F2-G: Advanced Imaging Technology for Whole Body Imaging

Transcription

1 F2-G: Advanced Imaging Technology for Whole Body Imaging Abstract The Advanced Imaging Technology project began in the fall of 2010 with the goal of developing an improved multi-modality portal-based passenger screening system. Millimeter-wave (mm-wave), x-ray backscatter, infrared sensing, and terahertz sensing are being considered. The GHz mm-wave imaging system has produced several hardware and data processing innovations. These include: a novel Blade Beam reflector transmitting antenna that produces narrow target illumination to allow accurate stacked 2D reconstructions of the 3D surface; a carefully positioned multistatic array receiving antenna for artifact-free imaging; and a fast data processing technique, based on the Fast Multipole Method (FMM), that produces 2D SAR images from scattered field sample. The specially-built hardware platform facilitates reconfigurable sensor placement in order to develop the multistatic imaging radar system. In addition, a patent-pending algorithm has been developed for determining the dielectric constant of weak dielectric objects attached to the body. These improvements leads to faster, more accurate whole body imaging to improve the security screening process, with proved detection capabilities validated by means of measurements carried out with a first mmwave portal prototype. I. PARTICIPANTS Faculty/Staff Name Title Institution Phone Carey M. Rappaport Professor NU rappapor@ece.neu.edu Jose A.Martinez-Lorenzo Research NU jmartine@ece.neu.edu Professor Ann Morgenthaler Consultant NEU 7bradford@gmail.com Dan Busioc Consultant NEU db.ipaq@gmail.com Richard Moore Consultant NEU rhmoore@partners.org Borja Gonzalez-Valdes Postdoc NEU bbgonzale@ece.neu.edu Students Name Degree Pursued Institution Intended Year of Graduation Yolanda Rodriguez- Vaqueiro MS NU Rodriguezvaqueiro.y@husky. neu.edu Luis Tirado PhD NU ltirado@gmail.com 2014 Spiros Mantzavinos MS NU mantzavinos.s@husky.neu.edu 2013 Scott Kilcoyne MS NU kilcoyne.sc@husky.neu.edu 2015 Greg Allen BS NU allan.g@husky.neu.edu 2016 Kathryn Williams MS NU kathrynawilliams@gmail.com 2012 Matthew Nickerson BS NU mail@mattnickerson.net 2016 Justin Rooney BS NU rooney.jus@husky.neu.edu 2016 Ryan Miller BS NU miller.rya@husky.neu.edu 2016 James Rooney BS NU rooney.j@husky.neu.edu

2 II. PROJECT OVERVIEW AND SIGNIFICANCE Increasingly, individuals who enter secure areas, airport departure gates, office buildings, stadiums, arenas, and even malls must pass through screening portals which ensures that they are not carrying hidden weapons or explosive threats. These screening portals must be able to detect unusual or anomalous objects concealed under clothing, but be able to do so with a minimum amount of delay, exposure to harmful radiation, or privacy violation. High resolution human body imaging is an effective means of identifying dangerous objects attached to the body under clothing [1]-[3]. Terahertz wave sensing [4],[5] and X-ray radar [6],[7] provide good resolution allowing the detection of small concealed objects, but the former is based on expensive, cutting-edge technology and relies on mechanical scanning for its speed and accuracy, while the X-ray based systems make use of low doses of ionizing emissions [8]. Current state-of-the-art millimeter wave portal imaging systems [1] are mostly based on monostatic radar and Fourier inversion. Although these systems are inherently fast, they present some disadvantages as for example, reconstruction artifacts such as dihedral effects and misrepresenting sudden indentations and protrusions due to the monostatic nature of the collected electric field data. The current state-of-the-art portal-based mm-wave scanning technology uses a monostatic radar configuration in conjunction with Fourier inversion, and a 2D maximum intensity projection to display the resulting images Although these systems are inherently fast, they present some disadvantages as for example, reconstruction artifacts such as dihedral effects and misrepresenting sudden indentations and protrusions due to the monostatic nature of the collected electric field data. More advanced techniques for concealed object reconstruction can be found in the literature [9]. However, for practical 3D human body screening, real-time capabilities are required, so fast methods for geometry reconstruction are needed. The system that has been developed under ALERT support is based on fast multistatic Synthetic Radar Aperture (SAR) imaging and introduces several new contributions to the field of millimeter wave imaging III. RESEARCH AND EDUCATION ACTIVITY A. State-of-the-Art and Technical Approach The aim of the millimeter-wave portal imaging system presented in this work is to produce real-time threedimensional high-resolution images of the whole human body and possible objects concealed under clothing. In the proposed portal-based multistatic system, the body is illuminated by an incident millimeter-wave beam which is generated by a novel elliptical-parabolic reflector antenna which generates a narrow beam in elevation while illuminating the body with constant amplitude in azimuth. Then, the field scattered by the section under illumination is captured by two parallel horizontal receiving antenna arrays (see Figure 1). An advance multistatic imaging algorithm is used to transform the scattered field information into a reconstruction of the contour of the human body along with any objects that might be placed on it. The transmitting reflector and receiving arrays are translated vertically, and the two-dimensional retrieved images are stacked to form a full body surface reconstruction. B. Mm-wave portal system As indicated above, mm-wave illumination is provided by a novel elliptical-parabolic reflector antenna design [15]. This transmitting reflector antenna takes advantage of the fact that for the body-scanning application of interest, the body curvature varies much more in the horizontal direction than in height. As a doublycurved surface, it combines parabolic curvature in the horizontal plane with elliptical curvature in the vertical plane to generate a blade beam focusing radiated field at a narrow horizontal slice (an approximate -3dB

3 beamwidth of 1 cm is achieved) of an object to be imaged, as depicted in Figure 2. With just this slice illuminated, the field scattered from an object will only be due to this narrow portion of the object. In consequence, the human body reflectivity is reconstructed in the slice which is being illuminated by the beam (see Figure 1). This kind of processing transforms the 3D reconstruction problem into multiple 2D reflectivity reconstructions, reducing the computation time for imaging algorithm. We have proved the validity of the profile reconstruction technique for three-dimensional reconstruction using a cylindrical observation domain [16]. However, this kind of two-dimensional approach requires a huge number of receivers in order to avoid slower two-dimensional scanning. In consequence, it is very important to achieve the reconstruction with a much more limited number of observation points in order to decrease the system cost and acquisition and processing times. For this purpose, two parallel horizontal receiving arrays are used (see Figure 1). Inversion is performed for this pair of one-dimensional arrays instead of a costly and complicated two-dimensional array. Multiple frequencies are used to improve the reconstruction results. The range resolution of the system will be given in terms of its bandwidth as:, where c is the speed of the light and BW is the available frequency bandwidth. For the GHz frequency band used, the expected resolution is then 25 mm. For the first prototype of the system, the array of receivers is simulated using only one moving receiver to create a synthetic aperture. Open waveguides are used as both transmitter and receiver antennas. In order to decrease the cost of the system, COTS components are used to sweep frequencies in the desired bands. Figure 1. General scheme of the proposed Millimeter-Wave Portal for Human Body Imaging. C. Data processing algorithm A new implementation of the SAR imaging by means of multipolar expansion, the inverse Fast Multipole Method (ifmm), [16], is used to reconstruct the currents induced in each independent slice and thus to determine the body shape. This method is based on the multipolar expansion of Figure 2. Schematic representation of the beam generated by the transmitting elliptic-parabolic reflector antenna, and the illumination that produces on the human body torso. The array of receivers is also plotted. the electromagnetic field integral equation relating the scattered fields to a set of equivalent electric currents defined on the slice-under-study. These equivalent currents are directly related to the human body (and concealed objects) reflectivity levels and shapes. With regard to traditional mm-wave SAR imaging techniques, there are two main advantages of the FMM [17], [18]: i) FMM uses a dyadic formulation that takes into account the field and current polarization information. This information can be combined with SAR image reflectivity to improve the detection of small objects, as

4 induced current polarization is strongly related to the object shape. ii) FMM is tailored to enhance calculation speed-up. The underlying idea of FMM is to divide the scattered field domain (the receiving arcs) and the reflectivity reconstruction slice into several groups. Thus, instead of calculating the interactions of all the points on the arcs with all the points on the slice, only the interactions between the groups are calculated, thus reducing the number of operations to be done. In addition, the FMM application to inverse problems has other advantages which are discussed in [16]. Consequently, the FMM-based SAR imaging method is able to recover an SAR image of one slice in less than 2 seconds using a conventional desktop computer. This feature is of special relevance, as 2D SAR images are generated while the mm-wave system scans along the elevation axis. Thus, once the system has finished vertical scanning, all the 2D SAR images are available for a final 3D processing. A 3D reflectivity image can be generated by concatenating the reconstructed 2D SAR images. Since these images exhibit the highest reflectivity values at the points placed close to the true profile, the points with larger amplitudes in the image are selected to identify the body contour for each slice. Even when the profile can be clearly identified by observing the highest amplitude values, the development of an automatic image processing method that is able to extract the exact contour is a challenging image-processing task. Among different possibilities (e.g. contour extraction), the processing used in this contribution makes use of direct processing based on isosurfaces: the 3D geometry is created by joining points of different slices having the same reflectivity values. In consequence, it is possible to recover not only the geometry, but also its reflectivity. In the case of small concealed metallic objects, high reflectivity will make identification straightforward. D. Application Example In order to evaluate the performance of the manufactured mm-wave scanning portal, a practical test case has been selected. The human body has been emulated by means of a mannequin covered by skin simulant. A 2.5x2.5x3 cm metal cube placed on top of it is selected for evaluating concealed objects detection capabilities. The mm-wave portal prototype as well as the mannequin with the metal cube attached is depicted in Figure 3. For this configuration, the distance between the reflector antenna dish and the mannequin is 60 cm, which is the distance at which a narrow beam in elevation is generated. The horn antenna receiver is placed 30 cm away from the mannequin torso, as shown in Figure 4. Figure 3. Photos of the manufactured testbed for human body imaging.

5 As mentioned in Section II, the system is intended to collect the scattered field on two antenna array arcs. In this prototype, mechanical scanning is used, acquiring the scattered field on a set of points located on the same positions where the receivers would be mounted. According to sampling criterion to avoid aliasing effects, receivers are placed every.5 cm, resulting in 185 sampling points in an 80º-arc. Another limitation is in using just one arc instead of two, so the scattered field information available on each slice will be half of that available in the final mm-wave portal. Figure 4. 2D view of the imaging system. Measurement and application example parameters. A 2D cut of the mm-wave scanning system is depicted in Figure 4. The mannequin cross-section is approximately 30 x 19 cm. Reflectivity is reconstructed across an area of similar size (30 x 20 cm), discretized into ΔS = (0.2 λ)2 square patches. In consequence, for every 2D slice, the reflectivity is calculated at 73,151 points from the scattered field data collected at 185 points. As mentioned above, the FMM technique generates the SAR image reflectivity in less than 2 seconds. Further speed improvement is possible by using parallel computing capabilities. With regard to vertical scanning, 13 slices separated 1 cm along the z-axis are considered, covering the vertical distance of the Area-Under-Test (blue surface) defined in Figure 2. The metal cube is placed at approximately half of the vertical domain (6.5 cm). SAR images retrieved on several slices (3 cm, 6 cm, and 9 cm) are plotted in Figure 5. As mentioned above, it is observed that the highest reflectivity values follow the true profile of the geometry under study. It must be noted that the reflectivity image -3dB beamwidth agrees with the frequency bandwidth of 6 GHz, which provides ~2.5 cm range resolution. The SAR image corresponding to the 6 cm slice presents an intense reflectivity spot in front of the mannequin torso. This spot corresponds to the 2.5 cm metal cube. Note that even the 9 cm slice shows high reflectivity values in the region corresponding to the vertical projection of the metal cube, probably due to reflections and diffraction effects. 2D SAR images are stacked to provide a first 3D impression of the reflectivity. Figure 6 shows the mannequin torso and the metal cube stacking several slices. In this figure the high reflectivity values due to the metal cube are clearly visible. The 2D stacked slices are processed together to obtain a 3D reflectivity representation. As the slices are close enough in vertical direction (1 cm), reflectivity isosurfaces are selected to produce the 3D model. Figure 7 represents two isosurfaces corresponding to -4 db and -11 db reflectivity levels. Clearly, the -4 db spot matches the placement of the metal cube, while the -11 db isosurface fits the mannequin torso. This highresolution image demonstrates that a relatively small object (a metal cube of 2.5 x 2.5 x 3 cm) is detectable, proving the viability of the proposed system. An algorithm has also been developed that can be used with both conventional and multistatic nearfield mmwave radar scanning systems that supplements their imaging capabilities with dielectric characterization. Our algorithm identifies the value of the dielectric constant of an object attached to a person s skin. With predictive accuracy of better than 90%, this approach can indicate the presence of concealed volumes of material with the dielectric constant of explosives. The extra information provided will allow security person-

6 nel to make quick determinations of whether detected foreign objects have the potential of being threats. If a given volume of foreign matter has a dielectric constant of 3, it is not paper, cloth, glass, food, or rubber, but it might be TNT. By ruling out these typical items that might cause false alarms, the algorithm has the potential of reducing the overall system false alarm rate by as much as an order of magnitude without compromising probability of detection. This is turn will greatly reduce the need for additional secondary inspection. In the case of dielectric materials, such as plastics, rubber, glass, and explosives, a small amount of an incident wave is reflected from the front surface of an object, but most of wave will penetrate through the material. The velocity for this propagating field will be the speed of light in free space scaled by the index of refraction of the material, where is the relative dielectric constant of the dielectric material. Consider the general multistatic case of a distant transmitter illuminating the target scattering volume in yellow, and a separate receiver, position nearer to the scattering volume, as shown in Fig. 8. For the wave leaving the transmitter r t, reflecting from the conductor and ending up at a receiver r r, the differential velocity over the distance Δr1 + Δr2 in the yellow block leads to a phase change (in terms of frequency f): ΔΦ=2πf/c ( Δr_1 + Δr_2 )(1- (ε_r )) The phase term error introduced in the reconstruction will displace the position of the bright spot corresponding to the skin reflection in the reconstructed image to a virtual distance: Δr_3 = ( Δr_1 + Δr_2 )( (ε_r )-1)/2 This effect is not taken into account in the standard imaging formulation in since the velocity in free space is used to reconstruct the currents on each pixel of the image, but it can be used to identify the dielectric constant of the material under test. Using the weak reflected signal from the front surface of the dielectric object, the object thickness can be determined. This distance is combined with the virtual distance Δr 3, which is identified as the distance between the nominal conductive skin surface and the position of the retarded spot to determine the object s dielectric constant. These two measurements can be inferred from the image and the estimated dielectric constant can be derived by using: Figure 5. Reconstructed SAR images (reflectivity, in db) for several slices (z = 3, 6 and 9 cm) from measured responses from mannequin illuminated by the Blade Beam reflector antenna transmitter. Green dotted line represents the approximate profile of the mannequin and the metal cube. Figure 6. Reconstructed SAR images (reflectivity, in db) for several slices from measured responses from mannequin illuminated by the Blade Beam reflector antenna transmitter. Blue surface represents the arppximate mannequin torso. Gray cube represents the metal cube.

7 ε_r=(1+(d_echo/d_obj ))^2 E. Numerical Example Showing Dielectric Constant Characterization of Explosive Material. For this example, the radar operates from 55 to 70 GHz in 500 MHz-steps. The synthetic model data is simulated using FDFD computational modeling. The geometry of interest is similar to Figure 1 with two pure dielectric objects placed on 1-cm thick skin slab, with illumination by a distant cylindrical wave (see Fig. 9)*. Note the reconstruction of the weak (orange colored, highest position) reflection from each block s forward (top) surface, and the virtual displacement downward into the skin of the retarded skin reflection (yellow, lowest position). The values of d obj (4 cm and 2 cm for left and right blocks) and d echo (3 cm and 1.5 cm) can be viewed from the reconstructed image, and the dielectric constant can be derived from the simple formula in Figure 9. Traditional Millimeter Wave Imaging algorithms do not consider that electromagnetically penetrable objects are located on the surface of the person under test; and, therefore, the characteristic electromagnetic interaction and signature between a non-conducting, weak dielectric object and the person under test is not used to infer the dielectric constant of the object. The imaging algorithms presented here accounts for the explosives located on the surface of the person under test. As a result, the characteristic electromagnetic interaction and signature between the dielectric structure and the person under test is used in order to infer the dielectric constant of the explosive simulant. The algorithm can be easily adapted Figure 7 (above). Reflectivity (in db) of the stacked SAR images from experimental measurements. Isosurfaces joining points with the same reflectivity level are plotted. The mannequin torso and the metal cube are overimposed. * The transmitter is centered at (x, y) = (0, 10) m, the backscattered field on a 180º-arc placed R = 0.75 m from the geometry-under-test is calculated. The sampling rate is ΔΦ = 1.25º, which is about 0.5 λ at the center frequency. From the scattered field, the equivalent currents are retrieved on a 0.4 x 0.25 m domain, sampled each ΔS = (0.1λ)2. Figure 8: General geometry for computing dielectric constant characterization of the explosive material. Figure 9 (right): Reconstruction based on modeled data (a) object geometry, (b) SAR image and cuts along y-axis for object εr = 3.

8 to existing mm-wave scanners, such as the L3 ProVision system. IV. FUTURE PLANS Future work includes modeling with the Inverse Fast Multipole Method (IFMM), ray tracing method, and Physical Optics method, continuing to investigate optimal sparse array antenna and multistatic system configurations, and validating and inverting measured data from our novel prototype radar setup, testing the dielectric algorithm on simulated data and experimental hardware to quantify the dielectric characterization in conjunction with object imaging and producing Receiver Operator Characteristics analyzing Probability of Detection vs. Probability of False Alarm. We also plan imaging and reconstruction methods exploring the fusion of mm-wave and x-ray backscatter imaging. V. RELEVANCE AND TRANSITION Passenger screening is of major national interest. An improved technology platform and associated algorithms will reduce detection errors and decrease false positive results. Higher resolution coupled with new feature detection will allow more automatic threat detection, less human inspector involvement, and greater passenger comfort. A well-conceived experiment is essential to validate models, inversion principles, and the concept of operation. Infrastructure has been fabricated to be modular, expandable, and scalable, so it can be used as a platform for a variety of readily fused co-registered security screening modalities. High-precision computer-controlled motion allows rapid data collection and validation. Future advancements in reconstruction techniques, artifact reduction, scan pattern, and mm-wave hardware will be readily implemented and tested on the flexible hardware platform. VI. LEVERAGING OF RESOURCES The portal scanner market is quite large, especially considering foreign airports and other transportation hubs. Improving multimodal sensing technology will clearly lead to new products and processes for this large market. As terrorists become increasingly sophisticated, advanced technology becomes all the more necessary to ensure efficient safety. We will be developing collaborations with vendors to provide additional resources for the effort. If the advanced technology leads to just a 10% reduction in required screening labor, it would save the TSA more than $100M/yr. VII. DOCUMENTATION A. Journal Papers 1. Martínez-Lorenzo, J. A., Quivira, F., and Rappaport, C. M., SAR imaging of suicide bombers wearing concealed explosive threats, Progress In Electromagnetics Research, Vol. 125, 2012, Álvarez, Y., Martínez-Lorenzo, J.Á, Las-Heras, F., Rappaport, C., An inverse fast multipole method for geometry reconstruction using scattered field information, accepted for publication in IEEE Transactions on Antennas and Propagation, Vol. 60, no.7, July 2012, pp

9 3. Alvarez, Y., Gonzalez-Valdes, B., Martinez-Lorenzo, J.A., Las-Heras, F. and Rappaport, C., 3D Whole Body Imaging for Detecting Explosive-related Threats, accepted for publication in IEEE Transactions on Antennas and Propagation. 4. Gonzalez-Valdes, B., Alvarez, Y., Martinez-Lorenzo, J.A., Las-Heras, F., and Rappaport, C., Multistatic Three- Dimensional Millimeter-Wave Portal Based Imaging for Personnel Screening, submitted for publication in IEEE Transactions on Antennas and Propagation. 5. Alvarez, Y., Gonzalez-Valdes, B., Martinez-Lorenzo, J.A., Las-Heras, F. and Rappaport, C., An improved SAR based technique for accurate profile reconstruction, in review for publication in IEEE Transactions on Antennas and Propagation. 6. Gonzalez-Valdes, B., Alvarez, Y., Martinez-Lorenzo, J.A., Las-Heras, F., and Rappaport, C., SAR Processing for Profile Reconstruction and Dielectric Bodies Characterization, submitted for publication in IEEE Transactions on Antennas and Propagation. 7. Gonzalez-Valdes, B., Martinez-Lorenzo, J.A., Rappaport, C., and Pino, A., A New Physical Optics Based Approach to Subreflector Shaping for Reflector Antenna, accepted for publication in IEEE Transactions on Antennas and Propagation. 8. Gonzalez-Valdes, B., Martinez-Lorenzo, J.A., and Rappaport, C., A New Fast Algorithm for Radar Based Shape Reconstruction, submitted for publication in IEEE Transactions on Antennas and Propagation. B. Conference Presentations 1. Álvarez, Y., Martinez-Lorenzo, JA., Las-Heras, F., Rappaport, C., On the Fast Multipole Method Applications for Inverse Problems, EuCap: European Conference on Antennas and Propagation, Prague, Czech Republic, March Alvarez, Y., Valdes, B., Martinez-Lorenzo, J.A., Rappaport, C., Las-Heras, F., 3D Whole Body Imaging for Detecting Explosive-related Threats, accepted for publication in IEEE International Symposium on Antennas and Propagation and USNC/URSI International Symposium National Radio Science Meeting, Chicago, July 2012, four pages. 3. Rappaport, C., González-Valdés, B., The Blade Beam Reflector Antenna for Stacked Nearfield Millimeter- Wave Imaging, accepted for publication in IEEE International Symposium on Antennas and Propagation and USNC/URSI International Symposium National Radio Science Meeting, Chicago, July 2012, four pages. 4. Gonzalez-Valdes, B.,. Martinez-Lorenzo, J.A., Rappaport, C., Pino, A., Fast Multifrequency Algorithm for Radar Based Profile Reconstruction, accepted for publication in IEEE International Symposium on Antennas and Propagation and USNC/URSI International Symposium National Radio Science Meeting, Chicago, July 2012, four pages. 5. Williams, K., Chen, Z., Tirado, L., Gonzalez-Valdes, B., Martínez-Lorenzo, J.A., Rappaport, C., Ray Tracing for 3D Simulation and Inversion for Whole-Body Imaging, accepted for publication in IEEE International Symposium on Antennas and Propagation and USNC/URSI International Symposium National Radio Science Meeting, Chicago, July 2012, one page. 6. Martínez, J.A., Rodriguez-Vaqueiro, Y., Rubiños-López, O., García Pino, A., and Rappaport, C., A compressed sensing approach for detection of explosive threats at standoff distances using a Passive Array of Scatters, accepted for publication in IEEE Homeland Security Technology Conference, Waltham MA, November 2012, one page. 7. Ghazi, G., Martínez, J. A. and Rappaport, C., A new super-resolution algorithm for millimeter wave imaging for security applications, accepted for publication in IEEE Homeland Security Technology Conference, Waltham MA, November 2012, one page.

10 8. Gonzalez Valdes, B., Alvarez, Y., Martinez Lorenzo, J.A., Las Heras, F., and Rappaport, C., Three-dimensional Millimeter-Wave Portal for Human Body Imaging, accepted for publication in IEEE Homeland Security Technology Conference, Waltham MA, November 2012, one page. 9. Maio, P., Rappaport C., Naqvi, W., Rodriguez Vaqueiro, Y., Path Trajectory and Orientation Analysis for RF Phenomenological Scattering Understanding in a Wide Area Secure Perimeter System, accepted for publication in IEEE Homeland Security Technology Conference, Waltham MA, November 2012, one page. C. Technology Transfer Patent Applications Filed: 1. Doubly Shaped Reflector Transmitting Antenna for Millimeter-Wave Security Scanning System, July Signal Processing Algorithm for Explosive Detection and Identification using Electromagnetic Radiation, July 2012 D. Seminars, Workshops and Short Courses VIII. REFERENCES [1] D. M. Sheen, D. L. McMakin, T. E. Hall, Three-Dimensional Millimeter-Wave Imaging for Concealed Weapon Detection, IEEE Transactions on Microwave Theory and Techniques, Vol. 49, No. 9, pp , September [2] J. Fernandes, C. M. Rappaport, J. A. Martínez-Lorenzo, M. Hagelen, Experimental results for standoff detection of concealed body-worn explosives using millimeter-wave radar and limited view ISAR processing, 2009 IEEE Conference on Technologies for Homeland Security (HST 09). Waltham, MA, May 11-12, pp [3] A. Angell, C. Rappaport, Computational Modeling Analysis of Radar Scattering by Metallic Body-Worn

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