bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent clinical and pharmacological advancements of incretin-based therapy and the effects of incretin on physiology
Authors: Pal Bhaskar , Chattopadhyay Moitreyee 
Published: March 2024

Abstract
A novel therapeutic target for diabetes mellitus is incretin-based therapies, glucagon-like peptide-1, and glucose-dependent insulinotropic polypeptides are released from the gastrointestinal (GI) tract and act on beta cells of pancreatic islets by increasing the secretion of insulin. The management and prevention of diabetes require habitual and pharmacological therapies along with quality and healthy lifestyle. This includes maintaining the body weight, blood glucose level, cardiovascular risk, complexity, and co-morbidities. The utilization of glucagon-like peptide-1 (GLP-1) agonists is an object of research with favorable hemoglobin A1C levels and weight loss in type 1 diabetic patients. However, cost-effectiveness and tolerability, remain significant barriers for patients to using these medications. The risk of suicidal tendencies and thoughts of self-harm have been increased in patients receiving GLP-1 receptor agonists. Tirzepatide treatment showed a potent glucose-lowering effect and promoted weight loss with minimum GI adverse effects in animal studies as well as phase I and II human trials, in comparison with established GLP-1 receptor agonists. The glucose-dependent insulinotropic polypeptide receptor (GIPR) peptide-antagonist effectively blocks the action of gastric-inhibitory-polypeptide (GIP) in vitro and ex vivo in human pancreas and in vivo in rodent models. However, incretin-based therapies have received enormous attention in the last few decades for the treatment of diabetes, obesity, and other repurposing including central nervous system disorders. Therefore, in this article, we demonstrate the overview, physiological, and pharmacological advances of incretin-based pharmacotherapies and their physiological roles. Furthermore, the recent updates of glucagon-like peptide-1 receptor agonist, Glucagon-like peptide-2 receptor agonist, GLP-1/GIP co-agonists, GIP/GLP-1/glucagon triple agonist and GIP-antagonist are also discussed.
Original article Tracks of educational policy of the Emperor Alexander I St. Petersburg State Transport University under the ‟Priority-2030” program
Authors: Pokrovskaya O. D. 
Published: March 2024

The article examines the results of the implementation of the main tracks of the development program of the Emperor Alexander I St. Petersburg State Transport University (PGUPS) in the framework of participation in the strategic academic leadership program ‟Priority-2030”. Using the example of educational policy, the transformation of the scientiﬁc and educational ecosystem of the university as a third-generation university in the modern educational space is shown.The purpose of the study is to formulate the key results achieved by the staﬀ of the PGUPS as a result of participation in the Priority-2030 program.Priority-2030 is a large-scale state program to support the activities of Russian universities and is being implemented within the framework of the national project ‟Science and Universities”. The Priority-2030 program is aimed at improving Russia’s competitiveness in the ﬁeld of education, science and technology. It was launched on June 24, 2021, and its implementation period assumes 10 years.The methods of system analysis, theory of synergetics, project management and innovation were used.The key results of the implementation of the educational policy of PGUPS aimed at achieving strategic academic leadership within the framework of Priority-2030 are presented.
Improving the process of handing over passenger trains at passenger and passenger technical stations
Authors: Parshin P. K. , Pokrovskaya O. D. , Suyunbayev Sh. М. 
Published: March 2024

Measures were considered to increase the processing capacity of passenger and passenger technical stations by using the potential of existing railway automation and telemechanics systems with which railway stations are equipped, as well as by revising a number of requirements of regulatory acts of the Ministry of Transport of the Russian Federation and JSC Russian Railways.Materials from open sources on the Internet, systems theory, regulations of the Ministry of Transport of the Russian Federation, JSC Russian Railways, comparison of “as is” and “as will be” were used.Based on the results of the study, speciﬁc measures were proposed to increase the processing capacity of passenger and passenger technical stations by accelerating the processes of rearranging passenger trains during shunting work.
Managerial aspects spects of digitalization of the transport and logistics ecosystem
Authors: Lyubimenko A. I. , Fursova E. A. 
Published: March 2024

A virtual organization is the newest form of business organizations, one of the forms of which are distributed companies with their own production facilities and transport and logistics resources, or using the services of production and logistics centers located on diﬀerent continents and in diﬀerent countries, forming project/matrix management structures, attracting specialists from diﬀerent countries. The article discusses the advantages and risks of managing distributed organizations based on digital technologies. The authors characterize the ﬁelds of activity of distributed companies and assess the potential for their expansion. The trend towards digitalization of management processes determines the logic of transformation of the organizational structure model from a traditional hierarchical to an open, ﬂexible one. It is shown that transportation and logistics functions are critically important in ensuring the activities of distributed organizations, within the framework of which the transfer of raw materials, materials in progress, ﬁnished products, goods between production centers, sales centers, intermediaries of various kinds, customers and end consumers is realized.The following research methods were used: scientiﬁc review, monitoring, situational, retrospective and prospective analysis, as well as critical assessment and formulation of author’s judgments and conclusions on the scientiﬁc basis of leading scientists and specialists in the ﬁeld of economics, management, logistics, operational work management.
Transformation of business systems and international logistics technologies under the influence of digitization trends
Authors: Kott A. G. , Legkodymov D. A. , Fursova E. A. 
Published: March 2024

The scientiﬁc article reﬂ ects the main results of a comprehensive researching of the process of transformation of business systems and international logistics technologies under the inﬂuence of digitalization trends, primarily artiﬁcial intelligence, in the context of the widespread introduction of Industry 4.0 conceptual approaches into economic, production and distribution cycles.In the context of the globalization of the economy and the rapid development of technology, key changes in the processes of managing integrated supply chains under the inﬂuence of digital technologies and intelligent systems are considered. The aspects discussed in this article, ranging from digital tools in warehouse management to the use of blockchain and artiﬁcial intelligence in international logistics, highlight the importance of innovation in this area. Modern technologies such as warehouse management systems, robotic technologies, blockchain and artiﬁcial intelligence show potential for improving the eﬃciency of logistics processes and optimizing costs.The scientiﬁc signiﬁcance of this study lies in understanding these technological changes and their impact on international logistics structures. The emphasis in the work is on identifying the main trends aﬀecting the eﬃciency and sustainability of logistics systems in the context of digitalization at the present stage of scientiﬁc and technological progress and informatization of society. In conditions of constant competition, the timely introduction of new technologies is one of the critical factors for the successful positioning of a company in the market.
The use of quality tools to improve the efficiency of international transport corridors
Authors: Basyrov I. M. , Mezentseva P. M. , Gvozdkova A. I. , Novoseltseva E. A. 
Published: March 2024

In the context of the development of international trade and economic integration the opening of new international transport corridors (ITC) is becoming an urgent issue of ensuring the optimization of logistics processes, reducing time costs and improving the quality of service.This article discusses a comprehensive approach to improving international transport corridors, including the use of various quality and strategic planning tools. Each of these tools has its own characteristics and goals, but the overall objective is to improve processes, eliminate obstacles and improve the eﬃciency of the ITC. Some of the quality tools discussed in the article include: route optimization methods, resource and infrastructure management, as well as the use of information technology to monitor and manage processes within international transport corridors.Also, the use of quality tools will allow for cooperation and coordination between various participants of the ITC, such as the state, transport companies, freight forwarders and logistics services, which will ultimately contribute to the development of international trade and ensure a more sustainable and eﬃcient logistics infrastructure.
Methodological aspects of economic policy directions in relation to business structures in the region
Authors: Полянин А.В. , Родионов Д.Г. 
Published: March 2024

В статье рассматриваются методологические аспекты различных направлений экономической политики в отношении предпринимательских структур региона. Авторы анализируют основные стратегии и инструменты, используемые государственными органами для поддержки и развития предпринимательства на региональном уровне. Рассматриваются преимущества и недостатки различных подходов к стимулированию предпринимательской активности, а также их влияние на экономическое развитие региона. Делается упор на необходимости комплексного подхода к разработке и реализации экономической политики в сфере предпринимательства, а также на значимости сотрудничества государственных органов, бизнес-сообщества и общественных организаций для достижения положительных результатов в этой области. Детализированы шесть основных аспектов методологи региональной экономической политики в отношении предпринимательских структур: содействие развитию предпринимательского климата, стимулирование инноваций, привлечение инвестиций, развитие кадрового потенциала, формирование специализированных индустриальных и агроиндустриальных кластеров, организация межрегионального сотрудничества.
The article examines the methodological aspects of various directions of economic policy in relation to the business structures of the region. The authors analyze the main strategies and tools used by government agencies to support and develop entrepreneurship at the regional level. The advantages and disadvantages of various approaches to stimulating entrepreneurial activity, as well as their impact on the economic development of the region, are considered. The article focuses on the need for an integrated approach to the development and implementation of economic policy in the field of entrepreneurship, as well as on the importance of cooperation between government agencies, the business community and public organizations to achieve positive results in this area. Six main aspects of the methodology of regional economic policy in relation to entrepreneurial structures are highlighted and detailed: promoting the development of an entrepreneurial climate, stimulating innovation, attracting investment, developing human resources, forming specialized industrial and agroindustrial clusters, and organizing interregional cooperation.
Kelayakan Usaha Ternak Kelinci dengan Pemberian Pelet Limbah Pertanian
Authors: Lutfiaji Syaefullah Bangkit , Purwanta  , Okti Widayati  , Poppy Latifah  
Published: March 2024

Latar belakang: Potensi usaha kelinci saat ini cukup besar sebagai ternak hias maupun ternak konsumsi. Akan tetapi, kurangnya pengetahuan peternak dalam pemanfaatan limbah pertanian sebagai sumber pakan kelinci pengganti hijauan. Usaha yang dijalankan perlu memperhitungkan kelayakan usahanya, sehingga dalam penelitian ini akan melihat kelayakan usaha ternak kelinci yang diberikan pelet dari limbah pertanian.
Metode: Metode penelitian yang dilakukan adalah metode eksperimental sebanyak 24 (dua puluh empat) ekor. Penelitian dilaksanakan selama 2 (dua) bulan pemeliharaan kelinci dengan 4 (empat) perlakuan dan 3 (tiga) ulangan, selanjutnya hasil pemeliharaan dianalisis ekonominya.
Hasil: Hasil penelitian analisis analisis kelayakan usaha pada setiap perlakuan menunjukan nilai yang tidak berbeda pada biaya, penerimaan, pendapatan, break even point, R/C, rentabilitas, IOFC dan Harga Pokok Produksi.
Kesimpulan: Pemberian pelet dari limbah pertanian sebagai pakan ternak yang berbeda komposisi pada kelinci tidak berbeda akan tetapi dinyatakan layak.
Examining Teacher Well-Being: An Analysis of Resources Needs
Authors: Costa Christina Naegeli , Chandarlis Elias , Park Nansook 
Published: March 2024

This quantitative research explores the resource needs, challenges, and strengths of teachers and their influence on teacher well-being. Adopting a descriptive design with surveys as the primary instrument, the study aims to shed light on teacher well-being from a strengths-based perspective, a departure from the prevailing focus on stress and burnout in existing literature. Teachers operate in environments characterized by high stress and potential burnout, stemming from the demanding nature of their profession and encountering stressors across interpersonal, organizational, and institutional levels. Despite these challenges, most teachers demonstrate resilience and commitment to their work. However, there is a noticeable gap in research focusing on how teachers thrive and experience positivity within their school environments. Utilizing the Job-Demands Resources (JD-R) model as a theoretical framework, this study examines the relationship between resources and teacher well-being. The findings offer valuable insights into teacher resource needs and their overall well-being, which have practical implications for teacher training, professional development programs, and policy-making. These implications are aimed at mitigating teacher attrition, stress, and burnout while fostering resilience and well-being among educators. Furthermore, the study contributes to the refinement of the JD-R model and the broader understanding of teacher well-being. By providing a deeper insight into the mechanisms underlying teacher resilience, the findings serve as a foundational basis for future research in this critical domain.

Received: 2 February 2024 | Revised: 6 March 2024 | Accepted: 12 March 2024

Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.

Data Availability Statement
Data sharing is not available due to IRB protection of confidentiality set at the time of data collection. If you are interested in viewing deidentified data, please contact the first author.
SYNTHESIZING AI'S IMPACT ON CYBERSECURITY IN TELECOMMUNICATIONS: A CONCEPTUAL FRAMEWORK
Authors: Philip Olaseni Shoetan  , Olukunle Oladipupo Amoo  , Enyinaya Stefano Okafor  , Oluwabukunmi Latifat Olorunfemi  
Published: March 2024

As the telecommunications sector increasingly relies on interconnected digital infrastructure, the proliferation of cyber threats poses significant challenges to security and operational integrity. This review presents a conceptual framework for understanding and harnessing the potential of artificial intelligence (AI) in fortifying cybersecurity within the telecommunications industry. The framework integrates the transformative capabilities of AI with the unique demands of cybersecurity in telecommunications, aiming to enhance threat detection, mitigation, and response strategies. It encompasses a multidimensional approach that encompasses both technical and organizational facets, recognizing the interconnectedness of technology, human factors, and regulatory environments. Firstly, the framework delves into the application of AI in bolstering proactive threat intelligence gathering and analysis. Through advanced algorithms and machine learning techniques, AI empowers telecom operators to identify anomalous patterns, predict potential vulnerabilities, and pre-emptively adapt defensive measures. Secondly, it explores AI-driven solutions for dynamic risk assessment and adaptive cybersecurity protocols. By leveraging real-time data analytics and automated decision-making, telecom networks can swiftly adapt to evolving threats and ensure continuous protection against intrusions or breaches. Furthermore, the framework emphasizes the role of AI in augmenting human capabilities through intelligent automation and cognitive assistance. By offloading routine tasks and providing context-aware insights, AI enables cybersecurity professionals to focus on strategic initiatives and complex threat scenarios. Lastly, the framework addresses the imperative of ethical considerations, accountability, and transparency in deploying AI for cybersecurity in telecommunications. It advocates for responsible AI governance frameworks that prioritize privacy, fairness, and bias mitigation while fostering collaboration across industry stakeholders. In summary, this conceptual framework provides a roadmap for harnessing AI's transformative potential to fortify cybersecurity resilience in telecommunications, thereby safeguarding critical infrastructure and ensuring the integrity of global communication networks.
Keywords: AI, Cybersecurity, Telecommunication, Framework, Conceptual, Impact, Review.
DATA PRIVACY AND SECURITY IN IT: A REVIEW OF TECHNIQUES AND CHALLENGES
Authors: Oluwatoyin Ajoke Fayayola  , Oluwabukunmi Latifat Olorunfemi  , Philip Olaseni Shoetan  
Published: March 2024

In today's interconnected digital world, data privacy and security have emerged as paramount concerns for individuals, organizations, and governments alike. This review provides a comprehensive review of techniques and challenges surrounding data privacy and security in information technology (IT) systems. The review begins by outlining the significance of data privacy and security in IT, emphasizing the proliferation of sensitive information stored and transmitted across various digital platforms. With the exponential growth of data collection, storage, and processing, ensuring the confidentiality, integrity, and availability of data has become imperative. Next, the review delves into the techniques employed to safeguard data privacy and security in IT environments. Encryption techniques, such as symmetric and asymmetric cryptography, play a crucial role in protecting data from unauthorized access and interception. Additionally, access control mechanisms, including authentication and authorization protocols, help manage user privileges and restrict unauthorized entry into sensitive data repositories. Furthermore, anonymization and pseudonymization techniques are utilized to conceal personally identifiable information (PII) and mitigate the risk of identity theft and privacy breaches. Moreover, the review discusses the challenges associated with data privacy and security in IT ecosystems. These challenges include the evolving nature of cyber threats, such as malware, ransomware, and social engineering attacks, which constantly test the resilience of IT defenses. Additionally, compliance with regulatory frameworks, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), presents significant challenges for organizations striving to adhere to stringent data protection standards while maintaining operational efficiency. Furthermore, emerging technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), introduce novel security risks and privacy concerns due to their interconnected nature and reliance on vast amounts of data. In conclusion, the review underscores the critical importance of continuously evaluating and enhancing data privacy and security measures in IT systems to mitigate risks, comply with regulations, and foster trust among stakeholders in an increasingly digitalized world.
Keywords: Data, Privacy, Security, IT, AI.
PREDICTING STOCK MARKET MOVEMENTS USING NEURAL NETWORKS: A REVIEW AND APPLICATION STUDY
Authors: Adedoyin Tolulope Oyewole  , Omotayo Bukola Adeoye  , Wilhelmina Afua Addy  , Chinwe Chinazo Okoye  , Onyeka Chrisanctus Ofodile  , Chinonye Esther Ugochukwu  
Published: March 2024

In the rapidly evolving landscape of financial markets, the quest for accurate stock market predictions has never been more critical. This paper delves into the transformative potential of neural network models in forecasting stock market movements, offering a comprehensive examination of their effectiveness compared to traditional predictive models. With a focus on the evolution of stock market prediction methodologies, this study aims to uncover the nuanced dynamics of neural networks, their comparative analysis with other models, and the pivotal role of data preprocessing in enhancing prediction accuracy. Employing a qualitative analysis framework, the research meticulously synthesizes findings from selected studies, highlighting the superior performance of neural network models in capturing complex market patterns and adapting to volatility. The results underscore the significant impact of data quality and quantity, architectural nuances of neural networks, and the strategic implications for investors navigating the stock market's unpredictability. Despite the promising outcomes, the study acknowledges inherent challenges in the real-world application of these models, including data imperfections and the complexity of financial ecosystems. Conclusively, the paper advocates for ongoing innovation, interdisciplinary collaboration, and the strategic integration of advanced neural network architectures to overcome existing limitations. Recommendations emphasize the critical need for high-quality, diverse datasets and continuous model refinement to harness the full predictive power of neural networks in stock market forecasting. This study not only illuminates the path forward for investors and financial analysts but also sets the stage for future research in this dynamic field.
Keywords: Neural Network Models, Stock Market Prediction, Data Preprocessing, Model Accuracy, Financial Markets, Innovation.