Reviewerly/exHarmony huggingface dataset:
Prospects for the legalization of cryptocurrency in Ukraine, based on the experience of other countries

Presently, legal circles, both among theorists and practitioners, are particularly concerned about the legalisation of cryptocurrencies and transactions with them according to the current legislation. For this reason, the purpose of this work was to study approaches and methods to legalisation of income derived from cryptocurrency speculation based on the provisions of the tax legislation of Ukraine. A theoretical analysis of the general concepts under study was conducted, which in turn formed the object of this study. The common and distinctive features of the researched concepts were identified, thus establishing the relationship and dependence between them. As for the practical aspects, the study revealed them in the analysis of particular regulations, namely, the specific features of their implementation. Positions and opinions of various scholars on it were compared, which allowed for a qualitative coverage of ways to legalise the income that citizens receive from cryptocurrency speculation. On the basis of the analyzed scientific publications, the most successful and suitable for implementation in Ukraine, the experience of other countries, in particular the USA and Canada, has been determined. It has been proven that the legalization of citizens’ incomes received from cryptocurrency transactions is a necessary process for the economic development of the state.The practical value of the study lies in the fact that it can be used both by scholars, in the context of the primary source for further study of this issue, and by lawyers whose activities are related to cryptocurrencies. The scientific value of this study was covered in the description of effective approaches to transactions with income generated by cryptocurrencies, which have not yet been studied to the required level
Reducing Stress and Anxiety in the Metaverse: A Systematic Review of Meditation, Mindfulness and Virtual Reality

Meditation, or mindfulness, is widely used to improve mental health. With the emergence of Virtual Reality technology, many studies have provided evidence that meditation with VR can bring health benefits. However, to our knowledge, there are no guidelines and comprehensive reviews in the literature on how to conduct such research in virtual reality. In order to understand the role of VR technology in meditation and future research opportunities, we conducted a systematic literature review in the IEEE and ACM databases. Our process yielded 19 eligible papers and we conducted a structured analysis. We understand the state-of-art of meditation type, design consideration and VR and technology through these papers and conclude research opportunities and challenges for the future.
Risk-Aware Navigation for Mobile Robots in Unknown 3D Environments

Autonomous navigation in unknown 3D environments is a key issue for intelligent transportation, while still being an open problem. Conventionally, navigation risk has been focused on mitigating collisions with obstacles, neglecting the varying degrees of harm that collisions can cause. In this context, we propose a new risk-aware navigation framework, whose purpose is to directly handle interactions with the environment, including those involving minor collisions. We introduce a physically interpretable risk function that quantifies the maximum potential energy that the robot wheels absorb as a result of a collision. By considering this physical risk in navigation, our approach significantly broadens the spectrum of situations that the robot can undertake, such as speed bumps or small road curbs. Using this framework, we are able to plan safe trajectories that not only ensure safety but also actively address the risks arising from interactions with the environment.
An Extensive Evaluation of New Federated Learning Approaches for COVID-19 Identification

The World Health Organization (WHO) proclaimed the coronavirus of 2019 (COVID-19) a global pandemic in March 2020. Effective testing is essential to stop the epidemic from spreading. Using various clinical symptom data, artificial intelligence and machine learning approaches can aid in COVID-19 detection. While the federated learning (FL) strategy depending on decentralized data helps safeguard data privacy, a crucial factor in the health domain, the deep learning (DL) approach requiring centralized data is exposed to a significant risk of data privacy breaches. With an emphasis on both, this chapter examines current developments in using DL and FL approaches for COVID-19 identification.
Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery

The use of autonomous robots for delivery of goods to customers is an exciting new way to provide a reliable and sustainable service. However, in the real world, autonomous robots still require human supervision for safety reasons. We tackle the real-world problem of optimizing autonomous robot timings to maximize deliveries, while ensuring that there are never too many robots running simultaneously so that they can be monitored safely. We assess the use of a recent hybrid machine-learning-optimization approach COIL (constrained optimization in learned latent space) and compare it with a baseline genetic algorithm for the purposes of exploring variations of this problem. We also investigate new methods for improving the speed and efficiency of COIL. We show that only COIL can find valid solutions where appropriate numbers of robots run simultaneously for all problem variations tested. We also show that when COIL has learned its latent representation, it can optimize 10% faster than the GA, making it a good choice for daily re-optimization of robots where delivery requests for each day are allocated to robots while maintaining safe numbers of robots running at once.
Evolutionary Multi-Objective Deep Reinforcement Learning for Autonomous UAV Navigation in Large-Scale Complex Environments

Autonomous navigation of Unmanned Aerial Vehicles (UAVs) in large-scale complex environments presents a significant challenge in modern aerospace engineering, as it requires effective decision-making in an environment with limited sensing capacity, dynamic changes, and dense obstacles. Reinforcement Learning (RL) has been applied in sequential control problems, but the manual setting of hyperparameters, including reward functions, often results in suboptimal solutions and inadequate training. To address these limitations, we propose a framework that combines Multi-Objective Evolutionary Algorithms (MOEAs) with RL algorithms. The proposed framework generates a set of non-dominating parameters for the reward function using MOEAs, leading to diverse decision-making preferences, efficient convergence, and improved performance. The framework was tested on the autonomous navigation of UAVs and demonstrated significant improvement compared to traditional RL methods. This work offers a novel perspective on the problem of autonomous UAV navigation in large-scale complex environments and highlights the potential for further improvement through the integration of RL and MOEAs.
A Research Framework Focused on AI and Humans instead of AI versus Humans

Despite lacking a shared understanding and a generally accepted definition, Artificial intelligence (AI) is promoted and credited with miraculous abilities to solve all problems. To gain a more nuanced and deeper understanding of the design trade-offs associated with AI, this paper proposes a research framework that contrasts two competing frameworks: (1) AI versus Humans (characterized by strong AI and Artificial General Intelligence) focused on replacing human beings and (2) AI and Humans (characterized by intelligence augmentation and human-centered AI) focused on empowering human beings as individuals and communities. The arguments in the paper are supported by research activities that explored conceptual frameworks and inspiring prototypes. These developments have resulted in gaining a deeper understanding of how AI-type systems can contribute to quality of life aspects with a specific focus on rethinking and reinventing learning, education, working, and collaboration in the digital age.
Smart contract applications in tourism

Based on blockchain technology, smart contracts promise to revolutionize the way parties legally agree. Smart contracts could enable tourism service providers to trade directly with customers bypassing some intermediaries. The study aims at identifying the provided services, economic impact, partners, popularity, technical and technological factors of smart contract applications in various tourism areas. It investigates ten popular smart contract applications that cover a wide spectrum of tourism areas such as hotel reservations, airline tickets, car rentals, payment management, reward programmes, traveller identity, luggage tracking, validity of reviews and ratings and more. These applications are analysed with respect to their purpose, business model, economic impact, partners, provided services, popularity, as well as what cryptocurrency and blockchain they use. Smart contracts enable time and transaction cost savings, convenience, flexibility, security, trust, ease verification of personal data and more. Most applications gained popularity mainly during 2018–19. Almost every application uses a different cryptocurrency. Ethereum is the most popular platform followed by Hyperledger Fabric and Stellar. The development of a universal legislation as well as interoperability is a necessity for the wide adoption of smart contracts.
Digitalization and the prospects of cryptocurrency in Islamic finance

Are the principles of Islamic finance compatible with cryptocurrency? In the current age of digital transformation, to be followed perhaps by a quantum transformation in computing, plus the involvement of central banks, resource scarcity and climate change, this is the issue addressed in the article. Financial transactions are central to digitalization through fintech and other services. This conceptual article highlights the essentials of cryptocurrency, its history, structure and how it works. Different types of cryptocurrency mining will be examined and explained in detail. The primary purpose of this research is to investigate the extent to which cryptocurrency structure complies with the maxims of Islamic finance. The article discusses the question in relation to sharia jurisprudence and conformity with the views of Islamic finance scholars. Our discussion extends the rapidly growing literature on cryptocurrency by examining its compatibility with the conceptions of Mal (‘money’) in sharia and Islamic scholarship and its status as fiat money. Taking the view that despite recent glitches, cryptocurrency has a future in the financial ecosystem, we sketch the challenges of facing the introduction of cryptocurrency into Islamic finance. The research has profound policy implications: for the protocols and systems adopted by Islamic financial institutions, their regulation and the role of miners. This research is particularly relevant to avoiding the pitfalls that have so often befallen conventional financial institutions.
Artificial Intelligent Systems and the Problem of “Natural” Trust

The development of AI technologies has heightened the problem of humanitarian challenges at all levels of social regulations. Ethical issues and, in particular, the problem of trust have become relevant to the field of high technology, given the fact that AI performs increasingly significant managerial functions that previously could only be performed by humans. This issue is directly related to artificial intelligence systems, which have already been embodied in specific extensive projects. In this study, the authors analyze the concept of trust through the prism of technological development. For this purpose, the study presents an overview of historical and contemporary interpretations of the concept of trust and proves that this concept is relevant and necessary to control the risks that arise when integrating AI products into social life. The authors show that a rethinking of the concepts of ethics and morality in the new context is required. This is a necessary requirement for the creation of trusted AI and for the achievement of trust in human interaction with technology products. The authors conclude that it is necessary to build an interdisciplinary dialogue to integrate theory and practice from numerous fields. To do this, it is necessary to create a common knowledge base and a platform for communication between all stakeholders, but it is also important to create favorable conditions for sustainable and constructive interaction. Therefore, trust is a relevant concept that needs to be constructed in a multidimensional frame of reference that targets different stakeholders and also takes into account interaction between human and technology, in other words, at all levels and on all scales.
DIGITAL TRANSFORMATION OF THE GLOBAL EDUCATION MARKET

The global education market is undergoing significant changes due to modern digitalisation. The latest technologies are significantly changing learning technologies, the structure of education, international flows and their volume in general. The subject of the study is to assess the impact of digital transformation on the global world market. The aim of this article is to analyse the development processes of the global market for educational services in the context of modern challenges, in particular digital transformation, and its consequences for the higher education market. The methodology of the study included research, a review of scientific literature, graphic visualisation of digitalisation. The methods of system analysis and generalisation have made it possible to identify the main directions of transformation of the global and regional educational markets, to characterise the dynamics of the spread of the latest forms of education and the growth of their profitability, to confirm the turbulence and instability of internationalisation trends and the intensification of competition between traditional and new providers of educational services. Research has shown that the online education sector is developing and expanding rapidly. The amount of capital raised and its profitability are increasing, confirming the prospects of these investments. There is a growing variety of online education providers, which generally creates significant competition for traditional institutions such as universities. Educational products are becoming more diversified and there is a growing trend towards personalised and adaptive learning on online educational platforms using artificial intelligence and machine learning technologies. In recent years, there has been a significant increase in the number of students enrolled in various online courses, and there is a growing demand for distance learning and flexible, personalised learning options. The global education market is characterised by unstable dynamics of internationalisation due to various external factors such as the COVID-19 pandemic, military aggression, demographic factors, political and economic instability. Competition between traditional and new providers for students, market share and financial resources is intensifying. In general, despite the negative factors, the number of foreign students tends to increase, albeit rather unevenly across countries. The widespread use of ICT in education and other activities can pose potential threats and challenges: increased competition and lower quality of education, spread of unwanted and anti-social information.
The Fredkin gate in reversible and quantum environments

Reversible Computing circuits are characterized by low power consumption and their proximity to circuits for quantum computing. The Fredkin gate was one of the earliest proposed controlled reversible circuits, which however, was soon superseded by the Toffoli gate, the NOT, and CNOT gates, which constituting a flexible functionally complete set could also realize the Fredkin gate as a building block. In quantum computing circuits, the Fredkin gate (under the name controlled SWAP) plays an important role regarding the superposition of states. The present paper studies extensions of the Fredkin gate in terms of mixed polarity in the reversible domain and an application in quantum computing.
The Use of Blockchain in Aviation Safety Reporting Systems: A Framework Proposal

Objective The purpose of this study is to propose a blockchain-based framework for designing an incident reporting system in aviation.
PRIORITIES OF EDUCATIONAL POLICY

The article examines the directions of educational policy taking into account modern realities and modern challenges, as well as general trends in world development, based on the rights to education of citizens, guaranteed by the Constitution of the Republic of Armenia. State guarantees of access to quality education were analyzed, the urgency of the need to reform the current system, increasing the objectivity of assessing the educational results of graduates of general education schools and the need to reform the current system of final exams in general educational institutions and entrance exams to universities and colleges, the need to ensure equal opportunities for obtaining secondary and higher professional education. The need to introduce a system of state standards to expand access to education for students, regardless of place of residence and family income level, is substantiated.
Investigating a Computational Explanation of the Black Hole Illusion

Objective We investigated the role of Perrone’s algorithm in the Black Hole Illusion (BHI). After analyzing the algorithm and identifying two of its predictions, we empirically tested them with two on-line experiments.
Effective Spam Detection with Machine Learning

Abstract This paper aims to provide results of empirical experiments on the accuracy of different machine learning algorithms for detecting spam messages, using a public dataset of spam messages. The originality of our study lies in the integration of topic modeling, specifically employing Latent Dirichlet Allocation (LDA) alongside machine learning algorithms for spam detection. By extracting hidden topics and uncovering patterns in spam and non-spam messages, we provide unique insights into the distinguishing characteristics of spam messages. Moreover, the integration of machine learning is a powerful tool in bolstering risk control measures ensuring the sustainability of digital platforms and communication channels. The research tests the accuracy of spam detection classifiers on an open-source dataset of spam messages. The key findings of this study reveal that the Logistic Regression classifier achieved the highest F score of 0.986, followed by the Support Vector Machine classifier with a score of 0.98 and the Naive Bayes classifier with a score of 0.955. The study concludes that Logistic Regression outperforms Naive Bayes and Support Vector Machine in text classification, particularly in spam detection, emphasizing the role of machine learning techniques in optimizing risk management strategies for sustained digital ecosystems. This capability stems from Logistic Regression’s adeptness in modeling complex relationships, enabling it to achieve high accuracy on training and test datasets.
The Beginning of the Large-Scale Reconstruction of the Russian State Library: Architecture and Digitalization

The article reveals the foundations of design and research surveys, on the basis of which the Russian State Library (RSL) implemented the project of repair and restoration works for the central entrance of the library. The aim of the works was to adapt the cultural heritage object to modern use. The building complex, conceived in the mid — 1920s, was completed by 1940, but it was not fully commissioned until 1960. In the mid — 1970s, there was insufficient space to store the growing holdings. The front decoration of the central hall suffered enormous damage over the years. In 2019, a negative trend in the condition of the building was revealed. The main book depository was overloaded. The problems of the RSL are combined in a comprehensive investment programme for the reconstruction and restoration of infrastructure facilities. In 2019—2020, design solutions were developed for the repair and restoration of buildings and individual public spaces of the library. In 2021, the first stage of restoration of the entrance group began. The decision was made to carry out the work in a service-preserving environment and the challenge was to transform the very model of service to readers. The team working on the restoration made decisions reflecting the development of 21st century technologies and current standards for the automation of library processes. As a result of the works, new technological channels for the building operation and space for servicing readers were arranged, a climate control system was installed, the power supply and electric lighting system was replaced, historical interiors were restored, modern fire and engineering safety systems were created, a new centralized information and navigation complex for readers was deployed, etc. In 2023, a grandiose historical space was opened for the RSL readers.
The Results of the All-Russian Competition of Scientifi c Papers on Library Science, Bibliography and Bibliology — 2023

On 28 November 2023, within the framework of the All–Russian meeting of heads of federal and central regional libraries of Russia, the winners of the next All– Russian competition of scientifi c papers on library science, bibliography and book studies were solemnly awarded. On behalf of the Ministry of Culture of the Russian Federation, the competition was organized by the Russian National Library and co-organized by the Russian State Library with the support of the Russian Library Association. The competition is one of the main tools for assessing the effectiveness of scientifi c activity in the fi eld of librarianship. The competition contributes to the support and development of science in librarianship within the framework of the “Strategy for the development of librarianship in the Russian Federation for the period up to 2030” and meets the objectives set by the President of the Russian Federation in the “Fundamentals of State Cultural Policy” in the fi eld of development of research of social and humanitarian nature.