Review
Materials Science, Multidisciplinary
Zhi Hong, Logan Ward, Kyle Chard, Ben Blaiszik, Ian Foster
Summary: Scientific articles have long been the primary means of disseminating scientific discoveries, but extracting information from these papers has been a tedious and time-consuming task. Significant progress has been made in automated information extraction techniques by the computer science community, yet applying these techniques to scientific literature still faces technical and logistical challenges.
Article
Computer Science, Information Systems
Min Zhang, Brandon Fan, Ning Zhang, Wenjun Wang, Weiguo Fan
Summary: Online customer reviews play a crucial role in product innovation, but current research lacks focus on extracting innovation ideas from reviews. This study introduces a deep learning-based approach that effectively identifies sentences containing innovation ideas from online reviews.
INFORMATION PROCESSING & MANAGEMENT
(2021)
Article
Biochemical Research Methods
Lucy Lu Wang, Kyle Lo
Summary: This review discusses the resources and systems for text mining applications over the COVID-19 literature, compiling a list of 39 systems that provide search, discovery, visualization, and summarization functions. While many systems focus on search and discovery, some provide unique features such as summarizing findings over multiple documents or linking between scientific articles and clinical trials.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Public, Environmental & Occupational Health
Sana. S. S. BuHamra, Abdullah. N. N. Almutairi, Abdullah. K. K. Buhamrah, Sabah. H. H. Almadani, Yusuf. A. A. Alibrahim
Summary: This study utilizes Natural Language Processing (NLP) to construct an automated system for extracting causes of death and comorbidities in COVID-19 patients from electronic health records (EHRs). Findings show that septic shock or sepsis-related multiorgan failure is the leading cause of mortality, and acute respiratory distress syndrome (ARDS) is a common intermediate cause. Arrhythmia (AF) is determined to be the strongest predictor of intermediate cause of death.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Ecology
Ioannis Fytilakos
Summary: Text mining in fisheries scientific literature remains underexplored, and this study used quantitative text analysis to identify subtopic trends and knowledge gaps. Cluster analysis revealed four major thematic groups, and word categorization highlighted the continuous growth in literature engagement with ecological, economic, and social dimensions. Correspondence analysis showed relationships between two decades: 2001-2010 and 2011-present.
ECOLOGICAL INFORMATICS
(2021)
Article
Biology
Luke T. Slater, William Bradlow, Dino FA. Motti, Robert Hoehndorf, Simon Ball, Georgios V. Gkoutos
Summary: The study presents a heuristic algorithm for negation detection based on dependency graphs, showing strong performance in clinical text mining without the need for complex rule development and adaptation. Comparing with other rule-based algorithms, the algorithm may overlook advanced cases in certain situations, but it remains a fast, powerful, and stable alternative method.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Information Systems
Muhammad Aman, Said Jadid Abdulkadir, Izzatdin Abdul Aziz, Hitham Alhussian, Israr Ullah
Summary: This paper proposes a semantic-based unsupervised approach (KP-Rank) for keyphrase extraction, utilizing Latent Semantic Analysis (LSA) and clustering techniques, and introducing a novel frequency-based algorithm considering locality-based sentence, paragraph, and section frequencies. Experimental results demonstrate that KP-Rank achieved significant improvements on benchmark datasets from different domains.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Waseemullah, Zainab Fatima, Shehnila Zardari, Muhammad Fahim, Maria Andleeb Siddiqui, Ag. Asri Ag. Ibrahim, Kashif Nisar, Laviza Falak Naz
Summary: Text summarization is a technique for shortening long texts or documents. Manual summarization can be costly and time-consuming, while an extractive summarization model balances compression and retention ratios by preserving meaningful sentences and filtering out redundant information.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Binh T. Nguyen, Tung Tran Nguyen Doan, Son Thanh Huynh, Khanh Quoc Tran, An Trong Nguyen, An Tran-Hoai Le, Anh Minh Tran, Nhi Ho, Trung T. Nguyen, Dang T. Huynh
Summary: This paper presents an end-to-end framework for automatically collecting and processing real estate data in Vietnamese, which includes extracting useful information and storing computed data. The experiment results show that using PhoBERT (large) achieves the best performance.
Article
Plant Sciences
Gurnoor Singh, Evangelia A. Papoutsoglou, Frederique Keijts-Lalleman, Bilyana Vencheva, Mark Rice, Richard G. F. Visser, Christian W. B. Bachem, Richard Finkers
Summary: This study developed a pipeline using natural language processing on biological literature to generate knowledge networks, focusing on the flesh color trait of potato. The time-based analysis of these networks revealed connections between the trait and a candidate gene, demonstrating the potential of network-assisted hypothesis generation in scientific research.
Review
Computer Science, Artificial Intelligence
David M. Goldberg, Alan S. Abrahams
Summary: In recent years, online reviews have become an important way for consumers to express their opinions and feedback. However, the unstructured and voluminous nature of textual data makes it challenging for companies to effectively utilize this feedback. This study proposes a method for prioritizing online reviews by using text mining tools, focusing on identifying the most useful reviews pertaining to innovation opportunities for firms. The results demonstrate the effectiveness of the proposed technique in improving upon existing methods, and senior managers at a large manufacturing firm also validate the usefulness of the selected attribute types in online reviews.
DECISION SUPPORT SYSTEMS
(2022)
Review
Computer Science, Artificial Intelligence
Sergio Moro, Paulo Rita
Summary: This paper presents a comprehensive analysis of scientific literature using data and text mining techniques to uncover knowledge from online reviews. The majority of previous studies focused on qualitative textual data analysis, with fewer examining quantitative scores and reviewer profiles. The fields of information management and technology, e-commerce, and tourism were found to be prominent application domains. Future research should explore other potentially valuable domains, such as arts and education, as well as interdisciplinary approaches in the social sciences.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
(2022)
Article
Computer Science, Artificial Intelligence
Huchang Liao, Jiaxin Qi, Jiawei Zhang, Chonghui Zhang, Fan Liu, Weiping Ding
Summary: In this paper, a hospital selection approach based on a fuzzy multi-criterion decision-making method is proposed. This approach considers sentiment evaluation values of unstructured data from online reviews and structured data of public indexes simultaneously. The methodology involves collecting and processing online reviews, classifying topics and sentiments, quantifying sentiment analysis results using fuzzy numbers, and obtaining final preference scores of hospitals based on patients' preferences. A case study and robustness analysis are conducted to validate the effectiveness of the method.
INFORMATION FUSION
(2024)
Article
Business
Mihaly Retek
Summary: This article introduces an online scenario building platform developed by the author, which allows a high number of individual participants to create scenarios using various online methods. It provides a detailed presentation of the Two-axes method scenario and has been tested by individuals of various competencies. The platform also comes with a text mining package for logical and textual analysis of resulting scenarios.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2021)
Article
Computer Science, Information Systems
Belgacem Brahimi, Mohamed Touahria, Abdelkamel Tari
Summary: This paper proposes methods to extract valuable opinions from online movie reviews using n-gram and skip-n-gram models, subjective words, and feature reduction techniques to enhance sentiment analysis in Arabic. Experimental results demonstrate the effectiveness of these methods in improving sentiment classification results.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Chemistry, Physical
Anping Deng, Jiagang Wu
Summary: Rare earth ion doping has a significant effect on the phase structure, microstructure, strain, and electrostrictive properties of lead-free BNT-based ceramics. Moderate La3+ ion doping can drive the ceramics to nonergodic or ergodic relaxor states, resulting in enhanced strain response and high converse piezoelectric coefficient.
JOURNAL OF MATERIOMICS
(2022)
Article
Chemistry, Multidisciplinary
Ting Zheng, Yungang Yu, Haobin Lei, Fei Li, Shujun Zhang, Jianguo Zhu, Jiagang Wu
Summary: A new concept of structural gradient is proposed to address the challenge of the inferior temperature stability of lead-free potassium sodium niobate (KNN)-based ceramics. By designing compositionally graded multilayer composites with multiple successive phase transitions, the structural gradient ceramics exhibit superior temperature reliability. The excellent temperature stability is attributed to the synergistic contribution of continuous phase transition, strain gradient, and the complementary effect of each constituent layer. These findings provide a new paradigm for functional material design with outstanding temperature stability.
ADVANCED MATERIALS
(2022)
Article
Materials Science, Ceramics
Yang Li, Ting Zheng, Jiagang Wu
Summary: Bismuth ferrite-barium titanate (BF-BT)-based ferroelectrics have been widely studied for their adjustable structure features and multifunctional characteristics. In this work, defect engineering using selective oxides modification strategy was adopted to enhance both the electrostrain and ferroelectricity properties simultaneously. This approach effectively balanced domain configuration and relaxor state in the ceramics doped with MnO2, providing insights for modifying electrical properties in BF-BT-based ferroelectrics.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2022)
Article
Materials Science, Ceramics
Xianya Wang, Xinyu Liu, Haoyue Xue, Jie Yin, Jiagang Wu
Summary: Rarely studied dopant Sb is found to effectively overcome the drawbacks of high hysteresis and poor temperature stability in BNT-based piezoelectric ceramics, showing excellent electro-strain behavior over a wide temperature range of 40-120 degrees Celsius. This suggests that Sb-modified BNT-based ceramics have higher potential for practical actuator applications compared to previously reported materials.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2022)
Article
Engineering, Environmental
Xianya Wang, Xiaojun Wu, Diyan Yang, Jie Yin, Jiagang Wu
Summary: A novel dielectric energy-storage ceramic with high energy-storage efficiency and low applied electric field is designed based on the strategy of regulating polar nano sized regions (PNRs) state.
CHEMICAL ENGINEERING JOURNAL
(2022)
Article
Materials Science, Ceramics
Yuntao Huang, Haoyue Xue, Ting Zheng, Jiagang Wu
Summary: Achieving excellent pyroelectric performance is challenging for lead-free piezoelectric ceramics. In this study, (1-x)K0.48Na0.52NbO3-xBi(0.5)Ag(0.5)ZrO(3)-0.2%Fe2O3 (KNN-BAZ-Fe) lead-free ferroelectric ceramics with high Curie temperatures were prepared to improve pyroelectric performance. The variation of BAZ content promoted grain growth and resulted in the best pyroelectric coefficient when x = 0.05.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2023)
Article
Multidisciplinary Sciences
Jie Yin, Xiaoming Shi, Hong Tao, Zhi Tan, Xiang Lv, Xiangdong Ding, Jun Sun, Yang Zhang, Xingmin Zhang, Kui Yao, Jianguo Zhu, Houbing Huang, Haijun Wu, Shujun Zhang, Jiagang Wu
Summary: This study investigates the atomic-scale structure of lead-free relaxor ferroelectric Bi0.5Na0.5TiO3-based system and its relationship to the polar structure evolution and large dynamic electromechanical response. It is found that increased defect concentration is the main driving force for deviating polarizations with high-angle walls, while the driving force for deviating polarizations with low-angle walls changes. The competitive and synergetic equilibrium of anisotropic field versus random field contributes to the giant electromechanical response.
NATURE COMMUNICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Chongyang Li, Haoyue Xue, Ting Zheng, Jiagang Wu
Summary: In this study, a new relaxor ferroelectric material was designed to achieve good strain performance and stability at high temperatures by changing the temperature and electric field-dependent characteristics of nanodomains through doping. The introduction of BMN was found to decrease domain switching at high temperatures, which is crucial for improving the temperature stability of strain.
MATERIALS TODAY PHYSICS
(2022)
Article
Materials Science, Multidisciplinary
Wenbin Liu, Ting Zheng, Xuezheng Ruan, Zhenyong Man, Haoyue Xue, Laiming Jiang, Fuping Zhang, Guorong Li, Jiagang Wu
Summary: This study proposes a synergetic strategy to address the contradiction between piezoelectric performance and temperature stability in PZT-based piezoelectric ceramics by introducing lead vacancies through niobium doping and constructing a morphotropic phase boundary. By designing the PBZTN-x material system, good comprehensive properties and excellent temperature stability were achieved in the PBZTN-0.540 ceramics.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Xiang Lv, Nan Zhang, Yinchang Ma, Xi-xiang Zhang, Jiagang Wu
Summary: This study investigates the effect of the K/Na ratio on phase boundary engineering (PBE) of potassium sodium niobate ceramics. The K/Na ratio significantly influences the local environment and alters the ferroelectric domains and overall structure and performance. Higher Na+ content leads to local stress heterogeneity, while higher K+ content introduces local polar heterogeneity. Through appropriate coupling of local stress and polar heterogeneity, the piezoelectric properties and temperature stability of electrostrain are optimized on the Na-rich side. Therefore, besides seeking appropriate chemical dopants, carefully tailoring the K/Na ratio is also important for improving the piezoelectric properties of PBE-featured KNN-based ceramics.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2022)
Article
Materials Science, Ceramics
Yang Li, Ting Zheng, Bing Li, Jiagang Wu
Summary: The resistivity and leakage current of bismuth ferrite-barium titanate-based ceramics have been regulated in this study by changing the relaxation degree and defect dipoles. Introduction of Sb led to improved resistivity in relaxor ferroelectrics with chemical-homogeneous grain structure and strip-shaped/submicron-sized coexisted domains, while deteriorated properties appeared in relaxors with core-shell structure and tweed-like ferroelectric domains. The improved insulation in relaxor-ferroelectrics was attributed to decreased concentration of oxygen vacancies and Ti3+, while the emergence of core-shell structure and conductive channels resulted in decreased resistivity.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2023)
Article
Biochemistry & Molecular Biology
Typhaine Paysan-Lafosse, Matthias Blum, Sara Chuguransky, Tiago Grego, Beatriz Lazaro Pinto, Gustavo A. Salazar, Maxwell L. Bileschi, Peer Bork, Alan Bridge, Lucy Colwell, Julian Gough, Daniel H. Haft, Ivica Letunic, Aron Marchler-Bauer, Huaiyu Mi, Darren A. Natale, Christine A. Orengo, Arun P. Pandurangan, Catherine Rivoire, Christian J. A. Sigrist, Ian Sillitoe, Narmada Thanki, Paul D. Thomas, Silvio C. E. Tosatto, Cathy H. Wu, Alex Bateman
Summary: The InterPro database has been updated with new data content and website features, providing a more user-friendly access to protein sequence classification and functional domain identification. It has also integrated features from the retiring Pfam website and developed a card game to engage the non-scientific community. Furthermore, the database explores the benefits and challenges of using artificial intelligence for protein structure prediction.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Chao Wu, Xiaopeng Wang, Ying Tang, Haoyin Zhong, Xin Zhang, Anqi Zou, Jiliang Zhu, Caozheng Diao, Shibo Xi, Junmin Xue, Jiagang Wu
Summary: A fundamental understanding of the surface reconstruction process is crucial for the development of efficient electrocatalysts based on the lattice oxygen oxidation mechanism (LOM). Contrary to previous beliefs, the surface reconstruction in LOM-based metal oxides is found to be a spontaneous chemical reaction process rather than an electrochemical process. During this process, lattice oxygen atoms are attacked by adsorbed water molecules, leading to the formation of hydroxide ions (OH-). The leaching of metal-site soluble atoms from the oxygen-deficient surface also occurs. Additionally, it is discovered that enhancing surface hydrophilicity can accelerate the surface reconstruction process, providing further insights into the mechanism.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Multidisciplinary Sciences
Qinghua Wang, Jonathan Olshin, K. Vijay-Shanker, Cathy H. Wu
Summary: Chinese hamster ovary (CHO) cells are widely used in the pharmaceutical industry for mass production of therapeutic proteins. Research on CHO cell line development and bioprocess has been increasing in recent decades. Bibliographic mapping and classification of relevant research studies are important for identifying research gaps and trends.
Article
Multidisciplinary Sciences
Manju Anandakrishnan, Karen E. Ross, Chuming Chen, Vijay Shanker, Julie Cowart, Cathy H. Wu
Summary: In this study, a tool called KSFinder was developed to predict kinase-substrate links by capturing the inherent association of proteins in a network comprising 85% of the known human kinases. KSFinder outperformed other prediction models and showed a higher kinase coverage. Substrates of 432 kinases, including 68 understudied kinases, were predicted using KSFinder. The potential functions of two understudied kinases were hypothesized based on their predicted substrates.
