bluuebunny/crossref_metadata_2025 huggingface dataset:
Would Longer Sentences Lead to More Faithful Translation? Effects of Linguistic Features on Metafunctional Translation Equivalence in Chinese Classics
Authors: Yang Qingxin , Ma Jianjun , Feng Lei , Liu Xin
Published: February 2025

Systemic functional linguistics offers translation studies with a metafunctional view, but research on metafunctional translation equivalence remains limited. This study quantifies translation equivalence through a metafunctional framework, focusing on the impact of linguistic features on the translation of Chinese classics. Using the metafunctional equivalent-shift cline as a tool for measurement, this study examines how sentence length, antithesis, and subject ellipsis impact translation equivalence, based on the Bairenbaiyi corpus. The results reveal that translations generally maintain equivalence across the three metafunctions—ideational, interpersonal, and textual—with interpersonal function exhibiting the highest degree of equivalence. Longer sentences correlate with stronger equivalence, while antithesis and subject ellipsis negatively affect equivalence. These findings underscore the critical role of linguistic features of the source text for achieving translation equivalence, supporting Matthiessen's assertion that translation involves decision-making that requires compromises across the metafunctional spectrum.
Challenges in Teaching Medical English Vocabulary to Tertiary Students in China: A Systematic Literature Review
Authors: Cui Hongmei , Kaur Naginder
Published: February 2025

This study aims to provide a comprehensive review of the research perspective on current medical English vocabulary teaching over the last fifteen years (from 2009 to 2023). The objective is to offer references and measures for instructors, researchers, and higher educational institutions to improve medical English vocabulary teaching. To achieve this, a systematic literature review (SLR) methodology was employed, resulting in the selection and meticulous examination of 168 articles. As identified in this review, studies conducted on medical English vocabulary have mainly been non-empirical, focusing on describing terminologies and teaching strategies and taking undergraduates as the primary research participants. The most popular effective teaching strategies identified through the review encompasses word structure, mind mapping, etymology, and multimedia. It is noteworthy that there has been a significant sharp upward research trend from 2018 to 2023. Several factors influencing medical English vocabulary teaching have been illuminated, namely, non-diverse teaching strategies/methods, inadequate course/curriculum, shortage of professional teachers, and limited needs analysis. Despite numerous studies that have focused on medical English vocabulary teaching, few were recorded in the review of it. This study presents a holistic and in-depth review on medical English vocabulary teaching in the past fifteen years, which will provide educators and higher educational institutions with comprehensive understanding of the existing research landscape and contribute valuable references to ongoing and future scholarly pursuits within this field.
The Economic Shock in Arab and African American Female Fiction: A Socio-Economic Reading of the Mother-Daughter Relationship
Authors: Al-Rifaee Jumana , Mukattash Eman
Published: February 2025

The study explores the economic difficulties encountered by Arab American and African American mothers, as well as the adverse conditions they endure due to their economic and social circumstances, which are manifested in four selected novels. This study seeks to clarify the reasons behind these difficulties and their impacts on family relations, particularly between mothers and daughters. The introduction of new economic regulations, unfamiliar to the mothers, constitutes a significant shock, profoundly affecting their understanding of their daughters' attitudes and choices. This shift in perception often results in conflicts that strain and, in some cases, sever the bonds between mothers and daughters, as well as between daughters and their broader family networks. To achieve the research purpose, the study uses Mark Fisher's concept of "capitalist realism" to analyze Suzan Darraj's The Inheritance of Exile (2007), Randa Jarrar's A Map of Home (2008), Toni Morrison's A Mercy (2008), and Alice Walker's Possessing the Secret of Joy (1992). The concept elucidates how the new economic regulations, which mothers have not previously encountered in their homelands, impact their exploitation by landlords and the patriarchal system. In conclusion, the study reveals that harsh economic conditions break connections between African American mothers and their daughters, while changes in economic institutions lead to misunderstandings between Arab American mothers and their daughters, resulting in family crises that negatively affect and lead to the breakdown of the mother-daughter relationship.
Measuring the Impact of Meta-AI on English Reading Comprehension Score Enhancement: A Study Within Social Media Application
Authors: Allehyani Badr , Almashy Abduh , Jamshed Mohammad , Banu Sameena
Published: February 2025

The integration of AI with social media platforms is significantly influencing English language skills, reshaping how users engage with and learn the language. So far, no studies have specifically examined how AI affects English reading for first-year non-English major undergraduates in Saudi Arabia. This study investigates how Meta-AI combined with WhatsApp enhances reading comprehension. Two intact classes were randomly chosen and assigned to experimental (N=43) and control (N=49) groups in a quasi-experimental study. The experimental group received instruction through AI-enhanced social media, namely WhatsApp, while the control group continued with a conventional approach. Data were collected before and after treatment. Statistical analysis revealed that the experimental group enhanced reading comprehension significantly more than the control group, which received conventional teaching. The study implies that integrating AI with social media platforms like WhatsApp can improve substantially English reading comprehension, suggesting a beneficial shift towards technology-driven learning methods in education.
Using sewage sludge ash as a replacement for cement in mortar applications
Authors:   Laboratory of Exploitation and Valorization of Natural Resources in Arid Zones, Kasdi Merbah University Ouargla, Faculty of Applied Sciences, Route de Ghardaia BP.511, 30 000 Ouargla, Algeria, Meraghni Ahmed Amine , Khellou Abderrezak ,   Laboratory of Exploitation and Valorization of Natural Resources in Arid Zones, Kasdi Merbah University Ouargla, Faculty of Applied Sciences, Route de Ghardaia BP.511, 30 000 Ouargla, Algeria, Abani Saïd ,   Laboratory of Exploitation and Valorization of Natural Resources in Arid Zones, Kasdi Merbah University Ouargla, Faculty of Applied Sciences, Route de Ghardaia BP.511, 30 000 Ouargla, Algeria
Published: February 2025

In the quest for sustainable construction practices, integrating waste materials into the construction sector has gained significant attention. Sewage sludge ash (SSA) is a very attractive resource since it is readily available in large quantities and has the potential to provide significant environmental advantages. The present study, this study investigates the feasibility of utilizing supplementary cementitious materials (such as SSA) as a portion alternative to cement in mortar, aiming to reduce the environmental burden of sewage waste and enhance mortar properties. Experiments incorporated integrated SSA at 0% (control), 15%, 25%, 50%, and 75% of cement's weight. Characteristics of mortar were evaluated at 7, 28, 60, and 90 days, evaluating mechanical characteristics such as flexural and compressive strengths, as well as physical attributes including water absorption, dry bulk density, and apparent porosity. The findings revealed that SSA inclusion significantly influenced the physical and mechanical characteristics of the mortar. 28-day compressive strength of the mortar sample reached 31 MPa when 25% of the cement was substituted with SSA. In comparison, the control sample exhibited a compressive strength of 42.25 MPa, indicating that up to 25% substitution is feasible and meets standard norms. SSA inclusion decreased dry bulk densities, increased water absorption, and improved porosity. Thus, this study demonstrates the performance of using SSA as an environmentally friendly substance and economical cement alternative in sustainable construction materials.
Variable tube geometry micro channel heat exchanger (MCHX) using analytical and CFD analysis
Authors:   Dept. of Mechanical Eng., B.S. Abdur Rahman Crescent Institute of Science and Technology, India, A Ram , Kumar P D Jeya ,   Dept. of Mechanical Eng., B.S. Abdur Rahman Crescent Institute of Science and Technology, India, Doss Prince Arockia ,   Dept. of Mechanical Eng., B.S. Abdur Rahman Crescent Institute of Science and Technology, India
Published: February 2025

The aim of this study is to improve condenser performance by incorporating unique tubes and shapes that control the volume of refrigerant. Analytical calculations were performed to determine hydraulic diameters for various tubes and port shapes. The heat and pressure drop across the condenser were estimated using the calculated hydraulic diameters. The refrigerant pressure drop correlation was chosen based on its advantages, and the findings were compared to experimental data (component calorimeter results). For the first time, two-phase density was calculated analytically, and its impact on heat transfer was investigated. The analytical results were compared to CFD simulation and experimental data. The findings demonstrated that an analytical method may be employed in the early stages of design during the development of automotive cooling units and that it could then be correlated with experimental data. This will eliminate the cost of developing prototype parts and shorten the lead time to market.
Influence of hydroxyethyl cellulose on the stability of foamed concrete
Authors:   School of Architecture and Environmental Engineering, Silicon Lake College, Jiangsu, China, Sun Shuping , Liu Ronggui ,   School of Civil Engineering and Mechanics, Jiangsu University, Jiangsu, China, Chen Hongmei ,   Nantong Polytechnic Institute, Jiangsu, China, Sun Shu ,   Taizhou Vocational and Technical College, Jiangsu, China
Published: February 2025

As a lightweight material, foamed concrete has been widely used in construction because of its excellent lightweight properties, heat preservation and sound absorption. However, due to its low strength, its further application is limited. Hydroxyethyl cellulose (HEC) was employed in this study to modify the sodium dodecyl sulfate (SDS) based foaming agent to enhance the stability and performance of foamed concrete. The effects of HEC content on foam stability, bleeding, fluidity, strength, water absorption and internal pore structure were systematically investigated. The results indicate that as the HEC content increases, the foam stability improves, while the fluidity and water absorption of the foamed concrete slurry decrease. Compared with the control group (without HEC), the content of 0.15% HEC increased the 28-day compressive strength by 33.66%, reaching 2.75 MPa. Furthermore, HEC optimized the pore structure, significantly reducing the average pore diameter. When the HEC content reached 2%, the proportion of small pores was approximately 99%. These findings suggest that HEC effectively improves the overall performance of foamed concrete, offering a theoretical foundation for its broader application in engineering.
Enhancing concrete mechanical properties using nano-silica, calcined clay, and glass fibers optimized by response surface methodology
Authors:   Department of Civil Engineering, Chandigarh University, Mohali, India, Attari Ashish , Lallotra Balwinder ,   Department of Civil Engineering, Chandigarh University, Mohali, India
Published: February 2025

This study investigates the combined effects of nano-silica, calcined clay, and glass fibers on the mechanical properties of normal-grade concrete (M30), with a primary aim to utilize industrial waste materials and improve concrete performance while promoting environmental sustainability. Response Surface Methodology (RSM) was employed to optimize material proportions and evaluate their impact. The experimental design incorporated nano-silica (0– 10%), calcined clay (0–30%), and glass fibers (0–2%), corresponded to the minimum and maximum values in the range. A total of 120 specimens were tested to assess compressive strength, flexural strength, rebound hammer values, and ultrasonic pulse velocity (UPV). The optimized mix predicted compressive strength of 49.41 MPa, flexural strength of 9.05 MPa, rebound hammer value of 62 MPa, and UPV of 5445 m/s. Validation tests demonstrated observed compressive strength of 46.55 MPa, flexural strength of 8.05 MPa, rebound hammer value of 60 MPa, and UPV of 4890 m/s, with errors of 5.79%, 11.00%, 3.22%, and 10.19%, respectively. Analysis of variance (ANOVA), a statistical method for determining the significance of factors on observed outcomes, indicated that nano-silica had the most substantial impact on all performance metrics. The models showed high reliability, with R² values of 0.9653 for compressive strength, 0.9268 for flexural strength, 0.9266 for rebound hammer, and 0.8894 for UPV. The study demonstrates the potential of incorporating waste materials like calcined clay and nano-silica into concrete to enhance its mechanical properties and reduce environmental impact. This approach aligns with sustainable construction practices by lowering reliance on traditional cement, reducing carbon emissions, and promoting the reuse of industrial by products. The findings support the development of cost-effective, durable, and eco-friendly infrastructure, addressing the dual objectives of improved performance and environmental sustainability.
Forecasting California bearing ratio (CBR) of soil using machine learning algorithms: A review
Authors:   Department of Civil Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli-791109, Arunachal Pradesh, India, Tado Nabam , Medhajit Salam ,   Department of Civil Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli-791109, Arunachal Pradesh, India, Pal Dibyendu ,   Department of Civil Engineering, North Eastern Regional Institute of Science and Technology, Nirjuli-791109, Arunachal Pradesh, India
Published: February 2025

Traditionally California bearing ratio (CBR) is obtained by conducting laboratory testing, which is often time-consuming, laborious, and costly. This delays the design and construction processes of important structures. Recently, several researchers have predicted CBR using ML algorithms. This study focused on understanding the uses of various ML algorithms in the prediction of CBR of treated and natural soils, and other applications. Factors like OMC (30%), MDD (29%), LL (25%), PL (20%), and PI (19%) were mostly used as contributing factors for estimating CBR. ANN, RF, and CNN were the best models for predicting settlement of shallow foundation, bearing capacity of piles and slope stability, and landslide identification, respectively. DNN, GEP, and ELM-CSO were the best models in estimating CBR for granular soil, fine-grained soil, and lateritic soil, respectively, and RFR, AB-DT, LR, and ANN for other types of soils. ANN and BBO-MLP were the best models for expansive clay soil treated with HARHA, and pond ash treated with lime and lime sludge, whereas ANN was for lateritic soil treated with cement and RHA, sand with quartz, feldspar, calcite, corund, amorphous, and clay with pozzolan and lime powder, respectively. The quality and quantity of available training data were fundamental to observing the capacity of models, highlighting the importance of richer, better-labeled datasets.
EVALUATING THE PERFORMANCE OF RANDOM FOREST AND MONTE CARLO SIMULATION FOR FORECASTING MONTHLY TEMPERATURE VARIATION IN NORTHERN MINDANAO PHILIPPINES
Authors: Timbal Liezl , Luzano Warren
Published: February 2025

In this paper, we analyzed the historical temperature data spanning from 2010 to 2020 of Malaybalay City, Bukidnon using the random forest regression and Monte Carlo simulation. Such advanced methods were duly presented to enhance the accuracy of the monthly forecasting of temperatures. The results show that the random forest regression model has performed better, with an MSE of 0.67 and an RMSE of 0.82 on the test dataset, thus indicating that its temperature value predictions are closer to the real ones than ARIMA. However, ARIMA performed well on training data but had a much higher MSE of 3.03 and an RMSE of 1.74 on the test dataset, showing overfitting and less accuracy on the unseen data. The combined approach with random forest regression and Monte Carlo simulation returned an MSE of 0.68 and an RMSE of 0.83 against the test dataset, performing slightly better than ARIMA and behind the random forest model. These results further support how well random forest regression can model complex, nonlinear interactions, handle anomalies in various temperature data, and were further proved to be very effective in predicting temperatures.
DEĞİŞEN YAYILIMLI SIRALI LOJİSTİK REGRESYON MODELİ İLE BİREYLERİN UMUTLU OLMA DÜZEYLERİNİ ETKİLEYEN FAKTÖRLERİN BELİRLENMESİ
Authors: Ünver Şeyda
Published: February 2025

Bu çalışmanın amacı, Türkiye İstatistik Kurumu tarafından 2021 yılında yapılmış olan Yaşam Memnuniyeti Araştırması’nın mikro veri setinden yararlanarak Değişen yayılımlı sıralı lojistik regresyon modeli ile bireylerin kendi geleceklerinden umutlu olma düzeylerini etkileyen faktörleri belirlemektir. Model sonuçları incelendiğinde yaş, cinsiyet, eğitim düzeyi, çalışma durumu/sektör, mutluluk düzeyi, yaşamından memnuniyet düzeyi, sağlığından memnuniyet düzeyi ve gelir düzeyi değişkenlerinin anlamlı olduğu görülmektedir. Çalışmaya göre erkeklerin kadınlara göre kendi geleceklerinden umutlu/çok umutlu olma olasılıkları daha fazladır. Çalışmanın sonuçlarına göre, bireylerin umutlarını artırmayı hedefleyen politikaların ortaya konulması ve ülkenin ekonomik ve sosyal olarak gelişmesini sağlayacak, özellikle de bireylerin kendilerine olan inançlarını artıracak stratejilerin geliştirilmesi önemlidir.
GAİUS JULİUS CAESAR’İN İKTİDARA YÜKSELİŞİ
Authors: Kerem Ali
Published: February 2025

Julius Caesar sadece Roma tarihinin değil aynı zamanda antik dünyanın en önemli isimlerinden biri olarak hatırlanmaya değerdir. Şüphesiz Roma’nın köklü ailelerinden birine mensup olması kendisine önemli avantajlar sağlamıştır. Bununla beraber kariyerinin erken zamanlarında yaşanan politik bölünmeler iktidarını kurmasıyla sonuçlanan süreci kavrayabilmek açısından önemli ipuçları sunar. Bu bağlamda dönemin iki büyük ismi Gaius Marius ve Cornelius Sulla arasındaki iç savaşta gerek ailesinin politik duruşu gerekse de Marius ile olan bağlantısından dolayı ciddi tehlikelerle karşılaşmıştır. Söz konusu dönem de Roma’dan uzakta kalmayı tercih eden Caesar, Sulla’nın ölümünden sonra nihayet Roma’ya dönebilmiştir. Bu tarihten sonra politik arenada kendini gösterme fırsatı bulmuş, ordu saflarında adından sıkça söz ettirmeyi başarmıştır. Erken dönemlerinden itibâren sayısız savaşlara katılmış, içeride ve dışarıda elde ettiği zaferlerle iktidarını sağlam zemin üzerine oturtmuştur. Askerî sahadaki başarılarının yanı sıra, politik diplomasi alanındaki becerileri sayesinde zamanın en güçlü isimleriyle üçlü koalisyon kurarak elde ettiği gücü daha ileri seviyelere taşımasını bilmiştir. Bu açıdan Caesar’i iktidara taşıyan sürecin genel olarak askerî-politik şartlarını irdelemek çalışmamızın amacını oluşturacaktır. Bu bağlamda, Galya Savaşları ile ittifakın ortaklarından Gnaeus Pompeius ve Licinius Crassus’u gölgede bırakarak büyük bir şöhrete kavuşmuştur. Caesar’in artan gücünden rahatsızlık duyan senatonun önde gelen üyeleri çok geçmeden Pompeius’un etrafında toplanmıştır. Crassus’un Partlara karşı düzenlediği seferde beklenmedik şekilde hayatını kaybetmesinin ardından Pompeius ve Caesar arasındaki güç dengeleri de bozulmuştur. Nihayet Caesar’in sahip olduğu yetkilerin elinden alınması sonucunda ortaya çıkan anlaşmazlık iki tarafı büyük bir mücadelenin içerisine sürüklemiştir. Sonuçta, Caesar’in üstün askerî gücü ve liderliği sayesinde Pompeius ve taraftarları ezilmiş, Roma tek bir adamın otoritesi altına girmiştir. Zorlu geçen mücadelelerden sonra Caesar’in mutlak iktidarını kurması bir taraftan Cumhuriyet’ten İmparatorluğa doğru geçiş sürecini hızlandırırken öte taraftan kendisinden sonra gelen liderler için âdeta emsal teşkil etmiştir.
Community Policing Strategies in Prevention of Gender-Based Violence in Babati District Council, Northern Tanzania
Authors: Mpehongwa Gasper , Gabriel Gamaliel Israel
Published: February 2025

Community Policing Strategies in Prevention of Gender-Based Violence in Babati District Council, Northern Tanzania
Gene networks and metabolomic screening analysis revealed specific pathways of amino acid and acylcarnitine profile alterations in blood plasma of patients with Parkinson’s disease and vascular parkinsonism
Authors: Makarova A. A. , Melnikova P. M. , Rogachev A. D. , Demenkov P. S. , Ivanisenko T. V. , Predtechenskaya E. V. , Karmanov S. Y. , Koval V. V. , Pokrovsky A. G. , Lavrik I. N. , Kolchanov N. A. , Ivanisenko V. A.
Published: February 2025

Parkinson’s disease (PD) and vascular parkinsonism (VP) are characterized by similar neurological syndromes but differ in pathogenesis, morphology, and therapeutic approaches. The molecular genetic mechanisms of these pathologies are multifactorial and involve multiple biological processes. To comprehensively analyze the pathophysiology of PD and VP, the methods of systems biology and gene network reconstruction are essential. In the current study, we performed metabolomic screening of amino acids and acylcarnitines in blood plasma of three groups of subjects: PD patients, VP patients and the control group. Comparative statistical analysis of the metabolic profiles identified significantly altered metabolites in the PD and the VP group. To identify potential mechanisms of amino acid and acylcarnitine metabolism disorders in PD and VP, regulatory gene networks were reconstructed using ANDSystem, a cognitive system. Regulatory pathways to the enzymes converting significant metabolites were found from PD­specific genetic markers, VP­specific genetic markers, and the group of genetic markers common to the two diseases. Comparative analysis of molecular genetic pathways in gene networks allowed us to identify both specific and non­specific molecular mechanisms associated with changes in the metabolomic profile in PD and VP. Regulatory pathways with potentially impaired function in these pathologies were discovered. The regulatory pathways to the enzymes ALDH2, BCAT1, AL1B1, and UD11 were found to be specific for PD, while the pathways regulating OCTC, FURIN, and S22A6 were specific for VP. The pathways regulating BCAT2, ODPB and P4HA1 were associated with genetic markers common to both diseases. The results obtained deepen the understanding of pathological processes in PD and VP and can be used for application of diagnostic systems based on the evaluation of the amino acids and acylcarnitines profile in blood plasma of patients with PD and VP.
Ontologies in modelling and analysing of big genetic data
Authors: Podkolodnyy N. L. , Podkolodnaya O. A. , Ivanisenko V. A. , Marchenko M. A.
Published: February 2025

To systematize and effectively use the huge volume of experimental data accumulated in the field of bioinformatics and biomedicine, new approaches based on ontologies are needed, including automated methods for semantic integration of heterogeneous experimental data, methods for creating large knowledge bases and self-interpreting methods for analyzing large heterogeneous data based on deep learning. The article briefly presents the features of the subject area (bioinformatics, systems biology, biomedicine), formal definitions of the concept of ontology and knowledge graphs, as well as examples of using ontologies for semantic integration of heterogeneous data and creating large knowledge bases, as well as interpreting the results of deep learning on big data. As an example of a successful project, the Gene Ontology knowledge base is described, which not only includes terminological knowledge and gene ontology annotations (GOA), but also causal influence models (GO-CAM). This makes it useful not only for genomic biology, but also for systems biology, as well as for interpreting large-scale experimental data. An approach to building large ontologies using design patterns is discussed, using the ontology of biological attributes (OBA) as an example. Here, most of the classification is automatically computed based on previously created reference ontologies using automated inference, except for a small number of high-level concepts. One of the main problems of deep learning is the lack of interpretability, since neural networks often function as “black boxes” unable to explain their decisions. This paper describes approaches to creating methods for interpreting deep learning models and presents two examples of self-explanatory ontology-based deep learning models: (1) Deep GONet, which integrates Gene Ontology into a hierarchical neural network architecture, where each neuron represents a biological function. Experiments on cancer diagnostic datasets show that Deep GONet is easily interpretable and has high performance in distinguishing cancerous and non-cancerous samples. (2) ONN4MST, which uses biome ontologies to trace microbial sources of samples whose niches were previously poorly studied or unknown, detecting microbial contaminants. ONN4MST can distinguish samples from ontologically similar biomes, thus offering a quantitative way to characterize the evolution of the human gut microbial community. Both examples demonstrate high performance and interpretability, making them valuable tools for analyzing and interpreting big data in biology.
PlantReg: the reconstruction of links between transcription factor regulatory networks and biological processes under their control
Authors: Lavrekha V. V. , Omelyanchuk N. A. , Bogomolov A. G. , Zemlyanskaya E. V.
Published: February 2025

The description of the path from a gene to a trait, as the main task of many areas in biology, is currently being equipped with new methods affecting not only experimental techniques, but also analysis of the results. The pleiotropic effect of a gene is due to its participation in numerous biological processes involved in different traits. A widespread use of genome-wide sequencing of transcripts and transcription factor (TF) binding regions has made the following tasks relevant: unveiling pleiotropic effects of TFs based on the functions of their target genes; compiling the lists of TFs that regulate biological processes of interest; and describing the ways of TF functioning (their primary and secondary targets, higher order targets, TF interactions in the process under study). We have previously developed a method for the reconstruction of TF regulatory networks and proposed an approach that allows identifying which biological processes are controlled by these networks and how this control is exerted. In this paper, we have implemented the approach as PlantReg, a program available as a web service. The paper describes how the program works. The input consists of a list of genes and a list of TFs – known or putative transcriptional regulators of these genes. As an output, the program provides a list of biological processes enriched for these genes, as well as information about by which TFs and through which genes these processes are controlled. We illustrated the use of PlantReg deciphering transcriptional regulation of processes initiated at the early salt stress response in Arabidopsis thaliana L. With PlantReg, we identified biological processes stimulated by the stress, and specific sets of TFs that activate each process. With one of these processes (response to abscisic acid) as an example, we showed that salt stress mainly affects abscisic acid signaling and identified key TFs in this regulation. Thus, PlantReg is a convenient tool for generating hypotheses about the molecular mechanisms that control plant traits.
Computational identification of promising genetic markers associated with molecular mechanisms of reduced rice resistance to Rhizoctonia solani under excess nitrogen fertilization using gene network reconstruction and analysis methods
Authors: Antropova E. A. , Volyanskaya A. R. , Adamovskaya A. V. , Demenkov P. S. , Yatsyk I. V. , Ivanisenko T. V. , Orlov Y. L. , Haoyu Ch. , Chen M. , Ivanisenko V. A.
Published: February 2025

Although nitrogen fertilizers increase rice yield, their excess can impair plant resistance to diseases, particularly sheath blight caused by Rhizoctonia solani. This pathogen can destroy up to 50 % of the crop, but the mechanisms underlying reduced resistance under excess nitrogen remain poorly understood. This study aims to identify potential marker genes to enhance rice resistance to R. solani under excess nitrogen conditions. A comprehensive bioinformatics approach was applied, including differential gene expression analysis, gene network reconstruction, biological process overrepresentation analysis, phylostratigraphic analysis, and non-coding RNA co-expression analysis. The Smart crop cognitive system, ANDSystem, the ncPlantDB database, and other bioinformatics resources were used. Analysis of the molecular genetic interaction network revealed three potential mechanisms explaining reduced resistance of rice to R. solani under excess nitrogen: the OsGSK2-mediated pathway, the OsMYB44-OsWRKY6-OsPR1 pathway, and the SOG1-Rad51-PR1/PR2 pathway. Potential markers for breeding were identified: 7 genes controlling rice responses to various stresses and 11 genes modulating the immune system. Special attention was given to key participants in regulatory pathways under excess nitrogen conditions. Non-coding RNA analysis revealed 30 miRNAs targeting genes of the reconstructed gene network. For two miRNAs (Osa-miR396 and Osa-miR7695), about 7,400 unique long non-coding RNAs (lncRNAs) with various co-expression indices were found. The top 50 lncRNAs with the highest co-expression index for each miRNA were highlighted, opening new perspectives for studying regulatory mechanisms of rice resistance to pathogens. The results provide a theoretical basis for experimental work on creating new rice varieties with increased pathogen resistance under excessive nitrogen nutrition. This study opens prospects for developing innovative strategies in rice breeding aimed at optimizing the balance between yield and disease resistance in modern agrotechnical conditions.
Reconstruction of gene regulatory networks from single cell transcriptomic data
Authors: Rybakov M. A. , Omelyanchuk N. A. , Zemlyanskaya E. V.
Published: February 2025

Gene regulatory networks (GRNs) – interpretable graph models of gene expression regulation – are a pivotal tool for understanding and investigating the mechanisms utilized by cells during development and in response to various internal and external stimuli. Historically, the first approach for the GRN reconstruction was based on the analysis of published data (including those summarized in databases). Currently, the primary GRN inference approach is the analysis of omics (mainly transcriptomic) data; a number of mathematical methods have been adapted for that. Obtaining omics data for individual cells has made it possible to conduct large-scale molecular genetic studies with an extremely high resolution. In particular, it has become possible to reconstruct GRNs for individual cell types and for various cell states. However, technical and biological features of single-cell omics data require specific approaches for GRN inference. This review describes the approaches and programs that are used to reconstruct GRNs from single-cell RNA sequencing (scRNA-seq) data. We consider the advantages of using scRNA-seq data compared to bulk RNA-seq, as well as challenges in GRN inference. We pay specific attention to state-of-the-art methods for GRN reconstruction from single-cell transcriptomes recruiting other omics data, primarily transcription factor binding sites and open chromatin profiles (scATAC-seq), in order to increase inference accuracy. The review also considers the applicability of GRNs reconstructed from single-cell omics data to recover and characterize various biological processes. Future perspectives in this area are discussed.
GlucoGenes®, a database of genes and proteins associated with glucose metabolism disorders, its description and applications in bioinformatics research
Authors: Klimontov V. V. , Shishin K. S. , Ivanov R. A. , Ponomarenko M. P. , Zolotareva K. A. , Lashin S. A.
Published: February 2025

Data on the genetics and molecular biology of diabetes are accumulating rapidly. This poses the challenge of creating research tools for a rapid search for, structuring and analysis of information in this field. We have developed a web resource, GlucoGenes®, which includes a database and an Internet portal of genes and proteins associated with high glucose (hyperglycemia), low glucose (hypoglycemia), and both metabolic disorders. The data were collected using text mining of the publications indexed in PubMed and PubMed Central and analysis of gene networks associated with hyperglycemia, hypoglycemia and glucose variability performed with ANDSystems, a bioinformatics tool. GlucoGenes® is freely available at: https://glucogenes.sysbio.ru/genes/main. GlucoGenes® enables users to access and download information about genes and proteins associated with the risk of hyperglycemia and hypoglycemia, molecular regulators with hyperglycemic and antihyperglycemic activity, genes up-regulated by high glucose and/or low glucose, genes down-regulated by high glucose and/or low glucose, and molecules otherwise associated with the glucose metabolism disorders. With GlucoGenes®, an evolutionary analysis of genes associated with glucose metabolism disorders was performed. The results of the analysis revealed a significant increase (up to 40 %) in the proportion of genes with phylostratigraphic age index (PAI) values corresponding to the time of origin of multicellular organisms. Analysis of sequence conservation using the divergence index (DI) showed that most of the corresponding genes are highly conserved (DI < 0.6) or conservative (DI < 1). When analyzing single nucleotide polymorphism (SNP) in the proximal regions of promoters affecting the affinity of the TATA-binding protein, 181 SNP markers were found in the GlucoGenes® database, which can reduce (45 SNP markers) or increase (136 SNP markers) the expression of 52 genes. We believe that this resource will be a useful tool for further research in the field of molecular biology of diabetes.
From the editor
Authors: Kolchanov N. A.
Published: February 2025

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MetArea: a software package for analysis of the mutually exclusive occurrence in pairs of motifs of transcription factor binding sites based on ChIP-seq data
Authors: Levitsky V. G. , Tsukanov A. V. , Merkulova T. I.
Published: February 2025

ChIP-seq technology, which is based on chromatin immunoprecipitation (ChIP), allows mapping a set of genomic loci (peaks) containing binding sites (BS) for the investigated (target) transcription factor (TF). A TF may recognize several structurally different BS motifs. The multiprotein complex mapped in a ChIP-seq experiment includes target and other “partner” TFs linked by protein-protein interactions. Not all these TFs bind to DNA directly. Therefore, both target and partner TFs recognize enriched BS motifs in peaks. A de novo search approach is used to search for enriched TF BS motifs in ChIP-seq data. For a pair of enriched BS motifs of TFs, the co-occurrence or mutually exclusive occurrence can be detected from a set of peaks: the co-occurrence reflects a more frequent occurrence of two motifs in the same peaks, while the mutually exclusive means their more frequent detection in different peaks. We propose the MetArea software package to identify pairs of TF BS motifs with the mutually exclusive occurrence in ChIP-seq data. MetArea was designed to predict the structural diversity of BS motifs of the same TFs, and the functional relation of BS motifs of different TFs. The functional relation of the motifs of the two distinct TFs presumes that they are interchangeable as part of a multiprotein complex that uses the BS of these TFs to bind directly to DNA in different peaks. MetArea calculates the estimates of recognition performance pAUPRC (partial area under the Precision–Recall curve) for each of the two input single motifs, identifies the “joint” motif, and computes the performance for it too. The goal of the analysis is to find pairs of single motifs A and B for which the accuracy of the joint A&B motif is higher than those of both single motifs.
A novel approach to analyzing the evolution of SARS-CoV-2 based on visualization and clustering of large genetic data compactly represented in operative memory
Authors: Palyanov A. Yu. , Palyanova N. V.
Published: February 2025

SARS-CoV-2 is a virus for which an outstanding number of genome variants were collected, sequenced and stored from sources all around the world. Raw data in FASTA format include 16.8 million genomes, each ≈29,900 nt (nu­cleotides), with a total size of ≈500 ∙ 109 nt, or 465 Gb. We suggest an approach to data representation and organization, with which all this can be stored losslessly in the operative memory (RAM) of a common PC. Moreover, just ≈330 Mb will be enough. Aligning all genomes versus the initial Wuhan-Hu-1 reference sequence allows each to be represented as a data structure containing lists of point mutations, deletions and insertions. Our implementation of such data represen­tation resulted in a 1:1500 compression ratio (for comparison, compression of the same data with the popular WinRAR archiver gives only 1:62) and fast access to genomes (and their metadata) and comparisons between different genome variants. With this approach implemented as a C++ program, we performed an analysis of various properties of the set of SARS-CoV-2 genomes available in NCBI Genbank (within a period from 24.12.2019 to 24.06.2024). We calculated the distribution of the number of genomes with undetermined nucleotides, ‘N’s, vs the number of such nucleotides in them, the number of unique genomes and clusters of identical genomes, and the distribution of clusters by size (the number of identical genomes) and duration (the time interval between each cluster’s first and last genome). Finally, the evolution of distributions of the number of changes (editing distance between each genome and reference sequence) caused by substitutions, deletions and insertions was visualized as 3D surfaces, which clearly show the process of viral evolution over 4.5 years, with a time step = 1 week. It is in good correspondence with phylogenetic trees (usually based on 3–4 thousand of genome variant representatives), but is built over millions of genomes, shows more details and is independent of the type of lineage/clade classification.
Orthoweb: a software package for evolutionary analysis of gene networks
Authors: Ivanov R. A. , Mukhin A. M. , Kazantsev F. V. , Mustafin Z. S. , Afonnikov D. A. , Matushkin Y. G. , Lashin S. A.
Published: February 2025

This article introduces Orthoweb (https://orthoweb.sysbio.cytogen.ru/), a software package developed for the calculation of evolutionary indices, including phylostratigraphic indices and divergence indices (Ka/Ks) for individual genes as well as for gene networks. The phylostratigraphic age index (PAI) allows the evolutionary stage of a gene’s emergence (and thus indirectly the approximate time of its origin, known as “evolutionary age”) to be assessed based on the analysis of orthologous genes across closely and distantly related taxa. Additionally, Orthoweb supports the calculation of the transcriptome age index (TAI) and the transcriptome divergence index (TDI). These indices are important for understanding the dynamics of gene expression and its impact on the development and adaptation of organisms. Orthoweb also includes optional analytical features, such as the ability to explore Gene Ontology (GO) terms associated with genes, facilitating functional enrichment analyses that link evolutionary origins of genes to biological processes. Furthermore, it offers tools for SNP enrichment analysis, enabling the users to assess the evolutionary significance of genetic variants within specific genomic regions. A key feature of Orthoweb is its ability to integrate these indices with gene network analysis. The software offers advanced visualization tools, such as gene network mapping and graphical representations of phylostratigraphic index distributions of network elements, ensur­ing intuitive interpretation of complex evolutionary relationships. To further streamline research workflows, Orthoweb includes a database of pre-calculated indices for numerous taxa, accessible via an application programming inter­face (API). This feature allows the users to retrieve pre-computed phylostratigraphic and divergence data efficiently, significantly reducing computational time and effort.
A software module to assess the metabolic potential of mutant strains of the bacterium Corynebacterium glutamicum
Authors: Kazantsev F. V. , Trofimova M. F. , Khlebodarova T. M. , Matushkin Yu. G. , Lashin S. A.
Published: February 2025

Technologies for the production of a range of compounds using microorganisms are becoming increas­ingly popular in industry. The creation of highly productive strains whose metabolism is aimed to the synthesis of a specific desired product is impossible without complex directed modifications of the genome using mathematical and computer modeling methods. One of the bacterial species actively used in biotechnological production is Co­rynebacterium glutamicum. There are already 5 whole-genome flux balance models for it, which can be used for me­tabolism research and optimization tasks. The paper presents fluxMicrobiotech, a software module developed at the Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, which implements a se­ries of computational protocols designed for high-performance computer analysis of C. glutamicum whole-genome flux balance models. The tool is based on libraries from the opencobra community (https://opencobra.github.io) within the Python programming language (https://www.python.org), using the Pandas (https://pandas.pydata.org) and Escher (https://escher.readthedocs.io) libraries . It is configured to operate on a ‘file-in/file-out’ basis. The model, environmental conditions, and model constraints are specified as separate text table files, which allows one to pre­pare a series of files for each section, creating databases of available test scenarios for variations of the model. Or vice versa, allowing a single model to be tested under a series of different cultivation conditions. Post-processing tools for modeling data are set up, providing visualization of summary charts and metabolic maps.
A conceptual article: The teachers’ role in implementing cognitive reading strategies to enhance students' reading comprehension
Authors: Pertiwi Nestiti Lintang , Iftanti Erna
Published: February 2025

The ability to read well is essential for learning English. Students' reading comprehension can be influenced by the application of efficient reading practices. Cognitive reading strategies are one method that can be used to enhance reading comprehension abilities. By using cognitive reading strategies, students can visualize information, absorb information in a predictable way, make connections between the text and prior knowledge, and evaluate their understanding. This study investigates the teacher's role in implementing cognitive reading strategies to improve students' reading comprehension abilities. This article uses a descriptive qualitative approach with a literature study design. Data was gathered through literature searches on Sinta, Google Scholar, Neliti.com, and ResearchGate. By arranging and summarizing research findings from several chosen articles, a descriptive analysis of the data was conducted. The findings indicate that the role of teachers is essential in helping students apply cognitive reading strategies to improve their reading comprehension skills, such as providing direction and guidance on reading strategies, modeling strategies, providing a supporting learning environment, activating students' prior knowledge, assisting and providing feedback to students, facilitating cooperative practice. However, this article only used secondary data so that the weakness of this article is the limited availability of related literature. Concerning the consequences, it is advised that future researchers might investigate deeper into the specific aspects that determine the successful implementation of cognitive reading strategies.
Cultural content in English textbook: Analyzing the representation of culture in the English textbook “English for change”
Authors: Hakim Andrean Naufal Maula , Wahyuni Dewi Sri
Published: February 2025

The present study examines the representation of cultural content in cultural representation, English the 11th-grade English textbook “Bahasa Inggris: English for Change.” This descriptive qualitative research employs document analysis as the data collection technique. The study investigates the cultural representation in this Senior High School English textbook using Cortazzi and Jin’s (1999) cultural dimensions and Yuen’s (2011) cultural elements as the analytical framework. The analysis reveals that Indonesian culture is predominantly featured across all textbook units, resulting in a limited representation of foreign cultural dimensions. Practice elements are the most prevalent, followed by product, person, and perspective elements in terms of cultural distribution. The findings indicate an imbalanced representation between Indonesian and foreign cultures, as well as an uneven distribution of the cultural aspects outlined by Yuen's framework (2011). It is recommended that the textbook authors incorporate a more diverse range of cultures to enhance students’ intercultural knowledge.
Students’ engagement for academic success in intensive reading
Authors: Wahyuni Sri , Azami Mochamad Imron
Published: February 2025

The aim of this research is to investigate a significant relationship between students' engagement and their success in academic focus in intensive reading at a private university in Malang, Indonesia. This research used a quantitative approach with a correlational research design to analyze the data. The sample of participants are third semester English Education Department students selected using convenience sampling technique. The data were tested and analyzed using the SPSS application and the Pearson correlation test was used. The results revealed a positive moderate category (r = 0.532, p < 0.05) between students’ engagement including behavioral, affective, social, and cognitive engagement and their academic achievement. The findings emphasize the essential role of engagement of the students in the classroom to enhance their academic success in an intensive reading context. The findings was also found that three dimensions of students' engagement correlate with academic success, including behavioral, social and cognitive engagement. Meanwhile, affective engagement is a dimension of student's engagement that has less influence on their academics. From these findings, it is hoped that educators will develop strategies to increase student engagement, especially in the context of intensive reading.