Scientific Terms Research Articles

Geomatics: Technology and Applications - A Training Programme for Women Scientists

Abstract. Geomatics, also known as geospatial technology and geomatics engineering, analyzes spatially referenced geographical information. Geomatics is a scientific term. It consists of tools and techniques. Technology is advancing, and modern Geomatics has the utility of maps by analyzing it with many coverages, each with interrelated themes combined to give meaningful answers for decision-makers. A multidisciplinary approach is essential to analyze spatial and nonspatial parameters together for decision-making at the local and global levels. Spatial information represented in the form of thematic maps about the respective attribute data, the system called, Geographical Information System (GIS), has been more popular during the last decades in government and private sectors. The decision support system can take input of data from these sources and analyze multiple parameters together to plan and manage available resources. This training program was intended for women scientists, researchers, academia, and professionals who were engaged and using spatial information, and who wanted to add and upgrade their skills. It was anticipated that a proportion of the trainee participants would come from research and academia. This training program helped participants generate interest in the use of GIS technology in their respective research and professional domains. This paper elaborately describes the process, and structure of the short-term capacity-building training program, and its usefulness for young scientists and professionals, specifically a target group is ‘women in science’ who have not been able to remain in the continue its use and are interested in building a career in geospatial technology field.

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.

Historian Ilya Evgenyevich Zelenin as shown through his scientific library

The article analyses the scientific biography of Ilya Evgenyevich Zelenin – an outstanding agrarian historian, Doctor of Historical Sciences, Professor, leading researcher of the Institute of Russian History of the Russian Academy of Sciences. The main source used are copies of books presented to Zelenin, devoted to the agrarian and political history of Russia in the twentieth century. On their basis, a conclusion is made about the key elements of the historian's research credo, namely: painstakingness in working out the historiography of the issue, a wide archival search, accuracy of scientific terminology and understanding of the formality of ideological stamps. There are two stages in the author's scientific work, connected with the study of the history of state farm construction in the USSR and the history of agrarian policy of I. V. Stalin and N. S. Khrushchev, in each of which the historian achieved serious successes.

Generating Biomedical Hypothesis With Spatiotemporal Transformers.

Generating biomedical hypotheses is a difficult task as it requires uncovering the implicit associations between massive scientific terms from a large body of published literature. A recent line of Hypothesis Generation (HG) approaches - temporal graph-based approaches - have shown great success in modeling temporal evolution of term-pair relationships. However, these approaches model the temporal evolution of each term or term-pair with Recurrent Neural Network (RNN) independently, which neglects the rich covariation among all terms or term-pairs while ignoring direct dependencies between any two timesteps in a temporal sequence. To address this problem, we propose a Spatiotemporal Transformer-based Hypothesis Generation (STHG) method to interleave spatial covariation and temporal progression in a unified framework for constructing direct connections between any two term-pairs while modeling the temporal relevance between any two timesteps. Experiments on three biomedical relationship datasets show that STHG outperforms the state-of-the-art methods.

TRACING THE LINGUISTIC JOURNEY OF GEOLOGICAL TERMS - A PHILOLOGICAL STUDY OF STRATIGRAPHY AND MINERALOGY

The paper discusses the etymological history of "stratigraphy" and "mineralogy," two critical geological terms, from their ancient roots in Latin and Greek to modern times. In fact, such scientific terms represent not only the steps of scientific advancement but also the general trend of cultural interaction and close interrelation between linguistic, scientific, and technical developments. It thereby indicates how scientific progress and cross-cultural interactions have influenced the way one describes Earth's processes when these terms are put through philological development from medieval to Renaissance and modern times. Indeed, this is a technologically advanced science that has introduced terminologies such as radiometric dating and X-ray diffraction into geology, while recent times have seen many countries collaborating together on geological grounds with consequent efforts toward standardization in the use of geological terminology. The result is an instructive analysis of how language and science grow together, predictably changing as needed to accommodate an increasing knowledge base.

Scientific terms as a part of comparative tropes of modern Russian prose

Modern Russian prose is characterized by the active use of scientific terms from different fields of knowledge, which act as images of comparison for comparative tropes. Such tropes are marked by stylistic emphasis, as they contain new information for the addressee. Comparative tropes are defined as metaphors and similes of various structural types. The purpose of our work is to analyze the use of scientific terms as images of comparison for comparative constructions and determine their functions in the texts of modern Russian prose. The material for the study is the works of E. Vodolazkin, A. Ivanov, A. Ilichevsky, A. Matveeva, V. Pelevin, D. Rubina, A. Salnikova, O. Slavnikova, M. Stepnova, O. Vasyakina and others. The article discusses terms in tropes representing different fields of science: physics, chemistry, mathematics, medicine, biology, physiology, linguistics, literary criticism, art history, and computer science. The most active in the comparative tropes of modern prose are biological, medical, physical and computer terms. The productivity of these terms is associated with the rapid development of these areas of knowledge and their role in modern society. Regarding parts of speech, most of them are substantives. By metaphorizing, terms are subject to determinologization. In prose texts, terms often have distributors that clarify, specify or modify the image of comparison. In modern prose, scientific terms as part of tropes perform a number of functions: the function of figurative characteristics of a person, object or phenomenon, the evaluative function, the text-forming and conceptualizing functions. Scientific terms as part of metaphors and similes replenish and update the literature language.

A Review to Illustrate the Concept of Krimi in Ayurveda

Background: Knowledge of Krimi and its description in Vedas and Ayurvedic Samhitas is very unique and different from the concept of worm in modern medical science. Krimi is a broad terminology in ancient Indian science which encompasses various types of helminths, microorganisms such as bacteria, viruses, fungi, and protozoa causing a large variety of diseases. Materials and Methods: A narrative review was conducted and result was presented under the result. Result and Discussion: Krimi Roga is one among the various diseases which must be paid prime attention in terms of Ayurveda management. Drugs and formulations from herbal sources play key role in management of these helminthic and parasitic infections. A majority of patients being from pediatric age segment, the knowledge of Krimi Roga management may bring a boon to pediatric ailments. Conclusion: Ayurveda believes in Prakriti (specific body constitution of the individual), if we can change the internal environment of the intestine (Kostha) through Apkarshana, Prakriti Vighata and Nidana parivarjana using appropriate drugs as well as enhancing the strength of Agni; then, affinity towards production and multiplication of Krimi may be arrested and hence, the ailments can be treated. Krimi is a condition, affecting all age groups, but children have always been at risk due to their playful activities and lack of maintenance of adequate personal hygiene. Once infected, the entire family may eventually get affected from the infected children.[1] If we consider Drishya Krimi as worm infestation, In India, more than 200 million children are infected on an average with roundworm, hookworm, etc. In Ayurveda, several causes (nidanas) have been mentioned for development of Krimi (microbes/worms) in human body like Ajirna (indigestion in GIT), Adhyashana (eating even when the previous meal has not been digested), Asatmyaahara, Virudhasana, Malinasana (incompatible foods or unhygienic meal habit), Avyayam (sedentary lifestyle), Diwaswapna (sleeping during the daytime), Guru (heavy), Atisnigdha (excessively fatty diet), Atisheet Ahara-Vihara (cold

Science, Fiction, and Contemporary Media: Blurred Borders in Knowledge Dissemination in Michael Crichton’s The Andromeda Strain

This study examines the technical methods used by Michael Crichton to blur the lines between factual information and fictional elements in his novel The Andromeda Strain. The creative use of scientific terminology and artistic documentation that supports a sense of reality plays a role in creating a certain blurring that works to enhance the blurring of the boundaries between reality and imagination. The study aims to explore the novel within the framework of postmodern literary theory, questioning the concept of absolute truth, and emphasizing the role of language and literary discourse in constructing reality. Through a critical analysis of the novel, this study seeks to clarify the methods followed by Crichton to employ language and discourse to create an atmosphere of authenticity that contributes greatly to blurring the line between reality and imagination. In addition, the study comprehensively analyses modern media platform technologies that are used to erode the boundaries between objective reality and fictional narratives, and their consequent effects on the dissemination of information. The study concluded that Crichton's novel The Andromeda Strain embodies the successful integration of scientific concepts with fantasy elements, which resulted in a captivating and intellectually stimulating narrative.

Conoce Tus Opciones: The Challenges of Communicating Rip Current Information in Spanish

Abstract Rip currents are poorly understood by the public and thus a leading cause of weather-related fatalities in the United States. Individuals who speak languages other than English, such as Spanish-speaking communities, have been historically underserved by communication efforts for natural hazards and thus are at additional risk from rip currents. In response, the National Weather Service (NWS) has developed rip current outreach tools translated into Spanish in recent years, though their efficacy has not been systematically tested. We therefore surveyed members of the Spanish-speaking community in the New York City area to gain insights into how the NWS two-page rip current informational brochure is working and possible improvements to be made. The English version of the brochure was also tested, and the results from the two languages were compared. Quantitative survey results indicate that while both brochures are generally effective, several changes could be made to improve clarity, especially for Spanish speakers, who found more issues with the Spanish version. For example, the translation of the term rip current itself used by the NWS, “corrientes de resaca,” was determined to be confusing by some Spanish speakers, as were other pieces of text with complex scientific terms. Moreover, certain graphics contained in the brochure were difficult to understand for users in both languages. The results of this work can be used by the NWS and other agencies to improve their Spanish risk communication tools and can also be used as a guide when translating scientific information into other languages. Significance Statement Rip currents, narrow channels of fast-moving water that can pull swimmers away from the shore, are among the leading weather-related killers in the United States yet are poorly understood by the public. Recent efforts to reduce society’s vulnerability to rip currents include the translation of outreach materials from English to Spanish. This study evaluated a new National Weather Service Spanish rip current informational brochure and compared it to the English version. The results show that while both the English and Spanish brochures were generally effective at communicating risk, the Spanish version had more issues, primarily surrounding the translation of scientific terms and phrases. Findings from this research can help guide scientists in designing improved non-English severe weather outreach products.

Identifying Semantic Shift Reasons of Domain Entities Using Diachronic Embedding

ABSTRACTIn academic literature, the semantic evolution of scientific terms reflects the development of domain knowledge. While there have been studies using diachronic word embeddings to reveal cultural and social shifts, research on the semantic evolution of scientific terms remains limited. This paper proposes a method utilizing diachronic semantic vectors to elucidate the semantic evolution of scientific entities. Firstly, diachronic semantic vectors of entities are trained using incremental learning to compute the semantic shift (ΔA) of a given entity A between periods t1 and t2. Secondly, entities similar to ΔA in periods t1 and t2 are defined as leading reasons and accompanying reasons, respectively. The experiment result shows that the leading reasons can capture the shifts of entities in the nascent stage, and the accompanying reasons can capture the shifts of words in the mature stage. The proposed method offers a better quantitative insight into the details and reasons behind domain knowledge evolution.

QURANIC VERSES RELATED TO HALAL SCIENCE: A STUDY APPLYING THE TAFSIR AL-MAWDUIYMETHOD

To achieve success in the science and technology of halal, numerous kinds of stakeholders, including academics, industry players, and governmental entities, are making a major contribution. Simultaneously, there exists an interest in the discipline of philosophy that includes the discourse on epistemology, ontology, and axiology. This aims to inhibit the publics comprehension of halal science, which is fundamentally factual and scientific. As a result, the fundamental framework for comprehending halal science is through the study of the Quran. This paper analyzes the concept of halal science as presented in the Quran. This literature study employs a systematic approach of Tafsir al-Mawduiyto delineate and then examine the terminology of halal science in the Quran. The study identified three principal topics of halal science terminology in the Quran: first, the truth of the natural worlds creation second, revelation as the foundation of knowledge and third, human ethics and values. These three themes are the philosophy of Islamic science that are the basic paradigm in facing the theoretical issues of the halal science industry.

Artificial neural networks in economics: mathematical tool, model or methodology?

The purpose of this article is to assess the current interaction between artificial intelligence (AI) and economic science and to identify promising interdisciplinary areas of research that can significantly influence the methodology of understanding economic phenomena. To achieve this goal, the vague and partly even mystical term AI was replaced with а more scientific term «artificial neural networks» (ANN). The article uses methods of scientometric, epistemological and comparative analysis of the processes of ANN penetration into economics and other academic disciplines. The authors reveal the epistemological commonality and difference between AI and ANN and justify the shift in epistemological focus in research from general AI to ANN. The paper systematizes the use of ANN in economics: 1) ANN as a mathematical tool for solving economic problems; 2) ANN as a model of economic phenomena; 3) ANN as a methodology for understanding economic patterns. It shows the interaction of economics with neurosciences which occurs in two significantly different directions: from neurobiology, i.e. real nerve networks in living organisms, and, on the other hand, from ANN theory. The first direction is associated with neuroeconomics, the second has not yet been articulated, but shows an exponential growth in publications and is associated primarily with forming a new economic paradigm. The ANN paradigm in economics (and not only in economics) changes both the subject of cognition, introducing radically new forms/types of evidence and new research methods, and the object of cognition, changing the focus of study from individual economic behavior to the collective economic behavior of mega-subjects.

A Study on Translation Methods of Scientific and Technical Terms from the Perspective of Transknowletology—Take the English Rendition of “T’ien-kung K’ai-wu” Translated by E-tu Zen Sun as an Example

T'ien-kung K'ai-wu recognized as the first technological classic includes both agriculture and handicraft production. From the standpoint of transknowletology, this study examines how ancient science and technology terminology was translated in E-tu Zen Sun's English rendition of "T'ien-kung K'ai-wu." In accordance with the criticism tools and three criticism criteria for translation that were put forth by Professor Meng Xiangchun and Professor Yang Feng, the research findings elucidate the following characteristics of ancient science and technology terminology in "T’ien-kung K’ai-wu". Adhered to the principle of real meanings, the translator sought the genuine meaning within the " area of knowledge identity" and the " greatest common divisor" of knowledge. Under the premise of full preparations, the translator employed in-text interpretation and out-text explanation to facilitate communication and address the "scissors differential of knowledge" within the "area of knowledge discrepancy". Furthermore, under the principle of target text aesthetic conceptions, the translator could pay attention to the audience′s aesthetics and " area of knowledge conflict" , thereby fostering the " knowledge glocalization" come into being through free translation. The research findings hold significant value for the characteristics and techniques of translating scientific and technical terms in "T'ien-kung K'ai-wu" into English.

Диагностика сформированности смыслового чтения при работе учеников средней школы с учебными математическими текстами

Learning is working with a variety of educational texts based on reading, understanding, evaluating and interpreting information. To identify the result of reading an educational mathematical text and the quality of understanding the meaning of the text space created by educational materials, it is necessary to diagnose reading, namely, the level of semantic reading. In the modern study of reading, the PISA international monitoring, the concept of reading literacy, its components and levels are defined. The success of understanding more complex educational mathematical texts will depend on the level of reader literacy. If the levels of reading literacy have evaluation criteria and diagnostic apparatus, then how to assess the level of semantic reading? The article examines the relationship between the levels of reading literacy and text comprehension, models for assessing the semantic complexity of the text and semantic reading skills, various level structures for diagnosing the understanding of a mathematical educational text. Based on the studied scientific material, the complexity of the educational mathematical text "Triangle" was assessed according to criteria such as the number of words, simple words, scientific terms and their complexity, the number of mentions of scientific terms in each paragraph. Diagnostic material has also been created to check the understanding of this text, each task of which is aimed at determining the understanding of each information block and assessing the degree of development of semantic reading.

Незашоренные размышления в связи с внесением 22 мая 2024 г. в Государственную Думу проекта федерального конституционного закона «О Конституционном Собрании»

The proposed article discusses various scientific and legal, as well as practical and political aspects of the problem of legislative regulation of the convening of the Constitutional Assembly as the last constitutional body prescribed in the Constitution, but not yet activated, which has exclusive powers to decide on the issue of preserving the invariability of the current Constitution, drafting a new Constitution and its adoption or its submission to a national vote. The paper considers the significance and status of this institution, offers a historical excursion — previous attempts to adopt the law, substantiates the strategic nature of the Constitutional Assembly, the problem of election of its members and the popular vote on the draft of the new Constitution, analyses the correlation between the Constitutional Assembly and the State Duma, makes a proposal on how to update the Constitution of 1993, makes specific comments on the draft law submitted to the State Duma on 22 May 2024, raises the question of the possibility of an integrated approach to the drafting of the new Constitution. The article is oriented towards continuing the discussion on this issue in scientific and practical terms.

Constructing a Large Language Model to Generate Impressions from Findings in Radiology Reports.

Background The specialization and complexity of radiology makes the automatic generation of radiologic impressions (ie, a diagnosis with differential diagnosis and management recommendations) challenging. Purpose To develop a large language model (LLM) that generates impressions based on imaging findings and to evaluate its performance in professional and linguistic dimensions. Materials and Methods Six radiologists recorded imaging examination findings from August 2 to 31, 2023, at Shanghai General Hospital and used the developed LLM before routinely writing report impressions for multiple radiologic modalities (CT, MRI, radiography, mammography) and anatomic sites (cranium and face, neck, chest, upper abdomen, lower abdomen, vessels, bone and joint, spine, breast), making necessary corrections and completing the radiologic impression. A subset was defined to investigate cases where the LLM-generated impressions differed from the final radiologist impressions by excluding identical and highly similar cases. An expert panel scored the LLM-generated impressions on a five-point Likert scale (5 = strongly agree) based on scientific terminology, coherence, specific diagnosis, differential diagnosis, management recommendations, correctness, comprehensiveness, harmlessness, and lack of bias. Results In this retrospective study, an LLM was pretrained using 20 GB of medical and general-purpose text data. The fine-tuning data set comprised 1.5 GB of data, including 800 radiology reports with paired instructions (describing the output task in natural language) and outputs. Test set 2 included data from 3988 patients (median age, 56 years [IQR, 40-68 years]; 2159 male). The median recall, precision, and F1 score of LLM-generated impressions were 0.775 (IQR, 0.56-1), 0.84 (IQR, 0.611-1), and 0.772 (IQR, 0.578-0.957), respectively, using the final impressions as the reference standard. In a subset of 1014 patients (median age, 57 years [IQR, 42-69 years]; 528 male), the overall median expert panel score for LLM-generated impressions was 5 (IQR, 5-5), ranging from 4 (IQR, 3-5) to 5 (IQR, 5-5). Conclusion The developed LLM generated radiologic impressions that were professionally and linguistically appropriate for a full spectrum of radiology examinations. © RSNA, 2024 Supplemental material is available for this article.

Reflection of Explicitation in Scientific Translation: Neural Machine Translation vs. Human Post-Editing

The present paper reports on the findings of an empirical comparative study on the extent to which explicitation is employed in the translation of a scientific text as conducted by Google Neural Machine Translation (GNMT) vs its post-edited (PE) version. A recent report released in English by the World Meteorological Organization in September 2023 was selected as the source text for the present study. The purpose of the study is to reveal how domain-specific acronyms and technical terms are lexically expanded (explicitated) in a GNMT output compared to its post-edited (PE) version as performed by a team of professional translators at a translation service provider in Amman-Jordan. Explicitation in translation can be obligatory or optional. The type of explicitation investigated in the present study is optional, pragmatic explicitation. The results show that GNMT has its limitations in dealing with scientific terms and acronyms in translating scientific texts from English into Arabic. In contrast, human post-editing explicitated domain-specific terms and acronyms producing a text with a higher level of readability and naturalness for domain expert readers and non-expert readers.

Automatically Generated Texts for Fauna and Flora from Structured Data Based on a Controlled Vocabulary

Information systems like Xper3 and Fulgoromorpha Lists On the Web (FLOW) play a crucial role in managing and using biological data. These platforms store extensive collections of normalized data and structured taxonomic descriptions. By using controlled terminologies, they standardize the vocabulary, significantly enhancing the processes of identification, description, and comparison of various taxa. The massive assemblages of data hosted in these repositories could be reused to generate texts in natural languages automatically. The most immediate goal is to produce, from these information systems, more accessible and user-friendly displays in the form of taxon summary pages. This automated production of textual outputs is a great addition that can be continuously updated as the databases evolve. Can structured data be reused to provide better species pages and to ensure updating if the data evolves? Will AI assist in this process, or will specific computing be needed? To address these questions, multiple possible approaches have been identified. The most basic level of this process involves converting a single line from a taxon-by-character matrix into text that resembles natural language, similar to the descriptions found in botanical or zoological guides. The primary goal is to move beyond the rigid format of matrix lines or lists of characteristics (such as characters and states) of a species, and instead generate a coherent, easy-to-read paragraph intended for human eyes. To achieve this objective, a first solution is given by Descrxp, a tool currently developed in conjunction with Xper. The user specifies the desired key outline for the output, and Descrxp fills this canvas using the database contents. While this approach is highly reliable and adaptable to various contexts, its drawback is being labor-intensive, and requiring significant human input and oversight (Fig. 1). The second solution uses AI. Data on well-known taxa, and on more obscure taxa have been tested with ChatGPT 3.5 or 4.0. ChatGPT succeeds well at generating natural language descriptions for well-known taxa (Fig. 2), providing text that appears accurate and coherent due to the extensive information available online for these groups. However, when it comes to more obscure taxa, less represented on the internet, the results can be more inconsistent and unpredictable (Fig. 3). This variability can be explained by the quality of the data the model has been trained on, which is significantly richer for well-known species. Consequently, for lesser-known groups, the generated descriptions may lack the precision and reliability seen with more familiar taxa. However, if more careful attention is given to the output of chatGPT (Fig. 4), it is possible to notice that the AI filled part of the description with inaccurate characters. Due to its inability to recognize specific scientific terminology, and to process hierarchical information, chatGPT ends up producing an over-generalized and redundant description. To go further, it would be possible to use a comparison between taxa to produce a text that highlights the remarkable features of a taxon. Moreover, it could be interesting to try and synthesize several lines of the initial matrix to extract generalized descriptions of groups of taxa, such as the description of a genus based on its included species. Using data from FLOW, Fishbase, and Xper3, the French ACDC (Counterfactual Learning for Controlled Data-to-text) project is creating a variety of text outputs. These range from "fill-in-the-blank" canvas to fully AI-generated content, utilizing data matrices derived from these pilot databases.

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia.

Neurodegenerative pathologies such as Alzheimer's disease, Parkinson's disease, Huntington's disease, Amyotrophic lateral sclerosis, Multiple sclerosis, HIV-associated neurocognitive disorder, and others significantly affect individuals, their families, caregivers, and healthcare systems. While there are no cures yet, researchers worldwide are actively working on the development of novel treatments that have the potential to slow disease progression, alleviate symptoms, and ultimately improve the overall health of patients. Huge volumes of new scientific information necessitate new analytical approaches for meaningful hypothesis generation. To enable the automatic analysis of biomedical data we introduced AGATHA, an effective AI-based literature mining tool that can navigate massive scientific literature databases, such as PubMed. The overarching goal of this effort is to adapt AGATHA for drug repurposing by revealing hidden connections between FDA-approved medications and a health condition of interest. Our tool converts the abstracts of peer-reviewed papers from PubMed into multidimensional space where each gene and health condition are represented by specific metrics. We implemented advanced statistical analysis to reveal distinct clusters of scientific terms within the virtual space created using AGATHA-calculated parameters for selected health conditions and genes. Partial Least Squares Discriminant Analysis was employed for categorizing and predicting samples (122 diseases and 20889 genes) fitted to specific classes. Advanced statistics were employed to build a discrimination model and extract lists of genes specific to each disease class. Here we focus on drugs that can be repurposed for dementia treatment as an outcome of neurodegenerative diseases. Therefore, we determined dementia-associated genes statistically highly ranked in other disease classes. Additionally, we report a mechanism for detecting genes common to multiple health conditions. These sets of genes were classified based on their presence in biological pathways, aiding in selecting candidates and biological processes that are exploitable with drug repurposing.

NOUN MODIFIER STATISTICS

The article examines the statistics of 8 works by Ch. Aitmatov, written in the Kyrgyz language. These statistics are compared with statistics obtained from the epic Manas. In our case, the comparison was made using noun modifiers. In our opinion, the statistical data given below will be a certain extent contribute to the computerization of the Kyrgyz language. We believe that these data will be more accurate if supplemented with data obtained from official documents, journalism and scientific terms. Additionally, we note that, in our opinion, there is no need to model the building blocks. This is because the usages formed using the building blocks can live separately. The main problem is to find and model the algorithm that will change until it is built.