Photoisomerization Efficiency of a Solar Thermal Fuel in the Strong Coupling Regime

Strong exciton-photon coupling is achieved when the interaction between molecules and an electromagnetic field is increased to a level where they cannot be treated as separate systems. This leads to the formation of polaritonic states and an effective rearrangement of the potential energy surfaces, which opens the possibility to modify photochemical reactions. This work investigates how the strong coupling regime is affecting the photoisomerization efficiency and thermal backconversion of a norbornadiene–quadricyclane molecular photoswitch. The quantum yield of photoisomerization shows both an excitation wavelength and exciton/photon constitution dependence. The polariton-induced decay and energy transfer processes are discussed to be the reason for this finding. Furthermore, the thermal back conversion of the system is unperturbed and the lower polariton effectively shifts the absorption onset to lower energies. The reason for the unperturbed thermal backconversion is that it occurs on the ground state, which is unaffected. This work demonstrates how strong coupling can change material properties towards higher efficiencies in applications. Importantly, the experiments illustrate that strong coupling can be used to optimize the absorption onset of the molecular photoswitch norbonadiene without affecting the back reaction from the uncoupled quadricyclane

The burdens of poverty during the COVID-19 pandemic

Background: Individuals living at-risk-of-poverty have an increased risk of poor mental health. The pandemic and its societal impacts might have negative effects especially on this group widening the gap between rich and poor and also exacerbate gender gaps, which in turn might impact social cohesion. Aim: The objective of this longitudinal study was to determine if people living at-risk-of-poverty were more vulnerable to economic and psychosocial impacts of the pandemic and showed poorer mental health. Moreover, gender differences were analyzed. Method: We drew data from a sample of N = 10,250 respondents of two time points (T1 starting from October 2020, T2 starting from March 2021) of the Gutenberg COVID-19 Study. We tested for differences between people living at-risk-of-poverty and more affluent respondents regarding economic impacts, psychosocial stressors, as well as depressiveness, anxiety and loneliness, by comparing mean and distributional differences. To test for significant discrepancy, we opted for chi-square- and t-tests. Results: The analysis sample compromised N = 8,100 individuals of which 4,2% could be classified as living at-risk-of-poverty. 23% of respondents living at-risk-of-poverty had a decrease in income since the beginning of the pandemic–twice as many as those not living at-risk-of-poverty, who reported more often an increase in income. Less affluent individuals reported a decrease in working hours, while more affluent people reported an increase. Between our survey time points, we found a significant decrease in these economic impacts. Gender differences for economic changes were only found for more affluent women who worked more hours with no change in income. Less affluent respondents were more impacted by psychosocial stressors, depressiveness, anxiety, and loneliness. Gender differences were found particularly with regard to care responsibilities. Discussion: Our results indicate a widening in the gap between the rich and the poor at the beginning of the pandemic. Gender differences concerning economic changes affect more affluent women, but women in both income groups are more burdened by care responsibilities, which might indicate a heightened resurgence of gender role in times of crisis. This increase in inequality might have impacted social cohesion

Designing Ecosystems of Intelligence from First Principles

This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants -- what we call ''shared intelligence''. This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one's sensed world -- also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales: i.e., inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent's generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing -- leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first -- and key -- step towards such an ecology.Comment: 23+18 pages, one figure, one six page appendi

Dynamic Career Models and Inequality Research: A Reexamination of the Sørensen Model

This article presents a reexamination of the Sørensen model. This model derives the pattern of individual careers from structural considerations. If longitudinal data on individual careers are available, Sørensen's model provides two methods to infer the underlying structural parameter. This structural parameter gives a useful measure for unequal career chances. An implementation of these methods, using firm data, shows, however, that they lead to contradictory conclusions; this is shown to be the result of some unrealistic assumptions Sørensen uses in his derivation. Some more realistic assumptions are suggested that produce reasonable results. Finally, it is shown that despite these modifications, the main conclusions of the Sørensen model are preserved. This seems to be promising for future work with this model

Achieving temperature-size changes in a unicellular organism.

The temperature-size rule (TSR) is an intraspecific phenomenon describing the phenotypic plastic response of an organism size to the temperature: individuals reared at cooler temperatures mature to be larger adults than those reared at warmer temperatures. The TSR is ubiquitous, affecting >80% species including uni- and multicellular groups. How the TSR is established has received attention in multicellular organisms, but not in unicells. Further, conceptual models suggest the mechanism of size change to be different in these two groups. Here, we test these theories using the protist Cyclidium glaucoma. We measure cell sizes, along with population growth during temperature acclimation, to determine how and when the temperature-size changes are achieved. We show that mother and daughter sizes become temporarily decoupled from the ratio 2:1 during acclimation, but these return to their coupled state (where daughter cells are half the size of the mother cell) once acclimated. Thermal acclimation is rapid, being completed within approximately a single generation. Further, we examine the impact of increased temperatures on carrying capacity and total biomass, to investigate potential adaptive strategies of size change. We demonstrate no temperature effect on carrying capacity, but maximum supported biomass to decrease with increasing temperature

Genome-Wide Profiling of Histone H3 Lysine 4 and Lysine 27 Trimethylation Reveals an Epigenetic Signature in Prostate Carcinogenesis

BACKGROUND: Increasing evidence implicates the critical roles of epigenetic regulation in cancer. Very recent reports indicate that global gene silencing in cancer is associated with specific epigenetic modifications. However, the relationship between epigenetic switches and more dynamic patterns of gene activation and repression has remained largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: Genome-wide profiling of the trimethylation of histone H3 lysine 4 (H3K4me3) and lysine 27 (H3K27me3) was performed using chromatin immunoprecipitation coupled with whole genome promoter microarray (ChIP-chip) techniques. Comparison of the ChIP-chip data and microarray gene expression data revealed that loss and/or gain of H3K4me3 and/or H3K27me3 were strongly associated with differential gene expression, including microRNA expression, between prostate cancer and primary cells. The most common switches were gain or loss of H3K27me3 coupled with low effect on gene expression. The least prevalent switches were between H3K4me3 and H3K27me3 coupled with much higher fractions of activated and silenced genes. Promoter patterns of H3K4me3 and H3K27me3 corresponded strongly with coordinated expression changes of regulatory gene modules, such as HOX and microRNA genes, and structural gene modules, such as desmosome and gap junction genes. A number of epigenetically switched oncogenes and tumor suppressor genes were found overexpressed and underexpressed accordingly in prostate cancer cells. CONCLUSIONS/SIGNIFICANCE: This work offers a dynamic picture of epigenetic switches in carcinogenesis and contributes to an overall understanding of coordinated regulation of gene expression in cancer. Our data indicate an H3K4me3/H3K27me3 epigenetic signature of prostate carcinogenesis