Distinguishing Lead and Molecule States in Graphene-Based Single-Electron Transistors

Graphene provides a two-dimensional platform for contacting individual molecules, which enables transport spectroscopy of molecular orbital, spin and vibrational states. Here we report single-electron tunneling through a molecule that has been anchored to two graphene leads. Quantum interference within the graphene leads gives rise to an energy-dependent transmission and fluctuations in the sequential tunnel-rates. The lead states are electrostatically tuned by a global back-gate, resulting in a distinct pattern of varying intensity in the measured conductance maps. This pattern could potentially obscure transport features that are intrinsic to the molecule under investigation. Using ensemble averaged magneto-conductance measurements, lead and molecule states are disentangled, enabling spectroscopic investigation of the single molecule

Quantum Interference in Graphene Nanoconstrictions

We report quantum interference effects in the electrical conductance of chemical vapour deposited graphene nanoconstrictions fabricated using feedback controlled electroburning. The observed multi-mode Fabry-Pérot interferences can be attributed to reflections on potential steps inside the channel. Sharp anti-resonance features with a Fano line shape are observed. Theoretical modelling reveals that these Fano resonances are due to localised states inside the constriction, which couple to the delocalised states that also give rise to the Fabry-Pérot interference patterns. This study provides new insight into the interplay between two fundamental forms of quantum interference in graphene nanoconstrictions

Bullet impacts and built heritage damage 1640–1939

© 2018, The Author(s). Conflict damage to heritage has been thrust into the global spotlight during recent conflict in the Middle East. While the use of social media has heightened and enhanced public awareness of this ‘cultural terrorism’, the occurrence of this type of vandalism is not new. In fact, as this study demonstrates, evidence of the active targeting of sites, as well as collateral damage when heritage is caught in crossfire, is widely visible around Europe and further afield. Using a variety of case studies ranging from the 1640s to the 1930s, we illustrate and quantify the changing impact of ballistics on heritage buildings as weaponry and ammunition have increased in both energy and energy density potential. In the first instance, this study highlights the increasing threats to heritage in conflict areas. Second, it argues for the pressing need to quantify and map damage to the stonework in order to respond to these challenges

Antiepileptic drugs’ tolerability and safety – a systematic review and meta-analysis of adverse effects in dogs

<p>Various anti-epileptic drugs (AEDs) are used for the management of idiopathic epilepsy (IE) in dogs. Their safety profile is an important consideration for regulatory bodies, owners and prescribing clinicians. However, information on their adverse effects still remains limited with most of it derived from non-blinded non-randomized uncontrolled trials and case reports.</p><p><span>This poster won third place, which was presented at the Veterinary Evidence Today conference, Edinburgh November 1-3, 2016. </span></p><br /> <img src="https://www.veterinaryevidence.org/rcvskmod/icons/oa-icon.jpg" alt="Open Access" /

The Rewiring of Ubiquitination Targets in a Pathogenic Yeast Promotes Metabolic Flexibility, Host Colonization and Virulence

Funding: This work was funded by the European Research Council [http://erc.europa.eu/], AJPB (STRIFE Advanced Grant; C-2009-AdG-249793). The work was also supported by: the Wellcome Trust [www.wellcome.ac.uk], AJPB (080088, 097377); the UK Biotechnology and Biological Research Council [www.bbsrc.ac.uk], AJPB (BB/F00513X/1, BB/K017365/1); the CNPq-Brazil [http://cnpq.br], GMA (Science without Borders fellowship 202976/2014-9); and the National Centre for the Replacement, Refinement and Reduction of Animals in Research [www.nc3rs.org.uk], DMM (NC/K000306/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We thank Dr. Elizabeth Johnson (Mycology Reference Laboratory, Bristol) for providing strains, and the Aberdeen Proteomics facility for the biotyping of S. cerevisiae clinical isolates, and to Euroscarf for providing S. cerevisiae strains and plasmids. We are grateful to our Microscopy Facility in the Institute of Medical Sciences for their expert help with the electron microscopy, and to our friends in the Aberdeen Fungal Group for insightful discussions.Peer reviewedPublisher PD

Long-term health-related and economic consequences of short-term outcomes in evaluation of perinatal interventions

<p>Abstract</p> <p>Background</p> <p>Many perinatal interventions are performed to improve long-term neonatal outcome. To evaluate the long-term effect of a perinatal intervention follow-up of the child after discharge from the hospital is necessary because serious sequelae from perinatal complications frequently manifest themselves only after several years. However, long-term follow-up is time-consuming, is not in the awareness of obstetricians, is expensive and falls outside the funding-period of most obstetric studies. Consequently, short-term outcomes are often reported instead of the primary long-term end-point. With this project, we will assess the current state of affairs concerning follow-up after obstetric RCTs and we will develop multivariable prediction models for different long-term health outcomes. Furthermore, we would like to encourage other researchers participating in follow-up studies after large obstetric trials (> 350 women) to inform us about their studies so that we can include their follow-up study in our systematic review. We would invite these researchers also to join our effort and to collaborate with us on the external validation of our prediction models.</p> <p>Methods/Design</p> <p>A systematic review of neonatal follow-up after obstetric studies will be performed. All reviews of the Cochrane Pregnancy and Childbirth group will be assessed for reviews on interventions that aimed to improve neonatal outcome. Reviews on interventions primary looking at other aspects than neonatal outcome such as labour progress will also be included when these interventions can change the outcome of the neonate on the short or long-term. Our review will be limited to RCTs with more than 350 women. Information that will be extracted from these RCTs will address whether, how and for how long follow-up has been performed. However, in many cases long-term follow-up of the infants will not be feasible. An alternative solution to limited follow-up could be to develop prediction models to estimate long-term health outcomes of the newborn based on specific perinatal outcomes and other covariates. For the development of multivariable prediction models for several health outcomes, we will use data available from a Dutch cohort study of preterm (< 32 weeks) and/or small for gestational age infants (< 1500 g). These infants were born in The Netherlands in 1983 and followed until they reached the age of 19.</p> <p>Discussion</p> <p>The systematic review will provide insight in the extent and methods used for follow-up assessments after obstetric RCTs in the past. The prediction models can be used by future studies to extrapolate short-term outcomes to a long-term horizon or to indicate for which neonates long-term follow-up is required, as their outcomes (either absence or presence of sequelae) cannot be adequately predicted from short-term outcomes and clinical background characteristics.</p

Forecasting with Big Data: A Review

Big Data is a revolutionary phenomenon which is one of the most frequently discussed topics in the modern age, and is expected to remain so in the foreseeable future. In this paper we present a comprehensive review on the use of Big Data for forecasting by identifying and reviewing the problems, potential, challenges and most importantly the related applications. Skills, hardware and software, algorithm architecture, statistical significance, the signal to noise ratio and the nature of Big Data itself are identified as the major challenges which are hindering the process of obtaining meaningful forecasts from Big Data. The review finds that at present, the fields of Economics, Energy and Population Dynamics have been the major exploiters of Big Data forecasting whilst Factor models, Bayesian models and Neural Networks are the most common tools adopted for forecasting with Big Data