Exploring 4D Quantum Hall Physics with a 2D Topological Charge Pump

The discovery of topological states of matter has profoundly augmented our understanding of phase transitions in physical systems. Instead of local order parameters, topological phases are described by global topological invariants and are therefore robust against perturbations. A prominent example thereof is the two-dimensional integer quantum Hall effect. It is characterized by the first Chern number which manifests in the quantized Hall response induced by an external electric field. Generalizing the quantum Hall effect to four-dimensional systems leads to the appearance of a novel non-linear Hall response that is quantized as well, but described by a 4D topological invariant - the second Chern number. Here, we report on the first observation of a bulk response with intrinsic 4D topology and the measurement of the associated second Chern number. By implementing a 2D topological charge pump with ultracold bosonic atoms in an angled optical superlattice, we realize a dynamical version of the 4D integer quantum Hall effect. Using a small atom cloud as a local probe, we fully characterize the non-linear response of the system by in-situ imaging and site-resolved band mapping. Our findings pave the way to experimentally probe higher-dimensional quantum Hall systems, where new topological phases with exotic excitations are predicted

Accurate Liability Estimation Improves Power in Ascertained Case Control Studies

Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in non-randomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (Liability Estimator As a Phenotype, https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and demonstrate that this can lead to a substantial power increase

Experimental Measurement of the Berry Curvature from Anomalous Transport

Geometrical properties of energy bands underlie fascinating phenomena in a wide-range of systems, including solid-state materials, ultracold gases and photonics. Most famously, local geometrical characteristics like the Berry curvature can be related to global topological invariants such as those classifying quantum Hall states or topological insulators. Regardless of the band topology, however, any non-zero Berry curvature can have important consequences, such as in the semi-classical evolution of a wave packet. Here, we experimentally demonstrate for the first time that wave packet dynamics can be used to directly map out the Berry curvature. To this end, we use optical pulses in two coupled fibre loops to study the discrete time-evolution of a wave packet in a 1D geometrical "charge" pump, where the Berry curvature leads to an anomalous displacement of the wave packet under pumping. This is both the first direct observation of Berry curvature effects in an optical system, and, more generally, the proof-of-principle demonstration that semi-classical dynamics can serve as a high-resolution tool for mapping out geometrical properties

Seeds Buffering for Information Spreading Processes

Seeding strategies for influence maximization in social networks have been studied for more than a decade. They have mainly relied on the activation of all resources (seeds) simultaneously in the beginning; yet, it has been shown that sequential seeding strategies are commonly better. This research focuses on studying sequential seeding with buffering, which is an extension to basic sequential seeding concept. The proposed method avoids choosing nodes that will be activated through the natural diffusion process, which is leading to better use of the budget for activating seed nodes in the social influence process. This approach was compared with sequential seeding without buffering and single stage seeding. The results on both real and artificial social networks confirm that the buffer-based consecutive seeding is a good trade-off between the final coverage and the time to reach it. It performs significantly better than its rivals for a fixed budget. The gain is obtained by dynamic rankings and the ability to detect network areas with nodes that are not yet activated and have high potential of activating their neighbours.Comment: Jankowski, J., Br\'odka, P., Michalski, R., & Kazienko, P. (2017, September). Seeds Buffering for Information Spreading Processes. In International Conference on Social Informatics (pp. 628-641). Springe

Geospatial information infrastructures

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreflectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeflexibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the field and a solid basis for reflections about future developments

Negative phenotypic and genetic associations between copulation duration and longevity in male seed beetles

Reproduction can be costly and is predicted to trade-off against other characters. However, while these trade-offs are well documented for females, there has been less focus on aspects of male reproduction. Furthermore, those studies that have looked at males typically only investigate phenotypic associations, with the underlying genetics often ignored. Here, we report on phenotypic and genetic trade-offs in male reproductive effort in the seed beetle, Callosobruchus maculatus. We find that the duration of a male's first copulation is negatively associated with subsequent male survival, phenotypically and genetically. Our results are consistent with life-history theory and suggest that like females, males trade-off reproductive effort against longevity

Patient enablement requires physician empathy: a cross-sectional study of general practice consultations in areas of high and low socioeconomic deprivation in Scotland

<b>Background</b> Patient 'enablement' is a term closely aligned with 'empowerment' and its measurement in a general practice consultation has been operationalised in the widely used patient enablement instrument (PEI), a patient-rated measure of consultation outcome. However, there is limited knowledge regarding the factors that influence enablement, particularly the effect of socio-economic deprivation. The aim of the study is to assess the factors influencing patient enablement in GP consultations in areas of high and low deprivation.<p></p> <b>Methods</b> A questionnaire study was carried out on 3,044 patients attending 26 GPs (16 in areas of high socio-economic deprivation and 10 in low deprivation areas, in the west of Scotland). Patient expectation (confidence that the doctor would be able to help) was recorded prior to the consultation. PEI, GP empathy (measured by the CARE Measure), and a range of other measures and variables were recorded after the consultation. Data analysis employed multi-level modelling and multivariate analyses with the PEI as the dependant variable.<p></p> <b>Results</b> Although numerous variables showed a univariate association with patient enablement, only four factors were independently predictive after multilevel multivariate analysis; patients with multimorbidity of 3 or more long-term conditions (reflecting poor chronic general health), and those consulting about a long-standing problem had reduced enablement scores in both affluent and deprived areas. In deprived areas, emotional distress (GHQ-caseness) had an additional negative effect on enablement. Perceived GP empathy had a positive effect on enablement in both affluent and deprived areas. Maximal patient enablement was never found with low empathy.<p></p> <b>Conclusions</b> Although other factors influence patient enablement, the patients' perceptions of the doctors' empathy is of key importance in patient enablement in general practice consultations in both high and low deprivation settings

Total versus partial knee replacement in patients with medial compartment knee osteoarthritis : the TOPKAT RCT

Article history The research reported in this issue of the journal was funded by the HTA programme as project number 08/14/08. The contractual start date was in January 2010. The draft report began editorial review in February 2019 and was accepted for publication in October 2019. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HTA editors and publisher have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this report. Acknowledgements TOPKAT study group Chief investigator David Beard. Trial co-investigators Nigel Arden (Oxford), Helen Campbell (Oxford), Marion Campbell (Aberdeen), Andrew Carr (Oxford), Jonathan Cook (Aberdeen then Oxford), Helen Doll (Oxford), Ray Fitzpatrick (Oxford), David Murray (Oxford) and Andrew Price (Oxford). Trial management Mayret Castillo (until 2011), Cushla Cooper, Loretta Davies, Anne Duncan (until 2017), Gordon Fernie, Sophie Halpin (until 2015) and Alison McDonald. Trial administration Katie Chegwin, Jiyang Li (until 2018), Elena Rabaiotti (until 2013), Sandra Regan (until 2012) and Victoria Stalker (until 2014). Data management Diana Collins (until 2013), Janice Cruden, Akiko Greshon, Kay Holland and Beverley Smith (until 2017). Database/programming management Gladys McPherson. Trial statisticians Charles Boachie (until 2013), Jemma Hudson and Graeme MacLennan. Health economists Helen Campbell (until 2015), Francesco Fusco (until 2018), Seamus Kent and Jose Leal. We would also like to thank Hannah Wilson (DPhil student, University of Oxford) for her help with the update to the literature search. Research teams We are grateful to the participants and research teams at collaborating hospital sites: Aneurin Bevan University Health Board, Royal Gwent Hospital Ruth Jenkins, Mark Lewis [principal investigator (PI)] and Witek Mintowt-Czyz. Belfast Health and Social Care Trust, Musgrove Park Hospital, Belfast David Beverland (PI), Leeann Bryce, Julie Catney, Ian Dobie, Emer Doran and Seamus O’Brien. Chesterfield Royal Hospital NHS Foundation Trust Fazal Ali, Heather Cripps, Amanda Whileman, Phil Williams (PI) and Julie Toms. County Durham and Darlington NHS Foundation Trust Ellen Brown, Gillian Horner, Andrew Jennings (PI) and Glynis Rose. East Lancashire Hospitals NHS Trust, Royal Blackburn Hospital Frances Bamford, Wendy Goddard, Hans Marynissen (PI), Haleh Peel and Lyndsey Richards. Great Western Hospitals NHS Foundation Trust, Swindon Amanda Bell, Sunny Deo, Sarah Grayland, David Hollinghurst, Suzannah Pegler, Venkat Satish (PI) and Claire Woodruffe. Harrogate and District NHS Foundation Trust, Harrogate Nick London (PI), David Duffy, Caroline Bennett and James Featherstone. Hull and East Yorkshire Hospitals NHS Trust Joss Cook, Kim Dearnley, Nagarajan Muthukumar (PI), Laura Onuoha and Sarah Wilson. Maidstone and Tunbridge Wells NHS Trust, Medway Sandhu Banher, Eunice Emeakaroha, Jamie Horohan, Sunil Jain (PI) and Susan Thompson. Mid Yorkshire Hospitals NHS Trust Sarah Buckley, Aaron Ng (PI), Ajit Shetty and Karen Simeson. Milton Keynes University Hospital NHS Foundation Trust Julian Flynn, Meryl Newsom, Cheryl Padilla-Harris and Oliver Pearce (PI). NHS Grampian, Woodend Hospital, Aberdeen James Bidwell (PI), Alison Innes, Winifred Culley and Bill Ledingham and Janis Stephen. North Bristol NHS Trust Rachel Bray, Hywel Davies, Debbie Delgado, Jonathan Eldridge, Leigh Morrison, James Murray (PI), Andrew Porteous and James Robinson. North Cumbria University Hospitals NHS Trust, Carlisle Matt Dawson (PI), Raj Dharmarajan, David Elson, Will Hage, Nicci Kelsall and Mike Orr. North Tees and Hartlepool NHS Foundation Trust, Stockton-On-Tees Jackie Grosvenor, SS Maheswaran (PI), Claire McCue, Hemanth Venkatesh, Michelle Wild and Deborah Wilson. Oxford University Hospitals NHS Trust, Nuffield Orthopaedic Centre Chris Dodd, William Jackson (PI), Pam Lovegrove, David Murray, Jennifer Piper and Andrew Price. Royal United Hospitals Bath NHS Foundation Trust, Bath Neil Bradbury, Lucy Clark, Stefanie Duncan, Genevieve Simpson and Allister Trezies (PI). Sherwood Forest Hospitals NHS Foundation Trust, Kings Mill Hospital, Sutton in Ashfield Vikram Desai (PI), Cheryl Heeley, Kramer Guy and Rosalyn Jackson. South Devon Healthcare NHS Foundation Trust, Torbay Alan Hall, Gordon Higgins (PI), Michael Hockings, David Isaac and Pauline Mercer. Stockport NHS Foundation Trust, Stockport Lindsey Barber, Helen Cochrane, Janette Curtis, Julie Grindey, David Johnson (PI), and Phil Turner. The Hillingdon Hospitals NHS Trust David Houlihan-Burne (PI), Briony Hill, Ron Langstaff and Mariam Nasseri. The Ipswich Hospital NHS Trust, Ipswich Mark Bowditch, Chris Martin, Steven Pryke, Bally Purewal, Chris Servant (PI), Sheeba Suresh and Claire Tricker. University Hospitals of Leicester NHS Trust, Leicester Robert Ashford, Manjit Attwal, Jeanette Bunga, Urjit Chatterji, Susan Cockburn, Colin Esler (PI), Steven Godsiff, Tim Green, Christina Haines and Subash Tandon. University Hospitals of North Midlands NHS Trust, Stoke on Trent Racquel Carpio, Sarah Griffiths, Natalie Grocott and Ian dos Remedios (PI). University Hospital Southampton NHS Foundation Trust David Barrett, Phil Chapman-Sheath, Caroline Grabau, Jane Moghul, William Tice (PI) and Catherine Trevithick. United Lincolnshire Hospitals NHS Trust, Boston Rajiv Deshmukh, Mandy Howes, Kimberley Netherton, Dipak Raj (PI) and Nikki Travis. United Lincolnshire Hospitals NHS Trust, Lincoln Mohammad Maqsood, Rebecca Norton, Farzana Rashid, Alison Raynor, Mark Rowsell and Karen Warner. We would like to thank the external members of the TSC and DMC for their advice and support for the project. Trial Steering Committee Donna Dodwell as our patient representative, Simon Donell (chairperson) (University of East Anglia), Shawn Tavares (Royal Berkshire Hospital) and Jonathan Waite (South Warwickshire NHS Foundation Trust). Data Monitoring Committee Karen Barker (Oxford University Hospitals NHS Foundation Trust), Gordon Murray (chairperson) (University of Edinburgh) and Hamish Simpson (University of Edinburgh). Independent review and interpretation of results Professor David Torgerson (University of York). Professor Chris Maher (University of Sydney). Mr Peter Brownson (The Royal Liverpool and Broadgreen University Hospitals NHS Trust). Professor Simon Donell (University of East Anglia, Norwich). Mr Mark Mullins (Abertawe Bro Morgannwg University Health Board). Professor Jane Blazeby (Bristol University).Peer reviewedPublisher PD

Use of principal components to aggregate rare variants in case-control and family-based association studies in the presence of multiple covariates

Rare variants may help to explain some of the missing heritability of complex diseases. Technological advances in next-generation sequencing give us the opportunity to test this hypothesis. We propose two new methods (one for case-control studies and one for family-based studies) that combine aggregated rare variants and common variants located within a region through principal components analysis and allow for covariate adjustment. We analyzed 200 replicates consisting of 209 case subjects and 488 control subjects and compared the results to weight-based and step-up aggregation methods. The principal components and collapsing method showed an association between the gene FLT1 and the quantitative trait Q1 (P<10−30) in a fraction of the computation time of the other methods. The proposed family-based test has inconclusive results. The two methods provide a fast way to analyze simultaneously rare and common variants at the gene level while adjusting for covariates. However, further evaluation of the statistical efficiency of this approach is warranted