With the improvement of modern people’s living standards and the improvement of beverage production technology, lactic acid bacteria fermented drinks are popular among consumers with their special and functional properties. In this paper, we will clarify the fermentation function of lactic acid bacteria in the process of beverage processing and production, and understand its effect on improving the flavor and quality of beverage, as well as its nutritional and health value.It also pay attention to the precautions and possible hazards, and elaborate the significance and prospects in the development of contemporary beverages.
{"title":"Research Progress of Lactic Acid Bacteria in Fermented Beverage","authors":"Chenxiao Wu","doi":"10.61173/tbdmcj95","DOIUrl":"https://doi.org/10.61173/tbdmcj95","url":null,"abstract":"With the improvement of modern people’s living standards and the improvement of beverage production technology, lactic acid bacteria fermented drinks are popular among consumers with their special and functional properties. In this paper, we will clarify the fermentation function of lactic acid bacteria in the process of beverage processing and production, and understand its effect on improving the flavor and quality of beverage, as well as its nutritional and health value.It also pay attention to the precautions and possible hazards, and elaborate the significance and prospects in the development of contemporary beverages.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"71 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140452248","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}
With the rapid development of the Internet, an increasing number of devices are interconnected through the Internet, making the protection of user privacy during the information transmission process increasingly prominent. This paper categorizes user privacy issues into computer and mobile devices and analyzes their specific threats. Towards the end of the article, we propose methods for protecting user privacy from three perspectives.
{"title":"Research on User Privacy Issues in VR/AR Class Mobile Apps","authors":"Zihao Xiang","doi":"10.61173/k5kwft41","DOIUrl":"https://doi.org/10.61173/k5kwft41","url":null,"abstract":"With the rapid development of the Internet, an increasing number of devices are interconnected through the Internet, making the protection of user privacy during the information transmission process increasingly prominent. This paper categorizes user privacy issues into computer and mobile devices and analyzes their specific threats. Towards the end of the article, we propose methods for protecting user privacy from three perspectives.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"5 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958855","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}
The field of natural language processing, or NLP, uses its understanding of human language to find practical solutions to issues. It mainly includes two parts: the core task and the application. The core task represents the common problem that needs to be solved in various natural language application directions. It includes language models, morphology, grammar analysis, semantic analysis, etc. At the same time, the application section focuses on specific natural language processing tasks such as machine translation, information retrieval, question-answering systems, dialogue systems, etc. Natural language processing has made a significant contribution to the development of human society and the economy and provides strong support for all aspects of research work. Opinion mining, or sentiment analysis, is a subfield of natural language processing that develops systems for identifying and extracting ideas from text. Sentiment analysis is a hot topic since it has many practical applications. Many opinion-expressing texts are available on review sites, forums, blogs, and social media as the amount of publicly available information on the Internet grows. This unstructured information can then be automatically transformed into structured data about products, services, brands, politics, or other topics on which people can express their opinions using sentiment analysis systems. This information can be used for marketing analytics, public relations, product reviews, network sponsor ratings, product feedback, and customer service. With the rapid growth of labeled sample data sets and the notable enhancement in graphics processor (GPU) performance, convolutional neural network research has advanced rapidly and achieved remarkable leads to various computer vision tasks. By reviewing the application of CNN, we see that convolutional operations are naturally suitable for some text processing and, thus, naturally suitable for the background of sentiment analysis.
{"title":"An Overview of the Application of Convolutional Neural Networks inSentiment Analysis","authors":"Hao Wang","doi":"10.61173/t4sg2v25","DOIUrl":"https://doi.org/10.61173/t4sg2v25","url":null,"abstract":"The field of natural language processing, or NLP, uses its understanding of human language to find practical solutions to issues. It mainly includes two parts: the core task and the application. The core task represents the common problem that needs to be solved in various natural language application directions. It includes language models, morphology, grammar analysis, semantic analysis, etc. At the same time, the application section focuses on specific natural language processing tasks such as machine translation, information retrieval, question-answering systems, dialogue systems, etc. Natural language processing has made a significant contribution to the development of human society and the economy and provides strong support for all aspects of research work. Opinion mining, or sentiment analysis, is a subfield of natural language processing that develops systems for identifying and extracting ideas from text. Sentiment analysis is a hot topic since it has many practical applications. Many opinion-expressing texts are available on review sites, forums, blogs, and social media as the amount of publicly available information on the Internet grows. This unstructured information can then be automatically transformed into structured data about products, services, brands, politics, or other topics on which people can express their opinions using sentiment analysis systems. This information can be used for marketing analytics, public relations, product reviews, network sponsor ratings, product feedback, and customer service. With the rapid growth of labeled sample data sets and the notable enhancement in graphics processor (GPU) performance, convolutional neural network research has advanced rapidly and achieved remarkable leads to various computer vision tasks. By reviewing the application of CNN, we see that convolutional operations are naturally suitable for some text processing and, thus, naturally suitable for the background of sentiment analysis.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"6 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959127","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}
This article aims to study and explore the different types of batteries used in new energy electric vehicles, and classify them. As environmental preservation and sustainable development gain greater prominence, the adoption of new energy electric vehicles as a viable alternative to conventional fuel-based vehicles has surged. Concurrently, there have been remarkable advancements in battery technologies supporting these electric vehicles. Understanding the classification and characteristics of electric vehicle batteries is of great significance for promoting the development of the electric vehicle industry. This article will provide a detailed introduction to several major battery technologies, including lithium-ion batteries, sodium ion batteries, and solid-state-state batteries, and analyze their advantages and disadvantages; Application fields and future development trends.
{"title":"Types of Batteries for New Energy Electric Vehicles","authors":"Qizheng Chen","doi":"10.61173/1e54eb37","DOIUrl":"https://doi.org/10.61173/1e54eb37","url":null,"abstract":"This article aims to study and explore the different types of batteries used in new energy electric vehicles, and classify them. As environmental preservation and sustainable development gain greater prominence, the adoption of new energy electric vehicles as a viable alternative to conventional fuel-based vehicles has surged. Concurrently, there have been remarkable advancements in battery technologies supporting these electric vehicles. Understanding the classification and characteristics of electric vehicle batteries is of great significance for promoting the development of the electric vehicle industry. This article will provide a detailed introduction to several major battery technologies, including lithium-ion batteries, sodium ion batteries, and solid-state-state batteries, and analyze their advantages and disadvantages; Application fields and future development trends.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140451900","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}
Wireless charging technology has emerged as a promising solution for improving the convenience and efficiency of electric vehicle (EV) charging. This literature review examines the current state of the art in sustainable and safe wireless charging technology for electric vehicles. It provides insight into technological advances, safety considerations, and challenges associated with implementing wireless charging technology, safety considerations, and challenges associated with implementing wireless charging systems. Through a comprehensive examination of existing research and innovations, this review aims to provide insights into the future of wireless charging for electric vehicles.
{"title":"Continuously Safe Wireless Charging for Electric Vehicles","authors":"Yijun Ye","doi":"10.61173/xt6kfd33","DOIUrl":"https://doi.org/10.61173/xt6kfd33","url":null,"abstract":"Wireless charging technology has emerged as a promising solution for improving the convenience and efficiency of electric vehicle (EV) charging. This literature review examines the current state of the art in sustainable and safe wireless charging technology for electric vehicles. It provides insight into technological advances, safety considerations, and challenges associated with implementing wireless charging technology, safety considerations, and challenges associated with implementing wireless charging systems. Through a comprehensive examination of existing research and innovations, this review aims to provide insights into the future of wireless charging for electric vehicles.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"23 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140450141","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}
As data scales increase, traditional centralized graph algorithms struggle to meet modern computational demands. Distributed graph algorithms, which parallelize data processing across multiple computing nodes, have significantly improved the efficiency of handling large-scale graph data. This report explores the principles, application scenarios, key technologies, and challenges of distributed graph algorithms, aiming to provide a comprehensive perspective from local data to global solutions. With the rapid development of computer networks and big data technologies, solving large-scale graph data problems has become a hot research topic. Distributed graph algorithms can solve problems without global information and offer new solutions for processing massive graph structures. This report introduces the basic concepts, key technologies, and challenges of distributed graph algorithms and discusses methods for achieving global solutions starting from local data through case analyses.
{"title":"Distributed Graph Algorithms: From Local Data to Global Solutions","authors":"Jiaheng Zhang","doi":"10.61173/87grxw45","DOIUrl":"https://doi.org/10.61173/87grxw45","url":null,"abstract":"As data scales increase, traditional centralized graph algorithms struggle to meet modern computational demands. Distributed graph algorithms, which parallelize data processing across multiple computing nodes, have significantly improved the efficiency of handling large-scale graph data. This report explores the principles, application scenarios, key technologies, and challenges of distributed graph algorithms, aiming to provide a comprehensive perspective from local data to global solutions. With the rapid development of computer networks and big data technologies, solving large-scale graph data problems has become a hot research topic. Distributed graph algorithms can solve problems without global information and offer new solutions for processing massive graph structures. This report introduces the basic concepts, key technologies, and challenges of distributed graph algorithms and discusses methods for achieving global solutions starting from local data through case analyses.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"3 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958921","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}
The strategic board game Gomoku has become a compelling domain for artificial intelligence (AI) research, particularly in developing and applying machine learning techniques. This paper comprehensively analyzes advanced machine learning strategies in Gomoku, focusing on logistic regression for board evaluation, neural networks for pattern recognition, and reinforcement learning for strategic gameplay. We discuss integrating these techniques in creating a sophisticated AI capable of high-level play and adaptability. Through this exploration, we highlight the potential of AI in strategic decision-making and its broader applications beyond board games.
{"title":"Advanced Machine Learning Techniques in Gomoku: Strategy,Implementation, and Analysis","authors":"Jiajun Han","doi":"10.61173/4sda3g67","DOIUrl":"https://doi.org/10.61173/4sda3g67","url":null,"abstract":"The strategic board game Gomoku has become a compelling domain for artificial intelligence (AI) research, particularly in developing and applying machine learning techniques. This paper comprehensively analyzes advanced machine learning strategies in Gomoku, focusing on logistic regression for board evaluation, neural networks for pattern recognition, and reinforcement learning for strategic gameplay. We discuss integrating these techniques in creating a sophisticated AI capable of high-level play and adaptability. Through this exploration, we highlight the potential of AI in strategic decision-making and its broader applications beyond board games.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"27 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140449684","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}
With urbanization and population growth, the volume of waste generated is also increasing. Traditional waste management methods may become insufficiently efficient, necessitating more intelligent and sustainable solutions to meet this challenge. In traditional waste management systems, garbage trucks often collect waste according to a fixed schedule without considering the actual fill level of the garbage bins. This can lead to resource wastage and unnecessary carbon emissions. The research background of smart garbage bins is also closely related to environmental protection. By managing waste more effectively, reducing pollution to land and water sources is possible, contributing to achieving sustainable development goals. This study investigates the application of smart waste bin technology in urbanization, focusing on its potential in waste classification and environmental protection. The research encompasses three main stages: system design, prototype construction, and functional testing. In the system design phase, key components such as LED displays, ultrasonic sensors, and servo motors were selected based on functional requirements, and intelligent control was implemented using Arduino boards and the U8g2lib library. During the prototype construction phase, 3D printing and precise assembly were employed to ensure the effective layout of electronic components. The testing phase involved evaluating the performance of humidity sensors, ultrasonic sensors, and voice modules. The test indicates that the smart waste bins perform well in terms of sorting accuracy and ease of operation, but improvements are needed in real-time monitoring and user interaction. Overall, this study provides significant insights into the technological development of smart waste bins and their application in urban environments.
随着城市化和人口增长，产生的垃圾量也在不断增加。传统的垃圾管理方法可能会变得不够高效，因此需要更加智能和可持续的解决方案来应对这一挑战。在传统的垃圾管理系统中，垃圾车通常按照固定的时间表收集垃圾，而不考虑垃圾箱的实际装载量。这会导致资源浪费和不必要的碳排放。智能垃圾箱的研究背景也与环境保护密切相关。通过更有效地管理垃圾，可以减少对土地和水源的污染，有助于实现可持续发展目标。本研究探讨了智能垃圾桶技术在城市化进程中的应用，重点关注其在垃圾分类和环境保护方面的潜力。研究包括三个主要阶段：系统设计、原型构建和功能测试。在系统设计阶段，根据功能需求选择了 LED 显示屏、超声波传感器和伺服电机等关键部件，并使用 Arduino 板和 U8g2lib 库实现了智能控制。在原型构建阶段，采用了三维打印和精确装配，以确保电子元件的有效布局。测试阶段包括评估湿度传感器、超声波传感器和语音模块的性能。测试表明，智能垃圾桶在分类准确性和操作简便性方面表现良好，但在实时监控和用户互动方面仍需改进。总之，这项研究为智能垃圾桶的技术发展及其在城市环境中的应用提供了重要启示。
{"title":"Enhancing Urban Waste Management: Development and Application of Smart Garbage Bin Technologies","authors":"Ximing Fei, Piaopiao He, Haoran Ma, Yiming Qiu","doi":"10.61173/jprvvr82","DOIUrl":"https://doi.org/10.61173/jprvvr82","url":null,"abstract":"With urbanization and population growth, the volume of waste generated is also increasing. Traditional waste management methods may become insufficiently efficient, necessitating more intelligent and sustainable solutions to meet this challenge. In traditional waste management systems, garbage trucks often collect waste according to a fixed schedule without considering the actual fill level of the garbage bins. This can lead to resource wastage and unnecessary carbon emissions. The research background of smart garbage bins is also closely related to environmental protection. By managing waste more effectively, reducing pollution to land and water sources is possible, contributing to achieving sustainable development goals. This study investigates the application of smart waste bin technology in urbanization, focusing on its potential in waste classification and environmental protection. The research encompasses three main stages: system design, prototype construction, and functional testing. In the system design phase, key components such as LED displays, ultrasonic sensors, and servo motors were selected based on functional requirements, and intelligent control was implemented using Arduino boards and the U8g2lib library. During the prototype construction phase, 3D printing and precise assembly were employed to ensure the effective layout of electronic components. The testing phase involved evaluating the performance of humidity sensors, ultrasonic sensors, and voice modules. The test indicates that the smart waste bins perform well in terms of sorting accuracy and ease of operation, but improvements are needed in real-time monitoring and user interaction. Overall, this study provides significant insights into the technological development of smart waste bins and their application in urban environments.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"30 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140450191","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}
This paper presents a model that integrates a BERT encoder with a Capsule network, eliminating the traditional fully connected layer designed for downstream classification tasks in BERT in favor of a capsule layer. This capsule layer consists of three main modules: the representation module, the probability module, and the reconstruction module. It transforms the final hidden layer output of BERT into the final activation capsule probabilities to classify the text. By applying the model to sentiment analysis and text classification tasks, and comparing the test results with various BERT variants, the performance across all metrics was found to be superior. Observing the model’s handling of multiple entities and complex relationships, sentences with high ambiguity were extracted to observe the probability distribution of all capsules and compared with RNN-Capsule. It was found that the activation capsule probabilities for BERT-Capsule were significantly higher than the rest, and more pronounced than RNN-Capsule, indicating the model’s exceptional ability to process ambiguous information.
{"title":"Text classification by BERT-Capsules","authors":"Minghui Guo","doi":"10.61173/wcg0nf17","DOIUrl":"https://doi.org/10.61173/wcg0nf17","url":null,"abstract":"This paper presents a model that integrates a BERT encoder with a Capsule network, eliminating the traditional fully connected layer designed for downstream classification tasks in BERT in favor of a capsule layer. This capsule layer consists of three main modules: the representation module, the probability module, and the reconstruction module. It transforms the final hidden layer output of BERT into the final activation capsule probabilities to classify the text. By applying the model to sentiment analysis and text classification tasks, and comparing the test results with various BERT variants, the performance across all metrics was found to be superior. Observing the model’s handling of multiple entities and complex relationships, sentences with high ambiguity were extracted to observe the probability distribution of all capsules and compared with RNN-Capsule. It was found that the activation capsule probabilities for BERT-Capsule were significantly higher than the rest, and more pronounced than RNN-Capsule, indicating the model’s exceptional ability to process ambiguous information.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"6 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958840","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}
Sentiment analysis has a wide range of applications in the fields of opinion analysis, sentiment dialog, and product reviews. However, the sentiment information expressed in texts under different topics varies greatly; for example, a model that performs well on a movie review set has poor model classification on a social platform review set due to inconsistent recognition of antiphonal phrases, different expression of emoji sentiment, and missing contextual information. In this paper, the authors focus on tens of thousands of latest reviews of Chinese takeout platforms Meituan and Elema, and use the LSTM model in deep learning to double classify the data (positive and negative). This paper analyzes the performance of LSTM models in the field of sentiment analysis of takeout reviews and concludes that domain-specific text sentiment analysis requires specific analysis.
{"title":"Sentiment Analysis by Double Classification of Takeaway Platform Reviews Based on Deep Learning LSTM Models","authors":"Yunzhi Liao","doi":"10.61173/vcrwtn65","DOIUrl":"https://doi.org/10.61173/vcrwtn65","url":null,"abstract":"Sentiment analysis has a wide range of applications in the fields of opinion analysis, sentiment dialog, and product reviews. However, the sentiment information expressed in texts under different topics varies greatly; for example, a model that performs well on a movie review set has poor model classification on a social platform review set due to inconsistent recognition of antiphonal phrases, different expression of emoji sentiment, and missing contextual information. In this paper, the authors focus on tens of thousands of latest reviews of Chinese takeout platforms Meituan and Elema, and use the LSTM model in deep learning to double classify the data (positive and negative). This paper analyzes the performance of LSTM models in the field of sentiment analysis of takeout reviews and concludes that domain-specific text sentiment analysis requires specific analysis.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959270","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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