Array Resistivity Research Articles

Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets

This study evaluates the performance of multiple machine learning (ML) algorithms and electrical resistivity (ER) arrays for inversion with comparison to a conventional Gauss-Newton numerical inversion method. Four different ML models and four arrays were used for the estimation of only six variables for locating and characterizing hypothetical subsurface targets. The combination of dipole-dipole with Multilayer Perceptron Neural Network (MLP-NN) had the highest accuracy. Evaluation showed that both MLP-NN and Gauss-Newton methods performed well for estimating the matrix resistivity while target resistivity accuracy was lower, and MLP-NN produced sharper contrast at target boundaries for the field and hypothetical data. Both methods exhibited comparable target characterization performance, whereas MLP-NN had increased accuracy compared to Gauss-Newton in prediction of target width and height, which was attributed to numerical smoothing present in the Gauss-Newton approach. MLP-NN was also applied to a field dataset acquired at U.S. DOE Hanford site.

Adaptive Gradient Projection Correction Method for Resistivity Array Imaging Logging

Adaptive Gradient Projection Correction Method for Resistivity Array Imaging Logging

Estimation of aquifer parameters from electrical resistivity data and lithologs in Idah area, Northern Anambra basin, Nigeria

The parameters of the aquifers in Idah area were characterized by integrating resistivity and litholog data. To achieve this, a total of twenty-three (23) Soundings were conducted by applying the 1-D Schlumberger resistivity array and integrating it with borehole lithologs to empirically determine the aquifer parameters in the Idah area, Northern Anambra Basin, Nigeria. The results of the analyses indicate that the aquifer zone resistivity ranges from 36.65 – 2065.31 Ωm while the aquifer thickness is between 15.60 m and 66.66 m. Its values of the longitudinal conductance (S), transverse resistance (TR), and hydraulic conductivity (k) are 0.01-1.13 mhos, 1518.90-90265.88 Ωm2 , and 0.31-13.44 m/day, respectively. The transmissivity (T) values vary from 4.88 to 2 557.78 m /day. T is inversely proportional to TR with a correlation coefficient of 0.28. The result of the reflection coefficient is in the range of -0.79 to 0.66, while that of the fractured contrast is between 0.11 and 5.06. The results suggest that an aquifer system that is predominantly fracture-based is underlying the region. Lithification and diagenesis influence the hydrological properties. The northern–central portions of the map are more suitable for groundwater exploration /exploitation than the southern/eastern ends.

Comparison between double caliper, imaging logs, and array sonic log for determining the in-situ stress direction: A case study from the ultra-deep fractured tight sandstone reservoirs, the Cretaceous Bashijiqike Formation in Keshen8 region of Kuqa depression, Tarim Basin, China

The tight sandstone in the Tarim Basin has the characteristics of large burial depth and development of nature fractures due to concentrated in-situ stress. Identifying the present-day in-situ stress orientation is important in hydrocarbon exploration and development, but also a key scientific question in understanding naturally fractured reservoirs. This paper presents a case study where we integrate various methods using wireline and image-log data, to identify present-day in-situ stress direction of ultra-deep fractured tight sandstone reservoirs, in the Kuqa depression. We discuss the formation mechanism of the elliptical borehole, compares the advantages and applicable conditions of the double caliper method, resistivity image logs and array sonic logs method. The well borehole diameter is measured orthogonally, then the ellipse is fitted, and the in-situ stress orientation is identified by the azimuth of the short-axis borehole, but it fails in the borehole expansion section, the fracture development section and the borehole collapse section. The micro-resistivity image logs method reveals the borehole breakouts azimuth, and also the strike of induced fractures, which are used to determine the orientation of in-situ stress. However, under water-based mud conditions, it's hard to distinguish natural fractures from induced fractures by image logs. Under oil-based mud conditions, the induced fractures are difficult to identify due to the compromised image quality. As for the sonic log, shear waves will split when passing through an anisotropic formation, shear waves will split during propagation, and the azimuth of fast shear waves is consistent with the orientation of in-situ stress. However, it is usually affected by the anisotropy caused by the excessively fast rotation of the well log tools, so that the azimuth of fast shear wave cannot effectively reflect the orientation of the in-situ stress. Based on comprehensive assessment and comparison, in this paper we propose a method integrating various logging data to identify the orientation of in-situ stress. Among various types of logging data, the breakouts azimuth identified by image logs is proved to be the most credible in identifying the orientation of in-situ stress, while using the direction of induced fractures under water-based mud conditions is also viable. However, the azimuth of the fast shear wave is consistent with the orientation of maximum in-situ stress only when the rotation speed of the logging tool is low. The caliper method can be used as a reference for verifying the other two methods. Using this integrated method to study the orientation of in-situ stress in the Keshen 8 trap, the results show that faults are an important factor affecting the direction of in-situ stress, while multi-level faults will produce superimposed effects that cause the current direction of in-situ stress to change.

Comparison of Three Electrical Resistivity Arrays to Investigate Weak Zones in Soil, Along a Profile Southeast Baghdad City, Iraq

The electrical resistivity method is one of the geophysical methods for detecting weak subsurface zone. The 2D resistivity data were used to compare three electrode configurations, Wenner, Dipole-dipole, and Schlumberger, to detect weak subsurface zones along a profile south of Baghdad near the Bismayah pumping station. The results show many zones of low resistivity that may be weak zones. A dipole-dipole array is a large number of measurements and is more sensitive than others. The Wenner-Schlumberger array has a depth also higher than other arrays. Wenner array has higher signal strength than other arrays. Because it is more sensitive to horizontal and vertical structures, the dipole-dipole array is the optimum for mapping subsurface weak zone.

Series connection of quantum Hall resistance array and programmable Josephson voltage standard for current generation at one microampere

An accurate current can be realized by a series connection of an invariant voltage and resistance with zero interconnection resistance in the framework of Ohm’s law. In practice, however, accurate current realization is limited by the temporal drift and instability of employed resistors, solid-state voltage sources and interconnection wires against environmental fluctuations, such as temperature or atmospheric pressure. Here, we generated a current of 1 μA, determined by the Josephson voltage and quantized Hall resistance array (QHRA). A programmable Josephson voltage standard (PJVS), 1 MΩ QHRA and ultrastable low noise current amplifier (ULCA) are connected in series to generate and measure a current of 1 μA. The expected current is calculated as the ratio of the Josephson voltage to the QHRA plus the output resistance of the PJVS. The relative difference between the current measured by the ULCA and the calculated current is as small as 40 nA A−1 with a combined measurement uncertainty (k = 1) of 0.13 μA A−1.

Open-source learning as a skill for geoelectrical data processing: the case of pyGIMLi

It is important that new strategies are developed for the management of geoelectrical data produced from engineering and geoscience processing techniques. For this reason, the article demonstrates how pyGIMLi can be used for this purpose. pyGIMLi is an open-source library for the inversion of apparent resistivity array that are often obtained with different geoelectrical survey equipment. The aim is to be able to use this library unaided for various projects and/or to perform various data operations in which the results obtained are more specific and differentiated than those derived from other processing techniques, taking advantage of the fact that this tool is open-source.

Design of an enhanced mechanism for a new Kibble balance directly traceable to the quantum SI

The “Quantum Electro-Mechanical Metrology Suite” (QEMMS) is being designed and built at the National Institute of Standards and Technology. It includes a Kibble balance, a graphene quantum Hall resistance array and a Josephson voltage system, so that it is a new primary standard for the unit of mass, the kilogram, directly traceable to the International System of Units (SI) based on quantum constants. We are targeting a measurement range of 10 g to 200 g and optimize the design for a relative combined uncertainty of 2times 10^{-8} for masses of 100 g. QEMMS will be developed as an open hardware and software design. In this article, we focus on the design of an enhanced moving and weighing mechanism for the QEMMS based on flexure pivots.

Assessing the suitable electrical resistivity arrays for characterization of basement aquifers using numerical modeling

Numerical modeling analysis was used to assess the suitable electrical resistivity arrays for the characterization of geological structures, including dyke, horst, graben, sub-vertical, and vertical structures. These geological structures usually make up the aquifers interested in the hydrogeological evaluation of crystalline basement terrains. Six electrode configurations, including Wenner alpha (α), Wenner beta (β), Wenner gamma (γ), Schlumberger array, dipole-dipole array, and pole-dipole array, were used to assess the geological structures for groundwater exploration. The synthetic models of the geological structures were generated using RES2DMOD code, and 5% noise was added to all the models. The generated models were inverted using the RES2DINV code. The results show that the most suitable arrays for dyke and graben structures are Wenner alpha, while Wenner beta is the most suitable for the horst structure. The Schlumberger array was the best for both sub-vertical and vertical structures. This study has demonstrated the efficacy of numerical modeling in assessing the best resistivity arrays for 2D electrical resistivity imaging for groundwater exploration prior to geophysical field investigation.

Campylobacter Express Resistance Array for detecting the presence of fluoroquinolone- and macrolide-resistant Campylobacter jejuni and Campylobacter coli in broiler farms.

The aim of the study was to develop a microarray-based method for the detection of antibiotic-resistant Campylobacter in broiler farms to decrease the risk of contamination of chicken meat. A combination of DNA microarray and primer extension for rapid and simultaneous detection of fluoroquinolone- and macrolide-resistant Campylobacter jejuni/Campylobacter coli, termed Campylobacter Express Resistance Array (CAMERA), was used to analyse chicken caecal droppings. CAMERA assays could detect at least 105 colony forming units of C. jejuni/C. coli g-1 of chicken caecal contents spiked with C. jejuni/C. coli. To compare the CAMERA method and direct culturing method for screening antibiotic-resistant C. jejuni/C. coli in poultry farms, chicken caecal droppings obtained from 42 poultry houses were analysed using both methods. In total, 95.2% of the results (40/42 poultry houses) obtained using the CAMERA and culturing method were identical. In the remaining two poultry houses, the CAMERA could detect the prevalent strain of C. jejuni/C. coli based on results of the culturing method. The culturing method required >3days to isolate and identify antibiotic-resistant C. jejuni/C. coli. In contrast, the CAMERA required only 6h. This method can facilitate quick screening and control of fluoroquinolone- and macrolide-resistant C. jejuni/C. coli in broiler farms.

Time-lapse electrical resistivity tomography (ERT) monitoring of used engine oil contamination in laboratory setting

Geophysical methods are being used effectively for monitoring, characterizing, and mapping Light Non-Aqueous Phase Liquids (LNAPLs). Although Used Engine Oil (UEO) is one of the most common LNAPLs contaminants within the urban communities, not much attention has been given for the geophysical study of UEO contamination. The main objectives of this research were to monitor the migration of UEO, and to investigate the electrical characteristics of UEO as viscous LNAPL within a tank aquifer system using time-lapse electrical resistivity tomography (ERT). The ERT data were collected using 24 electrodes arranged as a miniature resistivity array. The contaminant was injected into the tank aquifer system, and the electrical changes of the contaminant were monitored for a period of 80 days. The time lapse results revealed vertical and lateral migration of the contaminant with the lateral migration dominating. The results also revealed increase in electrical resistivity values from day 1 until day 35, then a drastic decrease to day 50, then a slight increase to day 60, and then decrease till day 80. Based on the change of odour of the contaminated region from used engine oil odour to slightly rotten odour and based on relevant published research, it was interpreted that the decrease in electrical resistivity was associated with UEO degradation that might be caused by microbial activity. The results of this study show that time-lapse ERT is an effective geophysical method to monitor used engine oil contamination.

In situ particles deposition imaging in centrifugal fields by implemented SPH-DEM-ANN into linear sensor-type wireless electrical resistance tomography (lsWERT)

In situ particles deposition images in centrifugal fields have been reconstructed by combination of smoothed particle hydrodynamics, discrete element method, and artificial neural network (SPH-DEM-ANN) which are implemented into linear sensor-type wireless electrical resistance tomography (lsWERT). The implemented SPH-DEM-ANN into lsWERT has a training section and a real imaging section. The training section is composed of four components which are 1) calculation component of phase-particles position by SPH-DEM for bead- and liquid-particles position array XP and XL in two-dimensional centrifugal fields, 2) generation component of conductivity map by conductivity map generator for simulated phase-particles array Dsim consisting of element array Γ, node-particles array X^, and phase-particles conductivity array σ, 3) simulation component of normalized resistance by electrical forward problem for simulated normalized resistance array R~sim consisting of simulated resistance array Rsim and simulated reference resistance array Rˇsim, and 4) training component of model factors by ANN for weight factors ki, j and bias βj in hidden layers. After the 4th training component in the training section, the real imaging section reconstructed the in situ particles deposition images in centrifugal fields based on the experimental normalized resistance array R~exp under three bead-particles numbers NP = 40, 48, 56, and four rotational speeds ω =175, 205, 235, and 255 rpm. As the results, the implemented SPH-DEM-ANN into lsWERT is able to reconstruct the in situ particles deposition images accurately with four evaluation indicators which are the averaged difference of phase-particles array between Dsim and Dexp: D¯δ=0.915, the averaged deviation of normalized resistance array between R~exp and R~sim: R¯δ=0.153, the averaged deviation of particles maximum height ZmaxP by a high-speed camera (HSC): Z¯δ=7.18%, and the averaged root mean square error of surface particles deposition quadratic curve: RMSE¯=3.465.

The Role of Model Weighting Functions in the Gravity and DC Resistivity Inversion

This article aims at analyzing the inversion with the mostly used model weighting functions for both gravity and dc resistivity data. We show that the model weighting function built with depth weighting and compacting factor, formerly formulated for the gravity and magnetics problems, can be useful also for dc resistivity data. We provide a number of synthetic cases to discuss the pros and cons of each model-weighting function. For gravity and dc resistivity data, the comparison was made using the depth weighting with different exponents, the compactness, and, for the dc resistivity nonlinear problem, the roughness matrix under the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{1}$ </tex-math></inline-formula> <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</i> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{2}$ </tex-math></inline-formula> -norm constrained optimizations. As for the depth weighting, the value of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> exponent is decisive for the gravity problem, ranging from very low values for interfaces to 1 for compact sources. The dc resistivity data inversion is less sensitive to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> , but the above-indicated choice leads to faster convergence. Similarly, the role of compactness is decisive for reconstructing a compact source from gravity, while, for dc resistivity, it is especially useful to warrant an even faster convergence. Using the roughness matrix tends instead to provide a decrease in resolution at depth. We obtained interesting results for different types of dc resistivity arrays: the weighting function built with depth-weighting and compactness yields a more coherent source reconstruction than that using the roughness matrix. We also analyze two different real dc resistivity cases, which confirms, again, the usefulness of the depth weighting and compactness to model the deep resistive sources.

Utilizing NWCR optimized arrays for 2D ERT survey to identify subsurface structures at Penang Island, Malaysia

In this paper, the effectiveness of optimized and conventional resistivity arrays for resolving shallow geological features was investigated at Penang Island, Malaysia. The assessment was between the inversion results from Noise-Weighted Compare R (NWCR) optimized arrays, and commonly used conventional arrays (Dipole-Dipole (DD) and Wenner-Schlumberger (WS)). This is demonstrated using two field cases studies. The first case was conducted at an area characterized by fractures /cracks in the walls and ceiling of a heritage building in Georgetown city. The aim was to identify the weakness zone responsible for the observed fractures. The second case study was conducted in the main campus of Universiti Sains Malaysia (USM), to delineate the interface between the granitic bedrock and the unconsolidated sediments. In the first case, the results show a layer with a resistivity value of less than 2 Ohm-m between 2 m to 6 m depth. This layer could be the weak zone in the investigated area. The NWCR optimized arrays detected this zone better than the DD and WS. This finding correlates quite well with the shear wave velocity (Vs) model, with Vs less than 115 m/s in the same line and depth. For the second case study, the results were compared with the borehole log in the middle of the resistivity line. The ERT model obtained from the NWCR defines the granitic surface at around 32 m depth, which correlates well with the borehole log, while the model from the DD arrays underestimated depth. In summary, the NWCR optimized arrays give a more accurate image of the subsurface resistivity distribution, followed by the DD array. The WS array performed the least.

Non-contact harmonic magnetic field detection for parallel steel pipeline localization and defects recognition

A novel detection method and targets signal extraction algorithm for parallel steel pipeline localization and defects recognition based on harmonic magnetic field are proposed. An orthogonal vector differential focusing array detector was designed, which radiates high-frequency (HF) and ultra-low-frequency (ULF) electromagnetic waves to pipeline based on the principle of Frequency Modulated Continuous Wave (FMCW), and records the signals in parallel using high-sensitivity Tunnel Magneto Resistance (TMR) array sensors. The joint signal pre-processing algorithm of Combination Morphological Pulse Elimination (CMPE) and Quantum Genetic Gaussian Potential Stochastic Resonance (QGGPSR) is proposed to improve signal quality by adaptively eliminating random pulse and noise. The time–frequency analysis algorithm Complementary Ensemble Local Mean Decomposition (CELMD) is used to decompose the pipeline defects signal in detail, and the appropriate components are selected and fused into a correlation array signal cluster. Finally, the targets signal are separated by Limited-memory BFGS Independent Component Analysis (L-BFGS-ICA) based on machine learning optimization to enhance their legibility. The magnetic dipole harmonic simulation model and the 20# steel parallel pipeline experimental platform are established, and compared with the passive detection method to verify the effectiveness and practicality of the proposed method. The results show that this method can accurately locate parallel pipelines and detect different kinds of defects in noisy environment, which is of great significance for the application of non-contact Non-Destructive Testing (NDT) in practical engineering.

Deformation process modeling of the rock mass with spherical cavity created by explosion

The article discusses the solution to the axisymmetric problem of determining the stresses and displacements arising from the joint action on the asymmetric load (soil resistance) array and a centrally symmetric temperature field. The case of continuous one-dimensional inhomogeneity is considered, when the deformation characteristics of a rock mass with a spherical cavity obtained by explosion are the continuous functions of one of the coordinates - the radius. The solution of the original system of equations for the displacement components is sought in the form of expansions in Fourier series in Legendre polynomials. Using the method of variablesseparation, it is possible to reduce the problem to a system of two ordinary differential equations with variable coefficients, which is solved numerically. The stress state calculation of homogeneous and inhomogeneous massifs surrounding a spherical cavity has been carried out. A comparative analysis of the results obtained has been performed.

Rapid and simultaneous detection of fluoroquinolone- and macrolide-resistant Campylobacter jejuni/coli in retail chicken meat using CAMpylobacter Express Resistance Array (CAMERA)

A rapid method for the simultaneous detection of fluoroquinolone- and macrolide-resistant Campylobacter jejuni/coli in food products is long-awaited. In this study, we developed a DNA microarray-based method with primer extension, named CAMpylobacter Express Resistance Array (CAMERA). A series of oligonucleotide probes corresponding to each mutation in gyrA and rrl for fluoroquinolone and macrolide resistance, respectively, were selected and fixed on a membrane as capture probes for identifying C. jejuni/coli and detecting mutations conferring fluoroquinolone- and macrolide-resistance. The specificity was confirmed using 152 strains from livestock feces. Spiking of chicken meat samples revealed that CAMERA can detect 1–9 CFU/g C. jejuni/coli. Seventeen Campylobacter strains (16 C. jejuni and 1 C. coli) were isolated from 100 retail chicken meat samples via microbial culture. Using CAMERA, 16 of these 17 samples were positive for C. jejuni/coli, and the susceptibility to fluoroquinolone/macrolide could be determined (94% sensitivity and 100% specificity). The culture method requires more than 5–6 days for isolating C. jejuni/coli and determining antimicrobial susceptibility. In contrast, CAMERA requires <30 h from the beginning of the enrichment culture to the final determination of fluoroquinolone- and macrolide-resistant C. jejuni/coli. These results suggest that CAMERA is a rapid method for detecting C. jejuni/coli and is suitable for simultaneously determining the susceptibility to the two front-line drugs. This method may facilitate surveillance and control of fluoroquinolone- and macrolide-resistant C. jejuni/coli contamination in retail chicken meat.

Precision measurement of single-electron current with quantized Hall array resistance and Josephson voltage

A single electron pump was incorporated with a quantum Hall resistance and a Josephson voltage for the current evaluation in the framework of Ohm’s law. The pump current of about 60 pA level was amplified by a stable amplifier with a gain of 103 to induce a Hall voltage of about 60 mV level across a 1 MΩ Hall resistance array, which was compared with the Josephson voltage. The gain of the current amplifier was calibrated with a cryogenic current comparator bridge. For two different drive frequencies and repeated thermal cycles, the comparisons demonstrated that the pump current averaged over the first plateau was equal to ef within the combined uncertainty level of 0.3 × 10−6 (k = 1).

Void fraction measurement of gas–liquid two-phase flow with a 12-electrode contactless resistivity array sensor under different excitation patterns

This work focuses on the void fraction measurement of gas–liquid two-phase flow by a 12-electrode contactless resistivity array sensor. Such a sensor, which can realize different excitation patterns, is developed here. Five different excitation patterns (with 1, 2, 3, 4 or 5 electrodes) and three two-phase distributions (bubble flow, stratified flow and annular flow) are investigated. Two data processing approaches, the data average method and the principal component regression (PCR) method, are used to establish models of void fraction measurement and hence to implement it. Experiments on void fraction measurement are carried out with the 12-electrode contactless resistivity array sensor. The results show that the void fraction measurement performances are different under different excitation patterns. Among the five different excitation patterns studied, the one with five electrodes has the best performance and the absolute values of void fraction measurement errors of the three two-phase distributions are all less than 5.0% (using the data average method) and 3.0% (using the PCR method). Research results indicate that the 5-electrode excitation pattern + PCR combination is a new effective way to implement void fraction measurement of gas–liquid two-phase flow with the 12-electrode contactless resistivity array sensor.

Up-regulation of GLI1 in vincristine-resistant rhabdomyosarcoma and Ewing sarcoma

BackgroundThe clinical significance of GLI1 expression either through canonical Hedgehog signal transduction or through non-canonical mechanisms in rhabdomyosarcoma (RMS) or Ewing sarcoma (EWS) is incompletely understood. We tested a role for Hedgehog (HH) signal transduction and GL11 expression in development of vincristine (VCR) resistance in RMS and EWS.MethodsWe characterized baseline expression and activity of HH pathway components in 5 RMS (RD, Rh18, Ruch-2, Rh30, and Rh41) and 5 EWS (CHLA9, CHLA10, TC32, CHLA258, and TC71) cell lines. We then established VCR-resistant RMS and EWS cell lines by exposing cells to serially increasing concentrations of VCR and determining the IC50. We defined resistance as a ≥ 30-fold increase in IC50 compared with parental cells. We determined changes in gene expression in the VCR-resistant cells compared with parental cells using an 86-gene cancer drug resistance array that included GLI1 and tested the effect of GLI1 inhibition with GANT61 or GLI1 siRNA on VCR resistance.ResultsWe found evidence for HH pathway activity and GLI1 expression in RMS and EWS cell lines at baseline, and evidence that GLI1 contributes to survival and proliferation of these sarcoma cells. We were able to establish 4 VCR-resistant cell lines (Ruch-2VR, Rh30VR, Rh41VR, and TC71VR). GLI1 was significantly up-regulated in the Rh30VR, Rh41VR, and TC71VR cells. The only other gene in the drug resistance panel that was significantly up-regulated in each of these VCR-resistant cell lines compared with their corresponding parental cells was the GLI1 direct target and multidrug resistance gene, ATP-binding cassette sub-family B member 1 (MDR1). We established major vault protein (MVP), which was up-regulated in both vincristine-resistant alveolar RMS cell lines (Rh30VR and Rh41VR), as another direct target of GLI1 during development of drug resistance. Treatment of the VCR-resistant cell lines with the small molecule inhibitor GANT61 or GLI1 siRNA together with VCR significantly decreased cell viability at doses that did not reduce viability individually.ConclusionsThese experiments demonstrate that GLI1 up-regulation contributes to VCR resistance in RMS and EWS cell lines and suggest that targeting GLI1 may benefit patients with RMS or EWS by reducing multidrug resistance.