{"title":"Identification of stimulus-response relations for cultured neuronal networks using features of multiple temporal resolution levels","authors":"Muqi Yin, Wei Zhang, You Wang, Guang‐hua Li","doi":"10.1145/3523286.3524505","DOIUrl":"https://doi.org/10.1145/3523286.3524505","url":null,"abstract":"In recent years cultured neuronal networks have been used with the aim of unraveling how biological information transmits between neurons. Investigating the evoked activities of cultured neuronal networks helps acquire a better understanding of neural decoding. However, it is still challenging to quantitatively describe and predict evoked patterns for them. This study focuses on evoked patterns of cultured neuronal networks and aims to identify stimulus-response relations with extracted feature sets including spike-based and rate-based features. The majority of neural information is encoded in evoked activities of the post-stimulus intervals. By partitioning post-stimulus intervals, features with multiple temporal resolution levels were constructed. This study investigates the impact of temporal resolution level on accuracy in recognizing stimulus-response relations.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133023251","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}
{"title":"Design and Practice of the National Virtual Simulation Experimental Teaching Platform of \"Training of Production of Traditional Chinese Medicine Shuanghuanglian Oral Liquid\"","authors":"Kai Zhu, Shumin Wang, Yuan Liu, Zhi-Qiang Pei","doi":"10.1145/3523286.3524513","DOIUrl":"https://doi.org/10.1145/3523286.3524513","url":null,"abstract":"Abstract: For the practical teaching needs of TCM pharmacy related majors, Changchun University of Chinese Medicine and Nanjing Yaoyu Intelligent Technology Co., LTD, cooperated to develop the virtual simulation software of \"Training of Production of Traditional Chinese Medicine Shuanghuanglian Oral Liquid\". This software takes the practical operation of traditional Chinese medicine oral liquid as the main line, and the 2010 edition of pharmaceutical production management code (GMP) as the knowledge support. The software applies C#, framework, Unity3D and other technologies, uses game elements and modes, including modern TCM oral liquid production technology, production equipment, Standard operating procedure (SOP), TCM oral liquid production process quality control and workshop management. This software attracts users to participate in the form of a serious game, making up for the malpractice that the teaching is separated from the actual production, and improving students' understanding of the actual production of traditional Chinese medicine oral liquid.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133153408","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}
{"title":"Research on the Relationship between Increasing Carbon Dioxide Concentration and Extreme Weather Events","authors":"Yaqi Song","doi":"10.1145/3523286.3524525","DOIUrl":"https://doi.org/10.1145/3523286.3524525","url":null,"abstract":"Abstract—Carbon dioxide is the main greenhouse gas emitted through human activities that impact human beings and the natural ecosystem. According to a study done in 2019, human activities were seen to accumulate approximately 80 percent of all United States greenhouse gas emissions. The earth's carbon cycle depicts carbon dioxide as a naturally present gas circulating in plants, soil, ocean, animals, and the atmosphere. Therefore, the purpose of the study is to assess how an increase in the concentration of CO2 is correlated to more extreme weather events. The research was geared to help combat climate change since the impacts of severe weather are always catastrophic. Also, the study would help in improving public health, avoiding the runaway cost of climate change, protecting vital ecosystems and species, and preserving water resources and clean water. The research topic is carbon dioxide's role in extreme weather events. Literature studies were used in collecting qualitative data. From the analysis, the study found out that an increase in carbon dioxide concentration leads to more extreme weather and climate events in the atmosphere. It discovered that human-related emissions since the industrial revolution are responsible for an increase in carbon dioxide.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116534454","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}
{"title":"Modeling of Evolutionary Progress of Nonstructure Protein 1 Family from Influenza A Virus","authors":"Shaomin Yan, Guang Wu","doi":"10.1145/3523286.3524589","DOIUrl":"https://doi.org/10.1145/3523286.3524589","url":null,"abstract":"The evolutionary progress is mathematically how an indicator changes over time such as the brain weight changes over time. Thus, this can present in x-y coordinates, on where we can use mathematical and statistical methods to build the time-dependent relationships. Of mathematical methods, the mass-balance styled differential equation is most useful because we can use it to predict an evolutionary indicator in the future. We are particularly interested in the evolution of proteins from influenza A virus not only because influenza A virus causes influenza in humans and animals but also the proteins from influenza A virus have the longest records among viruses. Of 10 proteins from influenza A virus, the nonstructural protein 1 (NS1) gets much less attention than others. However, this ignorance does not minimize its importance because more and more functions have been found in NS1.This requires converting a protein into a numeric scale because the y-axis is better to set in a quantitative scale rather than a qualitative scale. Of 540-plus methods to convert amino acids into digital numbers, we developed the amino-acid pair predictability to do the job. In this communication, 2729 NS1 proteins of influenza A viruses filtered from 7826 full-length NS1 proteins of influenza A virus to eliminate identical sequences were employed. (1) We converted them into numeric format using the amino-acid pair predictability. (2) We presented these proteins in the y-axis according to their sampling time over the x-axis. (3) We determined upward and downward half-life as initial estimates for the analytical solution of mass-balance styled differential equations. (4) We used the analytical solution to fit the evolutionary progress of NS1 protein family. (5) We tested the goodness-of-fit to verify the fittings. The results demonstrated the positive possibility of such studies, and paved the pathway to simulate and predict the evolutionary progress of proteins in the future.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121153940","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}
Ying-Dan Cao, Y. Fan, Linnan Liao, Lidan Xu, Rongjun Cui
{"title":"Comparative Study on the Functions of Typical Biomedical Metadata","authors":"Ying-Dan Cao, Y. Fan, Linnan Liao, Lidan Xu, Rongjun Cui","doi":"10.1145/3523286.3524545","DOIUrl":"https://doi.org/10.1145/3523286.3524545","url":null,"abstract":"In the process of comparative analysis of data functions in typical biomedical colleges, it is necessary to use metadata standards to complete the organization and processing of biomedical scientific data. At the same time, it is necessary to explore the specific functional requirements of biomedical metadata from the research status of data function in biomedical college. Based on the corresponding models, this paper scientifically compares the specific functions of typical biomedical metadata from different perspectives, such as structure dimension, content dimension, correlation dimension and usage dimension, and explores the construction strategy of typical biomedical metadata.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121952912","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}
{"title":"Research on IOT in the environment of intelligent support for the aged","authors":"Zhenzhen Tang, Han-bin Wu, Chunge Li","doi":"10.1145/3523286.3524509","DOIUrl":"https://doi.org/10.1145/3523286.3524509","url":null,"abstract":"Today’s society is an age of aging society, but also an age of technology. How to ensure the quality of life and physical health of the elderly has become an important question for families and society. This paper aims to study the application status of Internet of Things technology in the elderly population. CNKI keyword search into the Internet of Things and the elderly precise search, there are 646 results. After carefully reading and studying the research results of others, this paper selects three prominent research results for analysis.. Internet of Things technology can improve the life of the elderly, enabling the elderly group to obtain more psychological satisfaction and life pleasure, thus improving the quality of life.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121997909","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}
Fan Peng, T. Yao, Zhenhui Wang, Jeffrey Zheng, Guangyu Yue
{"title":"New Hash-based Sequence Alignment Algorithm","authors":"Fan Peng, T. Yao, Zhenhui Wang, Jeffrey Zheng, Guangyu Yue","doi":"10.1145/3523286.3524539","DOIUrl":"https://doi.org/10.1145/3523286.3524539","url":null,"abstract":"With the gradual deepening of human understanding of the disease and the continuous improvement of diagnosis and treatment, precision medicine, a new medical concept medical model, has been proposed. High-throughput and high-accuracy gene sequence reading and high-accuracy and rapid gene sequence alignment provide the basis for diagnosing and treating precision medicine. This paper presents a new method based on matrix and linked-list to store sequence information. The hash values of the two hash functions are used as the coordinate values of the sequence in the matrix, and they can be used to find the target sequence. The algorithm is compared with five classical comparison algorithms.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122075561","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}
{"title":"Multivariate Modeling Analysis Based on Partial Least Squares Regression and Principal Component Regression","authors":"Yulei Chen, Xinwei Zhang, Qi Zou, Hepeng Wang, Shisheng Huang, Liang Lu","doi":"10.1145/3523286.3524584","DOIUrl":"https://doi.org/10.1145/3523286.3524584","url":null,"abstract":"In view of the high dimensionality of data in many fields and the serious multiple correlation between variables, this paper proposes an interpretable partial least square regression (PLSR) modeling method. Compared with principal component regression (PCR), when there are a large number of predictors, both PLSR and PCR model the response variables, and the predictors are highly correlated or even collinear. Both of these methods construct new predictors (called components) as linear combinations of the original predictors, but they construct these components in different ways. We use a series of cross-validation experiments to determine the number of components. This paper explores the effectiveness of the above-mentioned two methods. According to the mean square prediction error curve, when the number of components in PLSR is 3 and PCR is 4, better prediction accuracy is obtained.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132438120","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}
{"title":"URAMDS: Utterances Relation Aware Model for Dialogue Summarization: A Combined Model for Dialogue Summarization","authors":"Huichao Li","doi":"10.1145/3523286.3524577","DOIUrl":"https://doi.org/10.1145/3523286.3524577","url":null,"abstract":"Dialogue summarization, which aims to make summarization on the given dialogue automatically, is a challenging task in natural language processing. Compared to text summarization, it needs to consider the interaction between speakers and the colloquialization of expression to generate better summarization. Many existing methods treat dialogue as a plain sequence of text and simply ignore the structural information, which could be important for summarization generation of the dialogue. In this paper, to alleviate the above challenges, we propose a deep-learning-based method that combines a serialized model and a graph model. More specifically, we utilize a Sequence to Sequence (Seq2Seq) as the backbone to cope with the informal text and a Graph Neural Network (GNN) to take advantage of the structural information. The two models are combined by sharing the key information with each other. Besides, special attention is drawn to the specific speaker in our proposed method. Extensive experiments have shown the effectiveness of our proposed method.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129477523","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}