Mixture models for distance sampling detection functions

Funding: EPSRC DTGWe present a new class of models for the detection function in distance sampling surveys of wildlife populations, based on finite mixtures of simple parametric key functions such as the half-normal. The models share many of the features of the widely-used “key function plus series adjustment” (K+A) formulation: they are flexible, produce plausible shapes with a small number of parameters, allow incorporation of covariates in addition to distance and can be fitted using maximum likelihood. One important advantage over the K+A approach is that the mixtures are automatically monotonic non-increasing and non-negative, so constrained optimization is not required to ensure distance sampling assumptions are honoured. We compare the mixture formulation to the K+A approach using simulations to evaluate its applicability in a wide set of challenging situations. We also re-analyze four previously problematic real-world case studies. We find mixtures outperform K+A methods in many cases, particularly spiked line transect data (i.e., where detectability drops rapidly at small distances) and larger sample sizes. We recommend that current standard model selection methods for distance sampling detection functions are extended to include mixture models in the candidate set.Publisher PDFPeer reviewe

Coopetition as a development stimulator of enterprises in the networked steel sector

The article deals with the problems of coopetition, i.e. simultaneous cooperation and competition between enterprises. This phenomenon is becoming more and more common in the steel industry, initially in the dimension of individual alliances, and currently it takes a form of network connections. The different groups of enterprises are involved in these networks: global players, regional champions, as well as niche specialists. Through the coopetition companies achieve benefits (both internal and external) which are becoming the stimulator of survival and growth in a highly competitive steel industry

Susceptibility to increased high energy dense sweet and savoury food intake in response to the COVID-19 lockdown: The role of craving control and acceptance coping strategies

Emerging evidence indicates that for some people, the COVID-19 lockdowns are a time of high risk for increased food intake. A clearer understanding of which individuals are most at risk of over-eating during the lockdown period is needed to inform interventions that promote healthy diets and prevent weight gain during lockdowns. An online survey collected during the COVID-19 lockdown (total n = 875; analysed n = 588; 33.4 ± 12.6 years; 82% UK-based; mostly white, educated, and not home schooling) investigated reported changes to the amount consumed and changes to intake of high energy dense (HED) sweet and savoury foods. The study also assessed which eating behaviour traits predicted a reported increase of HED sweet and savoury foods and tested whether coping responses moderated this relationship. Results showed that 48% of participants reported increased food intake in response to the COVID-19 lockdown. There was large individual variability in reported changes and lower craving control was the strongest predictor of increased HED sweet and savoury food intake. Low cognitive restraint also predicted greater increases in HED sweet snacks and HED savoury meal foods. Food responsiveness, enjoyment of food, emotional undereating, emotional overeating and satiety responsiveness were not significant predictors of changes to HED sweet and savoury food intake. High scores on acceptance coping responses attenuated the conditional effects of craving control on HED sweet snack intake. Consistent with previous findings, the current research suggests that low craving control is a risk factor for increased snack food intake during lockdown and may therefore represent a target for intervention

Low Pressure Negative Ion Drift Chamber for Dark Matter Search

Weakly Interacting Massive Particles (WIMPs) are an attractive candidate for the dark matter thought to make up the bulk of the mass of our universe. We explore here the possibility of using a low pressure negative ion drift chamber to search for WIMPs. The innovation of drifting ions, instead of electrons, allows the design of a detector with exceptional sensitivity to, background rejection from, and signature of WIMPs.Comment: 5 pages submitted to PR

Sub MeV Particles Detection and Identification in the MUNU detector ((1)ISN, IN2P3/CNRS-UJF, Grenoble, France, (2)Institut de Physique, Neuch\^atel, Switzerland, (3) INFN, Padova Italy, (4) Physik-Institut, Z\"{u}rich, Switzerland)

We report on the performance of a 1 m$^{3}$ TPC filled with CF$_{4}$ at 3 bar, immersed in liquid scintillator and viewed by photomultipliers. Particle detection, event identification and localization achieved by measuring both the current signal and the scintillation light are presented. Particular features of $\alpha$ particle detection are also discussed. Finally, the ${54}$Mn photopeak, reconstructed from the Compton scattering and recoil angle is shown.Comment: Latex, 19 pages, 20 figure

Preliminary archaeoentomological analyses of permafrost-preserved cultural layers from the pre-contact Yup’ik Eskimo site of Nunalleq, Alaska : implications, potential and methodological considerations

Acknowledgements Site excavation and samples collection were conducted by archaeologists from the University of Aberdeen, with the help of archaeologists and student excavators from the University of Aberdeen University of Alaska Fairbanks and Bryn Mawr College, Kuskokwim Campus, College of Rural Alaska and residents of Quinhagak and Mekoryuk. This study is funded through AHRC grant to the project ‘Understanding Cultural Resilience and Climate Change on the Bering Sea through Yup’ik Ecological Knowledge, Lifeways, Learning and Archaeology’ to Rick Knecht, Kate Britton and Charlotta Hillderal (University of Aberdeen; AH/K006029/1). Thanks are due to Qanirtuuq Inc. and Quinhagak, Alaska for sampling permissions and to entomologists working at the CNC in Ottawa for allowing access to reference collections of beetles, lice and fleas. Yves Bousquet, Ales Smetana and Anthony E. Davies are specially acknowledged for their help with the identification of coleopteran specimens. Finally, we would also like to thank Scott Elias for useful comments on the original manuscript.Peer reviewedPublisher PD

SUSY Dark Matter in the Universe- Theoretical Direct Detection Rates

Exotic dark matter together with the vacuum energy or cosmological constant seem to dominate in the Universe. An even higher density of such matter seems to be gravitationally trapped in the Galaxy. Thus its direct detection is central to particle physics and cosmology. Current supersymmetric models provide a natural dark matter candidate which is the lightest supersymmetric particle (LSP). Such models combined with fairly well understood physics like the quark substructure of the nucleon and the nuclear structure (form factor and/or spin response function), permit the evaluation of the event rate for LSP-nucleus elastic scattering. The thus obtained event rates are, however, very low or even undetectable. So it is imperative to exploit the modulation effect, i.e. the dependence of the event rate on the earth's annual motion. Also it is useful to consider the directional rate, i.e its dependence on the direction of the recoiling nucleus. In this paper we study such a modulation effect both in non directional and directional experiments. We calculate both the differential and the total rates using both isothermal, symmetric as well as only axially asymmetric, and non isothermal, due to caustic rings, velocity distributions. We find that in the symmetric case the modulation amplitude is small. The same is true for the case of caustic rings. The inclusion of asymmetry, with a realistic enhanced velocity dispersion in the galactocentric direction, yields an enhanced modulation effect, especially in directional experiments.Comment: 17 LATEX pages, 1 table and 6 ps figures include

Exploring the behavioural drivers of veterinary surgeon antibiotic prescribing: a qualitative study of companion animal veterinary surgeons in the UK

Background: Multi-drug resistant bacteria are an increasing concern in both human and veterinary medicine. Inappropriate prescribing and use of antibiotics within veterinary medicine may be a contributory factor to antimicrobial resistance (AMR). The ‘One Health’ Initiative aims to work across species and environments to reduce AMR, however; little is currently known about the factors which influence antibiotic prescribing among veterinary surgeons in companion animal practice. This paper reports on qualitative data analysis of interviews with veterinary surgeons whose practice partially or wholly focuses on companion animals (N = 16). The objective of the research was to explore the drivers of companion animal veterinary surgeons’ antibiotic prescribing behaviours. The veterinary surgeons interviewed were all practising within the UK (England (n = 4), Scotland (n = 11), Northern Ireland (n = 1)). A behavioural thematic analysis of the data was undertaken, which identified barriers and facilitators to specific prescribing-related behaviours. Results: Five components of prescribing behaviours were identified: 1) confirming clinical need for antibiotics; 2) responding to clients; 3) confirming diagnosis; 4) determining dose, duration and type of antibiotic; and 5) preventing infection around surgery (with attendant appropriate and inappropriate antibiotic prescribing behaviours). Barriers to appropriate prescribing identified include: business, diagnostic, fear, habitual practice and pharmaceutical factors. Facilitators include: AMR awareness, infection prevention, professional learning and regulation and government factors. Conclusion: This paper uses a behavioural lens to examine drivers which are an influence on veterinary surgeons’ prescribing behaviours. The paper contributes new understandings about factors which influence antibiotic prescribing behaviours among companion animal veterinary surgeons. This analysis provides evidence to inform future interventions, which are focused on changing prescribing behaviours, in order to address the pressing public health concern of AMR

Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems

In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. - a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world