Scientific Research Research Articles

Functional alterations in overweight/obesity: focusing on the reward and executive control network.

Overweight (OW) and obesity (OB) have become prevalent issues in the global public health arena. Serving as a prominent risk factor for various chronic diseases, overweight/obesity not only poses serious threats to people's physical and mental health but also imposes significant medical and economic burdens on society as a whole. In recent years, there has been a growing focus on basic scientific research dedicated to seeking the neural evidence underlying overweight/obesity, aiming to elucidate its causes and effects by revealing functional alterations in brain networks. Among them, dysfunction in the reward network (RN) and executive control network (ECN) during both resting state and task conditions is considered pivotal in neuroscience research on overweight/obesity. Their aberrations contribute to explaining why persons with overweight/obesity exhibit heightened sensitivity to food rewards and eating disinhibition. This review centers on the reward and executive control network by analyzing and organizing the resting-state and task-based fMRI studies of functional brain network alterations in overweight/obesity. Building upon this foundation, the authors further summarize a reward-inhibition dual-system model, with a view to establishing a theoretical framework for future exploration in this field.

Exploring a practice‐based approach to elementary preservice science teacher preparation

AbstractThe science methods course model presented here, called an immersed methods course (IMC), engaged preservice elementary teachers in reform‐based science instructional approaches within authentic classroom settings and with elementary students in a guided format. Questions guiding the study were: (1) Did participation in the IMC model impact preservice teachers (PTs') science teaching self‐efficacy? (2) Which science methods course model activities/experiences did PTs identify as the most impactful on their science teaching? (3) How did participation in the IMC model impact PTs' understandings of science teaching? Participants were 138 elementary PTs from a Southeastern United States university. Data were collected from seven course sections over 3 years and included pre/post science teaching self‐efficacy survey data, post written responses, and interviews. Member checking approaches were also used to refine and establish the validity of findings. Researchers completed qualitative data analysis, which was complimented by quantitative statistical analysis. Findings across data sources suggest participation positively influenced PTs' science teaching self‐efficacy and beliefs about the effectiveness of the instructional approaches. Participation also helped PTs apply theories to practice and develop competency using the practices. Findings highlight how the IMC model mitigates constraints associated with current science teacher preparation approaches.

Особенности обучения английскому языку студентов неязыковых вузов с проявлением семантической и аграмматической дислексии

The article is devoted to the study of the peculiarities of teaching English to students experiencing difficulties in semantic and agrammatic dyslexia. The purpose of the study is to identify effective methods and strategies that can help students overcome these difficulties in the process of learning English in a non-linguistic university. As part of this work, a literature review was conducted, including scientific publications and research on the topic of teaching English in the presence of dyslexia. The classification of dyslexia was considered, its semantic and agrammatic manifestations were highlighted. As a result of the study, the main difficulties that students face when learning English in the context of dyslexia were highlighted. In the course of the work, recommendations were proposed for English language teachers that will help them to work effectively with students of non-linguistic universities with manifestations of semantic and agrammatic dyslexia.

ВЫБОР ПАРАМЕТРОВ ТЕХНИЧЕСКОГО СОСТОЯНИЯ ЭЛЕМЕНТОВ ПОГЛОЩАЮЩЕГО АППАРАТА, ОПРЕДЕЛЯЮЩИХ ЕГО БЕЗОТКАЗНОСТЬ

The problems to plan and ensure a given level of reliability of mechanical systems at all stages of their design and operation occupy an important place in the problem of ensuring the quality of machine-building products. With a significant number of scientific methods and approaches to solving theoretical and applied issues of reliability theory, one of the key directions is to determine the reliability indicators of technical systems and their elements, in particular a wide range of products including sliding friction pairs with periodic impacts. The study of failure origins, from the point of view of physical-mechanical processes occurring in surface layers of elements, under the influence of external factors, allows selecting parameters characterizing the functional state of the pair, and, as a result, its reliability. For example, for sliding friction pairs with periodic impacts, such a parameter is the geometric dimensions of the conjugate elements. The decrease in the geometric dimensions of conjugate elements, due to wear, characterizes the rate of change of the initial parameter values to the maximum permissible ones determining the failure, and can be approximated by linear, power, exponential and other dependencies obtained from actual measurements. According to the obtained functional dependencies of parameter changes over operating time, it makes possible to determine the norm for the parameter regulating their pre-failure state, beyond which failure prediction is possible with varying probability, and, as a result, the reliability of the system as a whole. The use of this method to reliability forecasting through the determination of the pre-failure state of the system can be projected onto technical objects, which performance indicators are geometric parameters that ensure the performance, first of all, of the functions of the elements themselves and the entire technical system, and worn out during operation.

Mapping science through editorial board interlocking: connections and distance between fields of knowledge and institutional affiliations

AbstractResearch is a global enterprise underpinned by the general belief that findings need to be true to be considered scientific. In the complex system of scientific validation, editorial boards (EBs) play a fundamental role in guiding journals’ review process, which has led many stakeholders of sciences to metaphorically picture them as the “gatekeepers of knowledge.” In an attempt to address the academic structure that governs sciences through editorial board interlocking (EBI, the cross-presence of EB members in different journals) and social network analysis, the aim of this study is threefold: first, to map the connection between fields of knowledge through EBI; second, to visualize and empirically test the distance between social and general sciences; and third, to uncover the institutional structure (i.e., universities) that governs these connections. Our findings, based on the dataset collected through the Open Editors initiative for the journals indexed in the JCR, revealed a substantial level of collaboration between all fields, as suggested by the connections between EBs. However, there is a statistically significant difference between the weight of the edges and the path lengths connecting the fields of natural sciences to the fields of social sciences (compared to the connections within), indicating the development of different research cultures and invisible colleges in these two research areas. The results also show that a central group of US institutions dominates most journal EBs, indirectly suggesting that US scientific norms and values still prevail in all fields of knowledge. Overall, our study suggests that scientific endeavor is highly networked through EBs.

Spatiotemporal differentiation of carbon budget and balance zoning: Insights from the middle reaches of the Yangtze River Urban Agglomeration, China

Urbanization has substantially changed land use and led to local growth and an overall imbalance in carbon emissions. Scientific analysis of carbon emissions from land use (CELU) and exploration of carbon balance zoning can provide useful references for regional low-carbon land use management in urban agglomerations. This study analyzed the spatiotemporal dynamics of CELU based on land use and socioeconomic data, and utilizing the emission coefficient method. The economic contribution coefficient of carbon emissions (ECC) and Ecological Support Coefficient of carbon emissions (ESC) was used as the basis for developing carbon balance zoning, and the main function positioning of counties was used to combine with carbon balance zoning. Subsequently carbon balance partitions with determinants across 190 counties in the Middle Reaches of the Yangtze River Urban Agglomeration (MRYRUA) was obtained. We found that the net carbon emissions from land use in MRYRUA increased from 1.242 to 4.049 million tons, showing a clear upward trend. Notably, the Gini coefficients of carbon emissions and sinks of the MRYRUA were both higher than 0.4, and the pressure on the regional carbon balance intensified. In addition, based on the carbon balance analysis, MRYRUA was divided into five types: low-carbon economic zones, low-carbon optimization zones, carbon intensity control zones and high-carbon optimization zones. These zones were used to combine with the main function positioning, and finally got 11 types of zoning results. In response, this study proposes different low-carbon land-use optimization strategies based on the carbon budget and comprehensive development characteristics of different zones.

A Look at Genomic Selection Techniques for Climate Change Adaptation and Production in Livestock

Livestock production profoundly intersects with global climate dynamics, contributing to greenhouse gas emissions and confronting vulnerability to climate impacts. In addressing these challenges, imperative adjustments are requisite to fortify the climate robustness of livestock systems. Notably, the prevalent reliance on commercial breeds with limited genetic diversity exposes production strategies to disruption, especially if these breeds are confined to environments that may lose economic viability under future climate scenarios. Consequently, understanding the adaptability of animal populations to forthcoming environmental conditions is paramount for sustaining livestock production. Assessing the genetic underpinnings of climate adaptation necessitates the exploration of tailored genomic selection techniques encompassing both production traits, presumed to have moderate heritability, and adaptation traits, presumed to have low heritability. Through a nuanced examination of genomic selection dynamics, insights into the genetic mechanisms fostering resilience in livestock populations amidst shifting environmental contexts are garnered. Employ genomic analysis to pinpoint genetic markers associated with traits like heat tolerance, disease resistance, and feed efficiency in livestock. Collaborate across disciplines to develop tailored breeding programs integrating these markers, and validate their effectiveness through rigorous field trials and ongoing monitoring to enhance livestock resilience and productivity in varied climatic conditions. Elucidating these mechanisms and their application in breeding programs offers a comprehensive understanding of how genetic advancements can enhance both production efficiency and climate resilience in livestock. This discourse aims to bridge the chasm between scientific inquiry and pragmatic implementation, thereby facilitating informed decision-making in livestock breeding strategies tailored to mitigate the ramifications of climate change.

[Research progress in the diagnosis and treatment of childhood glaucoma].

Childhood glaucoma is a disease that seriously endangers children's visual health. It will accompany the patients throughout their lives and bring a heavy burden to families and society. Most childhood blindness caused by glaucoma is preventable or treatable. Relevant research has made progress in recent years. Based on the new consensus reached by the World Glaucoma Association and the latest medical evidence at home and abroad, this article summarizes the definition, classification, diagnosis, molecular genetics, pathogenesis and comprehensive treatments including drugs and surgery of childhood glaucoma, with a focus on the application of various surgical methods, so as to provide reference for clinical and scientific research and improve the clinical diagnosis and treatment of childhood glaucoma.

Active Learning for Data Quality Control: A Survey

Data quality plays a vital role in scientific research and decision-making across industries. Thus it is crucial to incorporate the data quality control (DQC) process, which comprises various actions and operations to detect and correct data errors. The increasing adoption of machine learning (ML) techniques in different domains has raised concerns about data quality in the ML field. On the other hand, ML’s capability to uncover complex patterns makes it suitable for addressing challenges involved in the DQC process. However, supervised learning methods demand abundant labeled data, while unsupervised learning methods heavily rely on the underlying distribution of the data. Active learning (AL) provides a promising solution by proactively selecting data points for inspection, thus reducing the burden of data labeling for domain experts. Therefore, this survey focuses on applying AL to DQC. Starting with a review of common data quality issues and solutions in the ML field, we aim to enhance the understanding of current quality assessment methods. We then present two scenarios to illustrate the adoption of AL into the DQC systems on the anomaly detection task, including pool-based and stream-based approaches. Finally, we provide the remaining challenges and research opportunities in this field.

Towards Sustainable Agriculture: Integrating Agronomic Practices, Environmental Physiology and Plant Nutrition

Sustainable agriculture aims to meet the growing global demand for food without compromising environmental integrity. This review paper explores the integration of agronomic practices, environmental physiology, and plant nutrition as pathways toward sustainable crop production. Intensive agricultural practices have led to significant problems such as soil degradation, loss of biodiversity, and environmental pollution. Recent advancements in plant physiology have enhanced our understanding of plant growth and response to biotic and abiotic stresses. Optimizing crop production in a sustainable manner depends on insights into key processes like photosynthesis, water use efficiency, and nutrient uptake. This review discusses the role of plant growth-promoting microorganisms (PGPMs) as biofertilizers, providing an alternative to harmful agrochemicals. PGPMs can improve soil health and promote plant growth when applied to soil, seeds, or plant surfaces, reducing reliance on synthetic fertilizers and pesticides. Additionally, nanotechnology in agriculture is examined, illustrating how nanomaterials (NMs) and nano-based fertilizers can enhance nutrient absorption and increase crop yields. Beyond these scientific approaches, there is an urgent need to implement novel agricultural practices that support sustainability. The world population is growing at a disquieting rate, placing tremendous pressure on natural resources. This threatens future generations' access to nutritious food and clean air. Innovative approaches like climate-smart agriculture, organic farming, biodynamic agriculture, sustainable intensification, and regenerative agriculture, along with practices such as integrated farming systems, precision agriculture, integrated nutrient management, and integrated pest management, have proven to safeguard agricultural sustainability. By integrating these innovative approaches and practices, it is possible to meet the increasing demands for food while preserving the environment.

Attracting investments through crowdfunding platforms as a method for agro-industrial enterprises to enter the international market

Since agriculture is an important sector of the Russian economy, the problem of lack of capital in this sector is still relevant. The article shows that in the era of digital technologies, new sources of fundraising are emerging in the agro-industrial complex. Crowdfunding is one of such modern sources of financing in the world practice which is able to significantly expand the basis of the investment pyramid of the agricultural sector. In the course of the study, a review of domestic and foreign literature on this method of raising funds was conducted. General scientific methods were used: observation, comparison, measurement, analysis and synthesis, the method of logical reasoning, and specific scientific method of static analysis. A critical review of domestic and foreign practice has shown the main advantages and disadvantages of attracting financing through crowdfunding platforms. Also, as a result of the conducted research, it was found that this way of attracting investments not only solves problems of financing the agricultural sector, but is also a successful method for agricultural enterprises to enter foreign markets. In the era of innovative finance, this article contributes to the growing literature and initiatives to introduce and develop crowdfunding in the agri-food industry.

Climate model selection via conformal clustering of spatial functional data

AbstractClimate model selection stands as a critical process in climate science and research. It involves choosing the most appropriate climate models to address specific research questions, simulating climate behaviour, or making projections about future climate conditions. This paper proposes a new approach, using spatial functional data analysis, to asses which of the 18 EURO CORDEX simulation models work better for predicting average temperatures in the Campania region (Italy). The method involves two key steps: first, using functional data analysis to process climate variables and select optimal models by a hierarchical clustering procedure; second, validating the chosen models by proposing a new conformal prediction approach to the anomalies associated to each cluster.

Sociotechnical Imaginaries of Sharing and Emerging Postdigital Meaning-Making Practices in the Astronomy Community

AbstractFor decades, science communities have had digital technology embedded in their everyday work. However, new research infrastructures are amplifying the presence and use of digital technologies for scientists. In that respect, radio astronomy is undergoing a major transformation causing the community to enter a phase of postdigital work, due to the construction of the most sensitive telescope, the Square Kilometer Array Observatory (SKAO), which scales the presence of digital technology and the amount of data generated. As new digital research infrastructure is set up, sociotechnical imaginaries—symbols and visions of a shared future—emerge, while others become obsolete thus impacting structures and practices of meaning-making. In this paper, we explore the disruptive potential of sociotechnical imaginaries and how astronomers using SKA pathfinder and precursor telescope data respond to these imaginaries and incorporate them into their meaning-making. The analysis shows that postdigital imaginaries related to data circulation, storage, archiving, and reuse have been amplified as SKA facilities and services are set up. Two changes are highlighted regarding a new postdigital condition within the astronomy community. Firstly, as astronomers engage in new postdigital forms of collaboration, they need to reach a consensus on what types of analyses to use by agreeing which methods are appropriate. This affects how scientific questions and research proposals are negotiated collectively, impacting the agency of astronomers. Secondly, as digital tools are increasingly part of astronomers’ daily work, they have to rely on new data analysis methods, which determine what evidence is uninteresting. Overall, these changes pose new questions regarding how meaning-making processes are altered and the way science is undertaken because of these new entanglements of human and non-human actors.

The Role of Value Orientations of High School Students in the Process of Choosing a Professional Activity

This article delves into the intricate details of research that focuses on analyzing specific aspects of value orientation in the process of high school students determining their future professional paths. The study delves into the essence of self-determination in the professional realm, identifies the problem, offers solutions, and pinpoints factors for successful implementation. It underscores the crucial role of a complex value orientation in personality development and individuality formation. An individual's attitude towards themselves, the world, and the future, including their career, is reflected through priorities and values. These value orientations can serve as a dependable guide for high school students when making successful professional choices. The conducted research supports the hypothesis that value orientation is an essential factor in shaping a mature personality. Value orientation plays a pivotal role in making informed decisions about future careers. Labor value orientations are particularly important and can serve as a solid foundation for high school students as they navigate their professional paths.The purpose of this study is to study the influence of Labor value orientation on the process of professional self-determination of modern high school students.To achieve the purpose of the research, various methodological approaches are used, including systemic, socio-psychological and axiological approaches oriented on the humanist principle. Various methods have been used to conduct research, including theoretical analysis of scientific research, organizational approaches, and empirical methods such as observation, questionnaires, and psychodiagnostic methods.This article conducted a bibliometric analysis of the problem, as well as empirical research. Thanks to the experiment carried out, it turned out that most of the high school students surveyed suffer from a certain anxiety that prevents them from choosing professional preferences that correspond to their abilities, desires and needs.

Technological advances and challenges of reclaimed asphalt pavement (RAP) application in road engineering-a bibliometric analysis from 2000 to 2022.

Reclaimed asphalt pavement (RAP) is a valuable material that can be recycled and reused in road engineering to reduce environmental impact, resource utilization, and economic costs. However, the application of RAP in road engineering presents both opportunities and challenges. This study visually analyzes the knowledge background, research status, and latest knowledge structure of literature related to RAP using scientific metric methods such as VOSviewer and Citespace. The Web of Science (WoS) core collection database identified 2963 research publications from 2000 to 2022. Collaborative networks between highly cited references, journals, authors, academic institutions, countries, and funding organizations are analyzed in this study, along with a co-occurrence analysis of keywords for the RAP research publications. Results showed that the USA has long been a leader in RAP research, China surpassed the USA in annual publication output in 2019, increasing from 2 publications in 2002 to 177 publications in 2022, and has made significant investments in technological aspects. Chang'an University ranked first in total publication output (131 publications, 4.4%). Current major research themes include road performance, recycling technology, regeneration mechanisms, and the life cycle assessment of RAP. In addition, based on cluster analysis of keywords, text content analysis, and SWOT analysis, this study also discusses RAP's challenges and future development directions in road engineering. These findings provide scholars with valuable information to gain insight into technological advances and challenges in the field of RAP.

Digital marketing business models: Key stages, types and trends of development

The main goal of the article is to formalize the key business models of marketing of modern companies and substantiate the key stages, types and trends of development. The relevance and need to pay significant attention to the marketing digital business model when organizing a business is substantiated. Using structural and logical analysis and criticism of scientific research, the essence, advantages and disadvantages are determined, the main blocks, stages and key elements of the structure of business models of modern companies are argued. It has been proven that marketing digital business models serve as a logical and visual plan for organizing all business processes of companies from production, marketing, sales and logistics to building a hierarchy of profitability. The key development trends are substantiated and the most popular business models of business organization in modern conditions are structured on the basis of scientific generalization, structural and logical analysis and mathematical modeling. Practical significance is characterized by the fact that the marketing business models of world-class companies are generalized and structured, taking into account their specifics and characteristics. Practical recommendations and key stages of building a company’s business model and its implementation into reality have been formed to achieve strategic business goals.

Prerequisites-based course recommendation: recommending learning objects using concept prerequisites and metadata matching

The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate background knowledge to cognitively receive the recommended learning objects. For that reason, when designing an efficient e-learning recommendation method, these challenges should be considered. To address those issues, in this paper, we first propose extracting pairs concept prerequisites using Linked Open Data (LOD). Then, we evaluate the proposed list of prerequisite relationships using machine learning predictive models. Then, we present the recommendation approach based on matching concept’s prerequisites relation and courses metadata through a similarity score. The experimental result of prerequisite identification was evaluated using four well-known machine learning algorithms while achieving an accuracy of 90%. Moreover, using three known evaluation metrics, the final prerequisite-based recommendation demonstrates very good results (NDCG@10 = 86%). This solution will enhance recommendations on online learning platforms. Additionally, it will overcome the cold-start issue and accomplish the needed prerequisites and background knowledge for learners to attain their learning objectives.

Bibliometric Analysis of Scientific Publications on Communicative Behavior Problems

Purpose of research. The purpose of the study is to analyze the dynamics of the publication activity of scientific research in the field of studying communicative behavior. Communicative behavior is an object with an interdisciplinary research status. It falls into the area of research interest of various scientific fields. A bibliometric analysis of publication activity was carried out in connection with solving several tasks: to find out areas of knowledge in which the greatest publication activity is concentrated, to study the methods that are used in various fields of communicative behavior analysis, to identify organizations that are included in this research search.Methods. The study was conducted in two scientific electronic databases: the Russian Scientific Electronic Library Elibrary.ru and the international open platform for researchers and scientific organizations Lens. The bibliometric analysis was used as the research method. It involves the quantification of documentary information flows and it is based on quantitative research indicators reflecting the state of science as a whole or its individual branches.Results. As a result of the bibliometric analysis of publication activity on the problems of scientific research in the field of communicative behavior, communicative behavior in the digital environment and communicative behavior in social networks, a significant increase in publication activity was revealed in both international and Russian information databases over the past 10 years (2013 - 2023). It is also noted that the predominant number of publications on the issues studied is concentrated in the field of psychology. However, we can trace a shift in the focus of foreign research on communicative behavior towards digitalization in information technology, and Russian research towards the field of digital technologies in the educational environment.Conclusion. The results obtained indicate the high relevance, as well as the scientific and practical significance of the research topic on the problems of communicative behavior in general, as well as communicative behavior in the digital environment and social networks, in particular.

The Research of Collaborative System of Remote Sensing Monitoring Based on Bimodal Cloud

Abstract. Cloud service is based on cloud computing, Offering a On-Demand service to every terminal equipment of computing resource pool. This paper designed and developed a coordinated operating system based on bimodal cloud. This system is taken mutual scheduling mechanism into account, which is capable of storing massive amounts of heterogeneous remote sensing data and provides fast indexing of data based on various characteristics, integrated Satellite transit forecast, DOM Produce, coordinated change information extraction and results sharing based on Nginx load balancing, in addition, the system designed two layer security system to ensure the safety of data results.The "YunYao" geographic information service rendering engine built on the dual-state cloud platform significantly outperforms mainstream platforms in the same testing environment. Its rendering speed surpasses ArcGIS Desktop by more than two times, exceeds GeoServer by more than four times, and is over seven times faster than ArcGIS Server. Remote sensing practitioners can quickly and conveniently utilize this system, while providing convenient functionalities that enable remote sensing scientists to independently conduct scientific research and development using this system. Experimentation and practice shows that this system simplified routine work flow, improved work efficiency, has a important reference meaning to remote sensing monitoring.

Types of Personality According to the Development Level of Social Intelligence

The problem of the fact associated with the scientific reflection of the processes that create typological relationships in modern psychological research is not high enough. In social and humanity sciences, there are procedures for simplifying this area as a logical and methodological basis for the development of typological and structural components. The article discusses the problem of personality typology in psychology and analyzes the results of the research on defining the specifics of the methodology of studying personality types based on the levels of social intelligence that ensured personality maturity. As a result of scientific research, the psycho types are divided into 4 types: imperative, declarative, explicit, and implicit, which differ from the function and level of social intelligence of a person as well as the correlational relations between indicators of social intelligence cluster of personality types have been determined.