Integration in energy and transport amongst Azerbaijan, Georgia and Turkey

A limited process of integration has been occurring amongst the countries of Georgia, Azerbaijan, and Turkey. From the mid-1990s to 2008, integration amongst the three countries has occurred in the energy and transport sectors, but not in other sectors, such as security, politics or trade beyond energy and transport. In the energy sector, this integration can be explained through neo-liberal institutionalist theory. Integration in the transport sector occurs due to a mixture of elements from the neo-liberal institutionalist, security communities and neo-functionalist theories of integration. In both sectors, transnational extra-regional actors (TERAs) are the explanatory variable in the integration

Assessing the impact of selective licencing schemes for private rental housing on mental health and well-being: protocol for a mixed-method natural experiment study in Greater London, UK.

INTRODUCTION: The UK private rental housing market has poorer quality housing compared with other sectors and is subjected to calls for better regulation. Poor quality housing poses risks to mental and physical health, and housing improvement can potentially benefit health and well-being. Local authorities have powers to implement selective licencing (SL) schemes in specific localities. Such schemes involve landlord registration, payment of licence fees, local authority inspection and requirements that landlords conduct any necessary renovation works to ensure housing standards are met. We aim to evaluate SL in Greater London and to test the feasibility of a national evaluation. METHODS AND ANALYSIS: We will measure individual-level and area-level impacts of SL in Greater London between 2011 and 2019. A difference-in-differences approach with propensity score-matched controls will be used. We propose to exploit data from the Annual Population Survey (APS) and health and social benefit registers to measure mental health and well-being at individual (self-reported anxiety) and area (Small Area Mental Health Index) level. We estimate 633 APS participants in our intervention groups compared with 1899 participants in control areas (1:3 ratio of intervention to control). Secondary outcomes will be self-reported well-being and residential stability at the individual level and incidence of police-recorded antisocial behaviour calls and population turnover at the area level. The study size of the area-level analyses will be 3684 lower layer super output areas (including controls). Qualitative semistructured interviews with lead implementers in several London boroughs will produce insights into variations and commonalities between schemes. ETHICS AND DISSEMINATION: Ethical approval was obtained from London School of Hygiene and Tropical Medicine's Ethics Committee (reference number 26481) and London Borough of Hackney. All interviewees will be asked for informed written consent. Study findings will be published in a peer-reviewed journal

Impact of selective licensing schemes for private rental housing on mental health and social outcomes in Greater London, England: a natural experiment study.

ObjectivesTo assess primary impact of selective Licensing (SL), an area-based intervention in the private rented housing market, on individual self-reported anxiety and neighbourhood mental health (MHI-Mental Healthcare Index) and secondary impacts on antisocial behaviour (ASB), population turnover and self-reported well-being.DesignDifference-in-difference (DiD) was used to evaluate effects of SL schemes initiated 2012-2018. 921 intervention areas (lower super output areas) were matched 3:1 using propensity scores derived from sociodemographic and housing variables (N=3.684 including controls). Average treatment effect on treated (ATT) was calculated for multiple time period DiD in area-level analyses. Canonical DiD was used for individual-level analysis by year of treatment initiation while adjusting for age, sex, native birth and occupational class.SettingIntervention neighbourhoods and control areas in Greater London, UK, 2011-2019.ParticipantsWe sampled 4474 respondents renting privately in intervention areas (N=17 347 including controls) in Annual Population Survey and obtained area-level MHI population data.InterventionsPrivate landlords in SL areas must obtain a licence from the local authority, allow inspection and maintain minimum housing standards.ResultsATT after 5 years was significantly lower for MHI (-7.5%, 95% CI -5.6% to -8.8%) than controls. Antidepressant treatment days per population reduced by -5.4% (95% CI -3.7% to -7.3), mental health benefit receipt by -9.6% (95% CI -14% to -5.5%) and proportion with depression by -12% (95% CI -7.7% to -16.3%). ASB reduced by -15% (95% CI -21% to -8.2%). Population turnover increased by 26.5% (95% CI 22.1% to 30.8%). Sensitivity analysis suggests overlap with effects of London 2012 Olympic regeneration. No clear patterns were observed for self-reported anxiety.ConclusionsWe found associations between SL and reductions in area-based mental healthcare outcomes and ASB, while population turnover increased. A national evaluation of SL is feasible and necessary

Common Limitations of Image Processing Metrics:A Picture Story

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide.Comment: This is a dynamic paper on limitations of commonly used metrics. The current version discusses metrics for image-level classification, semantic segmentation, object detection and instance segmentation. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorshi

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior authors: Paul F. J\"ager, Lena Maier-Hei

Phylogenomics and the evolution of hemipteroid insects.

Hemipteroid insects (Paraneoptera), with over 10% of all known insect diversity, are a major component of terrestrial and aquatic ecosystems. Previous phylogenetic analyses have not consistently resolved the relationships among major hemipteroid lineages. We provide maximum likelihood-based phylogenomic analyses of a taxonomically comprehensive dataset comprising sequences of 2,395 single-copy, protein-coding genes for 193 samples of hemipteroid insects and outgroups. These analyses yield a well-supported phylogeny for hemipteroid insects. Monophyly of each of the three hemipteroid orders (Psocodea, Thysanoptera, and Hemiptera) is strongly supported, as are most relationships among suborders and families. Thysanoptera (thrips) is strongly supported as sister to Hemiptera. However, as in a recent large-scale analysis sampling all insect orders, trees from our data matrices support Psocodea (bark lice and parasitic lice) as the sister group to the holometabolous insects (those with complete metamorphosis). In contrast, four-cluster likelihood mapping of these data does not support this result. A molecular dating analysis using 23 fossil calibration points suggests hemipteroid insects began diversifying before the Carboniferous, over 365 million years ago. We also explore implications for understanding the timing of diversification, the evolution of morphological traits, and the evolution of mitochondrial genome organization. These results provide a phylogenetic framework for future studies of the group

Diversity of Staphylococcus aureus Isolates in European Wildlife

Staphylococcus aureus is a well-known colonizer and cause of infection among animals and it has been described from numerous domestic and wild animal species. The aim of the present study was to investigate the molecular epidemiology of S. aureus in a convenience sample of European wildlife and to review what previously has been observed in the subject field. 124 S. aureus isolates were collected from wildlife in Germany, Austria and Sweden; they were characterized by DNA microarray hybridization and, for isolates with novel hybridization patterns, by multilocus sequence typing (MLST). The isolates were assigned to 29 clonal complexes and singleton sequence types (CC1, CC5, CC6, CC7, CC8, CC9, CC12, CC15, CC22, CC25, CC30, CC49, CC59, CC88, CC97, CC130, CC133, CC398, ST425, CC599, CC692, CC707, ST890, CC1956, ST2425, CC2671, ST2691, CC2767 and ST2963), some of which (ST2425, ST2691, ST2963) were not described previously. Resistance rates in wildlife strains were rather low and mecA-MRSA isolates were rare (n = 6). mecC-MRSA (n = 8) were identified from a fox, a fallow deer, hares and hedgehogs. The common cattle- associated lineages CC479 and CC705 were not detected in wildlife in the present study while, in contrast, a third common cattle lineage, CC97, was found to be common among cervids. No Staphylococcus argenteus or Staphylococcus schweitzeri-like isolates were found. Systematic studies are required to monitor the possible transmission of human- and livestock- associated S. aureus/MRSA to wildlife and vice versa as well as the possible transmission, by unprotected contact to animals. The prevalence of S. aureus/MRSA in wildlife as well as its population structures in different wildlife host species warrants further investigation

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe