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Machine learning has already shown promising potential in tiled-aperture coherent beam combining (CBC) to achieve versatile advanced applications. By sampling the spatially separated laser array before the combiner and detuning the optical path delays, deep learning techniques are incorporated into filled-aperture CBC to achieve single-step phase control. The neural network is trained with far-field diffractive patterns at the defocus plane to establish one-to-one phase-intensity mapping, and the phase prediction accuracy is significantly enhanced thanks to the strategies of sin-cos loss function and two-layer output of the phase vector that are adopted to resolve the phase discontinuity issue. The results indicate that the trained network can predict phases with improved accuracy, and phase-locking of nine-channel filled-aperture CBC has been numerically demonstrated in a single step with a residual phase of λ/70. To the best of our knowledge, this is the first time that machine learning has been made feasible in filled-aperture CBC laser systems.
This work investigates the spatio-temporal evolution of coherent structures in the wake of a generic high-speed train, based on a three-dimensional database from large eddy simulation. Spectral proper orthogonal decomposition (SPOD) is used to extract energy spectra and energy ranked empirical modes for both symmetric and antisymmetric components of the fluctuating flow field. The spectrum of the symmetric component shows overall higher energy and more pronounced low-rank behaviour compared with the antisymmetric one. The most dominant symmetric mode features periodic vortex shedding in the near wake, and wave-like structures with constant streamwise wavenumber in the far wake. The mode bispectrum further reveals the dominant role of self-interaction of the symmetric component, leading to first harmonic and subharmonic triads of the fundamental frequency, with remarkable deformation of the mean field. Then, the stability of the three-dimensional wake flow is analysed based on two-dimensional local linear stability analysis combined with a non-parallelism approximation approach. Temporal stability analysis is first performed for both the near-wake and the far-wake regions, showing a more unstable condition in the near-wake region. The absolute frequency of the near-wake eigenmode is determined based on spatio-temporal analysis, then tracked along the streamwise direction to find out the global mode growth rate and frequency, which indicate a marginally stable global mode oscillating at a frequency very close to the most dominant SPOD mode. The global mode wavemaker is then located, and the structural sensitivity is calculated based on the direct and adjoint modes derived from a local spatial analysis, with the maximum value localized within the recirculation region close to the train tail. Finally, the global mode shape is computed by tracking the most spatially unstable eigenmode in the far wake, and the alignment with the SPOD mode is computed as a function of streamwise location. By combining data-driven and theoretical approaches, the mechanisms of coherent structures in complex wake flows are well identified and isolated.
Web3 is a new frontier of internet architecture emphasizing decentralization and user control. This text for MBA students and industry professionals explores key Web3 concepts, starting from foundational principles and moving to advanced topics like blockchain, smart contracts, tokenomics, and DeFi. The book takes a clear, practical approach to demystify the tech behind NFTs and DAOs as well as the complex regulatory landscape. It confronts challenges of blockchain scalability, a barrier to mainstream adoption of this transformative technology, and examines smart contracts and the growing ecosystem leveraging their potential. The book also explains the nuances of tokenomics, a vital element underpinning Web3's new economic model. This book is ideal for readers seeking to stay on top of emerging trends in the digital economy.
Chapter 7 highlights key concepts in Decentralized Finance (DeFi) and compares it to traditional finance. It discusses major DeFi applications such as decentralized exchanges, lending/borrowing platforms, derivatives, prediction markets, and stablecoins. DeFi offers advantages, including open access, transparency, programmability, and composability. It enables peer-to-peer financial transactions without intermediaries, unlocking financial inclusion, efficiency gains, and innovation. However, risks such as smart contract vulnerabilities, price volatility, regulatory uncertainty, and lack of accountability persist. As DeFi matures, enhanced governance, security audits, regulation, and insurance will be vital to address these challenges. DeFi is poised to reshape finance if balanced with prudence. Important metrics to track growth include total value locked, trading volumes, active users, and loans outstanding. Research tools such as Dune Analytics, DeFi Llama, and DeFi Pulse provide data-driven insights. Overall, DeFi represents a profoundly transformative blockchain application, but responsible evolution is key. The chapter compares DeFi to traditional finance and analyzes major applications, benefits, risks, and metrics in this emerging field.
Chapter 1 provides an overview of the concepts and definitions inherent to Web3. It presents a deep exploration into the phenomenon of "Convergence of Convergence," a term coined to denote the convergence of various dimensions within Web3, such as technology, data, user interactions, business models, identity, and organizational structures. The chapter also offers a comparative study of Web3 from different perspectives – tracing its evolution in the Internet era, analyzing its implications for user experience, evaluating its regulatory aspects, and understanding its scalability. Each of these aspects is explored in a detailed, standalone section, allowing readers to comprehend the multifaceted nature of Web3. The overarching aim of this chapter is to foster a comprehensive understanding of Web3, delineating its significance as a major shift in the Internet paradigm and its potential for creating more decentralized, user-empowered digital ecosystems.
Chapter 11 envisions the future potential of Web3 technologies in reshaping the web. It covers key areas such as generative AI, DeFi, mobile apps, cloud infrastructure, and the Metaverse. In DeFi, the focus is on scalability, interoperability, regenerative finance, decentralized identity, and its integration with social networks. The convergence of generative AI and Web3 is examined through case studies and applications, while mobile apps are explored as nodes for consensus algorithms, providing decentralized and secure networks. The impact of Web3 on cloud infrastructure includes decentralized storage, blockchain-based authentication and authorization, decentralized computing resources, and token-based incentives. Lastly, the chapter delves into the Metaverse, discussing decentralized ownership, token economies, identity and privacy considerations, interoperability, and decentralized governance. Through these explorations, the chapter highlights the transformative potential of Web3 in fostering decentralization, inclusivity, and innovation in the digital era.
Chapter 10 explores the evolving regulatory landscape surrounding Web3 technologies. It highlights the need for coordinated and adaptive regulations to foster innovation while managing potential risks. The chapter examines the impact of major crypto company collapses in 2022 on regulatory frameworks and emphasizes the importance of proactive measures to protect investors and mitigate risks. It delves into the regulatory landscapes in the United States, the European Union, China, and Web3-friendly countries such as the United Arab Emirates, Singapore, Germany, and Switzerland. The chapter covers key initiatives, including the Executive Order Ensuring Responsible Development of Digital Assets and the Responsible Financial Innovation Act in the United States, as well as stablecoin regulations and regulatory challenges related to decentralized autonomous organizations (DAOs). It also explores the intersection of the General Data Protection Regulation (GDPR) and Web3, emphasizing the challenges of privacy and compliance. Overall, the chapter provides a comprehensive overview of regulatory considerations in Web3, addressing innovation, consumer protection, financial stability, and privacy concerns. It emphasizes the importance of regulatory coordination and adaptation to promote innovation while safeguarding against potential risks.
Chapter 2 leverages first principles thinking to reveal the seismic shift enabled by Web3’s self-sovereign Internet and decentralized economic architecture. Opportunities emerge in infrastructure, access, efficiency, accountability, and empowerment. On-chain data sharing and self-sovereign identity allow efficient bootstrapping in an open ecosystem. Decentralized finance increases financial access, while blockchain ID could facilitate inclusive programs such as universal basic income. By automating manual workflows, smart contracts and traceability boost efficiency. Immutable blockchain ledgers enhance transparency via innovations such as triple-entry accounting. The creator economy shifts power by enabling direct content monetization and ownership through NFT marketplaces, decentralized social platforms, and games. Despite adoption hurdles, Web3 fundamentally reshapes incentives around user control over identity, data, and value creation in a decentralized economy. Capturing the full potential requires reimagining economic systems, not just optimizing current models. This epochal shift promises to unlock tremendous value by aligning technology with empowerment in an open, user-centric Internet.
Chapter 5 explores the interconnected ecosystem enabling feature-rich smart contracts. It first covers oracles, which provide external data to blockchains, outlining use cases, design considerations, and business decisions around oracle solutions. It then discusses interoperability, explaining atomic swaps and various cross-chain bridge designs such as lock/mint, liquidity pools, and zkBridge for trustless transfers. Next, it examines the ecosystem for mitigating Miner Extractable Value (MEV), categorizing solutions into auctions, time/content-based ordering, and application-specific designs. It also highlights other vital components such as user-friendly wallets, performant RPC nodes, governance mechanisms for collective decision-making, and privacy-preserving techniques such as zero-knowledge proofs. By delving into these key building blocks, this chapter offers readers a comprehensive understanding of the dynamic smart contract ecosystem. It emphasizes how components such as oracles, bridges, MEV mitigation, governance, and privacy-preservation enable richer functionality, interoperability, fairness, and user experience, shaping decentralized applications’ future.