Evaluation of a rapid hybrid spectral-spatial domain 3D forward-modeling approach for loop-loop electromagnetic induction quadrature data acquired in low-induction-number environments

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. E447-E458 ◽  
Author(s):  
Julien Guillemoteau ◽  
Jens Tronicke
Keyword(s):  
Electrical Conductivity ◽  
Large Scale ◽  
Structural Information ◽  
Forward Modeling ◽  
Spatial Domain ◽  
Near Surface ◽  
Homogeneous Half Space ◽  
Subsurface Environments ◽  
Em Induction ◽  
The Right

When exploring subsurface environments using electromagnetic (EM) induction (EMI) tools, approximate forward-modeling methods based on a homogeneous half-space kernel have been extensively evaluated in the past. For large-scale exploration methods, such as magnetotellurics, marine EM, airborne EM, transient EM, and large offset loop-loop harmonic EM, such forward-modeling approaches are limited because the kernel depends strongly on the subsurface distribution of electrical conductivity. However, the response of small portable EMI loop-loop sensors applied in a low-induction number (LIN) context are known to be more linearly related to the true distribution of electrical conductivity. Thus, data collected using such sensors are more adapted to an approximate forward-modeling with a conductivity-independent kernel. We have evaluated the bias of such an approximate modeling for the case of portable multiconfiguration system measurements in 1D, 2D, and 3D contexts. Our result shows that the approximate approach tends to underestimate the conductivity of more conductive targets but is able to reproduce the right structural information. Compared with previous algorithms presented in the literature, we solved the approximate forward-modeling problem in the hybrid spectral-spatial domain to speed up the computation. Considering the level of accuracy in structural modeling as well as the computational efficiency of our hybrid spectral-spatial approach, we conclude that this method is especially suitable for near-surface, large-scale mapping applications in LIN environments as typically encountered in soil sciences and archaeological studies. For such applications, our approach can be implemented in rapid multichannel deconvolution procedures.

Toward subsurface magnetic permeability imaging with electromagnetic induction sensors: Sensitivity computation and reconstruction of measured data

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. E335-E345 ◽  
Author(s):  
Tim Klose ◽  
Julien Guillemoteau ◽  
François-Xavier Simon ◽  
Jens Tronicke
Keyword(s):  
Electrical Conductivity ◽  
Magnetic Permeability ◽  
Electromagnetic Induction ◽  
Synthetic Data ◽  
Forward Modeling ◽  
Measured Data ◽  
Modeling Method ◽  
Near Surface ◽  
Sensitivity Functions ◽  
Modeling Approach

In near-surface geophysics, small portable loop-loop electromagnetic induction (EMI) sensors using harmonic sources with a constant and rather small frequency are increasingly used to investigate the electrical properties of the subsurface. For such sensors, the influence of electrical conductivity and magnetic permeability on the EMI response is well-understood. Typically, data analysis focuses on reconstructing an electrical conductivity model by inverting the out-of-phase response. However, in a variety of near-surface applications, magnetic permeability (or susceptibility) models derived from the in-phase (IP) response may provide important additional information. In view of developing a fast 3D inversion procedure of the IP response for a dense grid of measurement points, we first analyze the 3D sensitivity functions associated with a homogeneous permeable half-space. Then, we compare synthetic data computed using a linear forward-modeling method based on these sensitivity functions with synthetic data computed using full nonlinear forward-modeling methods. The results indicate the correctness and applicability of our linear forward-modeling approach. Furthermore, we determine the advantages of converting IP data into apparent permeability, which, for example, allows us to extend the applicability of the linear forward-modeling method to high-magnetic environments. Finally, we compute synthetic data with the linear theory for a model consisting of a controlled magnetic target and compare the results with field data collected with a four-configuration loop-loop EMI sensor. With this field-scale experiment, we determine that our linear forward-modeling approach can reproduce measured data with sufficiently small error, and, thus, it represents the basis for developing efficient inversion approaches.

Transformation of VLF data into apparent resistivities and phases

Geophysics ◽  
1999 ◽  
Vol 64 (5) ◽  
pp. 1393-1402 ◽  
Author(s):  
Mehran Gharibi ◽  
Laust B. Pedersen
Keyword(s):  
Magnetic Field ◽  
Electrical Conductivity ◽  
Large Scale ◽  
Low Cost ◽  
Real Data ◽  
Geological Structure ◽  
Direct Estimate ◽  
Horizontal Magnetic Field ◽  
Near Surface ◽  
Full Solution

In the VLF method, the ratio between the vertical and the horizontal magnetic field or the total magnetic field anomaly is measured to detect localized changes in electrical conductivity contrasts. Although the VLF technique has probably been the most popular electromagnetic (EM) tool for mapping near‐surface geological structures in a large scale for the past few decades because of the low cost and speed with which surveys can be carried out, the measurements themselves do not give a direct estimate of electrical conductivity. A fast iterative method has been developed to estimate the impedance or apparent resistivity and phases from measurements of the magnetic components at the surface of a 2-D geological structure. From Maxwell’s equations in E-polarization, a relation was derived between the horizontal and vertical components of the magnetic field. A full solution has been obtained by making use of the fact that the secondary horizontal and vertical magnetic fields are of internal origin and form a Hilbert transform pair. Synthetic and real VLF data have been used to evaluate the performance and limitation of the method. Using synthetic and real data, one can achieve a full recovery of the E-polarization impedance as long as the length of the profile is sufficiently long. A number of precautions must be taken to ensure reliable estimation of impedance results.

Why Has There Been No People’s Power Rebellion in North Korea?

2018 ◽  
pp. 1-34
Author(s):  
Andrew Jackson
Keyword(s):  
Rural Areas ◽  
North Korea ◽  
Large Scale ◽  
Political Elite ◽  
Information Control ◽  
Al Jazeera ◽  
The North ◽  
New Information ◽  
Effective System ◽  
The Right

One scenario put forward by researchers, political commentators and journalists for the collapse of North Korea has been a People’s Power (or popular) rebellion. This paper analyses why no popular rebellion has occurred in the DPRK under Kim Jong Un. It challenges the assumption that popular rebellion would happen because of widespread anger caused by a greater awareness of superior economic conditions outside the DPRK. Using Jack Goldstone’s theoretical expla-nations for the outbreak of popular rebellion, and comparisons with the 1989 Romanian and 2010–11 Tunisian transitions, this paper argues that marketi-zation has led to a loosening of state ideological control and to an influx of infor-mation about conditions in the outside world. However, unlike the Tunisian transitions—in which a new information context shaped by social media, the Al-Jazeera network and an experience of protest helped create a sense of pan-Arab solidarity amongst Tunisians resisting their government—there has been no similar ideology unifying North Koreans against their regime. There is evidence of discontent in market unrest in the DPRK, although protests between 2011 and the present have mostly been in defense of the right of people to support themselves through private trade. North Koreans believe this right has been guaranteed, or at least tacitly condoned, by the Kim Jong Un government. There has not been any large-scale explosion of popular anger because the state has not attempted to crush market activities outright under Kim Jong Un. There are other reasons why no popular rebellion has occurred in the North. Unlike Tunisia, the DPRK lacks a dissident political elite capable of leading an opposition movement, and unlike Romania, the DPRK authorities have shown some flexibility in their anti-dissent strategies, taking a more tolerant approach to protests against economic issues. Reduced levels of violence during periods of unrest and an effective system of information control may have helped restrict the expansion of unrest beyond rural areas.

White Backlash

2015 ◽  
Author(s):  
Marisa Abrajano ◽  
Zoltan L. Hajnal
Keyword(s):  
Ethnic Diversity ◽  
Republican Party ◽  
Large Scale ◽  
White Americans ◽  
Political Beliefs ◽  
White Backlash ◽  
Political Spectrum ◽  
Racial Divide ◽  
The Right ◽  
Political Backlash

This book provides an authoritative assessment of how immigration is reshaping American politics. Using an array of data and analysis, it shows that fears about immigration fundamentally influence white Americans' core political identities, policy preferences, and electoral choices, and that these concerns are at the heart of a large-scale defection of whites from the Democratic to the Republican Party. The book demonstrates that this political backlash has disquieting implications for the future of race relations in America. White Americans' concerns about Latinos and immigration have led to support for policies that are less generous and more punitive and that conflict with the preferences of much of the immigrant population. America's growing racial and ethnic diversity is leading to a greater racial divide in politics. As whites move to the right of the political spectrum, racial and ethnic minorities generally support the left. Racial divisions in partisanship and voting, as the book indicates, now outweigh divisions by class, age, gender, and other demographic measures. The book raises critical questions and concerns about how political beliefs and future elections will change the fate of America's immigrants and minorities, and their relationship with the rest of the nation.

Evaluation of Ovaries in Patients with Polycystic Ovary Syndrome using Shear Wave Elastography

2020 ◽  
Vol 16 (5) ◽  
pp. 578-583
Author(s):  
Aysegul Altunkeser ◽  
Zeynep Ozturk Inal ◽  
Nahide Baran
Keyword(s):  
Shear Wave ◽  
Large Scale ◽  
Polycystic Ovary ◽  
Shear Wave Elastography ◽  
Left Ovary ◽  
Control Group ◽  
Tissue Elasticity ◽  
Group I ◽  
Pcos Group ◽  
The Right

Background: Shear wave electrography (SWE) is a novel non-invasive imaging technique which demonstrate tissue elasticity. Recent research evaluating the elasticity properties of normal and pathological tissues emphasize the diagnostic importance of this technique. Aims: Polycystic ovarian syndrome (PCOS), which is characterized by menstrual irregularity, hyperandrogenism, and polycystic overgrowth, may cause infertility. The aim of this study was to evaluate the elasticity of ovaries in patients with PCOS using SWE. Methods: 66 patients diagnosed with PCOS according to the Rotterdam criteria (PCOS = group I) and 72 patients with non-PCOS (Control = group II), were included in the study. Demographic and clinical characteristics of the participants were recorded. Ovarian elasticity was assessed in all patients with SWE, and speed values were obtained from the ovaries. The elasticity of the ovaries was compared between the two groups. Results: While there were statistically significant differences between the groups in body mass index (BMI), right and left ovarian volumes, luteinizing hormone and testosterone levels (p<0.05), no significant differences were found between groups I and II in the velocity (for the right ovary 3.89±1.81 vs. 2.93±0.72, p=0.301; for the left ovary 2.88±0.65 vs. 2.95±0.80, p=0.577) and elastography (for the right ovary 36.62±17.78 vs. 36.79±14.32, p=0.3952; for the left ovary 36.56±14.15 vs. 36.26±15.10, p=0.903) values, respectively. Conclusion: We could not obtain different velocity and elastography values from the ovaries of the patients with PCOS using SWE. Therefore, further large-scale studies are needed to elucidate this issue.

scholarly journals A Novel Method to Predict Drug-Target Interactions Based on Large-Scale Graph Representation Learning

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2111
Author(s):  
Bo-Wei Zhao ◽  
Zhu-Hong You ◽  
Lun Hu ◽  
Zhen-Hao Guo ◽  
Lei Wang ◽  
...  
Keyword(s):  
Drug Target ◽  
Large Scale ◽  
Computational Models ◽  
Structural Information ◽  
Characteristic Curve ◽  
Representation Learning ◽  
Graph Representation ◽  
Convolutional Network ◽  
Novel Method

Identification of drug-target interactions (DTIs) is a significant step in the drug discovery or repositioning process. Compared with the time-consuming and labor-intensive in vivo experimental methods, the computational models can provide high-quality DTI candidates in an instant. In this study, we propose a novel method called LGDTI to predict DTIs based on large-scale graph representation learning. LGDTI can capture the local and global structural information of the graph. Specifically, the first-order neighbor information of nodes can be aggregated by the graph convolutional network (GCN); on the other hand, the high-order neighbor information of nodes can be learned by the graph embedding method called DeepWalk. Finally, the two kinds of feature are fed into the random forest classifier to train and predict potential DTIs. The results show that our method obtained area under the receiver operating characteristic curve (AUROC) of 0.9455 and area under the precision-recall curve (AUPR) of 0.9491 under 5-fold cross-validation. Moreover, we compare the presented method with some existing state-of-the-art methods. These results imply that LGDTI can efficiently and robustly capture undiscovered DTIs. Moreover, the proposed model is expected to bring new inspiration and provide novel perspectives to relevant researchers.

scholarly journals Influence of the Upstream Terrain on the Formation of a Cold Frontal Snowband in Northeast China

2021 ◽  
Author(s):  
Na Li ◽  
Baofeng Jiao ◽  
Lingkun Ran ◽  
Zongting Gao ◽  
Shouting Gao
Keyword(s):  
Gravity Waves ◽  
Northeast China ◽  
Large Scale ◽  
Control Experiment ◽  
Vertical Motion ◽  
Near Surface ◽  
Inertial Instability ◽  
Two Factors ◽  
Negative Effect ◽  
Conditional Instability

AbstractWe investigated the influence of upstream terrain on the formation of a cold frontal snowband in Northeast China. We conducted numerical sensitivity experiments that gradually removed the upstream terrain and compared the results with a control experiment. Our results indicate a clear negative effect of upstream terrain on the formation of snowbands, especially over large-scale terrain. By thoroughly examining the ingredients necessary for snowfall (instability, lifting and moisture), we found that the release of mid-level conditional instability, followed by the release of low-level or near surface instabilities (inertial instability, conditional instability or conditional symmetrical instability), contributed to formation of the snowband in both experiments. The lifting required for the release of these instabilities was mainly a result of frontogenetic forcing and upper gravity waves. However, the snowband in the control experiment developed later and was weaker than that in the experiment without upstream terrain. Two factors contributed to this negative topographic effect: (1) the mountain gravity waves over the upstream terrain, which perturbed the frontogenetic circulation by rapidly changing the vertical motion and therefore did not favor the release of instabilities in the absence of persistent ascending motion; and (2) the decrease in the supply of moisture as a result of blocking of the upstream terrain, which changed both the moisture and instability structures leeward of the mountains. A conceptual model is presented that shows the effects of the instabilities and lifting on the development of cold frontal snowbands in downstream mountains.

scholarly journals An evaluation of water quality at Sandhill Wetland: implications for reclaiming wetlands above soft tailings deposits in northern Alberta, Canada

2021 ◽  
Author(s):  
Jeremy A. Hartsock ◽  
Jessica Piercey ◽  
Melissa K. House ◽  
Dale H. Vitt
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Surface Water ◽  
Water Chemistry ◽  
Water Quality Monitoring ◽  
Total Alkalinity ◽  
Near Surface ◽  
Water Quality Guidelines ◽  
Quality Guidelines ◽  
Annual Water

AbstractThe experimental Sandhill Wetland is the first permanent reclamation of a composite tailings deposit, and annual water quality monitoring is of specific interest for evaluating and predicting long-term reclamation performance. Here, we present water chemistry monitoring data obtained from Sandhill Wetland (years 2009–2019) and compare results to twelve natural reference wetlands and to environmental quality guidelines for Alberta surface waters. By comparing water quality at Sandhill Wetland and natural sites to established guidelines, we can begin to document the natural background water quality of wetlands in the region and examine if guideline exceedances are seen in natural undisturbed environments, or appear only at active reclamation sites. At Sandhill Wetland the dominant ions in near-surface water were bicarbonate, sulfate, chloride, sodium, calcium, and magnesium. Since the first growing season concentrations for these ions have increased annually, causing concurrent increases in electrical conductivity. In year 2019, water chemistry at Sandhill Wetland was most comparable to regional saline fens, systems that exhibit elevated electrical conductivity and high sodicity. Near-surface water at Sandhill Wetland exceeded water quality guidelines for three substances/properties (dissolved chloride, iron, and total alkalinity) in the most recent year of monitoring. The saline fen natural sites also exceeded water quality guidelines for the same chemical substances/properties, suggesting guideline exceedances are a norm for some natural wetland site types in the region. Of note, in each year of monitoring at Sandhill Wetland, dissolved organic compounds evaluated in sub- and near-surface water were below detection limits.

Introduction: Configuring the Green New Deal

2021 ◽  
pp. 103530462110176
Author(s):  
Anna Sturman ◽  
Natasha Heenan
Keyword(s):  
Land Use ◽  
Indigenous Peoples ◽  
New Deal ◽  
Large Scale ◽  
Political Strategy ◽  
Right Wing ◽  
Jel Codes ◽  
Economic Stagnation ◽  
Political Project ◽  
The Right

We introduce a themed collection of articles on approaches to configuring a Green New Deal as a response to the current capitalist crisis marked by ecological breakdown, economic stagnation and growing inequality. The Green New Deal is a contested political project, with pro-market, right-wing nationalist, Keynesian, democratic socialist and ecosocialist variants. Critiques of the Green New Deal include pragmatic queries as the feasibility of implementation, and theoretical challenges from the right regarding reliance on state forms and from the left regarding efforts to ameliorate capitalism. They also include concerns about technocratic bias and complaints about lack of meaningful consultation with Indigenous peoples on proposals for large-scale shifts in land use. Debates over the ideological orientation, political strategy and implementation of the Green New Deal must now account for the economic and employment impacts of COVID. JEL Codes: Q43, Q54, Q56, Q58

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