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.
Grid-enhancing technologies for clean energy systems
Renewable energy source integration into energy systems can contribute to transmission congestion, which requires time-consuming and capital-intensive upgrades to address. Grid-enhancing technologies (GETs) can increase the capacity of grids with minimal investment, preventing congestion and curtailment of renewable energy. In this Review, we discuss the principles and uses of GETs, which use software and/or hardware to interpret real-time conditions to better use the existing capacity of grid assets. GETs include dynamic line ratings, dynamic transformer ratings, power flow controls, topology optimization, advanced conductor technologies, energy storage systems, and demand response. These GETs can enhance system performance individually, but the deployment of multiple GETs together would greatly increase their effect on the grid capacity and stability by removing multiple capacity bottlenecks in parallel. Infrastructure for real-time data acquisition, transmission and analysis is key to successfully deploying GETs but requires further development and commercialization for broader deployment.
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