Excavations at Knowth Volume 6: The Passage Tomb Archaeology of the Great Mound at Knowth

The Brú na Bóinne complex in County Meath, Ireland, is one of the greatest Neolithic landscapes in northern Europe. Anyone who has ever had the chance to see these sites will know that these are truly monumental feats of engineering and it is only through experiencing these sites first hand that one is able to appreciate the size and scale of the monuments in this landscape. Rightly so, these sites have featured heavily in narratives of the Irish Neolithic where they are often described as the pinnacle of megalithic design and construction. These sites, however, cannot be considered ‘typical’. While there are other, large passage tombs, and other complexes of sites such as Loughcrew and Carrowkeel, Brú na Bóinne stands apart in terms of the sheer scale of the megalithic endeavour. These monuments have also been subjected to extensive amounts of research and fieldwork over the years, much still ongoing. Indeed, despite this landscape having been the focus for research for decades, new discoveries are being made all the time, as we saw in the summer of 2018 when drought conditions revealed previously unknown sites through parch marks seen from above

Microtomography with 3-D visualization

The facility has been developed for producing high quality tomographs of order one micrometer resolution. Three dimensional volumes derived from groups of adjacent tomographic slices are then viewed and navigated in a stereographic viewing facility. This facility is being applied to problems in geological evaluation of oil reservoir rock, medical imaging, protein chemistry, and CADCAM

Prediction of photoperiodic regulators from quantitative gene circuit models

Photoperiod sensors allow physiological adaptation to the changing seasons. The external coincidence hypothesis postulates that a light-responsive regulator is modulated by a circadian rhythm. Sufficient data are available to test this quantitatively in plants, though not yet in animals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their lightsensitive proteins are thought to form an external coincidence sensor. We use 40 timeseries of molecular data to model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, the models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modelling makes this complexity explicit and may thus contribute to crop improvement

First validation of high-resolution satellite-derived methane emissions from an active gas leak in the UK

Atmospheric methane (CH4) is the second-most-important anthropogenic greenhouse gas and has a 20-year global warming potential 82 times greater than carbon dioxide (CO2). Anthropogenic sources account for g1/4g% of global CH4 emissions, of which 20g% come from oil and gas exploration, production and distribution. High-resolution satellite-based imaging spectrometers are becoming important tools for detecting and monitoring CH4 point source emissions, aiding mitigation. However, validation of these satellite measurements, such as those from the commercial GHGSat satellite constellation, has so far not been documented for active leaks. Here we present the monitoring and quantification, by GHGSat's satellites, of the CH4 emissions from an active gas leak from a downstream natural gas distribution pipeline near Cheltenham, UK, in the spring and summer of 2023 and provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys. We also use a Lagrangian transport model, the UK Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME), to estimate the flux from both satellite-and ground-based observation methods and assess the leak's contribution to observed concentrations at a local tall tower site (30gkm away). We find GHGSat's emission estimates to be in broad agreement with those made from the in situ measurements. During the study period (March-June 2023) GHGSat's emission estimates are 236-1357gkggCH4gh-1, whereas the mobile surface measurements are 634-846gkggCH4gh-1. The large variability is likely down to variations in flow through the pipe and engineering works across the 11-week period. Modelled flux estimates in NAME are 181-1243gkggCH4gh-1, which are lower than the satellite-and mobile-survey-derived fluxes but are within the uncertainty. After detecting the leak in March 2023, the local utility company was contacted, and the leak was fixed by mid-June 2023. Our results demonstrate that GHGSat's observations can produce flux estimates that broadly agree with surface-based mobile measurements. Validating the accuracy of the information provided by targeted, high-resolution satellite monitoring shows how it can play an important role in identifying emission sources, including unplanned fugitive releases that are inherently challenging to identify, track, and estimate their impact and duration. Rapid, widespread access to such data to inform local action to address fugitive emission sources across the oil and gas supply chain could play a significant role in reducing anthropogenic contributions to climate change.</p

Estimating bank default with generalised extreme value regression models

The paper proposes a novel model for the prediction of bank failures, on the basis of both macroeconomic and bank-specific microeconomic factors. As bank failures are rare, in the paper we apply a regression method for binary data based on extreme value theory, which turns out to be more effective than classical logistic regression models, as it better leverages the information in the tail of the default distribution. The application of this model to the occurrence of bank defaults in a highly bank dependent economy (Italy) shows that, while microeconomic factors as well as regulatory capital are significant to explain proper failures, macroeconomic factors are relevant only when failures are defined not only in terms of actual defaults but also in terms of mergers and acquisitions. In terms of predictive accuracy, the model based on extreme value theory outperforms classical logistic regression models

A partial wave analysis of the π0π0\pi ^0\pi ^0 system produced in π−p\pi ^-p charge exchange collisions

A partial wave analysis of the of the $\pi ^0\pi ^0$ system produced in the charge exchange reaction: $\pi ^-p\to \pi ^0\pi ^0n$ at an incident momentum of $18.3 GeV/c$ is presented as a function of ${\pi ^0\pi ^0}$ invariant mass, $m_{\pi^0\pi^0}$, and momentum transfer squared, $| {t} |$, from the incident $\pi^-$ to the outgoing ${\pi ^0\pi ^0}$ system.Comment: 24 pages total,8 pages text, 14 figures, 1 table. Submitted to Phys Rev

Spatial Patterns of Aflatoxin Levels in Relation to Ear-Feeding Insect Damage in Pre-Harvest Corn

Key impediments to increased corn yield and quality in the southeastern US coastal plain region are damage by ear-feeding insects and aflatoxin contamination caused by infection of Aspergillus flavus. Key ear-feeding insects are corn earworm, Helicoverpa zea, fall armyworm, Spodoptera frugiperda, maize weevil, Sitophilus zeamais, and brown stink bug, Euschistus servus. In 2006 and 2007, aflatoxin contamination and insect damage were sampled before harvest in three 0.4-hectare corn fields using a grid sampling method. The feeding damage by each of ear/kernel-feeding insects (i.e., corn earworm/fall armyworm damage on the silk/cob, and discoloration of corn kernels by stink bugs), and maize weevil population were assessed at each grid point with five ears. The spatial distribution pattern of aflatoxin contamination was also assessed using the corn samples collected at each sampling point. Aflatoxin level was correlated to the number of maize weevils and stink bug-discolored kernels, but not closely correlated to either husk coverage or corn earworm damage. Contour maps of the maize weevil populations, stink bug-damaged kernels, and aflatoxin levels exhibited an aggregated distribution pattern with a strong edge effect on all three parameters. The separation of silk- and cob-feeding insects from kernel-feeding insects, as well as chewing (i.e., the corn earworm and maize weevil) and piercing-sucking insects (i.e., the stink bugs) and their damage in relation to aflatoxin accumulation is economically important. Both theoretic and applied ramifications of this study were discussed by proposing a hypothesis on the underlying mechanisms of the aggregated distribution patterns and strong edge effect of insect damage and aflatoxin contamination, and by discussing possible management tactics for aflatoxin reduction by proper management of kernel-feeding insects. Future directions on basic and applied research related to aflatoxin contamination are also discussed