This article explores the ways that ecclesiastical record books produced by national and local Church courts in Scotland were bound up in the contests for legitimacy around the Scottish Revolution. The article argues that adherents to the National Covenant used paper record books and the practices that surrounded them, as well as their printed output, to legitimise their protest movement and to attack their opponents. Reconstructing the Church in paper represented an essential part of the Covenanters’ protest, reconstructing the Church after the fall of episcopacy.

Analysis of length-frequency data using the ELEFAN (Electronic Length-Frequency Analysis) approach and software is widely used to quantify the growth, mortality, longevity, and related parameters of Recent marine animals. Here we analyze a sample (n = 211) of the Ediacaran metazoan Parvancorina minchami Glaessner, 1958, from the Vendian siliciclastic marine deposits of the southeastern White Sea region, Russia. The results fit a von Bertalanffy equation with the parameters L∞ = 2 cm, K = yr−1 (with t0 not estimated) and an instantaneous rate of mortality (M) of 1.44 yr−1, implying M/K ≈ 2, as commonly occurs in Recent small invertebrates. These parameter values also imply a longevity for P. minchami of about 4 yr. The concepts and approach used here, previously applied to an Ordovician trilobite and a Cambrian radiodont, suggest that inferences on growth, mortality, longevity, and related parameters can be obtained from suitable size-frequency samples of long-extinct metazoans, opening new vistas on their growth dynamics and functional roles in ancient ecosystems.

The common-cause hypothesis says that factors regulating the sedimentary record also exert macroevolutionary controls on speciation, extinction, and biodiversity. I show through computational modeling that common cause factors can, in principle, also control microevolutionary processes of trait evolution. Using Bermuda and its endemic land snail Poecilozonites, I show that the glacial–interglacial sea-level cycles that toggle local sedimentation between slow pedogenesis and rapid eolian accumulation could also toggle evolution rates between long slow phases associated with large geographic ranges and short rapid phases associated with small, fragmented ranges and “genetic surfing” events. Patterns produced by this spatially driven process are similar to the punctuated equilibria patterns that Gould inferred from the fossil record of Bermuda, but without speciation or true stasis. Rather, the dynamics of this modeled system mimic a two-rate Brownian motion process (even though the rate parameter is technically constant) in which the contrast in rate and duration of the phases makes the slower one appear static. The link between sedimentation and microevolution in this model is based on a sediment-starved island system, but the principles may apply to any system where physical processes jointly control the areal extents of sedimentary regimes and species’ distributions.

Organismal morphology was at the core of study of biodiversity for millennia before the formalization of the concept of evolution. In the early to mid-twentieth century, a strong theoretical framework was developed for understanding both pattern and process of morphological evolution, and the 50 years since the founding of this journal capture a transformational period in the quantification of morphology and in analytical tools for estimating how morphological diversity changes through time. We are now at another inflection point in the study of morphological evolution, with the availability of vast amounts of high-resolution data sampling extant and extinct diversity allowing “omics”-scale analysis. Artificial intelligence is accelerating the pace of phenomic data acquisition even further. This new reality, in which the ability to obtain data is quickly outpacing the ability to analyze it with robust, realistic evolutionary models, brings a new set of challenges. Phylogenetic comparative methods have provided new insights into the processes generating morphological diversity, but the reliance on molecular data and resultant exclusion of fossil data from most large phylogenetic trees has well-established negative impacts on evolutionary analyses, as we demonstrate with examples of standard single-rate evolutionary models, mode- and rate-shift models, and a recently described Ornstein-Uhlenbeck climate model. Further development of methods for phylogenetic comparative analysis of high-dimensional data is needed, but existing tools can refine our understanding and expectations of morphological evolution and the generation of morphological diversity under different scenarios, as we demonstrate with analyses of placental skull evolution through the Cenozoic. Fully transitioning the study of morphological evolution into the omics era will involve the development of tools to automate the extraction of meaningful, comparable morphometric data from images, integrate fossil data into large phylogenetic trees and downstream evolutionary analyses, and generate robust models that accurately reflect the complexity of evolutionary processes and are well-suited for high-dimensional data. Combined, these advancements will solidify the emerging field of evolutionary phenomics and appropriately center it around the analysis of deep-time data.

This article seeks to re-read and reassess the significance of the famous novel Kokoro by Natsume Sôseki (1867-1916), one of the main figures of Japanese modern literature. The novel is about two consecutive stories of friendship. A young student establishes friendship with an older man, the Master, who himself experienced a very strong friendship with a young man from the same village in his youth, until a love affair tragically separated them. We consider the ambiguous links, contrasts, and parallels between the different bonds in the novel, issues of generation gaps, relationships with the family, philosophical loneliness, and the belittling of women in the portrayal of friendship in the novel.

The crystal structure of flumethasone has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory techniques. Flumethasone crystallizes in space group P21 (#4) with a = 6.46741(5), b = 24.91607(20), c = 12.23875(11) Å, β = 90.9512(6)°, V = 1971.91(4) Å3, and Z = 4 at 298 K. The crystal structure consists of O–H⋯O hydrogen-bonded double layers of flumethasone molecules parallel to the ac-plane. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

We chart and assess the scope and utilisation of state-supplied hospital infrastructure in British Africa, c. 1900–60. Using archival sources, we examine the heterogeneity in colonial administrations’ investment into curative healthcare provision across various regions of British Africa. Our research highlights significant disparities in healthcare provision during the colonial period. These disparities were shaped by a range of observable factors, including differences in colonial policies, budgets, investment priorities, and the availability of medical personnel. We test stylised facts about public goods provision derived from previous literature and highlight the importance of understanding the historical context in shaping healthcare systems in Africa today.

In today’s world, smart algorithms—artificial intelligence (AI) and other intelligent systems—are pivotal for promoting the development agenda. They offer novel support for decision-making across policy planning domains, such as analysing poverty alleviation funds and predicting mortality rates. To comprehensively assess their efficacy and implications in policy formulation, this paper conducts a systematic review of 207 publications. The analysis underscores their integration within and across stages of the policy planning cycle: problem diagnosis and goal articulation; resource and constraint identification; design of alternative solutions; outcome projection; and evaluation. However, disparities exist in smart algorithm applications across stages, economic development levels, and Sustainable Development Goals (SDGs). While these algorithms predominantly focus on resource identification (29%) and contribute significantly to designing alternatives—such as long-term national energy policies—and projecting outcomes, including predicting multi-scenario land-use ecological security strategies, their application in evaluation remains limited (10%). Additionally, low-income nations have yet to fully harness AI’s potential, while upper-middle-income countries effectively leverage it. Notably, smart algorithm applications for SDGs also exhibit unevenness, with more emphasis on SDG 11 than on SDG 5 and SDG 17. Our study identifies literature gaps. Firstly, despite theoretical shifts, a disparity persists between physical and socioeconomic/environmental planning applications. Secondly, there is limited attention to policy-making in development initiatives, which is critical for improving lives. Future research should prioritise developing adaptive planning systems using emerging powerful algorithms to address uncertainty and complex environments. Ensuring algorithmic transparency, human-centered approaches, and responsible AI are crucial for AI accountability, trust, and credibility.