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What can and can’t be copied is a matter of law, but also of aesthetics, culture, and economics. The act of copying, and the creation and transaction of rights relating to it, evokes fundamental notions of communication and censorship, of authorship and ownership—of privilege and property. This volume conceives a new history of copyright law that has its roots in a wide range of norms and practices. The essays reach back to the very material world of craftsmanship and mechanical inventions of Renaissance Italy where, in 1469, the German master printer Johannes of Speyer obtained a five-year exclusive privilege to print in Venice and its dominions. Along the intellectual journey that follows, we encounter John Milton who, in 1644 accused the English parliament of having been deceived by the ‘fraud of some old patentees and monopolizers in the trade of bookselling’ (i.e. the London Stationers’ Company). Later revisionary essays investigate the regulation of the printing press in the North American colonies as a provincial and somewhat crude version of European precedents, and how, in the revolutionary France of 1789, the subtle balance that the royal decrees had established between the interests of the author, the bookseller, and the public, was shattered by the abolition of the privilege system. Some of the essays also address the specific evolution of rights associated with the visual and performing arts. The volume is a companion to the digital archive Primary Sources on Copyright (1450-1900), funded by the UK Arts and Humanities Research Council (AHRC). Privilege and Property is recommended in the Times Higher Education Textbook Guide (November, 2010).

The Court of Justice of the European Union has seen a dramatic and controversial increase in copyright cases during the last decade. This study investigates empirically two claims: (i) that the Court has failed to develop a coherent copyright jurisprudence (lacking domain expertise, copyright specific reasoning, and predictability); (ii) that the Court has pursued an activist, harmonising agenda (resorting to teleological interpretation of European law). We analyse the allocation of copyright and database right cases by Chambers of the Court, Advocate General (AG) and Reporting Judge, and investigate the biographical background of the Judges and AGs sitting. We trace patterns of reasoning in the Court's approach through quantitative content analysis. Legal topoi that are employed in the opinions and decisions are linked to the outcomes of each case.

About ten years ago, chemically fueled systems have emerged as a new class of synthetic materials with tunable properties. Yet, applications of these materials are still scarce. In part, this is due to an incomplete characterization of the viscoelastic properties of those materials, which has – so far – mostly been limited to assessing their linear response under shear load. Here, we fill some of these gaps by comparing the viscoelastic behavior of two different, carbodiimide fueled Fmoc-peptide systems. We find that both, the linear and non-linear response of the hydrogels formed by those Fmoc-peptides depends on the amount of fuel driving the self-assembly process – but hardly on the direction of force application. In addition, we identify the concentration of accumulated waste products as a novel, so far neglected parameter that crucially affects the behavior of such chemically fueled hydrogels. With the mechanistic insights gained here, it should be possible to engineer a new generation of dynamic hydrogels with finely tunable material properties that can be tailored precisely for such applications, where they are challenged by mechanical forces. The mechanical properties of out-of-equilibrium, chemically fueled supramolecular materials are largely unexplored. Here, the effect of applied load and the concentration of reaction side products on the viscoelastic properties of chemically fueled supramolecular hydrogels is investigated.

Machine learning, a subfield of artificial intelligence (AI), relies on large corpora of data as input for learning algorithms, resulting in trained models that can perform a variety of tasks. While data or information are not subject matter within copyright law, almost all materials used to construct corpora for machine learning are protected by copyright law: texts, images, videos, and so on. There are global policy moves to address the copyright implications of machine learning, in particular in the context of so-called “foundation models” that underpin generative AI. This paper takes a step back, exploring empirically three technological settings through detailed case studies. We set out the established industry methodology of a lifecycle of AI (collecting data, organising data, model training, model operation) to arrive at descriptions suitable for legal analysis. This will allow an assessment of the challenges for a harmonisation of rights, exceptions and disclosure under EU copyright law. The three case studies are: Machine learning for scientific purposes, in the context of a study of regional short-term letting markets; Natural Language Processing (NLP), in the context of large language models; Computer vision, in the context of content moderation of images. We find that the nature and quality of data corpora at the input stage is central to the lifecycle of machine learning. Because of the uncertain legal status of data collection and processing, combined with the competitive advantage gained by firms not disclosing technological advances, the inputs of the models deployed are often unknown. Moreover, the “lawful access” requirement of the EU exception for text and data mining may turn the exception into a decision by rightholders to allow machine learning in the context of their decision to allow access. We assess policy interventions at EU level, seeking to clarify the legal status of input data via copyright exceptions, opt-outs or the forced disclosure of copyright materials. We find that the likely result is a fully copyright-licensed environment of machine learning that may have problematic effects for the structure of industry, innovation and scientific research.

Mucus is a self‐healing gel that lubricates the moist epithelium and provides protection against viruses by binding to viruses smaller than the gel's mesh size and removing them from the mucosal surface by active mucus turnover. As the primary nonaqueous components of mucus (≈0.2%–5%, wt/v), mucins are critical to this function because the dense arrangement of mucin glycans allows multivalence of binding. Following nature's example, bovine submaxillary mucins (BSMs) are assembled into “mucus‐like” gels (5%, wt/v) by dynamic covalent crosslinking reactions. The gels exhibit transient liquefaction under high shear strain and immediate self‐healing behavior. This study shows that these material properties are essential to provide lubricity. The gels efficiently reduce human immunodeficiency virus type 1 (HIV‐1) and genital herpes virus type 2 (HSV‐2) infectivity for various types of cells. In contrast, simple mucin solutions, which lack the structural makeup, inhibit HIV‐1 significantly less and do not inhibit HSV‐2. Mechanistically, the prophylaxis of HIV‐1 infection by BSM gels is found to be that the gels trap HIV‐1 by binding to the envelope glycoprotein gp120 and suppress cytokine production during viral exposure. Therefore, the authors believe the gels are promising for further development as personal lubricants that can limit viral transmission. Synthetic mucin gels mimic the material properties of native mucus, exhibiting transient liquefaction under large strain and immediate self‐healing behavior. These gels provide more lubricity and prophylactic activity against HIV compared to simple mucin solution that does not properlumimic native mucus. The gels show promise for further development of personal mucin‐based lubricants that can limit viral transmission.

Surface superhydrophobicity makes bacterial biofilms very difficult to fight, and it is a combination of their matrix composition and complex surface roughness which synergistically protects these biomaterials from wetting. Although trying to eradicate biofilms with aqueous (antibiotic) solutions is common practice, this can be a futile approach if the biofilms have superhydrophobic properties. To date, there are not many options available to reduce the liquid repellency of biofilms or to prevent this material property from developing. Here, we present a solution to this challenge. We demonstrate how the addition of metal ions such as copper and zinc during or after biofilm formation can render the surface of otherwise superhydrophobic B. subtilis NCIB 3610 biofilms completely wettable. As a result of this procedure, these smoother, hydrophilic biofilms are more susceptible to aqueous antibiotics solutions. Our strategy proposes a scalable and widely applicable step in a multi-faceted approach to eradicate biofilms.

The development and regulation of multi-purpose, large \"foundation models\" of AI seems to have reached a critical stage, with major investments and new applications announced every other day. Some experts are calling for a moratorium on the training of AI systems more powerful than GPT-4. Legislators globally compete to set the blueprint for a new regulatory regime. This paper analyses the most advanced legal proposal, the European Union's AI Act currently in the stage of final \"trilogue\" negotiations between the EU institutions. This legislation will likely have extra-territorial implications, sometimes called \"the Brussels effect\". It also constitutes a radical departure from conventional information and communications technology policy by regulating AI ex-ante through a risk-based approach that seeks to prevent certain harmful outcomes based on product safety principles. We offer a review and critique, specifically discussing the AI Act's problematic obligations regarding data quality and human oversight. Our proposal is to take liability seriously as the key regulatory mechanism. This signals to industry that if a breach of law occurs, firms are required to know in particular what their inputs were and how to retrain the system to remedy the breach. Moreover, we suggest differentiating between endogenous and exogenous sources of potential harm, which can be mitigated by carefully allocating liability between developers and deployers of AI technology.

History has normative force. There was no history of colonialism, gender, fashion or crime until there were contemporary demands to explain and justify certain values. During much of the twentieth century, ‘copyright’ history (the history of legal, particularly proprietary, mechanisms for the regulation of the reproduction and distribution of cultural products – as opposed to the history of art, literature, music, or the history of publishers and art-sellers) was not thought of as a coherent, or even necessary field of inquiry. It was a pursuit of individual often rather isolated scholars, not an urgent contribution to knowledge.¹ This was not always

The dynamic problem of enclosing an expanding fire can be modelled by a discrete variant in a grid graph. While the fire expands to all neighbouring cells in any time step, the fire fighter is allowed to block \\(c\\) cells in the average outside the fire in the same time interval. It was shown that the success of the fire fighter is guaranteed for \\(c>1.5\\) but no strategy can enclose the fire for \\(c\\leq 1.5\\). For achieving such a critical threshold the correctness (sometimes even optimality) of strategies and lower bounds have been shown by integer programming or by direct but often very sophisticated arguments. We investigate the problem whether it is possible to find or to approach such a threshold and/or optimal strategies by means of evolutionary algorithms, i.e., we just try to learn successful strategies for different constants \\(c\\) and have a look at the outcome. The main general idea is that this approach might give some insight in the power of evolutionary strategies for similar geometrically motivated threshold questions. We investigate the variant of protecting a highway with still unknown threshold and found interesting strategic paradigms. Keywords: Dynamic environments, fire fighting, evolutionary strategies, threshold approximation