Established Patterns Research Articles

Variability Assessment of Global Extreme Coastal Sea Levels Using Altimetry Data

This study assesses the variability of coastal extreme sea levels globally by utilizing nearly three decades of along-track, multi-mission satellite altimetry data. An altimetry-based global coastal database of the non-tidal residual sea level component has been produced. The climate variability of extremes is modeled through a parametric, non-stationary statistical model. This model captures intra-annual, inter-annual and long-term variations in non-tidal residual return levels. Comparisons with tide gauge data demonstrate the ability of altimetry data to capture the variability of coastal extreme sea levels. Our findings reveal a greater complexity in the monthly variability patterns of non-tidal residual extremes in tropical latitudes, often exhibiting multiple storm periods, contrasting with coasts in extratropical latitudes, which are mostly controlled by a winter–summer pattern. This study also highlights the significant influence of established climate circulation patterns on sea level extremes. The positive phase of the Arctic Oscillation pattern leads to increases of over 25% in non-tidal residual return levels in Northwestern Europe with respect to a neutral phase. Furthermore, return levels in the western coast of Central America could be 50% higher during El Niño compared to La Niña. Our results show a robust increasing trend in non-tidal residual return levels along most global coastlines. A comparative analysis shows that variations during the 1995–2020 period were primarily driven by intra-annual variations.

Teacher-student collaborated multiple instance learning for pan-cancer PDL1 expression prediction from histopathology slides

Programmed cell death ligand 1 (PDL1), as an important biomarker, is quantified by immunohistochemistry (IHC) with few established histopathological patterns. Deep learning aids in histopathological assessment, yet heterogeneity and lacking spatially resolved annotations challenge precise analysis. Here, we present a weakly supervised learning approach using bulk RNA sequencing for PDL1 expression prediction from hematoxylin and eosin (H&E) slides. Our method extends the multiple instance learning paradigm with the teacher-student framework, which assigns dynamic pseudo-labels for intra-slide heterogeneity and retrieves unlabeled instances using temporal ensemble model distillation. The approach, evaluated on 12,299 slides across 20 solid tumor types, achieves a weighted average area under the curve of 0.83 on fresh-frozen and 0.74 on formalin-fixed specimens for 9 tumors with PDL1 as an established biomarker. Our method predicts PDL1 expression patterns, validated by IHC on 20 slides, offering insights into histologies relevant to PDL1. This demonstrates the potential of deep learning in identifying diverse histological patterns for molecular changes from H&E images.

Thermal conductivity of urban and artificial soils: methodological aspects and mathematical modeling

There are various methods for experimental determination of the thermal conductivity dependence on soil moisture and substrates. The influence of the sample structure (monolith, bulk sample), sample temperature, the method of installing the probe into the sample on the obtained readings of the TEMPOS device was studied and methodological recommendations were proposed. The dependence of thermal conductivity of soils bulk samples and substrates on moisture is shown. The spread of thermal conductivity values in the moisture range from hygroscopic to full moisture capacity for soddy-podzolic soil is 0.229–1.430 W/(m*K), for peat – 0.250–0.521 W/(m*K), for sand – 0.280–2.605 W/(m*K), for a mixture – 0.234–1.568 W/(m*K). ). The influence of properties such as density, particle size distribution, specific surface area, organic matter content, salinity affected thermal properties to a lesser extent. The established patterns can be used to calculate the temperature regime of soils in solving a number of applied problems related to the construction of special soil objects, for example, when creating urban soil structures. For this, it is necessary either to determine the thermal conductivity experimentally, or to calculate it, using the physical parameters of soils and substrates. The first method is labor-consuming, the second is less accurate. As an example, the equations available for work in the HYDRUS-1D (Chang–Horton and Campbell) model are used. These equations either overestimate the thermal conductivity in the area of high substrate humidity, or underestimate the thermal conductivity in the area of low substrate humidity (sand, loam, peat and a mixture based on them).

Credit card transaction fraud detection based on machine learning

The rise of e-commerce payment systems has been swift due to our society's rapid advancement. However, the transparency and vulnerability of the internet have opened new avenues for illicit access, resulting in a significant surge in financial fraud cases, particularly credit card transaction fraud. Detecting and mitigating such incidents has become crucial. One branch of artificial intelligence, machine learning, offers a potent solution. It operates by utilizing various algorithms and models that rely on established patterns and reasoning without explicit instructions. By processing vast amounts of historical data, machine learning models can identify underlying data relationships, allowing them to make accurate predictions based on input data. Therefore, it emerges as a highly effective method for credit card transaction fraud detection. This paper reviews the research methods for credit card fraud, introduces credit card transaction fraud detection data sets, and outlines machine learning algorithms and models related to credit card fraud detection. It also considers the future prospects for machine learning development and possible challenges.

Inoculated biocrust cover and functions diverged over a gradient of soil textures and water availability

Restoring biological crust (biocrust) in disturbed drylands is challenging due to the difficult environmental conditions, such as limited soil moisture, low soil nutrients, and extreme temperatures, that impede growth. Understanding how the key components of biocrust—mosses, lichens, and cyanobacteria—react to different environmental factors informs the optimal timing, locations, and species composition for biocrust reintroduction, thereby increasing the likelihood of establishment. Here, we inoculated soils with a diverse range of biocrust organisms, analogous to seeding an area with diverse vascular plant seeds, and varied environmental conditions to observe how these changes influenced the development and functions of reintroduced biocrust. We found that by manipulating soil texture and time spent wet, we can change the proportional cover of biocrust within a restoration‐like setting. Specifically, we found that 4 months after inoculation, finer textured soils that received more water become dominated by moss cover, while coarser textured soils with less water remained dominated by cyanobacteria cover, and the interactions between texture and time spent wet strongly influenced cover. We found biocrust morphological group cover had a small, but detectable, effect on ecosystem functions (soil stability and nitrogenase activity, a proxy for nitrogen fixation), but that environmental conditions had a stronger impact on the functions we measured. Manipulative experiments in controlled environments, like this one, can help elucidate the mechanisms underlying the establishment rate and patterns of biocrusts post‐inoculation, and inform implementation of inoculations in the field.

Uncomfortable Knowledges and Transformative Learning: Reimagining the Museum in the Art of Gustafsson&Haapoja

ABSTRACT Destructive human action is causing interconnected ecological and social challenges on an unprecedented scale. Scholars and artists from varied fields have critically expressed their concern about this in their research and practice. In this article, we interrogate the transformative potential of critically engaged art by analysing the work of the Finnish artist duo Gustafsson&Haapoja, a collaboration between writer Laura Gustafsson and visual artist Terike Haapoja. Gustafsson&Haapoja’s work focuses on the intersecting human exceptionalist, racist, imperialist, patriarchal, and capitalist histories of violence towards nonhuman animals and dehumanised humans. These histories often provoke uncomfortable affects. As such, they can be challenging to confront. To account for this difficulty, we approach Gustafsson&Haapoja’s art through the idea of transformative learning, a process designed to shake established thinking and behavioural patterns. We investigate how Gustafsson&Haapoja’s art—and art more generally—could function as a transformative learning resource and enable sudden ruptures in hegemonic cultural norms, privileges, and power positions. We focus on how transformative learning emerges through central features in Gustafsson&Haapoja’s work: (1) their investigation and reimagination of the museum, an institution historically tied to notions of humanity and human action; and (2) their critical dissection of the complex relationship between Western-centric conceptualisations of humanity and its “others.” The article is based on a theoretical discussion and a qualitative analysis of works, exhibitions, and texts published by Gustafsson&Haapoja’s Museum of Becoming (2020–21) as well as an interview with the artists.

Chronotopische Landschaften in den fantastischen Romanen Raphaela Edelbauers

The works of Raphaela Edelbauer share a common theme in terms of the surrealistic landscapes in which they are set. Her historical novel Die Inkommensurablen (2023) features a village referred to as Weiler, which can seemingly be visited by multiple characters in their dreams. This dreamscape is not only a fantastic element in an otherwise realistic novel, but also an allegory of the shared belligerence within the Austrian society just before the outbreak of World War I. Similarly, the surreal setting of her contemporary novel Das flüssige Land (2019) functions as an allegory as well. The ground beneath the town of Groß-Einland is hollowed out, threatening its very existence, just as the shared guilt of the population’s crimes under the Nazi regime still lingers beneath the idyllic surface. Finally, her science fiction novel DAVE (2021) departs from the established pattern in that its setting is not the manifestation of a shared sentiment, but rather the mind of the eponymous artificial intelligence that narrates the story. In all these cases, however, the landscape is used to transform a subjective and abstract experience into a physical space.

Modeling brain network flexibility in networks of coupled oscillators: a feasibility study

Modeling the functionality of the human brain is a major goal in neuroscience for which many powerful methodologies have been developed over the last decade. The impact of working memory and the associated brain regions on the brain dynamics is of particular interest due to their connection with many functions and malfunctions in the brain. In this context, the concept of brain flexibility has been developed for the characterization of brain functionality. We discuss emergence of brain flexibility that is commonly measured by the identification of changes in the cluster structure of co-active brain regions. We provide evidence that brain flexibility can be modeled by a system of coupled FitzHugh-Nagumo oscillators where the network structure is obtained from human brain Diffusion Tensor Imaging (DTI). Additionally, we propose a straightforward and computationally efficient alternative macroscopic measure, which is derived from the Pearson distance of functional brain matrices. This metric exhibits similarities to the established patterns of brain template flexibility that have been observed in prior investigations. Furthermore, we explore the significance of the brain’s network structure and the strength of connections between network nodes or brain regions associated with working memory in the observation of patterns in networks flexibility. This work enriches our understanding of the interplay between the structure and function of dynamic brain networks and proposes a modeling strategy to study brain flexibility.

The Influence of Personality Shaping on Romantic Relationships in Early Adulthood

Intimacy is a type of interpersonal relationship that refers to a subjectively experienced emotional or physical closeness. In the modern society of individualization, the focus on emotional communication and confession, mutual knowledge, and understanding are at the heart of modern, intimate relationships. Patterns in intimate relationships are often related to the individual’s personality. Research has shown that personality building in infancy and early adulthood has important implications for romantic relationships, including attachment relationships, self-expansion, mindfulness, and changing established work patterns. Owing to the existent relevant academy of factors influencing romantic relationships is extensive, and the factors appear relatively independent, this literature review tries to reduce this confusing status quo by presenting a neoteric perspective. This literature review will provide empirical and conceptual insights from (i) an overview of the definitions and mechanisms of action of different theories and (ii) an analysis of the links between different factors.

Irritable bowel syndrome in children: pathogenetic significance of disorders of intestinal microbiota

Irritable bowel syndrome (IBS) is the most common functional disorder of the intestine in children. In recent years, IBS has been defined as functional pathology of the intestine, manifested by visceral recurrent pain that occurs at least once per week, characterized by the following two or more signs: associated with defecation; with changes in the frequency and shape of stools. These symptoms had to be noted in the patient for the last 3 months, with a total duration of at least 6 months, without signs of organic damage to the gastrointestinal tract (GIT). The gut microbiota is of particular importance in the pathogenesis of IBS. In patients with IBS, an increase in Enterobacteriaceae, Ruminococcus, Clostridium, Dorea species and a decrease in the number of Lactobacillus, Bifidobacterium and Faecalibacterium species were found. At the same time, a similar microbial profile was found in patients with different subtypes of IBS. The established patterns of changes in the composition of the microbiota in IBS in children and adults indicate IBS and functional disorders of the GIT to have a pronounced microbial pathogenesis. In this regard, the personalized use of prebiotics, probiotics, synbiotics, and fecal microbiota transplantation can effectively affect the intestinal microbiome in IBS. 
 Conclusion. Correction of disorders of intestinal microbiota is the most important method of treating IBS in children. Determining the patterns of formation of changes in the intestinal microbiome in IBS children creates new opportunities for improving methods of their correction.

Bacterial Patterning: A Promising Biofabrication Technique.

Bacterial patterning has emerged as a pivotal biofabrication technique in the biomedical field. In the past 2 decades, a diverse array of bacterial patterning approaches have been developed to enable the precise manipulation of the spatial distribution of bacterial patterns for various applications. Despite the significance of these advancements, there is a deficiency of review articles providing an overview of bacterial patterning technologies. In this mini-review, we systematically summarize the progress of bacterial patterning over the past 2 decades. This review commences with an elucidation of the definition and fundamental principles of bacterial patterning. Subsequently, we introduce the established bacterial patterning strategies, accompanied by discussions about the advantages and limitations of each approach. Furthermore, we showcase the biomedical applications of these strategies, highlighting their efficacy in spatial control of biofilms, biosensing, and biointervention. Finally, this mini-review is concluded with a summary and an outlook on future challenges and opportunities. It is anticipated that this mini-review can serve as a concise guide for those who are interested in this exciting and rapidly evolving research area.

Lung Cancer Prevalence in Virginia: A Spatial Zipcode-Level Analysis via INLA.

Examining lung cancer (LC) cases in Virginia (VA) is essential due to its significant public health implications. By studying demographic, environmental, and socioeconomic variables, this paper aims to provide insights into the underlying drivers of LC prevalence in the state adjusted for spatial associations at the zipcode level. We model the available VA zipcode-level LC counts via (spatial) Poisson and negative binomial regression models, taking into account missing covariate data, zipcode-level spatial association and allow for overdispersion. Under latent Gaussian Markov Random Field (GMRF) assumptions, our Bayesian hierarchical model powered by Integrated Nested Laplace Approximation (INLA) considers simultaneous (spatial) imputation of all missing covariates through elegant prediction. The spatial random effect across zip codes follows a Conditional Autoregressive (CAR) prior. Zip codes with elevated smoking indices demonstrated a corresponding increase in LC counts, underscoring the well-established connection between smoking and LC. Additionally, we observed a notable correlation between higher Social Deprivation Index (SDI) scores and increased LC counts, aligning with the prevalent pattern of heightened LC prevalence in regions characterized by lower income and education levels. On the demographic level, our findings indicated higher LC counts in zip codes with larger White and Black populations (with Whites having higher prevalence than Blacks), lower counts in zip codes with higher Hispanic populations (compared to non-Hispanics), and higher prevalence among women compared to men. Furthermore, zip codes with a larger population of elderly people (age ≥ 65 years) exhibited higher LC prevalence, consistent with established national patterns. This comprehensive analysis contributes to our understanding of the complex interplay of demographic and socioeconomic factors influencing LC disparities in VA at the zip code level, providing valuable information for targeted public health interventions and resource allocation. Implementation code is available at GitHub.

Sustainable Innovation: Fabrication and Characterization of Mycelium-Based Green Composites for Modern Interior Materials Using Agro-Industrial Wastes and Different Species of Fungi.

Mycelium-based bio-composites (MBCs) represent a sustainable and innovative material with high potential for contemporary applications, particularly in the field of modern interior design. This research investigates the fabrication of MBCs for modern interior materials using agro-industrial wastes (bamboo sawdust and corn pericarp) and different fungal species. The study focuses on determining physical properties, including moisture content, shrinkage, density, water absorption, volumetric swelling, thermal degradation, and mechanical properties (bending, compression, impact, and tensile strength). The results indicate variations in moisture content and shrinkage based on fungal species and substrate types, with bamboo sawdust exhibiting lower shrinkage. The obtained density values range from 212.31 to 282.09 kg/m3, comparable to traditional materials, suggesting MBCs potential in diverse fields, especially as modern interior elements. Water absorption and volumetric swelling demonstrate the influence of substrate and fungal species, although they do not significantly impact the characteristics of interior decoration materials. Thermal degradation analysis aligns with established patterns, showcasing the suitability of MBCs for various applications. Scanning electron microscope observations reveal the morphological features of MBCs, emphasizing the role of fungal mycelia in binding substrate particles. Mechanical properties exhibit variations in bending, compression, impact, and tensile strength, with MBCs demonstrating compatibility with traditional materials used in interior elements. Those produced from L. sajor-caju and G. fornicatum show especially promising characteristics in this context. Particularly noteworthy are their superior compression and impact strength, surpassing values observed in certain synthetic foams multiple times. Moreover, this study reveals the biodegradability of MBCs, reaching standards for environmentally friendly materials. A comprehensive comparison with traditional materials further supports the potential of MBCs in sustainable material. Challenges in standardization, production scalability, and market adoption are identified, emphasizing the need for ongoing research, material engineering advancements, and biotechnological innovations. These efforts aim to enhance MBC properties, promoting sustainability in modern interior applications, while also facilitating their expansion into mass production within the innovative construction materials market.

Malaysian Graduates Employability Challenges: A Critical Review

The COVID-19 pandemic has had far-reaching implications for individuals, societies, and economies, disrupting established patterns in education, employment, and career trajectories. This paper explores a narrative review of the literature that studied the graduates’ employability post pandemic. Narrative review is suitable to be applied in this study, as it tends to achieve exploratory research where a new or emerging field is explored, providing holistic perspective in which a wide range of studies is summarized, consequently synthesizing diverse evidence that highlight the trends across various studies. This review highlights the multifaceted challenges facing Malaysian graduates, emphasizing the far-reaching circumstance of the COVID-19 pandemic on graduates' employment dynamics. It underscores disparities in the quality of employment, wage gaps, and the vulnerability of workers in informal sectors. A range of factors impacting employability can be considered, including self-efficacy, curriculum support, employability skills development, and work placement learning. The study also explores the impact of postgraduate studies on employment prospects, gender disparities in employability skills, and the significance of soft skills and non-technical skills in aviation careers. Furthermore, it delves into how graduates' knowledge and soft skills development vary by education level and how emerging concepts like Industry 5.0 are reshaping the employment landscape. Confronting globalization and evolving labor market dynamics, graduates must embrace self-development and adaptability so forth meeting the changing needs of the job market.

Prescriptive Theorizing in Management Research: A New Impetus for Addressing Grand Challenges

AbstractAlthough management research has a rich tradition of both descriptive and prescriptive theorizing, the latter is often (and erroneously) viewed as unscientific, purely practice‐oriented, or simply a corollary of descriptive analysis. Prescriptive theorizing concerns how things should be and how they can be achieved, as opposed to descriptive theorizing, which focuses on why or how things are (interrelated). Accordingly, prescriptive theorizing has strong normative and instrumental properties, which are especially relevant when addressing pressing societal, ecological, and ethical concerns, also referred to as grand challenges, that demand a re‐evaluation of established norms and behavioural patterns. However, this opportunity is currently underutilized in the management literature, and there is a lack of guidance on how to leverage the principles of prescriptive theorizing. Therefore, I clarify its main characteristics, outline how scholars can construct rigorous prescriptive arguments, and show how normative and instrumental reasoning can promote positive social change. Embracing prescriptive theorizing as a vital complement to descriptive theorizing in management research provides scholars with an intellectual toolkit to actively engage in the urgent discourse on grand challenges and develop compelling new and impactful theories.

Quality Metrics and Reordering Strategies for Revealing Patterns in BioFabric Visualizations.

Visualizing relational data is crucial for understanding complex connections between entities in social networks, political affiliations, or biological interactions. Well-known representations like node-link diagrams and adjacency matrices offer valuable insights, but their effectiveness relies on the ability to identify patterns in the underlying topological structure. Reordering strategies and layout algorithms play a vital role in the visualization process since the arrangement of nodes, edges, or cells influences the visibility of these patterns. The BioFabric visualization combines elements of node-link diagrams and adjacency matrices, leveraging the strengths of both, the visual clarity of node-link diagrams and the tabular organization of adjacency matrices. A unique characteristic of BioFabric is the possibility to reorder nodes and edges separately. This raises the question of which combination of layout algorithms best reveals certain patterns. In this paper, we discuss patterns and anti-patterns in BioFabric, such as staircases or escalators, relate them to already established patterns, and propose metrics to evaluate their quality. Based on these quality metrics, we compared combinations of well-established reordering techniques applied to BioFabric with a well-known benchmark data set. Our experiments indicate that the edge order has a stronger influence on revealing patterns than the node layout. The results show that the best combination for revealing staircases is a barycentric node layout, together with an edge order based on node indices and length. Our research contributes a first building block for many promising future research directions, which we also share and discuss. A free copy of this paper and all supplemental materials are available at https://osf.io/9mt8r/?view_only = b70dfbe550e3404f83059afdc60184c6.

Distribution ofAcer negundoL. in the Karasye-Ozersky forest park of Yekaterinburg

The article is devoted to invasions ofAcer negundoL. 1753 in the forest park area of Yekaterinburg (Russia) based on population (age and vitality structure) and organismal parameters (morphometric indicators). The purpose of the work was to study the invasion of ashleaved maple in the forest park area of Yekaterinburg; the objectives of the study included the following tasks: establishing the ecological-cenotic location of the maple and studying the biological characteristics of the species during its distribution. The objects of the study were eight maple habitats in the Karasye-Ozersky forest park. In ontogenetic development, one life form is identified - a single-stem tree, two periods are defined - pregenerative and generative, and five ontogenetic states. All habitats are young, i.e. are at the initial stage of introduction, however, there are common features of invasion. Distribution begins from open edges, gradually penetrating under the forest canopy, while having high shade tolerance, seed productivity and growth rate,Acernegundoforms multitiered thickets, displacing and complicating the self-restoration of native flora in the Karasye-Ozersky Forest Park. Despite the wide range of distribution of maple in natural and anthropogenic ecosystems, there is an ecological and phytocenotic confinement to it in the forest park, and it is manifested in its distribution mainly in pine forests of mixed herbs with a tree canopy density of 0.5. The established patterns indicate a pronounced expansion of the species and its significant invasive potential.

Impacts of bamboo dominance and die‐off on seedling dynamics in a tropical secondary forest (Brazil)

AbstractAulonemia aristulata is a tropical bamboo species of mixed rhizome type and monocarpic flowering that can become super‐dominant after anthropogenic disturbances in tropical forests. The synchronized reproductive events of flowering and die‐off of monocarpic bamboo systems provide a rare opportunity to evaluate the temporal effects of bamboo dominance on forest regeneration. To evaluate the effects of bamboo dominance on forest regeneration, we compared the structure (abundance, richness, composition) and dynamics (mortality, recruitment, survival and growth) of tree and shrub seedling communities from two non‐contiguous forests stands (bamboo‐dominated vs. non‐dominated sites) for 2 years, before and after a synchronized reproductive event. Bamboo dominated plots had higher abundance, floristic richness and recruitment of tree and shrub seedlings when compared with bamboo non‐dominated plots. Bamboo die‐off did not represent an opportunity to improve establishment and investment in the vertical growth (height) of seedlings in bamboo‐dominated plots. We postulate that the mode of rhizome extension seen in bamboos might be a consistent trait determining the spatial pattern of occupation and population structure and thereby playing a fundamental role in the pattern of native tree community establishment after bamboo die‐off. The formulation of a management approach is necessary in order to better understand the biological traits of bamboo species and their influence on the spatial pattern of occupation and population structure. Additionally, this influence may differently impact restoration and definition of management practices, including the need for direct intervention by manually controlling bamboo cover following die‐off to promote and maintain seedling establishment and diversity.

Lasso-based state estimation for cyber-physical systems under sensor attacks

The development of algorithms for secure state estimation in vulnerable cyber-physical systems has been gaining attention in the last years. A consolidated assumption is that an adversary can tamper a relatively small number of sensors. In the literature, block-sparsity methods exploit this prior information to recover the attack locations and the state of the system. In this paper, we propose an alternative, Lasso-based approach and we analyse its effectiveness. In particular, we theoretically derive conditions that guarantee successful attack/state recovery, independently of established time sparsity patterns. Furthermore, we develop a sparse state observer, by starting from the iterative soft thresholding algorithm for Lasso, to perform online estimation. Through several numerical experiments, we compare the proposed methods to the state-of-the-art algorithms.

АТА-АНАЛАРДЫҢ ИНКЛЮЗИВТІ БІЛІМ БЕРУ ЖАҒДАЙЫНДА ПСИХОЛОГИЯЛЫҚ-ПЕДАГОГИКАЛЫҚ СҮЙЕМЕЛДЕУДЕГІ СЕРІКТЕСТІГІ

The article pays special attention to the place and importance of parents in the psychological and pedagogical support in the context of inclusive education. Children with disabilities have an impact on the quantitative and qualitative indicators of students with special educational needs, a global problem is widespread in our country. A child requiring special attention is highly dependent on their parents, making their proper attitude and support invaluable in the child's life. The article analyzes the need for comprehensive psychological and pedagogical assistance for such families. The purpose of the study is to address the issue of partnership in supporting parents with children in the context of inclusive education. Task: to study the importance of the rehabilitation potential of parents with children within an inclusive education environment, to analyze the impact on child support. The study highlights the forecast for the effectiveness of parent partnerships in psychological and pedagogical support within inclusive education. It was noted that in an inclusive setting, positive parental influence on the child optimizes their relationship with the social environment. The implementation of established patterns in a civilized state increasingly emphasizes the importance of psychological and pedagogical support in inclusive education. Maximizing this development, while ensuring the successful completion of the general education program tailored to the individual characteristics of each child, is among the key issues in modern education.