Pub Date : 2022-07-01DOI: 10.2352/j.imagingsci.technol.2022.66.4.040408
Bo Wang, Fengqiang Yuan, Zhiwei Lv, Ying He, Zongren Chen, Jianhua Hu, Jun Yu, Shuzhao Zheng, Hai Liu
. Thyroid nodules classification in ultrasound images is actively researched in the field of medical image processing. However, due to the low quality of ultrasound images, severe speckle noise, the complexity and diversity of nodules, etc., the classification and diagnosis of thyroid nodules are extremely challenging. At present, deep learning has been widely used in the field of medical image processing, and has achieved good results. However, there are still many problems to be solved. To address these issues, we propose a mask-guided hierarchical deep learning (MHDL) framework for the thyroid nodules classification. Specifically, we first develop a Mask RCNN network to locate thyroid nodules as the region of interest (ROI) for each image, to remove confounding information from input ultrasound images and extract texture, shape and radiology features as the low dimensional features. We then design a residual attention network to extract depth feature map of ROI, and combine the above low dimensional features to form a mixed feature space via dimension alignment technology. Finally, we present an AttentionDrop-based convolutional neural network to implement the classification of benign and malignant thyroid nodules in the mixed feature space. The experimental results show that our proposed method can obtain accurate nodule classification results, and hierarchical deep learning network can further improve the classification performance, which has immense clinical application value. c (cid:13) 2022 Society for Imaging Science and Technology. [DOI: 10.2352
{"title":"Hierarchical Deep Learning Networks for Classification of Ultrasonic Thyroid Nodules","authors":"Bo Wang, Fengqiang Yuan, Zhiwei Lv, Ying He, Zongren Chen, Jianhua Hu, Jun Yu, Shuzhao Zheng, Hai Liu","doi":"10.2352/j.imagingsci.technol.2022.66.4.040408","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2022.66.4.040408","url":null,"abstract":". Thyroid nodules classification in ultrasound images is actively researched in the field of medical image processing. However, due to the low quality of ultrasound images, severe speckle noise, the complexity and diversity of nodules, etc., the classification and diagnosis of thyroid nodules are extremely challenging. At present, deep learning has been widely used in the field of medical image processing, and has achieved good results. However, there are still many problems to be solved. To address these issues, we propose a mask-guided hierarchical deep learning (MHDL) framework for the thyroid nodules classification. Specifically, we first develop a Mask RCNN network to locate thyroid nodules as the region of interest (ROI) for each image, to remove confounding information from input ultrasound images and extract texture, shape and radiology features as the low dimensional features. We then design a residual attention network to extract depth feature map of ROI, and combine the above low dimensional features to form a mixed feature space via dimension alignment technology. Finally, we present an AttentionDrop-based convolutional neural network to implement the classification of benign and malignant thyroid nodules in the mixed feature space. The experimental results show that our proposed method can obtain accurate nodule classification results, and hierarchical deep learning network can further improve the classification performance, which has immense clinical application value. c (cid:13) 2022 Society for Imaging Science and Technology. [DOI: 10.2352","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42453306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.2352/j.imagingsci.technol.2022.66.4.040410
Wenda Xie, Jun Yu, Xiaobo Jiang, Zongren Chen
{"title":"Natural Feature Recognition of Multi Pose Face Images based on Augmented Reality","authors":"Wenda Xie, Jun Yu, Xiaobo Jiang, Zongren Chen","doi":"10.2352/j.imagingsci.technol.2022.66.4.040410","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2022.66.4.040410","url":null,"abstract":"","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43192019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-01DOI: 10.2352/j.imagingsci.technol.2022.66.4.040405
Kun Zhang, Liting Zhang, Xiao-hong Wang, Xinshuai Hua, Xuan Gao
{"title":"DiM-PCNet:3D Point Clouds Classification with Multi-scale and Multi-level Feature Net","authors":"Kun Zhang, Liting Zhang, Xiao-hong Wang, Xinshuai Hua, Xuan Gao","doi":"10.2352/j.imagingsci.technol.2022.66.4.040405","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2022.66.4.040405","url":null,"abstract":"","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43613241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-01DOI: 10.2352/j.imagingsci.technol.2022.66.3.030510
Selvagumar Senthurran, W. T. Yuen Peter, U. Soori, J. Piper, J. David, D. Andre, M. Richardson
.
{"title":"Modelling of A New X-Ray Backscatter Imaging System: Simulation Investigation","authors":"Selvagumar Senthurran, W. T. Yuen Peter, U. Soori, J. Piper, J. David, D. Andre, M. Richardson","doi":"10.2352/j.imagingsci.technol.2022.66.3.030510","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2022.66.3.030510","url":null,"abstract":".","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44777264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-01DOI: 10.2352/j.imagingsci.technol.2022.66.3.030509
Robert Y. Chung, Y. Liu
. The Pantone R (cid:13) Formula Guide (or Guide), printed using specially-formulated inks on specified substrates, has been used widely by brands to specify brand color aims. While the Guide is silent on brand color tolerance, there are two competing criteria that influence the brand color tolerance, i.e., perceptibility and acceptability. Perceptibility-based color tolerance focuses on “Can I see the difference?” and the permissive difference is in the just-noticeable difference (JND) region. Acceptability-based color tolerance, focusing on “Can I accept the outcome?”, requires fit-for-use cases to identify what the just-acceptable difference (JAD) is. Instead of conducting psychometric tests, this research uses the 2019 Pantone R (cid:13) Formula (Coated) Guide, consisting of 2140 CIELAB colors, and data analyses of the “neighboring color difference” to investigate what is the acceptability-based color tolerance. The result shows that the acceptability-based color tolerance (3 (cid:49) E 00 ) has more margin than the perceptibility-based color tolerance (2 (cid:49) E 00 ).
{"title":"Acceptability-based Brand Color Tolerance, A Case Study","authors":"Robert Y. Chung, Y. Liu","doi":"10.2352/j.imagingsci.technol.2022.66.3.030509","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2022.66.3.030509","url":null,"abstract":". The Pantone R (cid:13) Formula Guide (or Guide), printed using specially-formulated inks on specified substrates, has been used widely by brands to specify brand color aims. While the Guide is silent on brand color tolerance, there are two competing criteria that influence the brand color tolerance, i.e., perceptibility and acceptability. Perceptibility-based color tolerance focuses on “Can I see the difference?” and the permissive difference is in the just-noticeable difference (JND) region. Acceptability-based color tolerance, focusing on “Can I accept the outcome?”, requires fit-for-use cases to identify what the just-acceptable difference (JAD) is. Instead of conducting psychometric tests, this research uses the 2019 Pantone R (cid:13) Formula (Coated) Guide, consisting of 2140 CIELAB colors, and data analyses of the “neighboring color difference” to investigate what is the acceptability-based color tolerance. The result shows that the acceptability-based color tolerance (3 (cid:49) E 00 ) has more margin than the perceptibility-based color tolerance (2 (cid:49) E 00 ).","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42125418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-01DOI: 10.2352/j.imagingsci.technol.2022.66.3.030508
G. Geleijnse, L. Veder, M. Hakkesteegt, R. M. Metselaar
{"title":"The Objective Measurement and Subjective Perception of Flexible ENT Endoscopes’ Image Quality","authors":"G. Geleijnse, L. Veder, M. Hakkesteegt, R. M. Metselaar","doi":"10.2352/j.imagingsci.technol.2022.66.3.030508","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2022.66.3.030508","url":null,"abstract":"","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48397431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-14DOI: 10.2352/J.ImagingSci.Technol.2023.67.3.030405
Jinze Sha, A. Goldney, A. Kadis, Jana Skirnewskaja, T. Wilkinson
In a computer-generated holographic projection system, the image is reconstructed via the diffraction of light from a spatial light modulator. In this process, several factors could contribute to non-linearities between the reconstruction and the target image. This paper evaluates the non-linearity of the overall holographic projection system experimentally, using binary phase holograms computed using the one-step phase retrieval (OSPR) algorithm, and then applies a digital pre-distortion (DPD) method to correct for the non-linearity. Both a notable increase in reconstruction quality and a significant reduction in mean squared error were observed, proving the effectiveness of the proposed DPD-OSPR algorithm.
{"title":"Digital Pre-Distorted One-Step Phase Retrieval Algorithm for Real-Time Hologram Generation for Holographic Displays","authors":"Jinze Sha, A. Goldney, A. Kadis, Jana Skirnewskaja, T. Wilkinson","doi":"10.2352/J.ImagingSci.Technol.2023.67.3.030405","DOIUrl":"https://doi.org/10.2352/J.ImagingSci.Technol.2023.67.3.030405","url":null,"abstract":"In a computer-generated holographic projection system, the image is reconstructed via the diffraction of light from a spatial light modulator. In this process, several factors could contribute to non-linearities between the reconstruction and the target image. This paper evaluates the non-linearity of the overall holographic projection system experimentally, using binary phase holograms computed using the one-step phase retrieval (OSPR) algorithm, and then applies a digital pre-distortion (DPD) method to correct for the non-linearity. Both a notable increase in reconstruction quality and a significant reduction in mean squared error were observed, proving the effectiveness of the proposed DPD-OSPR algorithm.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42226543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.2352/j.imagingsci.technol.2021.65.4.040405
J. F. Dijksman, U. Stachewicz
Abstract On-demand electrohydrodynamic jetting also called electrohydrodynamic atomization (EHDA) is a method to jet small amounts of fluid out of a nozzle with a relatively large diameter by switching on and off an electrical field between the nozzle and the substrate. The total amount of volume deposited is up to 5 pL. The set-up consists of a vertically placed glass pipette with a small nozzle directed downward and a flat substrate placed close to the end of the nozzle. Inside the pipette, an electrode is mounted close to the entrance of the nozzle. The electrode is connected to a high voltage power amplifier. Upon switching on the electrical field, the apparent surface tension drops, the meniscus deforms into a cone and fluid starts to flow toward the nozzle deforming the meniscus. At a certain moment the cone reaches the Taylor cone dimensions and from its tip a jet emerges that decomposes into a stream of charged fL droplets that fly toward the substrate. This process stops when the pulse is switched off. After switching off, the meniscus returns slowly to its equilibrium position. The process is controlled by different time constants, such as the slew rate of the power amplifier and the RC time of the electrical circuit composed of the electrical resistance in the fluid contained in the nozzle between the electrode and the meniscus, and the capacitance of the gap between the meniscus and the flat substrate. Another time constant deals with the fluid flow during the growth of the meniscus, directly after switching on the pulse. This fluid flow is driven by hydrostatic pressure and opposed by a viscous drag in the nozzle. The final fluid flow during droplet formation is governed by the balance between the drag of the charge carriers inside the fluid, caused by the current associated with the charged droplets leaving the meniscus and the viscous drag. These different phenomena will be discussed theoretically and compared to experimental results.
{"title":"On-demand Electrohydrodynamic Jetting of an Ethylene Glycol and Water Mixture—System of Controlled Picoliter Fluid Deposition","authors":"J. F. Dijksman, U. Stachewicz","doi":"10.2352/j.imagingsci.technol.2021.65.4.040405","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2021.65.4.040405","url":null,"abstract":"Abstract On-demand electrohydrodynamic jetting also called electrohydrodynamic atomization (EHDA) is a method to jet small amounts of fluid out of a nozzle with a relatively large diameter by switching on and off an electrical field between the nozzle and the substrate. The\u0000 total amount of volume deposited is up to 5 pL. The set-up consists of a vertically placed glass pipette with a small nozzle directed downward and a flat substrate placed close to the end of the nozzle. Inside the pipette, an electrode is mounted close to the entrance of the nozzle. The electrode\u0000 is connected to a high voltage power amplifier. Upon switching on the electrical field, the apparent surface tension drops, the meniscus deforms into a cone and fluid starts to flow toward the nozzle deforming the meniscus. At a certain moment the cone reaches the Taylor cone dimensions and\u0000 from its tip a jet emerges that decomposes into a stream of charged fL droplets that fly toward the substrate. This process stops when the pulse is switched off. After switching off, the meniscus returns slowly to its equilibrium position. The process is controlled by different time constants,\u0000 such as the slew rate of the power amplifier and the RC time of the electrical circuit composed of the electrical resistance in the fluid contained in the nozzle between the electrode and the meniscus, and the capacitance of the gap between the meniscus and the flat substrate. Another time\u0000 constant deals with the fluid flow during the growth of the meniscus, directly after switching on the pulse. This fluid flow is driven by hydrostatic pressure and opposed by a viscous drag in the nozzle. The final fluid flow during droplet formation is governed by the balance between the drag\u0000 of the charge carriers inside the fluid, caused by the current associated with the charged droplets leaving the meniscus and the viscous drag. These different phenomena will be discussed theoretically and compared to experimental results.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49001531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.2352/j.imagingsci.technol.2021.65.4.040406
Motoki Miyoshi, Parinya Punpongsanon, D. Iwai, Kosuke Sato
Abstract FDM 3D printers allow massive creativity in personal products, but their potential has been limited due to inability to manipulating material properties. Previous work had demonstrated that the desired roughness could be presented simply by controlling the spatial density of tiny pins on a printed surface. This article offers a means of providing the desired softness perception of a printed surface and the desired roughness to expand the haptic dimension over which a user can exert control. Specifically, we control the softness by manipulating the infill structures of a printed surface. However, it is known that a skin contact area affects softness perception. The roughness, which is controlled by pins’ density, may also affect the perceived softness of a printed surface. Therefore, we investigate how the internal structures and the density of the pins affect softness perception. Through psychophysical experiments, we derive a computational model that estimates the perceived softness from the density of the pins and the infill density of a printed surface.
{"title":"SoftPrint: Investigating Haptic Softness Perception of 3D Printed Soft Object in FDM 3D Printers","authors":"Motoki Miyoshi, Parinya Punpongsanon, D. Iwai, Kosuke Sato","doi":"10.2352/j.imagingsci.technol.2021.65.4.040406","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2021.65.4.040406","url":null,"abstract":"Abstract FDM 3D printers allow massive creativity in personal products, but their potential has been limited due to inability to manipulating material properties. Previous work had demonstrated that the desired roughness could be presented simply by controlling the spatial\u0000 density of tiny pins on a printed surface. This article offers a means of providing the desired softness perception of a printed surface and the desired roughness to expand the haptic dimension over which a user can exert control. Specifically, we control the softness by manipulating the infill\u0000 structures of a printed surface. However, it is known that a skin contact area affects softness perception. The roughness, which is controlled by pins’ density, may also affect the perceived softness of a printed surface. Therefore, we investigate how the internal structures and the\u0000 density of the pins affect softness perception. Through psychophysical experiments, we derive a computational model that estimates the perceived softness from the density of the pins and the infill density of a printed surface.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48667488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.2352/j.imagingsci.technol.2021.65.4.040407
Ming Wang, Lisa Parrillo-Chapman, Lori Rothenberg, Yixin Liu, Jiajun Liu
Abstract This research explored the potential for ink-jet printing to replicate the coloration and finishing techniques of traditional denim fabric and standardized the reproduction and evaluation procedure. Although denim fabric is widely consumed and very popular, one drawback to denim is that the finishing and manufacturing processes are energy and water intensive and can cause environmental hazards as well as generation of pollution through water waste, particularly at the finishing stage. Textile ink-jet printing has the potential to replicate some of the coloration and finishing techniques of traditional denim fabric without negative environmental impacts. A two-phase research project was conducted. In Phase I (P1), an optimal standard production workflow for digital denim reproduction (including color and finishing effects) was established, and six different denim samples were reproduced based on the workflow. In Phase II, an expert visual assessment protocol was developed to evaluate the acceptance of the replicated digital denim. Twelve ink-jet printing, color science, and denim industry experts finished the assessment.
{"title":"Digital Textile Ink-Jet Printing Innovation: Development and Evaluation of Digital Denim Technology","authors":"Ming Wang, Lisa Parrillo-Chapman, Lori Rothenberg, Yixin Liu, Jiajun Liu","doi":"10.2352/j.imagingsci.technol.2021.65.4.040407","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2021.65.4.040407","url":null,"abstract":"Abstract This research explored the potential for ink-jet printing to replicate the coloration and finishing techniques of traditional denim fabric and standardized the reproduction and evaluation procedure. Although denim fabric is widely consumed and very popular, one drawback\u0000 to denim is that the finishing and manufacturing processes are energy and water intensive and can cause environmental hazards as well as generation of pollution through water waste, particularly at the finishing stage. Textile ink-jet printing has the potential to replicate some of the coloration\u0000 and finishing techniques of traditional denim fabric without negative environmental impacts. A two-phase research project was conducted. In Phase I (P1), an optimal standard production workflow for digital denim reproduction (including color and finishing effects) was established, and six\u0000 different denim samples were reproduced based on the workflow. In Phase II, an expert visual assessment protocol was developed to evaluate the acceptance of the replicated digital denim. Twelve ink-jet printing, color science, and denim industry experts finished the assessment.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41310563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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