Multifunctional Polyoxometalate Platforms for Supramolecular Light-Driven Hydrogen Evolution

Multifunctional supramolecular systems are a central research topic in light-driven solar energy conversion. Here, we report a polyoxometalate (POM)-based supramolecular dyad, where two platinum-complex hydrogen evolution catalysts are covalently anchored to an Anderson polyoxomolybdate anion. Supramolecular electrostatic coupling of the system to an iridium photosensitizer enables visible light-driven hydrogen evolution. Combined theory and experiment demonstrate the multifunctionality of the POM, which acts as photosensitizer/catalyst-binding-site[1] and facilitates light-induced charge-transfer and catalytic turnover. Chemical modification of the Pt-catalyst site leads to increased hydrogen evolution reactivity. Mechanistic studies shed light on the role of the individual components and provide a molecular understanding of the interactions which govern stability and reactivity. The system could serve as a blueprint for multifunctional polyoxometalates in energy conversion and storage

The four weeks before lockdown during the COVID-19 pandemic in Germany: A weekly serial cross-sectional survey on risk perceptions, knowledge, public trust and behaviour, 3 to 25 March 2020

Background: During the COVID-19 pandemic, public perceptions and behaviours have had to adapt rapidly to new risk scenarios and radical behavioural restrictions. Aim: To identify major drivers of acceptance of protective behaviours during the 4-week transition from virtually no COVID-19 cases to the nationwide lockdown in Germany (3–25 March 2020). Methods: A serial cross-sectional online survey was administered weekly to ca 1,000 unique individuals for four data collection rounds in March 2020 using non-probability quota samples, representative of the German adult population between 18 and 74 years in terms of age × sex and federal state (n = 3,910). Acceptance of restrictions was regressed on sociodemographic variables, time and psychological variables, e.g. trust, risk perceptions, self-efficacy. Extraction of homogenous clusters was based on knowledge and behaviour. Results: Acceptance of restrictive policies increased with participants’ age and employment in the healthcare sector; cognitive and particularly affective risk perceptions were further significant predictors. Acceptance increased over time, as trust in institutions became more relevant and trust in media became less relevant. The cluster analysis further indicated that having a higher education increased the gap between knowledge and behaviour. Trust in institutions was related to conversion of knowledge into action. Conclusion: Identifying relevant principles that increase acceptance will remain crucial to the development of strategies that help adjust behaviour to control the pandemic, possibly for years to come. Based on our findings, we provide operational recommendations for health authorities regarding data collection, health communication and outreach

Analysis of CP Violation in Neutralino Decays to Tau Sleptons

In the minimal supersymmetric standard model, tau sleptons $\tilde \tau_{1,2}$ and neutralinos $\tilde \chi^0_{1,2}$ are expected to be among the lightest supersymmetric particles that can be produced copiously at future $e^+e^-$ linear colliders. We analyze $\tilde \tau$ pair and $\tilde \chi_1^0 \tilde \chi_2^0$ production under the assumption $m_{\tilde \chi_1^0} < m_{\tilde \tau_1} < m_{\tilde \chi_2^0}$, allowing the relevant parameters of the SUSY Lagrangian to have complex phases. We show that the transverse and normal components of the polarization vector of the $\tau$ lepton produced in $\tilde \chi_2^0$ decays offer sensitive probes of these phases.Comment: LaTeX, 30 pages with 10 .eps figure

CP Violation in Tau Slepton Pair Production at Muon Colliders

We discuss in detail signals for CP violation in the Higgs boson and tau-slepton sectors through the production processes $\mu^+\mu^- \to \tilde{\tau}_i^- \tilde{\tau}_j^+$, where $i,j=1,2$ label the two $\tau$ slepton mass eigenstates in the minimal supersymmetric standard model. We assume that the soft breaking parameters of third generation sfermions contain CP violating phases, which induce CP violation in the Higgs sector through quantum corrections. We classify all the observables for probing CP violation in the Higgs boson and $\tau$ slepton sectors. These observables depend on the initial muon beam polarization, where we include transverse polarization states. If the heavy Higgs bosons can decay into tau slepton pairs, a complete determination of the CP properties of the neutral Higgs boson and $\tau$--slepton systems is possible. The interference between the Higgs boson and gauge boson contributions could also provide a powerful method for probing CP violation, if transversely polarized muon beams are available. We show in detail how to directly measure CP violation in the tau slepton system, under the assumption that the neutral Higgs mixing angles are determined through the on--shell production of the neutral Higgs bosons.Comment: 38 pages, 9 figures Including 7 eps ones. A figure to show the dependence on tan(beta) and the mass parameters of the sfermion sectors and a reference added. To appear in Phys. Rev.

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.&#xd;&#xa;In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

Reasoning with heuristics

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational achievement. Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats’ neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments