In recent years, an increasing number of studies on human-computer interaction is taking place, due to the pervasive speech interfaces implemented in systems such as cell phones, personal and home automation assistants. These studies include automatic speech recognition (ASR) and speech synthesis, and are considering a wider variety of conditions of the signals, such as noise and reverberation, and accents and age-related effects as well. For example, one of the key challenges is the development of ASR for children’s speech. Since the current systems have a dependency on language and accents, thus, to improve it, the investigations of speech recognition technologies suitable for children are needed. In this paper, we assess commercial ASR systems for the recognition of Costa Rican children’s speech, for users with ages ranging between three and fourteen years old. To establish a comparison and numeric validation of the ASR systems in recognizing children’s isolated words, we conducted a large subjective listening test that computes the differences and challenges that remains for the state-of-the art ASR systems. The results provide evident numeric differences between ASR systems and human perceptions, especially for younger children. Additionally, we provide suggestions for future research directions in the field.
{"title":"Assessing costa rican children speech recognition by humans and machines","authors":"Maribel Morales-Rodríguez, Marvin Coto-Jiménez","doi":"10.18845/tm.v35i8.6453","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6453","url":null,"abstract":"In recent years, an increasing number of studies on human-computer interaction is taking place, due to the pervasive speech interfaces implemented in systems such as cell phones, personal and home automation assistants. These studies include automatic speech recognition (ASR) and speech synthesis, and are considering a wider variety of conditions of the signals, such as noise and reverberation, and accents and age-related effects as well. For example, one of the key challenges is the development of ASR for children’s speech. Since the current systems have a dependency on language and accents, thus, to improve it, the investigations of speech recognition technologies suitable for children are needed. In this paper, we assess commercial ASR systems for the recognition of Costa Rican children’s speech, for users with ages ranging between three and fourteen years old. To establish a comparison and numeric validation of the ASR systems in recognizing children’s isolated words, we conducted a large subjective listening test that computes the differences and challenges that remains for the state-of-the art ASR systems. The results provide evident numeric differences between ASR systems and human perceptions, especially for younger children. Additionally, we provide suggestions for future research directions in the field.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84560844","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}
According to several studies, children’s speech is more dynamic and inconsistent compared to an adult’s speech. This aspect can be considered in the task of recognizing the age of the person who speaks and of great importance in many applications, such as humancomputer interaction, security on Internet and education assistants. Those applications have a dependency on language and accent, due to the different sounds and styles that characterize the speakers. This paper presents the initial results on the identification of Costa Rican children’s speech, in a database created for this purpose, consisting of words pronounced by adults and children of several ages. For this first study we chose the most common vowel of the language, and extract a set of common acoustic features to determine its applicability in distinguishing between adults and children of an age range. The outcome results shows promising results in the classification using a single vowel, that improves according to the number of vowels used to extract the acoustic features. This means that an automatic system could be able to improve its capacity to identify age as more speech information is received and transcribed, but cannot be very accurate in short interactions.
{"title":"A first study on age classification of costa rican speakers based on acoustic vowel analysis","authors":"Victor Yeom-Song, Marvin Coto-Jiménez","doi":"10.18845/tm.v35i8.6466","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6466","url":null,"abstract":"According to several studies, children’s speech is more dynamic and inconsistent compared to an adult’s speech. This aspect can be considered in the task of recognizing the age of the person who speaks and of great importance in many applications, such as humancomputer interaction, security on Internet and education assistants. Those applications have a dependency on language and accent, due to the different sounds and styles that characterize the speakers. This paper presents the initial results on the identification of Costa Rican children’s speech, in a database created for this purpose, consisting of words pronounced by adults and children of several ages. For this first study we chose the most common vowel of the language, and extract a set of common acoustic features to determine its applicability in distinguishing between adults and children of an age range. The outcome results shows promising results in the classification using a single vowel, that improves according to the number of vowels used to extract the acoustic features. This means that an automatic system could be able to improve its capacity to identify age as more speech information is received and transcribed, but cannot be very accurate in short interactions.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77040798","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}
Melvin Ramírez Bogantes, Jose Luis Vásquez Vásquez, Carlos M. Travieso González
Falta español
西班牙缺乏
{"title":"Presentación número especial","authors":"Melvin Ramírez Bogantes, Jose Luis Vásquez Vásquez, Carlos M. Travieso González","doi":"10.18845/tm.v35i8.6431","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6431","url":null,"abstract":"Falta español","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83251914","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}
Jose-Arturo Molina-Mora, Diana Chinchilla-Montero, Carolina Castro-Peña, F. García
A classical strategy to analyse the protein content of a biological sample is the two-dimensional gel electrophoresis (2D-GE). This technique separates proteins by both isoelectric point and molecular weight, and images are taken for subsequent analyses. However, analyses of 2D-GE images require standardized image analysis due to susceptibility of gels to get deformed, presence of overlapping spots and stripes, fuzzy and unstained spots, and others. This represent a difficulty for final users (researchers), which demand for free and user-friendly solutions. We have previously reported the standardization of a protocol to analyse 2D-GE images, and in the current study we applied it to two new bacterial isolates Pseudomonas aeruginosa C25 and C50. We first extracted periplasmic proteins after exposure to antibiotics, and we then run a 2D-GE analysis. Images were analysed using our standardized protocol, achieving the identification of protein spots using CellProfiler after pre-processing step. Comparison between strains was done using differential spot analysis, revealing a specific pattern in the protein expression between bacteria. These results will help to study the biological meaning of these strains using proteomic profiling under different conditions.
{"title":"Two-dimensional gel electrophoresis image analysis of two Pseudomonas aeruginosa clones","authors":"Jose-Arturo Molina-Mora, Diana Chinchilla-Montero, Carolina Castro-Peña, F. García","doi":"10.18845/tm.v35i8.6452","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6452","url":null,"abstract":"A classical strategy to analyse the protein content of a biological sample is the two-dimensional gel electrophoresis (2D-GE). This technique separates proteins by both isoelectric point and molecular weight, and images are taken for subsequent analyses. However, analyses of 2D-GE images require standardized image analysis due to susceptibility of gels to get deformed, presence of overlapping spots and stripes, fuzzy and unstained spots, and others. This represent a difficulty for final users (researchers), which demand for free and user-friendly solutions. We have previously reported the standardization of a protocol to analyse 2D-GE images, and in the current study we applied it to two new bacterial isolates Pseudomonas aeruginosa C25 and C50. We first extracted periplasmic proteins after exposure to antibiotics, and we then run a 2D-GE analysis. Images were analysed using our standardized protocol, achieving the identification of protein spots using CellProfiler after pre-processing step. Comparison between strains was done using differential spot analysis, revealing a specific pattern in the protein expression between bacteria. These results will help to study the biological meaning of these strains using proteomic profiling under different conditions.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86670250","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}
Denoising speech signals represent a challenging task due to the increasing number of applications and technologies currently implemented in communication and portable devices. In those applications, challenging environmental conditions such as background noise, reverberation, and other sound artifacts can affect the quality of the signals. As a result, it also impacts the systems for speech recognition, speaker identification, and sound source localization, among many others. For denoising the speech signals degraded with the many kinds and possibly different levels of noise, several algorithms have been proposed during the past decades, with recent proposals based on deep learning presented as state-of-the-art, in particular those based on Long Short-Term Memory Networks (LSTM and Bidirectional-LSMT). In this work, a comparative study on different transfer learning strategies for reducing training time and increase the effectiveness of this kind of network is presented. The reduction in training time is one of the most critical challenges due to the high computational cost of training LSTM and BLSTM. Those strategies arose from the different options to initialize the networks, using clean or noisy information of several types. Results show the convenience of transferring information from a single case of denoising network to the rest, with a significant reduction in training time and denoising capabilities of the BLSTM networks.
{"title":"Assessing the effectiveness of transfer learning strategies in BLSTM networks for speech fenoising","authors":"Marvin Coto-Jiménez, Astryd González-Salazar, Michelle Gutiérrez-Muñoz","doi":"10.18845/tm.v35i8.6448","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6448","url":null,"abstract":"Denoising speech signals represent a challenging task due to the increasing number of applications and technologies currently implemented in communication and portable devices. In those applications, challenging environmental conditions such as background noise, reverberation, and other sound artifacts can affect the quality of the signals. As a result, it also impacts the systems for speech recognition, speaker identification, and sound source localization, among many others. For denoising the speech signals degraded with the many kinds and possibly different levels of noise, several algorithms have been proposed during the past decades, with recent proposals based on deep learning presented as state-of-the-art, in particular those based on Long Short-Term Memory Networks (LSTM and Bidirectional-LSMT). In this work, a comparative study on different transfer learning strategies for reducing training time and increase the effectiveness of this kind of network is presented. The reduction in training time is one of the most critical challenges due to the high computational cost of training LSTM and BLSTM. Those strategies arose from the different options to initialize the networks, using clean or noisy information of several types. Results show the convenience of transferring information from a single case of denoising network to the rest, with a significant reduction in training time and denoising capabilities of the BLSTM networks.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82115125","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}
Cancer is one of the main dead causes worldwide. It is re- sponsible for an approximate of 1 out of 6 deaths globally and lung cancer is along breast cancer, the most common types of cancer in the population, which confirms the importance of studies associated with it. This work presents an approach toward lung cancer histological tissue images segmentation based on colour. The proposed method for the segmentation is K-means clustering, providing promising results that may become as an assistance for pathologists, as it can help them reduce the time consumed reviewing the slides and giving a more objective perspective in order to provide a diagnose and specific treatment.
{"title":"Automated adenocarcinoma lung cancer tissue images segmentation based on clustering","authors":"Bryan Cervantes-Ramirez, Francisco Siles","doi":"10.18845/tm.v35i8.6442","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6442","url":null,"abstract":"Cancer is one of the main dead causes worldwide. It is re- sponsible for an approximate of 1 out of 6 deaths globally and lung cancer is along breast cancer, the most common types of cancer in the population, which confirms the importance of studies associated with it. This work presents an approach toward lung cancer histological tissue images segmentation based on colour. The proposed method for the segmentation is K-means clustering, providing promising results that may become as an assistance for pathologists, as it can help them reduce the time consumed reviewing the slides and giving a more objective perspective in order to provide a diagnose and specific treatment.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77153769","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}
During the past decades, a vast amount of audio data has be- come available in most languages and regions of the world. The efficient organization and manipulation of this data are important for tasks such as data classification, searching for information, diarization among many others, but also can be relevant for building corpora for training models for automatic speech recognition or building speech synthesis systems. Several of those tasks require extensive testing and data for specific languages and accents, especially when the development of communication systems with machines is a goal. In this work, we explore the application of several classifiers for the task of discriminating speech and music in Costa Rican radio broadcast. This discrimination is a first task in the exploration of a large corpus, to determine whether or not the available information is useful for particular research areas. The main contribution of this exploratory work is the general procedure and selection of algorithms for the Costa Rican radio corpus, which can lead to the extensive use of this source of data in many own applications and systems.
{"title":"Comparison of four classifiers for speech-music discrimination: a first case study for costa rican radio broadcasting","authors":"Joseline Sánchez-Solís, Marvin Coto-Jiménez","doi":"10.18845/tm.v35i8.6463","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6463","url":null,"abstract":"During the past decades, a vast amount of audio data has be- come available in most languages and regions of the world. The efficient organization and manipulation of this data are important for tasks such as data classification, searching for information, diarization among many others, but also can be relevant for building corpora for training models for automatic speech recognition or building speech synthesis systems. Several of those tasks require extensive testing and data for specific languages and accents, especially when the development of communication systems with machines is a goal. In this work, we explore the application of several classifiers for the task of discriminating speech and music in Costa Rican radio broadcast. This discrimination is a first task in the exploration of a large corpus, to determine whether or not the available information is useful for particular research areas. The main contribution of this exploratory work is the general procedure and selection of algorithms for the Costa Rican radio corpus, which can lead to the extensive use of this source of data in many own applications and systems.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73280572","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}
Ogbolu Melvin-Omone, Bence Takács, Roland Dóczi, Tivadar Garamvólgyi, Lászlo Szücs, Péter Galambos, Tamás Haidegger, Miklós Vincze, Kristóf Papp, Daniel Drexler, György Eigner, Abdallah Benhamida, Ezter Koroknai, Peter Dombai, Miklos Kozlovszky
This paper describes a Mass Ventilation System (MVS) which serves as a medical ventilator system. It can be used to ventilate large number of COVID-19 patients in parallel (5 – 50+) with personalized respiratory parameters. The system has been designed to be medically suitable for both non-invasive and invasive patient ventilation. It protects healthcare workers with its centralized air filtering solution, it increases the effectiveness of the healthcare workers with its networked communication and it can be operated in a temporary emergency hospital setup. In this paper, we describe the basic concept and building blocks of the system.
{"title":"Personalized patient ventilation at large scale: Mass Ventilation System (MVS)","authors":"Ogbolu Melvin-Omone, Bence Takács, Roland Dóczi, Tivadar Garamvólgyi, Lászlo Szücs, Péter Galambos, Tamás Haidegger, Miklós Vincze, Kristóf Papp, Daniel Drexler, György Eigner, Abdallah Benhamida, Ezter Koroknai, Peter Dombai, Miklos Kozlovszky","doi":"10.18845/tm.v35i8.6450","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6450","url":null,"abstract":"This paper describes a Mass Ventilation System (MVS) which serves as a medical ventilator system. It can be used to ventilate large number of COVID-19 patients in parallel (5 – 50+) with personalized respiratory parameters. The system has been designed to be medically suitable for both non-invasive and invasive patient ventilation. It protects healthcare workers with its centralized air filtering solution, it increases the effectiveness of the healthcare workers with its networked communication and it can be operated in a temporary emergency hospital setup. In this paper, we describe the basic concept and building blocks of the system.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79777291","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}
Dayron Romero-Godoy, David Sánchez-Rodríguez, Itziar Alonso-González, Francisco Delgado-Rajó
Indoor positioning is a problem that has not yet been solved efficiently and accurately. In outdoors the most effective solution is the Global Position System (GPS), but it cannot be used indoors due to the weakening of the signal, so other solutions have been studied. These approaches could be applied to define a map for the guidance of blind people, tourism or navigation for autonomous robots. In this paper, the study, design, implementation and evaluation of a robust obstacle detection and mapping system is proposed. Thus, it can be used to alert of near objects presence and avoid possible collisions in an indoor navigation. The system is based on a Time-of-Flight (ToF) camera and a Single Board Computer (SBC) like Raspberry PI or NVIDIA Jetson Nano. In order to evaluate the system several real experiments were carried out. This kind of system can be integrated on a wheelchair and help the handicapped person to move indoors or take data from an indoor environment and recreate it in a 2D or 3D images.
{"title":"A low cost collision avoidance system based on a ToF camera for SLAM approaches","authors":"Dayron Romero-Godoy, David Sánchez-Rodríguez, Itziar Alonso-González, Francisco Delgado-Rajó","doi":"10.18845/tm.v35i8.6465","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6465","url":null,"abstract":"Indoor positioning is a problem that has not yet been solved efficiently and accurately. In outdoors the most effective solution is the Global Position System (GPS), but it cannot be used indoors due to the weakening of the signal, so other solutions have been studied. These approaches could be applied to define a map for the guidance of blind people, tourism or navigation for autonomous robots. In this paper, the study, design, implementation and evaluation of a robust obstacle detection and mapping system is proposed. Thus, it can be used to alert of near objects presence and avoid possible collisions in an indoor navigation. The system is based on a Time-of-Flight (ToF) camera and a Single Board Computer (SBC) like Raspberry PI or NVIDIA Jetson Nano. In order to evaluate the system several real experiments were carried out. This kind of system can be integrated on a wheelchair and help the handicapped person to move indoors or take data from an indoor environment and recreate it in a 2D or 3D images.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79128453","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}
Knowledge about artificial intelligence (AI) is becoming increasingly important for many careers, especially those based in science and engineering. Besides formal education, the impact of AI on society lead to consider educational projects for teaching the fundamental concepts of AI at wider audiences, including high school levels. This can help more general audiences to better understand how AI works, with the hope that also parents and educators can help students develop a healthy appreciation for implications and limitations, along with an appropriate relationship and deeper interest on it. In this paper, we present a pilot project for teaching an AI-based classification method that is empirically evaluated with real data of a real problem, which can be understood and tackled with basic mathematical tools and activities suitable for high school students. With this proposal, we aim to show how audio and speech applications can inform a wider audience about advances in AI, its characteristics, and its future impact on society. Results and lessons learned from this project can form the basis for further projects using different tools and data, according to students’ interests and initiative.
{"title":"Exploring the potential of an audio application for teaching AI-based classification methods to a wider audience","authors":"Gabriel Coto-Fernández, Marvin Coto-Jiménez","doi":"10.18845/tm.v35i8.6444","DOIUrl":"https://doi.org/10.18845/tm.v35i8.6444","url":null,"abstract":"Knowledge about artificial intelligence (AI) is becoming increasingly important for many careers, especially those based in science and engineering. Besides formal education, the impact of AI on society lead to consider educational projects for teaching the fundamental concepts of AI at wider audiences, including high school levels. This can help more general audiences to better understand how AI works, with the hope that also parents and educators can help students develop a healthy appreciation for implications and limitations, along with an appropriate relationship and deeper interest on it. In this paper, we present a pilot project for teaching an AI-based classification method that is empirically evaluated with real data of a real problem, which can be understood and tackled with basic mathematical tools and activities suitable for high school students. With this proposal, we aim to show how audio and speech applications can inform a wider audience about advances in AI, its characteristics, and its future impact on society. Results and lessons learned from this project can form the basis for further projects using different tools and data, according to students’ interests and initiative.","PeriodicalId":42957,"journal":{"name":"Tecnologia en Marcha","volume":null,"pages":null},"PeriodicalIF":0.1,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85687008","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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