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The earliest extant mathematical books from China contain a lot of problems and data about grains. They also betray a close relationship with imperial bureaucracy in this respect. Indeed, these texts quote administrative regulations about grains. For instance, the Book on mathematical procedures 箅數書, found in a tomb sealed ca. 186 BCE, has a section in common with the \"regulations on granaries\" from the Qin statutes in eighteen domains, known thanks to slips excavated at Shuihudi. Mathematical writings also deal with official vessels used to measure grains. They cast light on statements from, and practices evidenced by, official histories and administrative documents. This article addresses the following issues.

Combining methods in social scientific research has recently gained momentum through a research strand called Mixed Methods Research (MMR). This approach, which explicitly aims to offer a framework for combining methods, has rapidly spread through the social and behavioural sciences, and this article offers an analysis of the approach from a field theoretical perspective. After a brief outline of the MMR program, we ask how its recent rise can be understood. We then delve deeper into some of the specific elements that constitute the MMR approach, and we engage critically with the assumptions that underlay this particular conception of using multiple methods. We conclude by offering an alternative view regarding methods and method use.

Machines powered by artificial intelligence increasingly mediate our social, cultural, economic and political interactions. Understanding the behaviour of artificial intelligence systems is essential to our ability to control their actions, reap their benefits and minimize their harms. Here we argue that this necessitates a broad scientific research agenda to study machine behaviour that incorporates and expands upon the discipline of computer science and includes insights from across the sciences. We first outline a set of questions that are fundamental to this emerging field and then explore the technical, legal and institutional constraints on the study of machine behaviour. Understanding the behaviour of the machines powered by artificial intelligence that increasingly mediate our social, cultural, economic and political interactions is essential to our ability to control the actions of these intelligent machines, reap their benefits and minimize their harms.

Studying and protecting each and every living species on Earth is a major challenge of the 21 st century. Yet, most species remain unknown or unstudied, while others attract most of the public, scientific and government attention. Although known to be detrimental, this taxonomic bias continues to be pervasive in the scientific literature, but is still poorly studied and understood. Here, we used 626 million occurrences from the Global Biodiversity Information Facility (GBIF), the biggest biodiversity data portal, to characterize the taxonomic bias in biodiversity data. We also investigated how societal preferences and taxonomic research relate to biodiversity data gathering. For each species belonging to 24 taxonomic classes, we used the number of publications from Web of Science and the number of web pages from Bing searches to approximate research activity and societal preferences. Our results show that societal preferences, rather than research activity, strongly correlate with taxonomic bias, which lead us to assert that scientists should advertise less charismatic species and develop societal initiatives (e.g. citizen science) that specifically target neglected organisms. Ensuring that biodiversity is representatively sampled while this is still possible is an urgent prerequisite for achieving efficient conservation plans and a global understanding of our surrounding environment.

Eric Lander, Françoise Baylis, Feng Zhang, Emmanuelle Charpentier, Paul Berg and specialists from seven countries call for an international governance framework. Eric Lander, Françoise Baylis, Feng Zhang, Emmanuelle Charpentier, Paul Berg and specialists from seven countries call for an international governance framework. Embryo culture dish used for in vitro fertilisation

The immune system enables organisms to combat infections and to eliminate endogenous challenges. Immune responses can be evoked through diverse inducible pathways. However, various constitutive mechanisms are also required for immunocompetence. The inducible responses of pattern recognition receptors of the innate immune system and antigen-specific receptors of the adaptive immune system are highly effective, but they also have the potential to cause extensive immunopathology and tissue damage, as seen in many infectious and autoinflammatory diseases. By contrast, constitutive innate immune mechanisms, including restriction factors, basal autophagy and proteasomal degradation, tend to limit immune responses, with loss-of-function mutations in these pathways leading to inflammation. Although they function through a broad and heterogeneous set of mechanisms, the constitutive immune responses all function as early barriers to infection and aim to minimize any disruption of homeostasis. Supported by recent human and mouse data, in this Review we compare and contrast the inducible and constitutive mechanisms of immunosurveillance.Constitutive innate immune mechanisms, such as restriction factors, RNA interference, antimicrobial peptides, basal autophagy and proteasomal degradation, exert early host defence activities that also aim to minimize tissue damage and homeostatic disruption by limiting the activation of inducible innate immunity.

Citizen scientists around the world are collecting data with their smartphones, performing scientific calculations on their home computers, and analyzing images on online platforms. These online citizen science projects are frequently lauded for their potential to revolutionize the scope and scale of data collection and analysis, improve scientific literacy, and democratize science. Yet, despite the attention online citizen science has attracted, it remains unclear how widespread public participation is, how it has changed over time, and how it is geographically distributed. Importantly, the demographic profile of citizen science participants remains uncertain, and thus to what extent their contributions are helping to democratize science. Here, we present the largest quantitative study of participation in citizen science based on online accounts of more than 14 million participants over two decades. We find that the trend of broad rapid growth in online citizen science participation observed in the early 2000s has since diverged by mode of participation, with consistent growth observed in nature sensing, but a decline seen in crowdsourcing and distributed computing. Most citizen science projects, except for nature sensing, are heavily dominated by men, and the vast majority of participants, male and female, have a background in science. The analysis we present here provides, for the first time, a robust ‘baseline’ to describe global trends in online citizen science participation. These results highlight current challenges and the future potential of citizen science. Beyond presenting our analysis of the collated data, our work identifies multiple metrics for robust examination of public participation in science and, more generally, online crowds. It also points to the limits of quantitative studies in capturing the personal, societal, and historical significance of citizen science.

We advance an account that grounds cognition, specifically decision-making, in an activity all organisms as autonomous systems must perform to keep themselves viable—controlling their production mechanisms. Production mechanisms, as we characterize them, perform activities such as procuring resources from their environment, putting these resources to use to construct and repair the organism's body and moving through the environment. Given the variable nature of the environment and the continual degradation of the organism, these production mechanisms must be regulated by control mechanisms that select when a production is required and how it should be carried out. To operate on production mechanisms, control mechanisms need to procure information through measurement processes and evaluate possible actions. They are making decisions. In all organisms, these decisions are made by multiple different control mechanisms that are organized not hierarchically but heterarchically. In many cases, they employ internal models of features of the environment with which the organism must deal. Cognition, in the form of decision-making, is thus fundamental to living systems which must control their production mechanisms. This article is part of the theme issue ‘Basal cognition: conceptual tools and the view from the single cell’.

This paper argues that biological organisation can be legitimately conceived of as an intrinsically teleological causal regime. The core of the argument consists in establishing a connection between organisation and teleology through the concept of self-determination: biological organisation determines itself in the sense that the effects of its activity contribute to determine its own conditions of existence. We suggest that not any kind of circular regime realises self-determination, which should be specifically understood as self-constraint: in biological systems, in particular, self-constraint takes the form of closure, i.e. a network of mutually dependent constitutive constraints. We then explore the occurrence of intrinsic teleology in the biological domain and beyond. On the one hand, the organisational account might possibly concede that supra-organismal biological systems (as symbioses or ecosystems) could realise closure, and hence be teleological. On the other hand, the realisation of closure beyond the biological realm appears to be highly unlikely. In turn, the occurrence of simpler forms of self-determination remains a controversial issue, in particular with respect to the case of self-organising dissipative systems.

We argue that deliberative decision making that is inclusive, transparent and accountable can contribute to more trustworthy and legitimate decisions on difficult ethical questions and political trade-offs during the pandemic and beyond.