score ◽  
Using Data ◽  
Very High

Abstract The study objective was to quantify the ability of genetic merit for a generated carcass index to differentiate animals on primal carcass cut weights using data from 1,446 herds on 9,414 heifers and 22,413 steers with weights for 14 different primal carcass cuts (plus 3 generated groups of cuts). The carcass genetic merit index was compromised of carcass weight (positive weight), conformation (positive weight), and fat score (negative weight), each equally weighted within the index. The association analyses were undertaken using linear mixed models; models were run with or without carcass weight as a covariate. In a further series of analyses, carcass weight and carcass fat score were both included as covariates in the models. Whether the association between primal cut yield and carcass weight differed by genetic merit stratum was also investigated. Genetic merit was associated (P < 0.001) with the weight of all cuts evaluated even when adjusted to a common carcass weight (P < 0.01); when simultaneously adjusted to a common carcass weight and fat score, genetic merit was not associated with the weight of the cuberoll or the group cuts termed minced-meat. The weight of the different primal cuts increased almost linearly within increasing genetic merit, with the exception of the rump and bavette. The difference in mean primal cut weight between the very low and very high genetic merit strata, as a proportion of the overall mean weight of that cut in the entire data set, varied from 0.05 (bavette) to 0.28 (eye of round); the average was 0.17. Following adjustment for differences in carcass weight, there was no difference in cut weight between the very low and very high strata for the rump, chuck tender, and mince cut group; the remaining cuts were heavier in the higher index animals with the exception of the cuberoll and bavette, which were lighter in the very high index animals. The association between carcass weight and the weight of each of the evaluated primal cuts differed (P < 0.05) by genetic merit stratum for all cuts evaluated with the exception of the rump, striploin, and brisket as well as the group cuts of frying and mincing. With the exception of these 5 primal (group) cuts, the regression coefficients of primal cut weight on carcass weight increased consistently for all traits with increasing genetic merit stratum, other than for the fillet, cuberoll, bavette, chuck and neck, and heel and shank.

A holistic approach to inversion of frequency-domain airborne EM data

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. G301-G312 ◽  
Author(s):  
Ross Brodie ◽  
Malcolm Sambridge
Keyword(s):  
Frequency Domain ◽  
Synthetic Data ◽  
Holistic Approach ◽  
Data Sets ◽  
Data Set ◽  
Zero Level ◽  
Airborne Electromagnetic ◽  
Available Information ◽  
Airborne Electromagnetic Data ◽  
Parameter Values

We have developed a holistic method for simultaneously calibrating, processing, and inverting frequency-domain airborne electromagnetic data. A spline-based, 3D, layered conductivity model covering the complete survey area was recovered through inversion of the entire raw airborne data set and available independent conductivity and interface-depth data. The holistic inversion formulation includes a mathematical model to account for systematic calibration errors such as incorrect gain and zero-level drift. By taking these elements into account in the inversion, the need to preprocess the airborne data prior to inversion is eliminated. Conventional processing schemes involve the sequential application of a number of calibration corrections, with data from each frequency treated separately. This is followed by inversion of each multifrequency sample in isolation from other samples.By simultaneously considering all of the available information in a holistic inversion, we are able to exploit interfrequency and spatial-coherency characteristics of the data. The formulation ensures that the conductivity and calibration models are optimal with respect to the airborne data and prior information. Introduction of interfrequency inconsistency and multistage error propagation stemming from the sequential nature of conventional processing schemes is also avoided. We confirm that accurate conductivity and calibration parameter values are recovered from holistic inversion of synthetic data sets. We demonstrate that the results from holistic inversion of raw survey data are superior to the output of conventional 1D inversion of final processed data. In addition to the technical benefits, we expect that holistic inversion will reduce costs by avoiding the expensive calibration-processing-recalibration paradigm. Furthermore, savings may also be made because specific high-altitude zero-level observations, needed for conventional processing, may not be required.

Probabilistic inversion of airborne electromagnetic data for basement conductors

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. E389-E400 ◽  
Author(s):  
Juerg Hauser ◽  
James Gunning ◽  
David Annetts
Keyword(s):  
Thin Plate ◽  
Parametric Bootstrap ◽  
Computationally Efficient ◽  
Prior Beliefs ◽  
Data Set ◽  
Layered Earth ◽  
Electromagnetic Data ◽  
Airborne Electromagnetic ◽  
Airborne Electromagnetic Data ◽  
Probabilistic Inversion

Probabilistic inversion of airborne electromagnetic data is often approximated by a layered earth using a computationally efficient 1D kernel. If the underlying framework accounts for prior beliefs on spatial correlation, the inversion will be able to recover spatially coherent interfaces and associated uncertainties. Greenfield exploration using airborne electromagnetic data, however, often seeks to identify discrete economical targets. In mature exploration provinces, such bodies are frequently obscured by thick, conductive regolith, and the response of such economic basement conductors presents a challenge to any layered earth inversion. A well-known computationally efficient way to approximate the response of a basement conductor is to use a thin plate. Here we have extended a Bayesian parametric bootstrap approach, so that the basement of a spatially varying layered earth can contain a thin plate. The resulting Bayesian framework allowed for the inversion of basement conductors and associated uncertainties, but more importantly, the use of model selection concepts to determine if the data supports a basement conductor model or not. Recovered maps of basement conductor probabilities show the expected patterns in uncertainty; for example, a decrease in target probability with increasing depth. Such maps of target probabilities generated using the thin plate approximation are a potentially valuable source of information for the planning of exploration activity, such as the targeting of drillholes to confirm the existence of a discrete conductor in a greenfield exploration scenario. We have used a field data set from northwest Queensland, Australia, to illustrate how the approach allowed inversion for a basement conductor and related uncertainties in a spatially variable layered earth, using the information from multiple survey lines and prior beliefs of geology.

scholarly journals The Effect of Testing Turnaround Time on COVID-19 Outbreak Severity Within U.S. Nursing Homes

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 732-732
Author(s):  
Annie Rhodes ◽  
Leland Waters ◽  
Faika Zanjani ◽  
Tracey Gendron ◽  
Rick Moore
Keyword(s):  
Nursing Homes ◽  
Turnaround Time ◽  
Test Results ◽  
Data Set ◽  
Independent Variable ◽  
Polymerase Chain ◽  
The Difference ◽  
Using Data ◽  
Post Hoc ◽  
To Receive

Abstract COVID-19 has brought renewed attention to infectious diseases in U.S. nursing homes (NHs). The Testing turnaround time (TAT) of SARS-CoV-2 is vital information, supporting staff ability to make decisions regarding resource allocation. Methods Using data obtained from the National Healthcare Safety Network’s COVID-19 nursing home data set, we analyzed the TAT of laboratory polymerase chain reaction (PCR) testing on outbreak severity (number of people infected) for residents and staff. A MANOVA was performed on NHs submitting data over 26 weeks (May-November 2020). The independent variable was the average TAT for the two weeks prior (<24 hours, 1-2 days, 3-7 days, or 7+ days). Results N = 15,363 NHs. The TAT for the combined dependent variables of staff and resident COVID-19 cases. F(10,781,354) = 3161.265, Pillai’s trace = .078, p<.0005, partial η2=.4. The average outbreak severity for staff was 13.93 cases when TAT was < 24 hours, compared to 15.29 cases at 1-2 days. For residents, the difference was less pronounced but still significant. The average outbreak severity for residents was 17.07 cases when TAT was<24 hours, compared to 18.61 cases when the TAT was 1-2 days. Tukey post-hoc tests found significance for all levels of testing for residents and staff at p<.0005. Discussion Time differences to receive PCR test results from a laboratory are significant in outbreak severity for staff and residents. The most meaningful result positively impacting the ultimate spread and severity of gross cases is when the TAT for PCR results is < 1 day.

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

scholarly journals A data acquisition setup for data driven acoustic design

2021 ◽  
pp. 1351010X2098690
Author(s):  
Romana Rust ◽  
Achilleas Xydis ◽  
Kurt Heutschi ◽  
Nathanael Perraudin ◽  
Gonzalo Casas ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Interdisciplinary Approach ◽  
Computational Design ◽  
Surface Structures ◽  
Future Research ◽  
Data Set ◽  
Process Measures ◽  
First Results ◽  
Spatio Temporal ◽  
Automated Data Acquisition

In this paper, we present a novel interdisciplinary approach to study the relationship between diffusive surface structures and their acoustic performance. Using computational design, surface structures are iteratively generated and 3D printed at 1:10 model scale. They originate from different fabrication typologies and are designed to have acoustic diffusion and absorption effects. An automated robotic process measures the impulse responses of these surfaces by positioning a microphone and a speaker at multiple locations. The collected data serves two purposes: first, as an exploratory catalogue of different spatio-temporal-acoustic scenarios and second, as data set for predicting the acoustic response of digitally designed surface geometries using machine learning. In this paper, we present the automated data acquisition setup, the data processing and the computational generation of diffusive surface structures. We describe first results of comparative studies of measured surface panels and conclude with steps of future research.

Event detection of different English data sources based on transfer learning

2021 ◽  
pp. 1-11
Author(s):  
Yanan Huang ◽  
Yuji Miao ◽  
Zhenjing Da
Keyword(s):  
Transfer Learning ◽  
Event Detection ◽  
Visual Analysis ◽  
Learning Algorithm ◽  
Data Sources ◽  
Data Set ◽  
Data Source ◽  
Single Data Source ◽  
The Difference ◽  
Single Data

The methods of multi-modal English event detection under a single data source and isomorphic event detection of different English data sources based on transfer learning still need to be improved. In order to improve the efficiency of English and data source time detection, based on the transfer learning algorithm, this paper proposes multi-modal event detection under a single data source and isomorphic event detection based on transfer learning for different data sources. Moreover, by stacking multiple classification models, this paper makes each feature merge with each other, and conducts confrontation training through the difference between the two classifiers to further make the distribution of different source data similar. In addition, in order to verify the algorithm proposed in this paper, a multi-source English event detection data set is collected through a data collection method. Finally, this paper uses the data set to verify the method proposed in this paper and compare it with the current most mainstream transfer learning methods. Through experimental analysis, convergence analysis, visual analysis and parameter evaluation, the effectiveness of the algorithm proposed in this paper is demonstrated.

The Impact of Customer Loyalty and Restaurant Sanitation Grades on Revisit Intention and the Importance of Narrative Information: The Case of New York Restaurant Sanitation Grading System

2017 ◽  
Vol 59 (3) ◽  
pp. 275-284 ◽  
Author(s):  
Min Gyung Kim ◽  
Hyunjoo Yang ◽  
Anna S. Mattila
Keyword(s):  
New York ◽  
New York City ◽  
Customer Loyalty ◽  
York City ◽  
Letter Grades ◽  
The Difference ◽  
Revisit Intentions ◽  
Using Data ◽  
The Impact ◽  
Loyal Customers

New York City launched a restaurant sanitation letter grade system in 2010. We evaluate the impact of customer loyalty on restaurant revisit intentions after exposure to a sanitation grade alone, and after exposure to a sanitation grade plus narrative information about sanitation violations (e.g., presence of rats). We use a 2 (loyalty: high or low) × 4 (sanitation grade: A, B, C, or pending) between-subjects full factorial design to test the hypotheses using data from 547 participants recruited from Amazon MTurk who reside in the New York City area. Our study yields three findings. First, loyal customers exhibit higher intentions to revisit restaurants than non-loyal customers, regardless of sanitation letter grades. Second, the difference in revisit intentions between loyal and non-loyal customers is higher when sanitation grades are poorer. Finally, loyal customers are less sensitive to narrative information about sanitation violations.

Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F25-F34 ◽  
Author(s):  
Benoit Tournerie ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Apparent Resistivity ◽  
A Priori ◽  
Shift Factor ◽  
Static Shift ◽  
Geostatistical Model ◽  
Data Set ◽  
Resistivity Sounding ◽  
The Difference ◽  
Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

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