Reviewerly/exHarmony huggingface dataset:
The Effect of Financial Readiness on Earnings Retention in Terms of Virtual Technologies: Evidence from UAE Companies

The metaverse is not a concept that can be ignored. The fact that it expands across all industries and businesses shows that it is signaling the next phase of the web. The industry companies are a key player in this area as it is providing entryways into the metaverse through high-quality connectivity and strong network infrastructure. This paper focuses on industrial companies in the UAE in terms of metaverse techniques usages. The current research seeks to determine the impact of financial readiness as an independent variable on earnings retention as a dependent variable. The relationship between the variables was expressed through the hypothetical research model from which the hypothesis was derived. In order to achieve the objectives of the research and verify its hypothesis, it was applied to a sample of the industrial sector companies listed in the Dubai Stock Exchange, which number (7) companies that apply metaverse techniques, through the use of their published financial data for the period (2011–2020). The obtained data were analyzed using Microsoft Excel 2016. The results of the financial and statistical analysis of the industrial sector companies listed in the Dubai Stock Exchange found that financial readiness plays a role in influencing earnings retention based on apply metaverse techniques.
Fixed wh-expressions in classroom second language acquisition: databases of computational properties or utterance schemas?

This study adopts concepts from two competing approaches to second language acquisition (SLA) (usage based vs. generative) to analyse the effect of formulaic expressions (FEs) on learners&rsquo; L2 syntactic development. Using spoken transcripts of the longitudinal Barcelona English Language Corpus (BELC), we identify four learned fixed wh-expressions (FEswh), which are all produced by learners in advance of respective L2 competence. We measure learners&rsquo; use of these expressions and the evidence of related computational properties (e.g., wh-movement, do-support) and utterance schemas (e.g., [WH + AUX DO + X]) outside this use across a 7-year data collection period. Adopting a generative analysis, we find that an earlier and more frequent use of FEswh correlates with better L2 knowledge of the expressions&rsquo; associated computational properties. Then, adopting a usage-based &lsquo;traceback&rsquo; methodology (e.g., Lieven et al., 2003; Eskilsden, 2020), we find that learners accurately produce some L2 interrogatives that share utterance schemas of previously used FEswh that appear in their production data ontogenetically. Utterance schema extraction and generalisation of model surface forms may therefore facilitate the development of the more general L2 feature specifications on the functional categories for which these surface forms exemplify. From this, we argue that such a unified account of learners&rsquo; L2 development can offer a better description of the trends observed in the corpus than either usage-based or generative models can do independently.
The Future of Metaverse in Improving the Quality of Higher Education: A Systematic Review

The COVID-19 pandemic has had a significant negative impact on the educational system, resulting in an increased emphasis on expediting the process of digitalizing education. Therefore, the incorporation of Metaverse exhibits considerable promise in constructing a resilient framework for the future of higher education. The objective of this study is to examine the potential ramifications of Metaverse technology on higher education. More specifically, it aims to investigate the potential advantages that the higher education sector could derive from the envisioned virtual environment. The present study utilised a theoretical systematic review technique in accordance with the PRISMA approach to examine and synthesise extant material pertaining to the utilisation of the Metaverse in higher education. This study examines various concepts and terminology associated with the subject matter and explores their potential implications. The research findings presented in this study offer evidence to support the feasibility of incorporating virtual reality technology in the realm of higher education. This integration has the potential to better interactions between humans and computers, as well as improve the overall experience between students and teachers. To the best of the researcher's knowledge, this study is the first attempt to provide a thorough description of the educational Metaverse within the context of higher education. Additionally, the study aims to investigate the potential consequences of the educational Metaverse in the future. Furthermore, this research possesses practical significance as it has assisted educational authorities in understanding the importance of the Metaverse within the domain of higher education. As a result, this has enhanced their capacity to formulate objectives and strategies that are aligned with the concept of the Metaverse. Owing to the emerging nature of this particular field, there is a limited availability of relevant scholarly material. This work contributes to the existing body of knowledge and suggests the need for additional research.
Deep Learning Opacity, and the Ethical Accountability of AI Systems. A New Perspective

In this paper we analyse the conditions for attributing to AI autonomous systems the ontological status of “artificial moral agents”, in the context of the “distributed responsibility” between humans and machines in Machine Ethics (ME). In order to address the fundamental issue in ME of the unavoidable “opacity” of their decisions with ethical/legal relevance, we start from the neuroethical evidence in cognitive science. In humans, the “transparency” and then the “ethical accountability” of their actions as responsible moral agents is not in contradiction with the unavoidable “opacity” (unawareness) of the brain process by which they perform their moral judgements on the right action to execute. In fact, the moral accountability of our actions depends on what is immediately before and after our “moral judgements” on the right action to execute (formally, deontic first order logic (FOL) decisions). I.e., our moral accountability depends on the “ethical constraints” we imposed to our judgement before performing it in an opaque way. Anyway, our moral accountability depends overall on the “ethical assessment” or explicit “moral reasoning” after and over the moral judgement before executing our actions (deontic higher order logic (HOL) assessment). In this way, in the light of the AI “imitation game”, the consistent attribution of the status of ethically accountable artificial moral agents to autonomous AI systems depends on two similar conditions. Firstly, it depends on the presence of “ethical constraints” to be satisfied in their Machine Learning (ML) supervised optimization algorithm during its training phase, to give the system ethical skills (“competences”) in its decisions. Secondly – and definitely—, it depends on the presence in an AI autonomous system of a deontic HOL “ethical reasoner” to perform an automatic, and fully transparent assessment (metalogical deontic valuation) about the decisions taken by the ethically skilled ML algorithm about the right action to execute, before executing it. Finally, we show that the proper deontic FOL and HOL for this class of artificial moral agents is Kripke’s modal relational logic, in its algebraic topological formalization. This is naturally implemented in the dissipative QFT unsupervised deep learning of our brains, based on the “doubling of the degrees of freedom” (DDF), and then in the so-called “deep-belief” artificial neural networks for the statistical data pre-processing. This unsupervised learning procedure is also compliant with the usage of the “maximin fairness principle”, used as a balancing aggregation principle of the statistical variables in Sen’s formal theory of fairness.
DevSecOps for Web3

This chapter discusses the crucial role of DevSecOps in Web3 application development. DevSecOps combines development, security, and operation and is essential for Web3 applications that use public blockchains with real-time transaction settlement and immutability. Due to the lack of a “charge-back” option in public blockchains, Web3 applications require higher security standards than traditional financial systems. DevSecOps can help identify security issues early on in the development phase, and automated security tools can be employed during the build phase to detect security bugs. However, DevSecOps is not widely adopted among Web3 projects due to a lack of awareness and skills among DevSecOps professionals. Web3 applications rely on Web2 technologies that are vulnerable to security attacks, such as cloud hosting and centralized databases. Therefore, DevSecOps can enhance the security and integrity of Web3 applications, protect user data and transactions, and improve overall quality. This chapter provides practical insights into how to introduce DevSecOps into Web3 application development, and it also includes sample security tools for successful automation. By adopting DevSecOps, Web3 developers can ensure that their applications meet higher security standards and enhance the trust and confidence of their users.
A construction of strongly regular Cayley graphs and their applications to codebooks

&lt;abstract&gt;&lt;p&gt;In this paper, we give a kind of strongly regular Cayley graphs and a class of codebooks. Both constructions are based on choosing subsets of finite fields, and the main tools that we employed are Gauss sums. In particular, these obtained codebooks are asymptotically optimal with respect to the Welch bound and they have new parameters.&lt;/p&gt;&lt;/abstract&gt;
Economic Exploits and Risk Mitigation Strategies

This chapter delves into case studies related to token economics, highlighting risks, exploits, and potential solutions. It also discusses the opportunities and threats brought by artificial intelligence (AI) in the field of token economics. The first case study examines an economic exploit achieved through financial engineering and suggests risk adjustment as a potential solution. The second case study addresses risks associated with incentive mechanism design, proposing economy parameter adjustment as a solution. The third case study explores Bancor’s insurance mechanism exploited by Celsius and Bancor’s response to the issue. The chapter further examines the impact of AI on token economics, outlining its potential benefits and challenges. Ten key considerations for assessing economic risk metrics in token economics are presented, emphasizing the need for thorough analysis. Finally, the chapter underscores the importance of recognizing and addressing risks associated with token economics, given its growing significance in the evolving world of digital assets and Web3 technologies.
Security in Permissioned Blockchain

When enterprises adopt the blockchain technology for their use cases, they typically would choose to deploy a permissioned blockchain, in which only authorized parties would be able to run a blockchain node. With the smaller number of nodes run by known entities, these blockchain networks tend to have much higher throughput, use simplified consensus protocols, and be able to provide privacy features while gaining the benefits of transparency, integrity, etc. When adopting a permissioned blockchain solution, the participants need to pay special attention to the architecture design to make sure the number of nodes, the level of independence among the nodes, and the chosen consensus protocol would provide enough decentralization so that the architecture could support the business objectives as intended. They need to ensure a robust mechanism for onboarding new nodes and verifying the identity of each node during operations, and defining the strategy for removing nodes, ensuring that such action would not compromise the integrity of the overall architecture. The participants should then fully leverage the security practices within the organizations to secure each node as well as the communications between these nodes and synchronize on any need to upgrade the blockchain software or smart contracts.
Token Economics Model Creation and Security

This chapter offers a comprehensive exploration of token economics, its underlying principles, and the security challenges associated with it. The chapter begins by differentiating tokens from the economy and establishing that the design of token economies is not a novel concept. It then delves into the importance of token economics and the associated risks. The chapter further defines token economics and examines the interplay between Web3 security and token economics, touching upon Ponzinomics. It compares Web3 with existing economic structures and explicates the components of token economics. The Economics Design Framework is introduced, focusing on market design, mechanism design, and token design as vital elements in delivering real value to users and striking a balance between monetary policies and the value creation cycle. Subsequently, the chapter discusses token economics stress tests and economics risk monitoring and addresses cybersecurity risks in the context of token economics. The chapter concludes with a summary of the key points and an overview of ongoing research in the field of tokenomics.
Data Authenticity

This chapter provides a comprehensive overview of Data Authenticity in Web3 ecosystem using blockchain oracles, including their types, examples of data oracle providers, use cases, design considerations, and security attacks with their countermeasures. The chapter covers five types of blockchain oracles, including input, output, cross-chain, compute-enabled, and other types. Examples of data oracle providers are provided, along with their use cases, such as decentralized finance, dynamic NFTs and gaming, insurance, enterprise supply chain management, prediction markets, and sustainability. The chapter also discusses the design considerations that should be taken into account when building blockchain oracles. Additionally, it covers security attacks on oracles, including insider attacks, oracle bribery, oracle front-running, and oracle extortion. Finally, countermeasures to these security attacks are presented to mitigate the risks of oracle manipulation and ensure the integrity of blockchain networks. This book chapter is a valuable resource for anyone interested in understanding the importance of oracles in blockchain networks and how to design and secure them effectively.
Wallet Security

This chapter delves into wallet security in the blockchain ecosystem, discussing the types of wallets, their underlying technologies, and their critical role in securing digital assets and facilitating transactions. It emphasizes the importance of wallet security, covering past wallet hacks, auditing significance, and various tools and methodologies for auditing. The chapter explains the different types of blockchain wallets, comparing them to traditional banking systems and distinguishing between custodial and non-custodial wallets. It explores the technical aspects of wallets, including public and private keys, key management, smart contract wallets, multisignature wallets, and attack vectors. In summary, this chapter offers valuable insights and practical advice on wallet security in the blockchain space, focusing on risk mitigation, user education, and proactive auditing. It highlights the significance of robust wallet security measures for the safety, integrity, and long-term success of the blockchain ecosystem.
The C.I.A Properties of Web3 System

This chapter examines the aspects of the confidentiality, integrity, and availability (CIA) triad to blockchain technology from a cybersecurity perspective. The CIA triad is a fundamental concept that forms the basis of effective information security measures. The chapter discusses the importance of each of the CIA triad properties in protecting sensitive information and maintaining reliable systems. The chapter argues that the CIA triad is still relevant in the Web3 era, where blockchain technology is at the core of value-based and self-sovereign information systems. The chapter explores the unique advantages and challenges of blockchain technology in terms of the CIA triad. Regarding confidentiality, the chapter discusses the limitations of pseudo-anonymity in providing sufficient confidentiality of blockchain data without privacy-preserving technology or protocols. In terms of integrity, the chapter examines the immutability of the blockchain ledger and the importance of security and liveness in consensus algorithm design to ensure data integrity. Finally, the chapter addresses the availability of blockchain, which relies on data replication, scalability, latency, and on-chain and off-chain data. By understanding the CIA triad and its application to blockchain technology, security professionals can effectively prioritize and allocate resources to protect information and systems in the Web3 era.
Promoting Reading in the Era of Print and Pixels

Cultivating a habit of reading is a fundamental characteristic necessary for fostering a well-educated society. Reading plays a pivotal role in honing effective thinking skills and generating fresh knowledge. This piece seeks to explore reading habits in both traditional print and the contemporary digital age. The promotion of robust reading practices should continue to be a focal point in education, ensuring students are equipped for success in their future academic endeavours and professional careers.The primary objective of this article is to scrutinize the reading habits of students, discern the advantages that reading offers to individuals, and assess the impact that screen time may have on reading.
Interactivity and Engagement Tactics and Tools

This chapter examines interactivity and engagement strategies and techniques in education. Recognizing the significance of active student participation and engagement, the chapter examines various strategies and tools that can enhance interactivity and facilitate meaningful learning experiences. It discusses the transition from traditional inert learning methods to more interactive and participatory approaches, made possible by technological and pedagogical advancements. Group discussions, problem-solving activities, collaborative initiatives, and experiential learning are some of the strategies explored. The course also investigates the use of technological tools, such as educational software, online platforms, multimedia resources, and gamification, to increase student engagement. This chapter discusses the advantages of incorporating interactivity and engagement into education, such as enhanced knowledge retention, critical thinking skills, creativity, and motivation. Educators can create dynamic and stimulating learning environments that accommodate diverse learning styles and improve the overall educational experience by instituting effective interactivity and engagement strategies and employing the appropriate tools.
Preserving the Vitality of Small and Medium-sized Businesses: Ethical Considerations in the Face of High-Octane Nanosecond Trading Practices

This research paper examines the challenges faced by Small and Medium-sized Businesses (SMBs) in light of high-speed nanosecond trading practices driven by artificial intelligence (AI) advancements in financial markets. The traditional purpose of stock markets, originally aimed at facilitating business financing, has evolved significantly, raising ethical concerns that require immediate attention. We investigate the real-world implications of such trading practices through scenarios like Elon Musk pledging Tesla (TSLA) shares to acquire Twitter, highlighting the potential threats to financing deals and the overall ecosystem. Events such as the sudden halt of trading for SVB illustrate the market's vulnerability to instability, affecting SMBs seeking loans for critical investments. Our research establishes a direct link between the SVB collapse and its adverse impact on the construction industry, emphasizing the toll on both financial and physical aspects. Furthermore, we address the inadequacy of AI systems in processing ethical considerations within financial trading. We advocate for the integration of ethics, compliance, and AI in trading algorithms to prevent the systemic exploitation of instruments or sectors. In conclusion, we emphasize the importance of considering ethical dimensions in high-speed trading practices. Neglecting these ethical considerations risks sidelining innovation and economic growth. This research serves as a call to action to preserve SMBs' integrity and vitality in the ever-evolving landscape of financial markets.
Transfer Learning, Cross Learning and Co-Learning Across Newsvendor Systems with Operational Data Analytics (ODA)

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The Impact of Dollarization on the Agricultural and Industrial Sectors in the Egyptian Economy Post the 2011 Revolution

This paper will shed light on the fluctuations that happened to the exchange rate in Egypt and from 2011 post the 25th of January revolution until 2022. The great dependency on the dollar led to high increase in prices and rise in the inflation rates. In addition, this paper will analyse the impact of dollarization on the various sectors in the Egyptian economy, namely the agricultural and industrial sectors and display the dependency of those sectors on the value of the Dollar. The findings showed that the restrictions on imports raised the prices of imported raw materials and soil fertilizers, which caused shortages and increased the prices of both agricultural and industrial products.
A Study on the Perception of the Relationship between Beauty and Goodness before Confucius in China

The purpose of this thesis is to find wisdom for the happiness of modern people"s lives through the realization of beauty through lines and to utilize it educationally. The emergence of aesthetic consciousness in ancient China is inseparable from the aesthetic sensitivity of the ‘five tastes’, ‘five colors’, and ‘five senses’. It was emphasized that the pursuit of sensual beauty could create significant social effects that would be disadvantageous to the ruling class. Beauty is goodness, and goodness is beauty. True beauty is benevolent virtue and goodness, and is by no means the enjoyment of sexual desires. The views expressed by thinkers before Confucius on the problem of resolving the relationship between beauty and goodness were that, although there were differences, they all placed goodness above beauty, and beauty could not deviate from or violate goodness. The emphasis on the significance and value of social ethics and morals of beauty is a major characteristic of ancient Chinese aesthetics that was already clearly evident before Confucius.