Observation of an interaction between a domestic cat and a group of Eurasian otters in Aberdeen (UK)

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Productivity, Digital Footprint and Sustainability in the Textile and Clothing Industry

[EN] In recent years, there has been a shift from the linear economic model on which the textile and clothing industry is based to a more sustainable model. However, to date, limited research on the relationship between sustainability commitment and firm productivity has focused on the textile and clothing industry. This study addresses this gap and aims to explore whether the digital footprint of small and medium-sized textile companies in terms of their sustainable performance is related to their productivity. To this end, the paper proposes an innovative model to monitor the companies’ commitment to sustainable issues by analyzing online data retrieved from their corporate websites. This information is merged with balance sheet data to examine the impact of sustainability practices, capital and human capital on productivity. The estimated firm’s total factor productivity is explained as a function of the sustainability digital footprint measures and additional control variables for a sample of 315 textile firms located in the region of Comunidad Valenciana, Spain.This work was partially funded by MCIN/AEI/10.13039/501100011033 under grant PID2019-107765RB-I00.Domenech, J.; Garcia-Bernabeu, A.; Diaz-Garcia, P. (2023). Productivity, Digital Footprint and Sustainability in the Textile and Clothing Industry. Editorial Universitat Politècnica de València. 319-326. https://doi.org/10.4995/CARMA2023.2023.1644631932

Using a modelling approach to inform progress towards stoat eradication from the Orkney Islands

Funding For the analyses reported in this paper study, KZ was financed by the Bekker programme of the Polish National Agency for Academic Exchange (NAWA), grant PPN/BEK/2019/1/00036 to KZ. PGD and XL were supported in part by the NERC grant (NE/S011641/1). The ONWP funders: National Lottery Heritage Fund, EU life programme (LIFE17 UK/NAT/000557), Nature Scot and RSPB. Acknowledgements We would like to acknowledge all the ONWP staff and volunteers who have collected and facilitated the collection of data, all the landowners on Orkney who have generously given access to their land, the ONWP steering group members (Graham Neville and Daniel Brazier, NatureScot; Susan Shearer and Stuart West, Orkney Islands Council and Kirsty Nutt and Leigh Lock, RSPB) and the Technical Advisory Group (Peter Robertson, Newcastle University; Robbie Macdonald, University of Exeter; Des Thompson, NatureScot; Tony Martin, University of Dundee; Lindsay Waddell, National Gamekeepers' Organisation; Karen Varnham, RSPB; Grant Harper, Biodiversity Restoration; Angela Newport, Conservation Dog specialist).Peer reviewedPublisher PD

Housing prices and credit constraints in competitive search

We embed a competitive search model of the real estate market into a heterogeneous agentsetting where hoeholds face credit constraints and idiosyncratic turnover shocks. Householdscan accumulate a risk-free asset to build a down payment and to smooth non-housing consumption.There is an inelastic supply of identical homes. The model is "block recursive". Inequilibrium wealthier home buyers sort into submarkets with higher prices and shorter buyingtimes. We identify a novel amplification mechanism, arising from sorting, by which demandshocks can substantially affect housing prices. In particular, lowering down payment requirementsinduces entry of new buyers in the market and higher asset accumulation by currentsearchers, as these agents target more expensive (less congested) submarkets. This affects thedistribution of prices and trading probabilities, and thereby the wealth distribution. Our quantitativeresults suggest that the effects on the long-run level and dispersion of housing pricescan be significant.Support from the Spanish Ministerio Economía y Competitividad, grants ECO2016-76818-C3-1-P and ECO2017-86261-P, MDM 2014-0431, and Comunidad de Madrid, MadEco-CM (S2015/HUM-3444), is gratefully acknowledged

Live reptile smuggling is predicted by trends in the legal exotic pet trade

ACKNOWLEDGMENTS This research was funded by the Centre for Invasive Species Solutions (Project PO1-I-002). PG-D was partially supported by NERC grant NE/S011641/1 under the Newton Latam program. The authors acknowledge the Indigenous Traditional Owners of the land on which the University of Adelaide is built—the Kaurna people of the Adelaide Plains. We thank Jacob Maher and Talia Wittmann for sharing Australian zoo keeping data.Peer reviewedPublisher PD

Bearing all down under : The role of Australasian countries in the illegal bear trade

Declaration of Funding CRS and LG are grateful to the Environmental Investigation Agency (EIA) for generously supporting Monitor Conservation Research Society’s work on this project. PG-D was partially supported by NERC grant NE/S011641/1 under the Newton LATAM funding programme. Acknowledgements The authors acknowledge the CITES Management and Enforcement Authorities in Australia and New Zealand for assisting in the collection and curation of seizure and enforcement data. The authors acknowledge the Indigenous Traditional Owners of the land on which the University of Adelaide is built -the Kaurna people of the Adelaide Plains. Particular thanks to Jo Beath (Department of Agriculture, Water & Environment, Australia) and Dylan Swain (Department of Conservation, New Zealand) for facilitating provision of CITES seizure datasets. PC thanks Eric Cassey for checking the calculation of data summaries. PG-D thanks C. Jones and B. Warburton (MWLR New Zealand) for their support and help.Peer reviewedPostprin

Drivers of the Australian native pet trade : the role of species traits, socioeconomic attributes and regulatory systems

Acknowledgements We acknowledge that the land on which we conducted our research is the traditional land of the Kaurna people of the Adelaide Plains. We pay our respects to Kaurna elders past, present and emerging. We thank the South Australian Department for the Environment and Water for recording and facilitating access to all permit data used in our analysis. This research was funded by the Centre for Invasive Species Solutions (Project P01-I-002). PC was supported by an Australian Research Council Discovery grant (DP210103050). PG-D was supported by the NERC grant NE/S011641/1 under the Newton LATAM funding programme.Peer reviewedPublisher PD

Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework

Funding: This study was supported by funding from New Zealand’s Predator Free 2050 program under Predator Free 2050 Ltd. award SS/05/01 to PWM, and from National Institutes of Health award R01GM127418 to PWM. PG-D received funding from the New Zealand BioHeritage National Science Challenge (contract 1617-28-033 A to Manaaki Whenua – Landcare Research) and from Natural Environment Research Council grant NE/S011641/1 under the Newton Latam programme. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

On Chern-Simons Quivers and Toric Geometry

We discuss a class of 3-dimensional N=4 Chern-Simons (CS) quiver gauge models obtained from M-theory compactifications on singular complex 4-dimensional hyper-Kahler (HK) manifolds, which are realized explicitly as a cotangent bundle over two-Fano toric varieties V^2. The corresponding CS gauge models are encoded in quivers similar to toric diagrams of V^2. Using toric geometry, it is shown that the constraints on CS levels can be related to toric equations determining V^2.Comment: 14pg, 1 Figure, late