The COVID-19 pandemic illustrates perfectly how the operation of science changes when questions of urgency, stakes, values and uncertainty collide -in the 'post-normal' regime. Well before the coronavirus pandemic, statisticians were debating how to prevent malpractice such as p-hacking, particularly when it could influence policy 1 . Now, computer modelling is in the limelight, with politicians presenting their policies as dictated by 'science' 2 . Yet there is no substantial aspect of this pandemic for which any researcher can currently provide precise, reliable numbers. Known unknowns include the prevalence and fatality and reproduction rates of the virus in Pandemic politics highlight how predictions need to be transparent and humble to invite insight, not blame.

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Decision-making on numerous aspects of our daily lives is being outsourced to machinelearning (ML) algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. ML approaches-one of the typologies of algorithms underpinning artificial intelligence-are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AIdriven decision-making are outlined: (a) risk assessment in the criminal justice system, and (b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined.

Reversible and selective binding of a dynamically racemic europium(III) complex to α(1)-acid glycoprotein and α(1)-antitrypsin is characterised by a significant change in the europium total emission spectral fingerprint and the switching on of a large circularly polarised luminescence (CPL) signal from the metal centre. Observation of an induced CD into the ligand chromophore in the presence of α(1)-AGP allows a structure for the protein-bound complex to be postulated. A direct determination of elevated α(1)-AGP levels in human serum was achieved by monitoring changes in the intensity ratio of Eu emission bands.

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The reasons for and against composite indicators are briefly reviewed, as well as the available theories for their construction. After noting the strong normative dimension of these measures-which ultimately aim to 'tell a story', e.g. to promote the social discovery of a particular phenomenon, we inquire whether a less partisan use of a composite indicator can be proposed by allowing more latitude in the framing of its construction. We thus explore whether a composite indicator can be built to tell 'more than one story' and test this in practical contexts. These include measures used in convergence analysis in the field of cohesion policies and a recent case involving the World Bank's Doing Business Index. Our experiments are built to imagine different constituencies and stakeholders who agree on the use of evidence and of statistical information while differing on the interpretation of what is relevant and vital.

In this paper a photovoltaic (PV) technologies for electricity generation accounting scheme is proposed and applied. The adopted scheme aims to overcome limitations of conventional indicators such as EROI (Energy Return on Investment) and EPBT (Energy Payback Time) and to present a more comprehensive description of energy and material transformations. The proposed methodology is based on the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach. In this work, four dimensions of sustainability which should be addressed for the purpose of identifying the limiting factors of photovoltaic systems for electricity production are presented: Energy and Material Accessibility; Environmental Health Desirability; Technological Achievability; and Socioeconomic Acceptability. In relation to these four dimensions, the direct and indirect requirements of flow and fund elements (silver, energy carriers and water as flows; human time and land as funds) in photovoltaic power stations based on crystalline silicon wafer cells are evaluated and the implications of the overall performance and limitations of the present PV systems are discussed. These parameters are also compared with other electricity production technologies as well as benchmarked against the performance of the energy and mining sector of a modern country (Spain). It is concluded that the availability of silver could constrain photovoltaic cell manufacturing. Furthermore, the low power density of photovoltaic installations could drive a remarkable land rush. Finally, the human labor allocated in the fund-making process could represent a serious constraint in respect to the requirements of the metabolism of modern societies.

The VCD spectra of lanthanide chelates with two chiral ligands display conserved sequences of bands throughout the Ln series. Some compounds (Tm, Yb) feature increased bands and strongly improved signal-to-noise ratios, an effect we dub Lanthanide Induced VCD Enhancement (LIVE).