Scientific Texts Research Articles

Exploring Students’ Multimodal Representations of Ideas About Epistemic Reading of Scientific Texts in Generative AI Tools

Exploring Students’ Multimodal Representations of Ideas About Epistemic Reading of Scientific Texts in Generative AI Tools

A Centrality-Weighted Bidirectional Encoder Representation from Transformers Model for Enhanced Sequence Labeling in Key Phrase Extraction from Scientific Texts

Deep learning approaches, utilizing Bidirectional Encoder Representation from Transformers (BERT) and advanced fine-tuning techniques, have achieved state-of-the-art accuracies in the domain of term extraction from texts. However, BERT presents some limitations in that it primarily captures the semantic context relative to the surrounding text without considering how relevant or central a token is to the overall document content. There has also been research on the application of sequence labeling on contextualized embeddings; however, the existing methods often rely solely on local context for extracting key phrases from texts. To address these limitations, this study proposes a centrality-weighted BERT model for key phrase extraction from text using sequence labelling (CenBERT-SEQ). The proposed CenBERT-SEQ model utilizes BERT to represent terms with various contextual embedding architectures, and introduces a centrality-weighting layer that integrates document-level context into BERT. This layer leverages document embeddings to influence the importance of each term based on its relevance to the entire document. Finally, a linear classifier layer is employed to model the dependencies between the outputs, thereby enhancing the accuracy of the CenBERT-SEQ model. The proposed CenBERT-SEQ model was evaluated against the standard BERT base-uncased model using three Computer Science article datasets, namely, SemEval-2010, WWW, and KDD. The experimental results show that, although the CenBERT-SEQ and BERT-base models achieved higher and close comparable accuracy, the proposed CenBERT-SEQ model achieved higher precision, recall, and F1-score than the BERT-base model. Furthermore, a comparison of the proposed CenBERT-SEQ model to that of related studies revealed that the proposed CenBERT-SEQ model achieved a higher accuracy, precision, recall, and F1-score of 95%, 97%, 91%, and 94%, respectively, than related studies, showing the superior capabilities of the CenBERT-SEQ model in keyphrase extraction from scientific documents.

Artificial Intelligence: A Challenge to Scientific Communication.

Recent years have seen formidable advances in artificial intelligence. Developments include a large number of specialised systems either existing or planned for use in scientific research, data analysis, translation, text production and design with grammar checking and stylistic revision, plagiarism detection, and scientific review in addition to general-purpose AI systems for searching the internet and generative AI systems for texts, images, videos, and musical compositions. These systems promise more ease and simplicity in many aspects of work. Blind trust in AI systems with uncritical, careless use of AI results is dangerous, as these systems do not have any inherent understanding of the content they process or generate, but only simulate this understanding by reproducing statistical patterns extracted from training data. This article discusses the potential and risk of using AI in scientific communication and explores potential systemic consequences of widespread AI implementation in this context.

TRINCAS, FISSURAS E RACHADURAS

Introduction: The pathologies present in civil construction directly impact the durability, functional performance and safety of buildings. Among the most common manifestations are fissures, cracks and cracks, which, if not properly treated, can compromise the structural integrity of the works. Objective: This article aims to discuss the causes, classifications and repair methods of cracks, cracks and cracks, focusing on their implications for civil engineering. Materials and Methods: The present study carried out a bibliographical review, with a qualitative approach, using the deductive method, of exploratory classification, with the aim of generating knowledge for preparing a scientific text, in order to provide greater familiarity with the problem. Results and Discussion: The pathologies of fissures, cracks and cracks represent an important challenge for civil engineering, requiring an integrated approach that includes prevention, accurate diagnosis and adequate repair. Understanding the causes of these pathologies, classifying them correctly and applying appropriate repair methods are fundamental steps to guarantee the longevity and safety of buildings, in addition to minimizing future costs with corrective maintenance. Conclusion: It is concluded that prevention and monitoring are essential to minimize damage and maintenance costs, in addition to ensuring user safety.

Onomastic component of the normative-scientific macrotext “Russian language” in a dynamic aspect

INTRODUCTION. The problem of the formation of the Russian linguistic personality, in particular its onomastic component, is the subject of numerous scientific studies, covering its various aspects, including within a certain period of time. However, the previously mentioned problem has not been considered in dynamics. The purpose of the study is to characterize the onomastic space of the macrotext “Russian Language” in a dynamic aspect in the period from the 19th to the beginning of the 21st century.MATERIALS AND METHODS. The research material was onyms identified in normative scientific texts of the 19th – early 21st centuries and supplemented with appellatives, which are written with a capital letter. The following methods were used: statistical, classification, comparative, et al.RESULTS AND DISCUSSION. The concept of the normativescientific macrotext “Russian language” is formulated, its structure and onomastic content are determined. In the normative-scientific texts of each period, the most frequent onyms are identified, forming the common core (invariant) of the onomastic space.CONCLUSION. The study confirmed the thesis that the central place in the onomastic space belongs to anthroponyms, which in large part are among the precedent names that are of great importance in the formation of the Russian linguistic personality. This conclusion convincingly emphasizes the special role of the academic subject “Russian language” in this process. The prospects of the work are associated with the expansion of the study of systemic relations within the onomastic space, identifying the content and structure of the associative-cultural background of its key units, establishing the specifics of the functioning of proper names in the texts of textbooks on the Russian language in comparison with normative-scientific texts on other subjects, et al.

Proper name in a normative scientific text

INTRODUCTION. The ability of a proper name to reflect both subject information and multifaceted background information puts it on a par with the main carrier of scientific knowledge – a term. In the study of linguistic expression of knowledge, the question of the role and place of onomastic vocabulary in the content of school education becomes relevant. The purpose of the study is to analyze the qualitative composition, quantitative parameters and nature of the relationship of proper names in the structure of existing educational texts, which will allow us to formulate requirements for the organization of the onomastic content of newly created texts.MATERIALS AND METHODS. The research material was an array of proper names extracted by the method of continuous sampling from the texts of textbooks and programs on all subjects of general secondary education in the late 1980s – early 2000s. When processing the obtained material, presented in the Database format, analytical, comparative, field methods, elements of the statistical method were used. RESULTS AND DISCUSSION. The total number and composition of onomastic units in educational texts were determined, the frequency and prevalence rates of these units were established, the core and peripheral components of this onomastic space were distinguished, the ratio of recurring and single onyms was revealed, their role in expressing subject knowledge was characterized, and the conditions for the optimal organization of educational onomastic space were formulated.CONCLUSION. The obtained data provide an idea of the volume and nature of the onomastic fragment of the generally binding scientific knowledge reflected in the normative scientific texts of the analyzed era. These results create the basis for the implementation of a systematic approach to the organization of onomastic vocabulary within the framework of normative scientific texts. Comparison of the obtained data with data from other time periods will allow us to determine the onomastic invariant and variable elements in different time concepts of the composition of basic onomastic knowledge.

Network for knowledge Organization (NEKO): An AI knowledge mining workflow for synthetic biology research

Large language models (LLMs) can complete general scientific question-and-answer, yet they are constrained by their pretraining cut-off dates and lack the ability to provide specific, cited scientific knowledge. Here, we introduce Network for Knowledge Organization (NEKO), a workflow that uses LLM Qwen to extract knowledge through scientific literature text mining. When user inputs a keyword of interest, NEKO can generate knowledge graphs to link bioinformation entities and produce comprehensive summaries from PubMed search. NEKO significantly enhance LLM ability and has immediate applications in daily academic tasks such as education of young scientists, literature review, paper writing, experiment planning/troubleshooting, and new ideas/hypothesis generation. We exemplified this workflow's applicability through several case studies on yeast fermentation and cyanobacterial biorefinery. NEKO's output is more informative, specific, and actionable than GPT-4's zero-shot Q&A. NEKO offers flexible, lightweight local deployment options. NEKO democratizes artificial intelligence (AI) tools, making scientific foundation model more accessible to researchers without excessive computational power.

Anti-aging versus positive-aging language in scientific literature: Raising questions for future research

Ageism is one of the most common forms of discrimination among older adults. Although applicable in regards to discrimination against all age groups, the term ageism is predominantly used in relation to the treatment of older people. Anti-aging language refers to the use of words, phrases and sentences when talking with or about older adults. Terms such as "old people," "old age," "elderly", "the elderly" and "the aged" are in the form of anti-aging speaking, and it is recommended that the terms "older people", "older adults", "seniors" and "later life" be used instead of the latter mentioned terms, indicating there is a growing sense that emphasis on a positive perception and illustration of aging. There is a lack of evidence on the diversity, frequency, range of terms and expressions and examples of anti-aging speaking, and also the other end, positive aging. In this perspective study, we raised questions to address the existing gap, with the hope to help future researchers in the use of negative/positive semantic words or negative/positive attitudes towards the older adults and examples of anti-aging/positive aging speaking in scientific texts. Raising such research questions might be useful in capturing the spirit of the field and some of its focus, and revealing how scientists talk about aging, or whether they use or are trying to combat ageist language.

Not only blonde hair

Women are affected from the so-called Gender Science Stereotype (GSS) according to which they are always considered as less competent than men in scientific fields for the only reason of being women, hence being obstacled and discriminated while pursuing that career. The scope of this study is to test whether some well-known stereotypes, such as the ‚dumb blonde‘ (i.e., blonde women are considered dumb or naïve), could explicitly effect the GSS and how they interact with each other. To investigate this, we manipulated pictures of a woman (Exp. 1) and a man (Exp. 2), by modifying (i) hair colour; (ii) hair length; (iii) glasses and (iv) make-up (Exp.1 ) or beard (Exp. 2), obtaining in this way 36 pictures for each experiment (3x3x2x2). Each picture was presented twice, once associated with a scientific text and once with a novel. Here we are presenting preliminary data, where participants (n = 45) were asked to evaluate, on a 10-points Likert scale, the authorship’s likelihood. Results show a negative effect of blonde hair (‘’dumb blonde’’) for both genders and heavy make-up for women, as well as a positive effect of glasses for both genders and of beard for men. Interestingly, although no gender-science stereotype has been found for women (Exp. 1), this emerged in Exp. 2. The interaction between scientific genre and make-up for women show that this stereotype is present when enhanced by other factors, such as the “highly” feminising effect of make-up. These results are discussed considering both perceptual and social theories.

From Evictions to Shame: Exploring Hysterectomy Through Metaphor

The present study analyzes metaphorical expressions related to hysterectomy in a diverse corpus comprising scientific texts, Reddit forums, and patient-authored articles and blogs. The research aims to understand how hysterectomy is discursively constructed and experienced by women. The corpus reveals a range of metaphors from clinical descriptions to personal and creative expressions. The analysis shows that metaphors not only reflect but also influence women's perceptions of their bodies and the procedure. The study identifies metaphors including the uterus as a 'tenant' or 'kidnapper,' and the procedure as an 'eviction' or a 'robbery', highlighting the emotional and psychological aspects of hysterectomy. Limitations include the corpus size, lack of metadata to establish more correlations, and its Western-centric perspective, suggesting the need for more inclusive research. The study contributes to the discourse on women's health, emphasizing the role of language in shaping medical experiences. It underscores the need for understanding metaphorical language to improve communication and support for women undergoing hysterectomy.

Types of Intratextual Glosses in the Charter of Military, Cannon and Other Matters Relating to Military Science

Purpose. The aim of the article is to describe intratextual glosses in the Charter of Military, Cannon and Other Matters Relating to Military Science, the reasons for and ways of introducing them into the text.Results. Three sources of gloss were identified: the author of Kriegsbuch L. Fronsperger, the translators (A. Radishevsky, M. Yuryev and I. Fomin) and the publishers of the text. The glosses in the German text were formed using the conjunctions oder (in the Russian translation it corresponds to the conjunctions syrech and ili), das ist (in the Russian syrech and to yest’) and mainly served to explain the borrowed vocabulary from the Latin, in isolated cases from the Italian and the Greek. The publishers' glosses are a few bracketed inclusions, inside which an explanation is given for some obsolete nominations or variants of words. Approximately 50 glosses entered by translators explain spatial measurements, chemicals and materials, names of persons by occupation or duties, military affairs. Syntactically, they are more often formed using the conjunctions syrech and to yest’, rarely the conjunction ili.Conclusion. Fronsperger’s rare glosses were oriented to the German reader of the second half of the 16th century, who was well acquainted with military and scientific terminology, numerous translators' glosses – to the Russian reader of the early 17th century, who was not familiar with European scientific texts of the New Age, publishers' glosses – to the reader of the second half of the 18th century, who no longer knew some Russian words of the 17th century.

Biomedical Engineering Literature: Advanced Reading Skills for Research and Practice

Medical engineering is a field of study that combines biological and medical sciences with engineering to develop improved healthcare technologies. It is imperative that you possess a deep understanding of both the material and the technical language used in this rapidly advancing field in order to effectively grasp key topics and navigate the rapidly expanding literature. This paper examines the future of the biomedical engineering profession through the lens of advanced reading strategies. It starts with the assertion that biomedical engineering literature presents three challenges: the level of density is technical, the area is interdisciplinary, and the growth of knowledge is exponential. In the view of the above challenges, the paper discusses various advanced reading skills in relation to biomedical engineers. These skills include the ability to critically read scientific texts, both at a fast pace for an overview and in detail for deeper understanding, to identify key ideas and methodologies relevant to the field, and to assess the validity of scientific claims and data representations. The paper also aims at pointing out how separate elements like the use of systematic reviews, of meta-analysis, of data visualization tools that complement reading, help the researcher in the process of managing gathered information from various sources. This paper describes teaching these skills for both academic and professional practice, with examples of how improved reading competencies can enhance research quality and contribute to innovations in medical technologies, tissue engineering, and clinical trials. Furthermore, the paper aims to discuss the future trends due to the increasing incorporation of continuous learning for addressing the challenges posed by novel technologies including artificial intelligence and nanotechnology that define the future of biomedical engineering. biomedical engineering students require the acquisition of higher order reading skills in preparation for information reading: national and international publications in the engineering profession, policy and technology in support of health care delivery systems, product development, and other purposes. The ideas stated and demonstrated in this paper should be practical to both beginning scholars and veteran professionals in the biomedical engineering field as well as useful for seminar and workshop participants in seminars and workshops on biomedical engineering literature.

Exploring the Challenges Faced by Translator Trainees in Translating Scientific and Technical Texts between Arabic and English: An Error Analysis Approach

Exploring the Challenges Faced by Translator Trainees in Translating Scientific and Technical Texts between Arabic and English: An Error Analysis Approach

Научно-академический дискурс в образовательном пространстве неязыкового вуза

The article deals with the phenomenon of scientific academic discourse. A nomenclature of discourse typological characteristics is analysed. The concept of scientific academic discourse is defined as a specialized type of institutional discourse. In our research we consider the scientific academic discourse as an integrative concept combining the features of scientific and academic types of discourse due to the interpenetration and intersection of their components. Cognitive and communicative aspects of scientific discourse are examined specific attributes of scientific texts such as harmony, consistency, objectivity and others are determined. The article focuses on the analysis of scientific discourse genre varieties. The authors describe the specifics of functioning of a research paper and a scientific report as main genres of scientific academic discourse, reveal their peculiarities in realizing English language oral and written discourse. From the theoretical and practical points of view both a research aper and a scientific report represent oral/ written communication aimed at scientific informing. The scientific polylexemic templates suggested in the article prove to be useful in academic writing.

Science in the Language of the Heart: Ukrainian Language and Literature in the New Ukrainiian School as a Driver of STEM Development

The article outlines the pathways for integrating STEM disciplines into the planning of Ukrainian language and literature lessons in secondary education institutions within the framework of the New Ukrainian School. It substantiates the growing need for interdisciplinary approaches that foster the development of core competencies while considering the advantages, potential risks, and limitations of the proposed methods. The emphasis is placed on the importance of combining humanities with natural and mathematical sciences to enhance students' understanding of a holistic worldview, illustrating the need to avoid focusing solely on one aspect of development (so-called «humanitarians» and «technocrats»). The article offers theoretical and practical recommendations for developing STEM projects that engage students in creative literary exploration through applying scientific principles and doctrines. The effective combination of STEM education principles with the field of philology enables the creation of a dynamic and effective educational environment where students perceive the interconnectedness of knowledge, develop a well-rounded intellect, and receive foundational preparation for higher education. Methods of linguistic analysis of scientific texts are discussed, demonstrating how language skills can be enhanced through scientific discourse. To illustrate the material, approximate schemes for planning integrated lessons with specific examples from both linguistic-literary and scientific perspectives are provided. To improve understanding and engagement of modern students, emphasis is placed on using digital tools and platforms that ensure integration, including online resources, interactive modeling, multimedia content and artificial intelligence. The necessity for alignment among educators of various disciplines is evident to ensure a fair assessment of proficiency in the state language and scientific literacy, which is a crucial issue during wartime when language matters become increasingly prominent, alongside scientific and mathematical literacy, for building an intellectually developed country.

Scientific publications and large language models: will neural network understand Russian science?

The impact of artificial intelligence technologies, neural networks, and chatbots on science and education has induced widespread discussion in the academic community. It is no longer possible to contain the use of neural networks such as ChatGPT for writing texts, including scientific texts. The present study is done in a qualitative approach. The aim of the study is to analyze the application of large language models on the example of ChatGPT in the scientific publishing activities of Russian scientists. The practice of using chatbots does not always satisfy the user and the scientific community as a whole. On the one hand, the user is confronted with the lack of the requested information. On the other hand, the scientific community, and especially editors and readers of scientific journals, question the feasibility of neural networks due to the shortcomings of large language models that have been widely disputed in scientific publications. This study shows that there is another reason to distrust neural networks. Incompleteness and opacity of the information produced by artificial intelligence is related to the texts on which neural networks are trained. For Russian science, this problem poses a serious threat, since popular artificial intelligence companies use mostly English-language texts to teach their neural nets. The author puts forward the opinion that the social and humanitarian knowledge produced in modern Russia remains outside the scope of texts used for training neural networks. This point of view is supported by research by Russian scientists on Arctic governance. The data is absent in the English-language texts of ChatGPT but reflected in Russian-language publications.

Unveiling Scholarly Insights: Quality Assurance in Open and Distance Education

Open and distance education (ODE) has continuously evolved, significantly influencing educational, daily, and professional spheres, thereby prompting interest in its sustainability and quality. This study explored global scientific perspectives on quality assurance in ODE using the science mapping method. Search terms centred on open education, distance education, and quality assurance; data was gathered from 4,224 scientific texts in the Web of Science Core Collection. Analyses were conducted using VOSviewer software. Co-authorship analyses explored scientific collaboration structures at the country level. Globally shared concepts of interest to the scientific community were addressed using co-occurrence analyses. A detailed examination of co-occurrence outputs led to classification related to general and emerging key concepts. Results depicted a widespread global interest in quality assurance in ODE, fostering connections based on new cultural similarities. The concept of quality assurance in ODE continues to be enriched and developed, gravitating towards focused learning and instruction, establishing strong ties with various components of regular education as well as human elements. However, the prevailing view of quality assurance has yet to encompass this diversity. Rather than consider the nature and current potential of ODE, it has maintained an externalized and technical perspective.

Gerakan Perubahan (Renaissence) Oleh Dinasti Umayyah II (Islam di Andalusia) Terhadap Berkembangnya Intelektual dan Kebudayaan di Eropa

The second period of the Umayyad dynasty, known as the Andalusian Umayyads, had a significant influence on the development of European civilization in the Middle Ages. After the fall of Damascus, this dynasty continued its rule in the Iberian Peninsula with its center in Cordoba. This article aims to analyze the influence of the Umayyad Dynasty II on Europe, especially in the fields of science, art, architecture and cross-cultural relations. The research method used in this article is a literature review, where literature study is a method that involves collecting, evaluating and synthesizing existing literature to answer research questions or understand a particular topic comprehensively. According to Danial and Warsiah, Literary Studies is research carried out by researchers by collecting a number of books and magazines related to research problems and objectives. The findings show that the Umayyad Dynasty in Andalusia not only contributed to the spread of Islamic knowledge, such as astronomy, medicine, and mathematics, but also became a catalyst for the development of science in Europe through intellectual transfer and translation of scientific texts. Apart from that, the architectural style promoted by the Umayyad II Dynasty played a role in the formation of European architectural styles, especially the Gothic and Romanesque styles. Through cultural interactions, the Umayyad II Dynasty introduced irrigation techniques, agriculture, and government systems that inspired European nations. The results of this study underline the importance of the influence of Islamic civilization in Andalusia in the development of European science and culture, which later became the foundation for the Renaissance.

Using drama to enrich a genre-based pedagogy for teaching academic writing across content areas

Drama has the potential to enrich and enliven established approaches to literacy learning, engaging students and expanding their possibilities for meaning-making. Drama-rich pedagogy is well-established as an effective tool in supporting language and literacy development. However, research to date has not explored the possibilities of using drama to enrich established genre-based approaches to teaching writing. This article reports on findings from an interventionist case study in an Australian primary school examining how a Year Three/Four teacher used drama-rich pedagogy to support students’ academic writing of a scientific explanation text. The findings indicate three key pedagogical benefits of employing drama to build conceptual understandings of the field of study and relevant academic language as part of a genre-based pedagogy for teaching writing. Firstly, drama experiences can make visible students’ prior knowledge of a topic, allowing teachers to identify, interrogate and transform students’ misconceptions through reflective dialogue on embodied experience. These embodied and interactive experiences also support the development of shared understandings of key concepts and language. Finally, drama experiences provide embodied and interactive contexts in which students can move from common sense to more abstract/technical understandings of the topic of study which they can apply in writing their own texts. In sharing these findings, this article aims to illustrate how drama can be used to develop the conceptual and linguistic understandings required by genre pedagogy in engaging, embodied ways that draw productively on the diverse resources that students bring to their learning.

Assessing Scientific Text Similarity: A Novel Approach Utilizing Non-Negative Matrix Factorization and Bidirectional Encoder Representations from Transformer

The patent serves as a vital component of scientific text, and over time, escalating competition has generated a substantial demand for patent analysis encompassing areas such as company strategy and legal services, necessitating fast, accurate, and easily applicable similarity estimators. At present, conducting natural language processing(NLP) on patent content, including titles, abstracts, etc., can serve as an effective method for estimating similarity. However, the traditional NLP approach has some disadvantages, such as the requirement for a huge amount of labeled data and poor explanation of deep-learning-based model internals, exacerbated by the high compression of patent content. On the other hand, most knowledge-based deep learning models require a vast amount of additional analysis results as training variables in similarity estimation, which are limited due to human participation in the analysis part. Thus, in this research, addressing these challenges, we introduce a novel estimator to enhance the transparency of similarity estimation. This approach integrates a patent’s content with international patent classification (IPC), leveraging bidirectional encoder representations from transformers (BERT), and non-negative matrix factorization (NMF). By integrating these techniques, we aim to improve knowledge discovery transparency in NLP across various IPC dimensions and incorporate more background knowledge into context similarity estimation. The experimental results demonstrate that our model is reliable, explainable, highly accurate, and practically usable.