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We find that the Campbell–Cochrane external-habit model can generate a value premium if the persistence of the consumption surplus is sufficiently low. Such low persistence is supported by micro evidence on consumption. If the mean and conditional volatility of consumption growth are highly persistent, as in the Bansal–Yaron long-run risk model, then fast-moving habit can also generate, without eroding the value premium: i) empirically sensible long horizon return predictability; and ii) a price–dividend ratio for market equity that exhibits the high autocorrelation found in the data. Fast-moving habit also delivers several empirical properties of market-dividend strips.

Error-corrected next-generation sequencing (ecNGS) is an emerging technology with the potential to revolutionize the field of genetic toxicology. Here, we present recommendations from an expert working group convened to discuss potential applications, advantages and challenges associated with implementing ecNGS in nonclinical safety studies.Error-corrected next-generation sequencing (ecNGS) is an emerging technology with the potential to revolutionize the field of genetic toxicology. Here, we present recommendations from an expert working group convened to discuss potential applications, advantages and challenges associated with implementing ecNGS in nonclinical safety studies.

Constantinides (1986) documents how the impact of transaction costs on per-annum liquidity premia in the standard dynamic allocation problem with i.i.d. returns is an order of magnitude smaller than the cost rate itself. Recent papers form portfolios sorted on liquidity measures and find spreads in expected per-annum return that are the same order of magnitude as the transaction cost spread. When we allow returns to be predictable and introduce wealth shocks calibrated to labor income, transaction costs are able to produce per-annum liquidity premia that are the same order of magnitude as the transaction cost spread.

To describe trends in the incidence of non-traumatic amputations among people with and without diabetes and estimate the relative risk of an individual with diabetes undergoing a lower extremity amputation compared to an individual without diabetes in the Republic of Ireland. All adults who underwent a nontraumatic amputation during 2005 to 2009 were identified using HIPE (Hospital In-patient Enquiry) data. Participants were classified as having diabetes or not having diabetes. Incidence rates were calculated using the number of discharges for diabetes and non-diabetes related lower extremity amputations as the numerator and estimates of the resident population with and without diabetes as the denominator. Age-adjusted incidence rates were used for trend analysis. Total diabetes-related amputation rates increased non-significantly during the study period; 144.2 in 2005 to 175.7 in 2009 per 100,000 people with diabetes (p = 0.11). Total non-diabetes related amputation rates dropped non-significantly from 12.0 in 2005 to 9.2 in 2009 per 100,000 people without diabetes (p = 0.16). An individual with diabetes was 22.3 (95% CI 19.1-26.1) times more likely to undergo a nontraumatic amputation than an individual without diabetes in 2005 and this did not change significantly by 2009. This study provides the first national estimate of lower extremity amputation rates in the Republic of Ireland. Diabetes-related amputation rates have remained steady despite an increase in people with diabetes. These estimates provide a base-line and will allow follow-up over time.

Genetic toxicity testing assesses the potential of compounds to cause DNA damage. There are many genetic toxicology screening assays designed to assess the DNA damaging potential of chemicals in early drug development aiding the identification of promising drugs that have low-risk potential for causing genetic damage contributing to cancer risk in humans. Despite this, in vitro tests generate a high number of misleading positives, the consequences of which can lead to unnecessary animal testing and/or the abandonment of promising drug candidates. Understanding chemical Mode of Action (MoA) is vital to identifying the true genotoxic potential of substances and, therefore, the risk translation into the clinic. Here we demonstrate a simple, robust protocol for staining fixed, human-lymphoblast p53 proficient TK6 cells with antibodies against ɣH2AX, p53 and pH3S28 along with DRAQ5™ DNA staining that enables analysis of un-lysed cells via microscopy approaches such as imaging flow cytometry. Here, we used the Cytek® Amnis® ImageStream®X Mk II which provides a high-throughput acquisition platform with the sensitivity of flow cytometry and spatial morphological information associated with microscopy. Using the ImageStream manufacturer’s software (IDEAS® 6.2), a masking strategy was developed to automatically detect and quantify micronucleus events (MN) and characterise biomarker populations. The gating strategy developed enables the generation of a template capable of automatically batch processing data files quantifying cell-cycle, MN, ɣH2AX, p53 and pH3 populations simultaneously. In this way, we demonstrate how a multiplex system enables DNA damage assessment alongside MN identification using un-lysed cells on the imaging flow cytometry platform. As a proof-of-concept, we use the tool chemicals carbendazim and methyl methanesulphonate (MMS) to demonstrate the assay’s ability to correctly identify clastogenic or aneugenic MoAs using the biomarker profiles established.

This paper numerically solves the decision problem of a multiperiod constant relative risk aversion individual who faces transaction costs and has access to two risky assets, both with predictable returns. With proportional transaction costs and independent and identically distributed returns, we numerically find the rebalancing rule to be a no-trade region for the portfolio weights with rebalancing to the boundary. The shape of the no-trade region depends on the correlation between the two risky assets. With predictable returns, there is instead a no-trade region for each state. We also examine several important economic questions, including the utility cost of not being able to buy on margin or short stock.

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25–5.0 μg/mL) and/or carbendazim (0.8–1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the “DeepFlow” neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for ‘mononucleates’, ‘binucleates’, ‘mononucleates with MN’ and ‘binucleates with MN’, respectively. Successful classifications of ‘trinucleates’ (90%) and ‘tetranucleates’ (88%) in addition to ‘other or unscorable’ phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

The literature documents a convex relation between past returns and fund flows of mutual funds. We show this to be consistent with fund incentives, because funds discard exactly those strategies which underperform. Past returns tell less about the future performance of funds which discard, so flows are less sensitive to them when they are poor. Our model predicts that strategy changes only occur after bad performance, and that bad performers who change strategy have dollar flow and future performance that are less sensitive to current performance than those that do not. Empirical tests support both predictions.

Despite its relative infancy, ecological science plays a pre‐eminent role in current environmental decision‐making globally and has, over recent decades, permeated a broad range of academic disciplines. Developments in two areas of philosophical thought in particular, environmental aesthetics and the aesthetics of science, beg an exploration of their intersection with respect to the role of aesthetics in ecological science. Here, we provide a contemporary synthesis of both environmental aesthetics and aesthetics of science to explore aesthetic dimensions of contemporary ecological science, highlighting three main areas of convergence: (1) the influence of aesthetic experiences and judgements of nature by ecologists on ecological science and our contemporary understanding of nature; (2) the development and role of ecological ‘taste’ among ecologists; and (3) moral, cultural and political implications of the ecological imagination as underpinned by current ecological science. We identify a risk for feedback mechanisms to perpetuate a relatively homogeneous ecological aesthetic as a result of reciprocal influences between ecological science and society which may further promote inadvertent policy advocacy and stifle scientific innovation. We suggest ecological science would benefit from increased aesthetic literacy and reflection by broadening the ecological imagination and intentionally facilitating more diverse and equitable science to inform policy outcomes. Our argument should be of interest to philosophers of science, ecologists and those that draw on their outputs. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.

Elite neoliberal policy consensus requires traditional parties of the left and right to progressively sever their connection with their traditional party bases. The task fell first on parties of the left, but now it falls too on parties of the right. Tony Abbott's Liberal National Party government provides a case study in how this challenge impacts on parties of the right, and how this impact is likely to play out.