Digitization as a research methodology in colonial natural history collections
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Insights from a century of data reveal global trends in ex situ living plant collections
Ex situ living plant collections play a crucial role in providing nature-based solutions to twenty-first century global challenges. However, the complex dynamics of these artificial ecosystems are poorly quantified and understood, affecting biodiversity storage, conservation and utilization. To evaluate the management of ex situ plant diversity, we analysed a century of data comprising 2.2 million records, from a meta-collection currently holding ~500,000 accessions and 41% of global ex situ species diversity. Our study provides critical insights into the historical evolution, current state and future trajectory of global living collections. We reveal sigmoidal growth of a meta-collection that has reached capacity in both total accessions and total diversity, and identify intrinsic constraints on biodiversity management, including a median survival probability of 15 years. We explore the impact of external constraints and quantify the influence of the Convention on Biological Diversity, which we link to reduced acquisition of wild-origin and internationally sourced material by 44% and 38%, respectively. We further define the impact of these constraints on ex situ conservation but highlight targeted initiatives that successfully mitigate these challenges. Ultimately, our study underscores the urgent need for strategic prioritization and the re-evaluation of ex situ biodiversity management to achieve both scientific and conservation goals.
The risk effects of corporate digitalization: exacerbate or mitigate?
This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.
A spatiotemporal style transfer algorithm for dynamic visual stimulus generation
Understanding how visual information is encoded in biological and artificial systems often requires the generation of appropriate stimuli to test specific hypotheses, but available methods for video generation are scarce. Here we introduce the spatiotemporal style transfer (STST) algorithm, a dynamic visual stimulus generation framework that allows the manipulation and synthesis of video stimuli for vision research. We show how stimuli can be generated that match the low-level spatiotemporal features of their natural counterparts, but lack their high-level semantic features, providing a useful tool to study object recognition. We used these stimuli to probe PredNet, a predictive coding deep network, and found that its next-frame predictions were not disrupted by the omission of high-level information, with human observers also confirming the preservation of low-level features and lack of high-level information in the generated stimuli. We also introduce a procedure for the independent spatiotemporal factorization of dynamic stimuli. Testing such factorized stimuli on humans and deep vision models suggests a spatial bias in how humans and deep vision models encode dynamic visual information. These results showcase potential applications of the STST algorithm as a versatile tool for dynamic stimulus generation in vision science.
How Shakespeare’s works have been reinterpreted, adapted and reshaped: a bibliometric review and trend analysis of Shakespeare studies from 2000 to 2023
Since transitioning into the post-theory era in 2000, Shakespearean studies have increasingly attracted interdisciplinary attention, engaging fields such as literature, performance studies, digital humanities, and cultural studies. Despite this broad interest, the discipline often lacks a cohesive framework to integrate these perspectives effectively. This study addresses this issue by applying bibliometric methods to data from the Web of Science Core Collection, using tools like VOSViewer and CiteSpace for analysis and visualization. By examining how Shakespeare’s works have been reinterpreted and adapted across diverse cultural and temporal contexts, the research employs the TCCM (Theory, Context, Characteristic, Methodology) framework to analyze thematic developments and interdisciplinary scope in Shakespeare studies from 2000 to 2023. Key findings reveal recurring research themes, including canonical text analysis, gender and performance, cross-cultural dissemination, adaptation, and the growing influence of digital humanities. The study identifies four distinct phases in the evolution of the field: the Initial Phase (2000–2005), focused on textual authenticity and literary value; the Transition Phase (2005–2010), marked by the integration of cultural studies and gender theory; the Mature Phase (2010–2019), exploring societal issues such as ethics and environmental humanities; and the Post-Pandemic Phase (2019–2023), emphasizing globalization and environmental concerns. These phases reflect shifts in academic priorities, methodologies, and interdisciplinary approaches, demonstrating the field’s responsiveness to global and technological developments. This study highlights the importance of deepening interdisciplinary integration and adopting emerging frameworks, such as new materialism, while combining distant and close reading techniques. These approaches offer a nuanced understanding of Shakespeare’s works, showcasing their enduring relevance and cultural transformation in a globalized and rapidly evolving academic landscape.
Power price stability and the insurance value of renewable technologies
To understand if renewables stabilize or destabilize electricity prices, we simulate European power markets as projected by the National Energy and Climate Plans for 2030 but replicating the historical variability in electricity demand, the prices of fossil fuels and weather. We propose a β-sensitivity metric, defined as the projected increase in the average annual price of electricity when the price of natural gas increases by 1 euro. We show that annual power prices spikes would be more moderate because the β-sensitivity would fall from 1.4 euros to 1 euro. Deployment of solar photovoltaic and wind technologies exceeding 30% of the 2030 target would lower it further, below 0.5 euros. Our framework shows that this stabilization of prices would produce social welfare gains, that is, we find an insurance value of renewables. Because market mechanisms do not internalize this value, we argue that it should be explicitly considered in energy policy decisions.
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