Pub Date : 2019-12-13DOI: 10.21533/scjournal.v8i2.180
A. Sokol
Recommender systems are necessary in current time, since the information available online can be overloading to a user. These systems are used everywhere, starting from the online shops to the websites that are focused on recommending particular item, such as videos to watch or songs to listen to. Recommender system that predicts the likings of a user based on their previous behavior is very popular when it comes to picking up the movies to watch. This paper talks more about the movie recommender systems, and explains the way that different types of recommendations can be used in order to test datasets and provide good recommendations for variety of users. are more likely to find interesting by guiding them towards that product more. Not just that they helped in the shopping field, but also in guiding user towards the videos that could be of his or hers interest, as well as songs or movies [1]. Users are more likely to watch the movie that has been suggested by the recommender system, or see a vide YouTube that was placed below the “Recommended” label. Since of the overwhelming information and constant movie releases, people also try to use recommender systems in order to find the movie that could be similar to those of their likings, or the movies that presents cast and plots that would be of their interest. This paper talks more about movie recommender systems and their types. It is also focused on testing out simple recommender system for movies that gives the user different types of recomm the data available. o on
{"title":"Movie Recommender System","authors":"A. Sokol","doi":"10.21533/scjournal.v8i2.180","DOIUrl":"https://doi.org/10.21533/scjournal.v8i2.180","url":null,"abstract":"Recommender systems are necessary in current time, since the information available online can be overloading to a user. These systems are used everywhere, starting from the online shops to the websites that are focused on recommending particular item, such as videos to watch or songs to listen to. Recommender system that predicts the likings of a user based on their previous behavior is very popular when it comes to picking up the movies to watch. This paper talks more about the movie recommender systems, and explains the way that different types of recommendations can be used in order to test datasets and provide good recommendations for variety of users. are more likely to find interesting by guiding them towards that product more. Not just that they helped in the shopping field, but also in guiding user towards the videos that could be of his or hers interest, as well as songs or movies [1]. Users are more likely to watch the movie that has been suggested by the recommender system, or see a vide YouTube that was placed below the “Recommended” label. Since of the overwhelming information and constant movie releases, people also try to use recommender systems in order to find the movie that could be similar to those of their likings, or the movies that presents cast and plots that would be of their interest. This paper talks more about movie recommender systems and their types. It is also focused on testing out simple recommender system for movies that gives the user different types of recomm the data available. o on","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"9 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130506183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.167
M. Can, Osman Gursoy
For the taxonomic classification of microbes, 16S ribosomal RNA (rRNA) gene sequences are widely used in environmental microbiology as reliable markers. Although the massive sequencing of 16S rRNA gene amplicons encompassing the full length of genes is not easy, because of the limitations of the current sequencing techniques, in databases Greengenes, RDP, and SILVA millions of rRNA gene sequences are uploaded. In this research, first a new similarity measure LCSS, for full length genes is defined. Then it is found that sequences reported for the same bacteria species demonstrate around 53% average sequence similarity in Greengenes and SILVA databases, while average similarity among genes reported for different bacteria species is around 15% only. This is 63%, and 20% respectively at genus level for the three data bases Greengenes, RDP, and SILVA. Hence, species, and genus-specific sequences constitute useful targets for diagnostic assays and other scientific investigations. In the present research, the built in function LongestCommonSubsequence is used repeatedly in computer algebra package MATHEMATICA to create an in silico pipeline for taxonomic classification uploaded new full-length sequences. Conclusions: Our results suggest that LongestCommonSubsequence similarity can be used for taxonomic classification of unknown bacteria through their full 16S ribosomal RNA (rRNA) gene sequences.
{"title":"Taxonomic Classification of Bacteria Using Common Substrings","authors":"M. Can, Osman Gursoy","doi":"10.21533/SCJOURNAL.V8I1.167","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.167","url":null,"abstract":"For the taxonomic classification of microbes, 16S ribosomal RNA (rRNA) gene sequences are widely used in environmental microbiology as reliable markers. Although the massive sequencing of 16S rRNA gene amplicons encompassing the full length of genes is not easy, because of the limitations of the current sequencing techniques, in databases Greengenes, RDP, and SILVA millions of rRNA gene sequences are uploaded. In this research, first a new similarity measure LCSS, for full length genes is defined. Then it is found that sequences reported for the same bacteria species demonstrate around 53% average sequence similarity in Greengenes and SILVA databases, while average similarity among genes reported for different bacteria species is around 15% only. This is 63%, and 20% respectively at genus level for the three data bases Greengenes, RDP, and SILVA. Hence, species, and genus-specific sequences constitute useful targets for diagnostic assays and other scientific investigations. In the present research, the built in function LongestCommonSubsequence is used repeatedly in computer algebra package MATHEMATICA to create an in silico pipeline for taxonomic classification uploaded new full-length sequences. Conclusions: Our results suggest that LongestCommonSubsequence similarity can be used for taxonomic classification of unknown bacteria through their full 16S ribosomal RNA (rRNA) gene sequences.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127104325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.171
Osman Gursoy, M. Can
16S ribosomal RNA (rRNA) gene sequences are reliable markers for the taxonomic classification of microbes and widely used in environmental microbiology. Production of 16S rRNA gene amplicons in large amounts, encompassing the full length of genes is not yet feasible, because of the limitations of the current sequencing techniques. They are mostly in short reads of length less than 300 base pairs. Hence, the selection of the most efficient hypervariable regions for phylogenetic analysis and taxonomic classification is a current research area. It is found that nine hypervariable regions (V1–V9), resides in bacterial 16S ribosomal RNA (rRNA) genes. Family, genus, and species-specific sequences within a given hypervariable region constitute useful targets for diagnostic assays and other scientific investigations. In this study systematic studies that compare the relative advantage of hypervariable regions grouped as V1–V2–V3, V4–V5–V6, and V7–V8–V9 for specific diagnostic goals are done. In the present research, the built in function Longest–Common–Subsequence in computer algebra package MATHEMATICA is used to create an in silico pipeline to evaluate the taxonomic classification sensitivity of the hypervariable regions compared with the corresponding full-length sequences. Conclusions: Our results suggest that V4–V5–V6 region might be an optimal sub-region for the design of universal primers with superior phylogenetic resolution for bacterial phyla.
{"title":"Hypervariable Regions in 16S rRNA Genes for the Taxonomic Classification","authors":"Osman Gursoy, M. Can","doi":"10.21533/SCJOURNAL.V8I1.171","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.171","url":null,"abstract":"16S ribosomal RNA (rRNA) gene sequences are reliable markers for the taxonomic classification of microbes and widely used in environmental microbiology. Production of 16S rRNA gene amplicons in large amounts, encompassing the full length of genes is not yet feasible, because of the limitations of the current sequencing techniques. They are mostly in short reads of length less than 300 base pairs. Hence, the selection of the most efficient hypervariable regions for phylogenetic analysis and taxonomic classification is a current research area. It is found that nine hypervariable regions (V1–V9), resides in bacterial 16S ribosomal RNA (rRNA) genes. Family, genus, and species-specific sequences within a given hypervariable region constitute useful targets for diagnostic assays and other scientific investigations. In this study systematic studies that compare the relative advantage of hypervariable regions grouped as V1–V2–V3, V4–V5–V6, and V7–V8–V9 for specific diagnostic goals are done. In the present research, the built in function Longest–Common–Subsequence in computer algebra package MATHEMATICA is used to create an in silico pipeline to evaluate the taxonomic classification sensitivity of the hypervariable regions compared with the corresponding full-length sequences. Conclusions: Our results suggest that V4–V5–V6 region might be an optimal sub-region for the design of universal primers with superior phylogenetic resolution for bacterial phyla.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114901614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.170
Rialda Spahic, Dzana Basic, Emina Yaman
The idea of chatbots firstly appeared in the 1960s. But only after more than half a century passed the world became ready for their implementation into the real life, this being a result of the rapid progress in natural language processing, artificial intelligence, and the global presence of text messaging applications. Today, specialized chatbots exist in different domains, thus helping organizations handle large amount of inquiries. Idea of this project was to develop one friendly chatbot with whom you can talk about politics, movies, weather, sport, emotions and similar everyday things. Friendly chatbot named Zeka, is a web-based chatbot developed with the help of Chatterbot library. Chatbot relies on different natural processing and machine learning algorithms altered by its developers to increase its performance.
{"title":"Zeka - Friendy Chatterbot","authors":"Rialda Spahic, Dzana Basic, Emina Yaman","doi":"10.21533/SCJOURNAL.V8I1.170","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.170","url":null,"abstract":"The idea of chatbots firstly appeared in the 1960s. But only after more than half a century passed the world became ready for their implementation into the real life, this being a result of the rapid progress in natural language processing, artificial intelligence, and the global presence of text messaging applications. Today, specialized chatbots exist in different domains, thus helping organizations handle large amount of inquiries. Idea of this project was to develop one friendly chatbot with whom you can talk about politics, movies, weather, sport, emotions and similar everyday things. Friendly chatbot named Zeka, is a web-based chatbot developed with the help of Chatterbot library. Chatbot relies on different natural processing and machine learning algorithms altered by its developers to increase its performance.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121348034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.168
E. Terzi
In this thesis covers two different examples which we solved with Analytic Hierarchy Process (AHP).The Analytic Hierarchy Process was explained with details in this study. People encounter problems which are difficult to solve and understand. Decision making becomes more complex with apply common procedures without knowing any decision making application. AHP is the one of the application to use in decision analysis problem which is helping to change non-numerical judgments to convert in the system with numerical values for decision making process. It allows us to find out which alternative is the optimum as a result in the problem. In this study, 2 problems were solved with AHP. On the first example, it is considered for making decision to buy new phone. There are suggested 3 criteria and 4 alternatives.
{"title":"Analytic Hierarchy Process (AHP) to Solve Complex Decision Problems","authors":"E. Terzi","doi":"10.21533/SCJOURNAL.V8I1.168","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.168","url":null,"abstract":"In this thesis covers two different examples which we solved with Analytic Hierarchy Process (AHP).The Analytic Hierarchy Process was explained with details in this study. People encounter problems which are difficult to solve and understand. Decision making becomes more complex with apply common procedures without knowing any decision making application. AHP is the one of the application to use in decision analysis problem which is helping to change non-numerical judgments to convert in the system with numerical values for decision making process. It allows us to find out which alternative is the optimum as a result in the problem. In this study, 2 problems were solved with AHP. On the first example, it is considered for making decision to buy new phone. There are suggested 3 criteria and 4 alternatives.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134552853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.173
Amar Čosić, Altijana Hromic Jahjefendic
The 16s-rRNA consists of hypervariable regions (V1 – V9) that demonstrate considerable sequence diversity among different bacteria. Species-specific sequences within a given hypervariable region constitute useful targets for diagnostic assays and other scientific investigations. Usually the size of the gene region is 1500 bp, which is large enough to be analyzed using bioinformatic tools and applied for detection. The need to advance the knowledge of the 16s-rRNA gene segments in bacterial strains would allow better understanding and better diagnostic possibilities when dealing with them. This could also be the basis for investigation of pathogenic microorganisms.
{"title":"Investigation Of 16S rRNA Gene And Gene Segments For The Determination Of Probiotics","authors":"Amar Čosić, Altijana Hromic Jahjefendic","doi":"10.21533/SCJOURNAL.V8I1.173","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.173","url":null,"abstract":"The 16s-rRNA consists of hypervariable regions (V1 – V9) that demonstrate considerable sequence diversity among different bacteria. Species-specific sequences within a given hypervariable region constitute useful targets for diagnostic assays and other scientific investigations. Usually the size of the gene region is 1500 bp, which is large enough to be analyzed using bioinformatic tools and applied for detection. The need to advance the knowledge of the 16s-rRNA gene segments in bacterial strains would allow better understanding and better diagnostic possibilities when dealing with them. This could also be the basis for investigation of pathogenic microorganisms.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129225388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.175
Haris Ačkar, A. Almisreb, M. A. Saleh
Image Enhancement is one of the most important and complex techniques in image processing technology. The main aim of image enhancement is to improve the visual appearance on an image and to offer a better representation of the image for Computer Vision Algorithms. In this paper,we is covered a few application fields of image enhancement with various images like grayscale, color, infrared and even with videos. The main objective of this paper is to highlight the drawbacks of the state of the art image enhancement techniques.
{"title":"A Review on Image Enhancement Techniques","authors":"Haris Ačkar, A. Almisreb, M. A. Saleh","doi":"10.21533/SCJOURNAL.V8I1.175","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.175","url":null,"abstract":"Image Enhancement is one of the most important and complex techniques in image processing technology. The main aim of image enhancement is to improve the visual appearance on an image and to offer a better representation of the image for Computer Vision Algorithms. In this paper,we is covered a few application fields of image enhancement with various images like grayscale, color, infrared and even with videos. The main objective of this paper is to highlight the drawbacks of the state of the art image enhancement techniques.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132447473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.172
A. Almisreb, M. A. Saleh
Transfer learning introduces the ability to perform deep learning models over a small set of data. This paper investigates the utilization of three fine-tuned Convolutional Neural Networks (CNNs), namely, Alexnet, Googlenet, and Vgg16. Alexnet and Googlenet consider as the state-of-the-art models in deep learning, while Vgg16 preference due to its depth. Each model was fine-tuned, trained, and tested over a dataset contains Bosnian Banknotes (BAM). The dataset covers 11 classes where 10 images were collected through mobile phone camera for each class. Alexnet showed a better performance in terms of completing the training while Vgg16 showed better performance in terms of accuracy as it achieved 100% compared to 95.24% for Alexnet. Googlenet showed less efficient performance by achieving 88.65%.
{"title":"Transfer Learning Utilization for Banknote Recognition: a Comparative Study Based on Bosnian Currency","authors":"A. Almisreb, M. A. Saleh","doi":"10.21533/SCJOURNAL.V8I1.172","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.172","url":null,"abstract":"Transfer learning introduces the ability to perform deep learning models over a small set of data. This paper investigates the utilization of three fine-tuned Convolutional Neural Networks (CNNs), namely, Alexnet, Googlenet, and Vgg16. Alexnet and Googlenet consider as the state-of-the-art models in deep learning, while Vgg16 preference due to its depth. Each model was fine-tuned, trained, and tested over a dataset contains Bosnian Banknotes (BAM). The dataset covers 11 classes where 10 images were collected through mobile phone camera for each class. Alexnet showed a better performance in terms of completing the training while Vgg16 showed better performance in terms of accuracy as it achieved 100% compared to 95.24% for Alexnet. Googlenet showed less efficient performance by achieving 88.65%.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128060240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.169
Osman Gursoy, M. Can
{"title":"On the Accuracy of the 16S-rRNA Gene Conserved Regions","authors":"Osman Gursoy, M. Can","doi":"10.21533/SCJOURNAL.V8I1.169","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.169","url":null,"abstract":"","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134025229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-27DOI: 10.21533/SCJOURNAL.V8I1.174
Faris Fazlic, Seyed Ali Hashemi, Ahmed Aletic, A. Almisreb, S. M. Norzeli, N. M. Din
With the global use of wireless sensor network technology in different fields and for different purposes such as health care monitoring, earth sensing, air pollution monitoring, military operations monitoring or surveillance system monitoring, a problem arises. Problem that could negatively impact previously started activities and observations if not handled in a right way. Authors of this paper discuss various vulnerabilities and security threads in different applications of WSN in the real world, such as intrusion, node capture attack, black hole attack or selective forwarding attack. Potential countermeasures are proposed formatted as protocols or architectures for secure transfer of data between friendly nodes, compromises on security measures with the goal of achieving secure and reliable connection. This paper could be used as a general representation of WSN security issue with which WSN engineers are faced on a daily basis.
{"title":"A Survey On Security In Wireless Sensor Network","authors":"Faris Fazlic, Seyed Ali Hashemi, Ahmed Aletic, A. Almisreb, S. M. Norzeli, N. M. Din","doi":"10.21533/SCJOURNAL.V8I1.174","DOIUrl":"https://doi.org/10.21533/SCJOURNAL.V8I1.174","url":null,"abstract":"With the global use of wireless sensor network technology in different fields and for different purposes such as health care monitoring, earth sensing, air pollution monitoring, military operations monitoring or surveillance system monitoring, a problem arises. Problem that could negatively impact previously started activities and observations if not handled in a right way. Authors of this paper discuss various vulnerabilities and security threads in different applications of WSN in the real world, such as intrusion, node capture attack, black hole attack or selective forwarding attack. Potential countermeasures are proposed formatted as protocols or architectures for secure transfer of data between friendly nodes, compromises on security measures with the goal of achieving secure and reliable connection. This paper could be used as a general representation of WSN security issue with which WSN engineers are faced on a daily basis.","PeriodicalId":243185,"journal":{"name":"Southeast Europe Journal of Soft Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116657309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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