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AbstractResearchers face the challenge of efficiently navigating vast scientific literature while valuing printed papers in the digital age. Printed materials facilitate deeper engagement and comprehension, leading to active reading engagement and enhanced retention. However, existing digital tools often need to pay more attention to the needs of researchers who value the tactile benefits of printed documents. In response to this gap, we introduce AR-PaperSync, a solution that leverages Augmented Reality (AR) and cross-device interaction technology. AR-PaperSync integrates the physical experience of printed papers with the interactive capabilities of digital tools. Researchers can navigate inline citations, manage saved references, and synchronize reading notes across mobile, desktop, and printed paper formats. Our user-centric approach, informed by in-depth interviews with six researchers, ensures that AR-PaperSync is tailored to its target users’ needs. A comprehensive user study involving 28 participants evaluated AR-PaperSync’s significantly enhanced efficiency, accuracy, and system usability and reduced cognitive load in academic reading tasks compared to conventional methods. These findings suggest that AR-PaperSync enhances the reading experience of printed scientific papers and provides a seamless integration of physical and digital reading environments for researchers. [ABSTRACT FROM AUTHOR]

Copyright of Grafica: Journal of Graphic Design / Documents de Disseny Gràfic is the property of Universitat Autonoma de Barcelona and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Dilemas Contemporáneos: Educación, Política y Valores is the property of Dilemas Contemporaneos: Educacion, Politica y Valores and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Scientific papers at this time are something that must be mastered by a student. Scientific articles produced by someone contribute new knowledge to the world of Education. This study aims to analyze the obstacles experienced by students when writing scientific articles. The research was conducted on biology education students at the Open University who are in their final semester and take scientific work courses as one of the graduation requirements. There were at least 13 students who were the research samples taken purposively. To obtain data, the researcher provided a questionnaire and conducted interviews with a sample of students. The data were then analyzed descriptively and resulted in the discovery that the main barriers of biology education students in writing scientific papers are lack of student experience in writing scientific papers especially in the components of scientific papers. They found it difficult when creating an introduction (54%), method (46%), and presenting results and discussions (54%). The recommendation from this study is the need to develop learning strategies in scientific work courses that can train students to get used to developing ideas and process these ideas into original articles and free from plagiarism.

In the evolving landscape of materials science, the exponential growth in scientific publications presents both an opportunity and a challenge. Efficiently extracting valuable insights from this vast volume of literature requires specialized tools that go beyond traditional methods. Here, we introduce MatNexus, a software package designed for the automated collection, processing, and analysis of text from scientific articles in the realm of materials science. MatNexus stands out with its integrated suite of modules, which facilitates the retrieval of scientific articles, processes textual data to uncover latent knowledge, generation of vector representations suitable for machine learning applications, and offers advanced visualization capabilities for these word embeddings. Our tool addresses the critical need for effective and reproducable text mining in materials science, an area marked by increasing complexity and data intensity. By making the exploration of materials more efficient and insightful, as exemplified in our case study on electrocatalysts, MatNexus represents a significant advancement in the field. It offers an end-to-end solution for harnessing the wealth of information available in scientific literature, thus aiding the discovery and innovation process in materials science.

Early researchers often struggle in writing scientific papers due to deficient writing skills and adapting to academic settings. In response, the Doctoral Program in Public Policy at the Faculty of Economics and Business at Universitas Trisakti organized a webinar with the intention of providing students with effective writing techniques. The webinar addressed important areas such as publishing in Scopus-indexed journals, composing successful manuscripts, maintaining writing consistency, and selecting appropriate venues for publication. The outcomes demonstrated that this webinar greatly enhanced the participants' confidence in scientific writing, with 85% strongly agreeing and 15% agreeing. Overall feedback from participants was positive, with 95% strongly agreeing and 5% agreeing that the activity was beneficial. Moreover, 90% expressed a strong wilingness to participate in future training, while 10% agreed. This paper's importance and benefits make it a valuable resource for widespread use, especially by new researchers aiming to enhance their scientific writing skills and strategies.

The rapid development of technology has resulted in a surge in the volume of digital data available. This situation creates a problem for users who need assistance in locating specific information within this massive collection of data, resulting in a time-consuming process. Automatic Text Summarization systems have been developed as a more effective solution than traditional summarization techniques to address this problem and improve user access to relevant information. It is well known that researchers in the health sciences find it difficult to keep up with the latest literature due to their busy schedules. This study aims to produce comprehensive abstracts of Turkish-language scientific papers in the field of health sciences. Although abstracts of scientific papers are already available, more thorough summaries are still needed. To the best of our knowledge, no previous attempt has been made to automatically summarize Turkish language health science papers. For this purpose, a dataset of 105 Turkish papers was collected from DergiPark. Term Frequency, Term Frequency-Inverse Document Frequency, Latent Semantic Analysis, TextRank, and Latent Dirichlet Allocation algorithms were chosen as extractive text summarization methods due to their frequent use in this field. The performance of the text summarization models was evaluated using recall, precision, and F-score metrics, and the algorithms gave satisfactory results for Turkish. [ABSTRACT FROM AUTHOR]

This study aims to explore the correlation between students' digital competence and indecision with the challenges they encounter during the online scientific writing assistance process amid the Covid-19 pandemic. Students faced multiple forms of hesitation, communication breakdowns, and missed opportunities for discussion during this process. The research findings target guidelines for writing scientific papers. Qualitative data was collected through an online survey of 100 students from public universities in Indonesia. The research instrument employed an online questionnaire distributed to students via the Google Forms application. Data analysis was conducted using qualitative and interpretive approaches based on the principles of content analysis. The results revealed that students experienced profound doubts and confusion when it came to organizing their thoughts while conducting research and writing scientific papers as final projects. This research suggests that students' digital intelligence alone is insufficient for accessing the information required by their intellectual intelligence in writing scientific papers. [ABSTRACT FROM AUTHOR]

Purpose - Technology development is getting faster, especially in the scope of education. The existence of increasingly advanced technology is a challenge to digital literacy competence in students, especially in writing scientific papers. This study aims to reveal the importance of mastering digital literacy in supporting the process of writing scientific papers for students. Method - The researcher used a qualitative descriptive method. The primary data in this study are the results of observations and interviews on the scientific writing habits of postgraduate students at the State Islamic University of Maulana Malik Ibrahim Malang in utilizing digital media. Findings - The result of this study is that the existence of digital literacy is very supportive of student scientific writing. The impact felt by students related to the competence of digital literacy in writing scientific papers is that 1) writing scientific papers becomes better and more effective because they can easily get references through digital journal portals; 2) learning anywhere becomes practical because there is no need to carry many books to move places; 3) improving the ability to find information; 4) improving analytical skills; and 5) improving critical thinking skills. Research Implications - The limitation of this research is that it has not fully revealed the supporting and inhibiting factors of digital literacy in the process of writing student scientific papers.

Writing scientific papers is an essential foundation in the academic sphere, requiring researchers, students, and academics to manage, refer to, and cite various sources that support their arguments and findings. Emerging as a solution to this challenge, Mendeley Reference has the potential to change the way writers manage references in the context of higher education. This Community Service Activity (PKM) aims to provide a more comprehensive understanding to students, especially those in the 7th semester of the PGSD major at the Teaching and Education Faculty of Buton Muslim University, regarding the benefits of using the Mendeley application in writing scientific assignments. This PKM is carried out through three stages: preparation, implementation, and evaluation. The evaluation results showed that most participants had a good understanding, but some required further training. The positive impact of the training can be seen in the academic and professional development of the participants. Therefore, as a follow-up, practical exercises will be intensified, increased structured discussions between participants and presenters, and gathering input from participants for future improvements. Overall, this training significantly contributes to providing students with essential skills in scientific writing and better preparation for future academic and professional challenges.

School teachers need scientific papers in proposing their promotion. However, in general, teachers are still constrained by their ability to write scientific papers. They still do not understand in writing scientific papers. Therefore, they need help to get out of the problem. The Research and Community Service Institute of Hasanuddin University held training and assistance in writing scientific papers and maximizing the use of Mendeley for teachers of SMP Negeri 1 Bungoro Pangkep Regency with the aim of 1) increasing the motivation of teachers of SMP Negeri 1 Bungoro Pangkep in writing scientific papers, 2) SMP Negeri 1 Bunggoro teachers can write scientific articles. The method used is training with lecture and question and answer methods. As for assistance, the discussion method is used through the zoom application. The results of the research show that 1) teachers are motivated to write scientific papers and 2) teachers are encouraged to write scientific papers as evidenced by the number of entries in their research.

Our goal is to reveal the social media knowledge cascade (SMKC) of the diffusion of scientific papers. PLoS Biology, one of the prestigious and influential open-access journals under PLoS, has received much attention from researchers. Using papers published in PLoS Biology as sample, we use the citation indicators and social media indicators of scientific papers to establish an SMKC network model that measures the relationship between the citation diffusion trajectory of scientific papers and their social media diffusion trajectory through knowledge bursts. Based on the number and type of knowledge bursts, we have identified three types of SMKCs: Social media and SMKC (S–S knowledge cascade), Citation and citation knowledge cascade (C–C knowledge cascade), and Social media and citation knowledge cascade (S–C knowledge cascade). Specifically, we focus on studying the S–C knowledge cascade type in SMKC. We explored the relationship between social media diffusion trajectory knowledge bursts and citation diffusion trajectory knowledge bursts, the prompting effect of S–C knowledge cascades on paper's citation and the pivot node characteristics of the paper S–C knowledge cascade. Our research found that, in the S–C knowledge cascade papers the knowledge burst of the paper on the social media diffusion trajectory is the decisive factor for the knowledge burst in the citation diffusion trajectory. Only part of the knowledge burst in the citation diffusion trajectory will immediately cause the social media diffusion trajectory knowledge bursts. The stronger a paper's SMKC, the easier it is to become a highly cited paper. The type of pivot node is more inclined to the burst of knowledge on the trajectory of social media diffusion. We analyzed the trajectory of knowledge dissemination in the life cycle of scientific papers from a dynamic perspective. We revealed the general features of SMKCs in the process of scientific paper diffusion. [ABSTRACT FROM AUTHOR]

Predatory journals have been defined as a fraudulent model that takes advantage of the golden route implemented by some open access publications. These journals exploit the business of charging authors, promising quick and low-cost publication. However, they do not comply with the tasks of any scientific journal, such as peer review or digital preservation of original writings, and therefore they publish papers of questionable quality, methodology and reproducibility. For these reasons, this research aims to determine the level of knowledge that active researchers of the Universidad Tecnológica Metropolitana (UTEM) have about predatory journals. For the study, a survey was used as a data collection instrument, which was sent to the active researchers from the UTEM. From the results obtained, it was possible to conclude that the UTEM researchers are familiar with the term predatory journals and can identify certain characteristics of these journals, such as the fact that they do not perform an adequate peer review process, offer a fast publication process at low cost, and have similar titles to those of renowned journals, in addition to being able to identify some tools for their detection. [ABSTRACT FROM AUTHOR]

Copyright of Information Library Magazine 'INFOLIB' is the property of National Library of Uzbekistan named after Alisher Navoi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Lack of mastery of receptive and expressive language in students with hearing impairments affects the ability to compose scientific papers. Assistive technology for writing scientific papers can support students with hearing impairments in completing scientific paper assignments at various semester levels. This research aims to develop assistive technology that can make it easier for students with hearing impairments to participate in learning in tertiary institutions to create accessible learning for students with hearing impairments. Sign language application “PESAN KULIAH” (Guidelines for Writing Scientific Papers) is made by adjusting the characteristics of hearing impairments to make it easier to understand how to write various kinds of scientific papers. The method used in this research is R and D with ADDIE type. The results of the study show that the “PESAN KULIAH” application which contains explanation features about the types of scientific papers, writing systematics, and examples of scientific papers and is equipped with sign language videos by Sign Language Interpreters is proven to support the understanding of students with hearing impairments in understanding writing procedures and terms. contained in the preparation of papers, scientific reports, scientific articles, and theses.

Copyright of Pregled is the property of University of Sarajevo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Principals and teachers play a strategic role in improving the quality of education as shown by the best experience (Best Practice) in carrying out their main tasks and functions. Best practices need to be disseminated and published in order to be a reflection and inspiration for others to improve the quality of education. However, the facts show that principals and teachers do not yet have adequate knowledge and skills in compiling best practice scientific papers. This community service activity aims to improve skills in compiling best practice scientific papers for teachers and principals at Private Education Foundations. The training is carried out online with the following methods: lecture, question and answer, discussion, guidance, and performance. The success of community service is shown by: 1) the number of participants exceeding the target of 50 increases to 53 people; 2) attendance reached 92.96% (very good); 3) The increase in the pre test - post test scores reached 76% (Good); 4) The number of training products reached 71.69% (Good) with a product quality score of 77.80 (Good). This success shows the enthusiasm of the participants and very high awareness of the importance of writing best practices for increasing the professionalism of teachers and principals.

Teachers in schools not only have to be good at teaching in the classroom, but, like lecturers in higher education, have an obligation to be able to conduct research and compile scientific articles. So it is important for teachers to have mastery in organizing references or literature properly. The use of reference management software is something that teachers must know and be able to use. In general, teachers at SMA 1 Muhammadiyah Baubau do not have the knowledge and skills to use the reference management system, so this community service activity is carried out with the aim of providing knowledge and skills for teachers at SMA 1 Muhammadiyah Baubau regarding reference management software. The applications provided are Zotero, and EndNote, and Mendeley. The activity was held for two days, starting with a survey of participant knowledge and continued with training on reference management software, and ending with a post-test for participants to measure the level of participant mastery. The survey results showed that most of the training participants did not have a good understanding of reference management software including its operation. After the training, 90% of the trainees stated that the Zotero application is quite easy to use when compared to the End-Note application. 54% of participants stated that the Zotero application is easier to operate, while 43% stated that the EndNote application is easier to use, meaning that the two applications are almost as easy to operate. Another finding was that the training participants expressed their satisfaction with the speaker 's mastery of the material including the presentation of the material that was interesting and easily understood by the participants.

The emergence of new technologies in the current digital era has led to new challenges and innovative solutions. Researchers are utilizing this revolution for their study, leading to a significant increase in the number of scientific publications globally. Scientific papers typically appear to be complex and difficult to grasp. Understanding the vital phrase in a complex string of terms is quite challenging, but understanding the vital information is crucial for researchers. A crucial factor in determining, whether a publication among the enormous number of publications, is worthy of being accepted is the success of the publications. Peer reviews, which are provided by reviewers who are typically experts in the field, are used in this approach. It is possible to explore scientific peer reviews and foretell the effectiveness of the publications by using Sentiment Analysis (SA, also referred to as opinion mining). Several Machine Learning (ML) algorithms have been used by researchers to analyze scientific peer papers. This literature review seeks to give a comprehensive account of what researchers have done in this field so far and where the current research stands right now. [ABSTRACT FROM AUTHOR]

With the growth in scientific papers, citation recommendation which enables researchers to find useful references efficiently and further to promote academic communication and cooperation has become increasingly important. However, little research has been done to explore how to recognize the semantically relevant references according to research scenarios and the context of the paper citation. Motivated by the research gap, the present study attempts to adopt SciBERT to represent text and expand its semantics through the fusion of WordNet knowledge. Further, core themes from references are automatically extracted by TextRank to solve the problem of incomplete content extraction. In this case, the model named SciBERT + DPCNN is constructed for semantic representation and citation recommendation of scientific papers. Afterwards, multiple experiments are designed and implemented in three parts to verify the effectiveness of the model. The first result is that the outcomes of SciBERT + DPCNN obtain the highest among all baseline models. Additionally, when the model performs in 1 WordNet fusion at the end of the sentence, the best outcomes are 84.72%, 84.80%, 84.72%, and 84.71% in terms of accuracy, precision, recall, and F1-score, respectively. Ultimately, for the classification results of the reference structure, the long text 'title + abstract + TextRank full text (except the title and abstract)' outperforms most short text 'title + abstract' without WordNet fusion. However, when WordNet is fused for the classification, the short text is mostly more accurate than the long text. [ABSTRACT FROM AUTHOR]

We stand at the threshold of a revolution in science. It is possible that soon scientific writing as we know it will undergo a rapid change, all thanks to the ChatGPT 3.5 language model. The appearance of this tool on the technology market in November 2022 caused a massive stir among Internet users and the academic world. It turned out that chat has the potential to generate completely new and unique scientific texts. In the wake of ChatGPT, similar tools by technology giants came and are coming. Given the above, the scientific community has only a brief moment to try to answer the following questions: whether the texts generated in this way have real scientific value, whether it is ethical for researchers to use them, how to regulate copyright on the use of AI, what are the potential capabilities of artificial intelligence for writing scientific papers. The indicated themes are reflected in the presented text. [ABSTRACT FROM AUTHOR]

Compiling scientific papers is one of the efforts that can be made by lecturers in developing their professional competence. By writing scientific papers, a lecturer can develop his writing skills, and develop himself to be able to integrate ideas and present them in a structured manner. This activity was carried out to increase lecturer awareness in writing scientific papers and provide education related to writing scientific articles. Preparation for the activity was carried out on August 28 2021 and the core activity was in the form of a coaching clinic for writing scientific articles and was carried out on September 4, 2021. The main target for this activity is young lecturers who have little experience writing articles. The implementation of this service uses coaching clinics, discussions, and assistance. The results of this dedication show an increase in the ability or skills of lecturers and their understanding of writing scientific articles.

The objectives of this study are to determine the ability of students Pendidikan Bahasa dan Sastra Indonesia (PBSI), FKIP, Universitas PGRI Yogyakarta (UPY) in writing scientific papers; and to find out the difficulties of students in writing scientific papers. The research method used is descriptive qualitative. The population in this study were PBSI students who were conducted in the odd semester of the 2021/2022 academic year. The sample is 31 students of class G-1 who take Psycholinguistics courses. Data in the form of scientific papers were collected in the middle of the semester of Psycholinguistics lectures. The scientific paper was analyzed using research instruments. The writing ability assessed includes five aspects, namely (1) ideas, (2) organization, (3) grammar, (4) diction, and (5) spelling. Based on the assessment, each is categorized into five, namely (1) very good with a score range of 86-100, (2) good with a score range of 68-85, (3) sufficient with a score range of 48-67, (4) less with range of values from 32 to 47, and (5) very less with a range of values

The Scientific paper is a required subject for final year Muamalat Diploma students at UiTMCTKD in semester 5. The Wheel of Fortune Interactive PnP Innovation Project (PWoFKi) method is used to assess students' comprehension of input for writing a scientific paper or research paper that was given in the form of a lecture during a scientific paper writing workshop held prior to students registering for this subject. This strategy was developed to encourage students to be more enthusiastic about comprehending all of the critical procedures involved in producing scientific articles without becoming bored, stiff, or passive in response to the feedback provided. The employment of (PWoFKi), which employs an intriguing gaming method, can be studied as a teaching and learning mechanism (PnP) in promoting learning delight. As a result, the goal of this study is to assess students' understanding of the appropriateness of using PWoFKi in the PnP process for the subject of Scientific Papers (IMU304), as well as to pique students' interest in the subject of Scientific Papers (IMU304), in order to improve the learning and teaching environment. A questionnaire was provided to 57 participants in a pilot research. To assess students' perceptions of implementation, data was analysed using SPSS 24 and compared to the mean score (PWoFKi). The results show that the mean score is 4.26 on a 5-point scale. This suggests that the innovation of usage (PWoFKi) in PnP topic IMU 304 can solve the problem of boredom while also making students have fun and improving their knowledge of the learning delivered. One of the games that may be used to interact and communicate for learning goals is the PWoFKi technique. The study's findings indicate that the PWoFKi method is a novel strategy in the IMU304 PnP process that can be used by any students pursuing Diploma, Degree, Masters, or Doctorate degrees in any public or private higher education institution.

In this perspective, I will argue that we must reconsider how we write scientific articles. Instead of using the stiff style that has become the norm in academic writings, we should focus on clarity and informality. It's time to abandon old conventions that make scientific articles so unpleasant to read. [ABSTRACT FROM AUTHOR]

Copyright of Revista Telos is the property of Revista Telos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, we propose a way to link the scholarly contents of scientific papers by constructing a knowledge graph based on the semantic organization of argumentation units and relations in scientific papers. We carried out an argumentation graph data model aimed at linking multiple discourses, and also developed a semantic annotation platform for scientific papers and an argumentation graph visualization system. A construction experiment was performed using 12 articles. The final argumentation graph has 1,262 nodes and 1,628 edges, including 1,628 intra-article relations and 190 inter-article relations. Knowledge evolution representation, strategic reading, and automatic abstracting use cases are presented to demonstrate the application of the argumentation graph. In contrast to existing knowledge graphs used in academic fields, the argumentation graph better supports the organization and representation of scientific paper content and can be used as data infrastructure in scientific knowledge retrieval, reorganization, reasoning, and evolution. Moreover, it supports automatic abstract and strategic reading. [ABSTRACT FROM AUTHOR]

This study aims to determine the creative thinking patterns of students contained in scientific papers. The method used is a qualitative research method. Sources of data in research are students and documents in the form of papers. There are three data collection techniques, namely (1) reading papers, (2) interviews, and (3) observation. The results of this study show a pattern of lateral thinking that appears in several developments of ideas. Then, there are still traditional thinking patterns. Factors that cause traditional thinking are (1) experience, (2) sources of information, (3) lack of confidence, and (4) willingness to learn. [ABSTRACT FROM AUTHOR]

Copyright of Ruthenian Studies / Rusinistični Studii is the property of Faculty of Philosophy, University of Novi Sad and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of the study is to determine the factors for increasing the representation of the Ukrainian scientific community in the international scientific community and raising the international scientific authority of Ukraine. Used Results of the annual G20 evaluation - the effectiveness of research in 2019, conducted by the Institute of Scientific Information (ISI), part of the Web of Science Group. The principles of introduction of scientometric methods of research of publishing activity of scientists in the international and Ukrainian scientific space are considered. Based on the processing of statistical material and the obtained quantitative estimates, a comparative analysis of the effectiveness of research in the G20 and Ukraine according to the Web of Science. In this area, some differences between Ukraine and countries that are world leaders in the organization of the research process are shown. Recommendations for increasing the representation of the Ukrainian scientific community on the Web of Science platform and raising the international scientific authority of Ukraine are offered.

Plagiarism Detection Systems play an important role in revealing instances of a plagiarism act, especially in the educational sector with scientific documents and papers. The idea of plagiarism is that when any content is copied without permission or citation from the author. To detect such activities, it is necessary to have extensive information about plagiarism forms and classes. Thanks to the developed tools and methods it is possible to reveal many types of plagiarism. The development of the Information and Communication Technologies (ICT) and the availability of the online scientific documents lead to the ease of access to these documents. With the availability of many software text editors, plagiarism detections becomes a critical issue. A large number of scientific papers have already investigated in plagiarism detection, and common types of plagiarism detection datasets are being used for recognition systems, WordNet and PAN Datasets have been used since 2009. The researchers have defined the operation of verbatim plagiarism detection as a simple type of copy and paste. Then they have shed the lights on intelligent plagiarism where this process became more difficult to reveal because it may include manipulation of original text, adoption of other researchers' ideas, and translation to other languages, which will be more challenging to handle. Other researchers have expressed that the ways of plagiarism may overshadow the scientific text by replacing, removing, or inserting words, along with shuffling or modifying the original papers. This paper gives an overall definition of plagiarism and works through different papers for the most known types of plagiarism methods and tools. [ABSTRACT FROM AUTHOR]

Text representation is the preliminary work for in-depth analysis and mining of information in scientific papers. It directly affects the effects of downstream tasks such as, scientific papers classification, clustering, and similarity calculation. However, recent researches mainly considered citation network and partial structural information, which is insufficient when representing scientific papers. Therefore, in order to improve the performance of text representation model, this paper proposed MV-HATrans, a text representation model that combines multi-viewpoint information, such as the semantic information of knowledge graph and structural information. This model extracts word information from three aspects, including contextual content, part of speech, and word meaning of WordNet. Based on combination of hierarchical attention mechanism and transformer, the model achieves the full text representation of scientific papers. Finally, this paper uses the binary experimental dataset AAPR, which indicates whether scientific papers are accepted or not, and applies the proposed model of text representation to achieve the goal of automatic quality assessment. Results show that in the quality classification of scientific papers, adopting part-of-speech information and semantic information based on WordNet definitions can effectively achieve the accuracy of prediction as 70.14%. Among all the structural modules, authors and abstracts contributes the most to the quality classification of scientific papers, especially authors as 9.51%. [ABSTRACT FROM AUTHOR]

Currently, many summarization models are based on Transformer architectures, which regard text as a connected graph of words and tokens, thus fail to fully leverage the text's hierarchical structure. However, hierarchical structural information is crucial in understanding long documents, especially scientific papers. To exploit the structural information, we propose a H eterogeneous T ree structure augmented with T riplet P ositions for extractive Sum marization of scientific papers (HTPosum). The proposed model constructs a heterogeneous tree for each document, introducing section nodes and a global node to capture the documents' structural information. The tree is then augmented with a novel triplet position, which consists of three values that represent the depth, parent width position, and sibling width position of each node in a tree. The triplet position provides a unified view of the document structure. Experimental results show that the proposed model achieves state-of-the-art extractive performance on the PubMed and arXiv datasets compared with the latest scientific paper summarization models. • A heterogeneous tree is built to model scientific papers' hierarchical structure. • A triplet position and unique triplet position encoding method is proposed. • The proposed model achieves competitive results compared to latest baselines. [ABSTRACT FROM AUTHOR]

Subject categories of scholarly papers generally refer to the knowledge domain(s) to which the papers belong, examples being computer science or physics. Subject category classification is a prerequisite for bibliometric studies, organizing scientific publications for domain knowledge extraction, and facilitating faceted searches for digital library search engines. Unfortunately, many academic papers do not have such information as part of their metadata. Most existing methods for solving this task focus on unsupervised learning that often relies on citation networks. However, a complete list of papers citing the current paper may not be readily available. In particular, new papers that have few or no citations cannot be classified using such methods. Here, we propose a deep attentive neural network (DANN) that classifies scholarly papers using only their abstracts. The network is trained using nine million abstracts from Web of Science (WoS). We also use the WoS schema that covers 104 subject categories. The proposed network consists of two bi-directional recurrent neural networks followed by an attention layer. We compare our model against baselines by varying the architecture and text representation. Our best model achieves micro-F1 measure of 0.76 with F1 of individual subject categories ranging from 0.50 to 0.95. The results showed the importance of retraining word embedding models to maximize the vocabulary overlap and the effectiveness of the attention mechanism. The combination of word vectors with TFIDF outperforms character and sentence level embedding models. We discuss imbalanced samples and overlapping categories and suggest possible strategies for mitigation. We also determine the subject category distribution in CiteSeerX by classifying a random sample of one million academic papers.

This article is part of an ongoing research. The research aims to analyze the national scientific production of Information Science, from 2010 to 2020, published in journals indexed in the Web of Science and Scopus databases. In order to achieve the general objective, the following specific objectives were chosen: Analyze the scientific production of teachers\researchers from postgraduate programs in Information Science; Identify the most important themes approached in the scientific production of graduate programs in Brazil; Identify the most productive authors of each postgraduate program; Check collaboration in the area; Survey the titles of the most productive journals in the studied period; Characterize the most productive programs. It is a descriptive research with quantitative and qualitative approaches. The quantitative approach will use bibliometric and scientometric techniques to assist in measuring the researcher's productivity. When the scientific production was surveyed from 2010 to 2020 in the Web of Science and Scopus databases, 3,000 articles and reviews were found. So as to identify the main themes addressed, it was chosen to identify the keywords and the relevance in the studied period. 1,093 authors were found in the Web of Science database and in the Scopus database 6,886 authors who produced 2,206 articles and reviews in the period from 2010 to 2020. When verifying the existing collaboration in the area of Information Science in the period 2010-2020, there is an expressive institutional collaboration in the total academic production. Institutional collaboration corresponds to 34% of academic production. To survey the most productive journals in the period studied, publications in 48 journals were found in both databases. To characterize the most productive programs, the following references were adopted: year of beginning of the programs, number of teachers of the programs, areas of concentration of the programs, the stricto sensu postgraduate modalities of each program, the evaluation by CAPES of the master's and doctorate and the regional location. It was noted that there is a concentration of programs in the Southeast region. [ABSTRACT FROM AUTHOR]

There are increasing environmental and economic demands for the production of chemicals of industrial interest from renewable resources. Among the renewable products, short‐chain carboxylic acids (C1‐C6) stand out due to their importance in many sectors of the economy. Within this class, a wide variety of acids are industrially valuable as the precursors of many other chemicals for different applications, technological solutions, and markets. This makes it difficult to identify the most promising from a technical and economic standpoint. In this work, data on scientific papers and patents published between 2008 to 2017, related to the main bio‐based carboxylic acids, are used to identify the acids that are generating growing scientific and industrial interest. The biochemical processes in patents associated with the production of such acids are evaluated using a multicriteria approach that integrates valuation patent criteria. The results of this study show that acids that are of substantial commercial interest, such as acetic, citric, lactic, acrylic, and methacrylic acids, have the highest growth rate both in scientific papers and patents. In terms of biochemical processes, the multicriteria decision analysis showed that the most relevant processes described in patents were associated with 'drop‐in' acids such as methacrylic, adipic, maleic, acrylic, and glutaric acids. There is also a clear indication of the emergence of studies on low volume acids such as acetoacetic, acetolactic, muconic, and levulinic acids. In conclusion, the analysis shows that emerging scientific and technological production is conservative, focusing on acids with established markets, especially for the substitution of petrochemicals for immediate demand. © 2020 Society of Industrial Chemistry and John Wiley & Sons Ltd [ABSTRACT FROM AUTHOR]

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