The Fall of Z-Library: The “Burning of the Library of Alexandria” or Protection for Authors Against AI Companies

The development and advancement of artificial intelligence (“AI”) is changing the way we use technology while creating an ongoing battle between media and technology companies. With AI companies gathering data from the internet to train programs like ChatGPT, authors have growing concerns about unpermitted use of their work when pirated copies of their books exist illegally online through shadow libraries. This article examines the popular shadow library known as Z-Library and the views of its proponents and opponents. In addition, this article will discuss the training process AI companies use and the data sets containing content from shadow libraries. While companies like Getty Images and The New York Times filed suit against AI companies, this article specifically focuses on the class action lawsuits filed by authors for unauthorized use of their books to train AI models. Copyright law may offer a solution to protect these author’s works. This article will examine the current limitations of copyright law and the difficulties of proving copyright infringement. This article attempts to explore the current legal action, claims these authors raise, and possible defenses they will have to overcome. This article will also examine solutions like agreements with authors and paying them royalties to compensate them for the use of their work. Regardless of how the court cases come out, these authors need a solution to ensure their content is not exploited by AI companies

Computational Study of Protein Dynamics and Allostery through Molecular Modeling and Machine Learning

This thesis studies the complexities of protein dynamics and allostery, presenting methodologies that leverage combined computational approaches, including molecular modeling and machine learning, to investigate these phenomena. Protein dynamics bridge conformational ensembles and their corresponding functional states. It further plays a critical role in a wide range of biological processes. Therefore, studying protein dynamics is essential for understanding how proteins fulfill their biological functions. Allostery plays a pivotal role in biological processes, acting as a fundamental mechanism through which proteins transmit signals and regulate their activity. Despite its critical importance in biology, the specific allosteric mechanisms governing most proteins remain elusive. Employing a multifaceted computational approach, the first study initially delves into microsecond molecular dynamics (MD) simulations of AsLOV2, uncovering the critical role of β-sheets in mediating its conformational changes and allosteric signal transmission. By integrating simulation data with experimental findings and mutational analyses, key hydrogen bonds pivotal for allostery are identified. Advancing the discourse, this thesis highlights the integration of machine learning (ML) and deep learning (DL) techniques for the study of protein allostery, including studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. This leads to two pivotal projects that utilize ML and DL to further our understanding and capabilities in protein dynamics and allostery. Automated Machine Learning (AutoML) is employed for the precise prediction of allosteric sites, showcasing a model that not only achieves a remarkable 82.7% ranking probability for identifying allosteric sites within the top three predictions, but also validates its robustness by making predictions for proteins beyond the initial dataset. The final model is deployed to the Protein Allosteric Sites Server to facilitate the research in this field. The variational Autoencoder (VAE) model is rigorously evaluated for its ability to assist protein conformation exploration. It is demonstrated that VAE can retain critical properties in a high-dimensional conformational space and predict physically plausible conformations that are infrequently accessed through traditional MD simulations, thereby providing valuable seed conformations for initiating new simulation studies. Further, MD simulations and a Markov state model are utilized to characterize the functional conformational states of these variants. This analysis focuses on changes in the receptor-binding domain of the SARS-CoV-2 spike protein, particularly the alterations in conformational mobility that might enhance the virus’s transmissibility and immune evasion. Integrated with further perturbation-based approaches, the analysis provides insights into potential immune escape mechanisms. This work not only extends computational methodologies for probing protein allostery, but also presents adaptable workflows for addressing broader biochemistry challenges, marking a unique contribution to the computational study of protein dynamics and allostery

Unveiling the Dark Side of Innovation: Sustainability, Cobalt Mining, and Modern-Day Slavery

As the need and demand for sustainability come to the forefront of innovative efforts by technology companies, the use of rechargeable batteries has only become more prominent. A critical mineral in the manufacture of such batteries is cobalt. Looking deeper into how manufacturers get their hands on cobalt exposes the troubling cobalt-mining practices largely taking place within the Democratic Republic of Congo (DRC). This article dives into the underbelly of the cobalt-mining industry, revealing the egregious human-rights abuses occurring in the DRC and examining the current legal and ethical landscape surrounding cobalt mining around the world. In both small-scale artisanal mines and larger industrial mines, child labor, physical and verbal abuse, and non-livable, low wages are commonplace. As the mines expand, and the land, homes, and farms of Congolese residents are destroyed in the process, Congolese people wind up with little to no choice but to work in the mines. This article addresses how current legislation and initiatives in the United States and internationally miss the mark in responding to the increasing volume of problems in the DRC’s cobalt mines, and how past cases involving human rights abuses in the supply chains of United States companies have panned out. Finally, this article emphasizes the need for change and reform as innovation efforts continue to increase worldwide

Baseball Decision-Making: Optimizing At-bat Simulations

Pitch selection in baseball plays a crucial role, involving pitchers, catchers, and batters working together. This practice, dating back to early baseball, has seen teams try various methods to gain an advantage. This research aims to use reinforcement learning and pitch-by-pitch Statcast data to improve batting strategies. It also builds on previous statistical work (sabermetrics) to make better choices in pitch selection and plate discipline. The dataset used, including over 700,000 pitches for each full season and 200,000 pitches for the COVID-shortened 2020 season, encompasses a wealth of crucial metrics including pitch release point, velocity, and launch angle. This study dives deep into player interactions and pitch behavior, seeking to find new ideas that could change how teams approach their offensive tactics. By analyzing player performance and applying advanced stats, this research hopes to uncover hidden patterns. To ensure accuracy in pitch type classification, a critical aspect of our analysis, we reclassified pitch types. By incorporating 15 distinct variables, ranging from release point coordinates to spin rates, we enhanced the granularity of pitch type identification. These variables were normalized and subjected to UMAP dimensionality reduction, resulting in the creation of 2D vector embeddings for each pitch. This methodology not only refines pitch classification but also unlocks a deeper understanding of player interactions and pitch behavior

Unlawful Seizure: The Legal Implications Of Russia’s Re-Registration Of Leased Aircraft

During the Russian invasion of Ukraine, Russia passed a law allowing its domestic airlines to reregister foreign-owned aircraft on the Russian aircraft registry. This law raises important questions about dual registration—forbidden under international law—since the prior foreign aviation authorities had not consented to the deregistration of the subject aircraft. Even as lessors revoked airworthiness certificates, Russia re-registered more than 350 leased aircraft. The most significant problem in civil aviation today is Russia’s re-registration law, which undermines predictability, order, and safety. This essay argues that Russia passed its registration law because its war left it with few other options. This does not make Russia’s actions legally defensible, but the context helps frame potential solutions, which will be explored after examining the international aircraft registration regime and the legal implications of Russia’s actions

Tort Claims Arising From Military Aircraft Crashes Are Not Preempted By The Federal Aviation Act

The Second Circuit\u27s landmark ruling in Jones v. Goodrich Pump & Engine Control Sys., Inc. establishes crucial precedent by asserting that tort claims stemming from military aircraft crashes are not field or conflict preempted by the Federal Aviation Act (the Act). This decision, the first of its kind at the appellate level, carries far-reaching implications. The court’s rationale, grounded in the Act’s plain language, emphasizes that “public aircraft,” including military ones, are exempt from Federal Aviation Administration regulation. Title 49, section 44701(a)(1), explicitly excludes public aircraft from the Act’s purview. While the court’s analysis relies on the Act’s text, it is fortified by a comprehensive examination of legislative history dating back to the early days of aviation. This Article contends that the Second Circuit’s reasoning, supported by both statutory language and over a century of legislative evolution, should serve as a universally adopted guideline. The separation of civil and military aircraft regulation, initiated in the Paris Convention of 1919 and continued through subsequent legislative acts, underscores the distinct standards governing military aviation. The inherent divergence in purpose and design between civil and military aircraft, coupled with Congress’s consistent exclusion of military aircraft from FAA regulation, solidifies the argument against preemption. As the sole appellate authority on this matter, the Jones decision provides a robust foundation for future courts facing Federal Aviation Act preemption challenges in “public aircraft” tort cases

Donald Trump and the Collapse of Checks and Balances

This Essay analyzes Donald Trump’s erosion of checks and balances during his presidency and how President Trump will likely seek to complete their collapse if he regains power. Its First Part shows that congressional willingness to check presidential abuses of power declined during Trump’s presidency and will likely get much weaker in a second term. It also shows that President Trump figured out how to evade checks and balances from Congress in his first term and examines his plans to further usurp congressional powers. Part Two looks at the judicial role in facilitating or checking presidential power through a lens sharpened by an effort to understand how checks and balances might collapse. This Essay’s analysis enables us to see how events that most observers experience as a series of disconnected dramatic clashes over policy (or that largely escape notice altogether) have partially collapsed the constraints that constitutional democracy depends upon, and how this collapse will likely accelerate if Trump becomes President again