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In 2018, the position paper 'Imaging the adult with congenital heart disease: a multimodality imaging approach' was published. The paper highlights, in the first part, the different imaging modalities applied in adult congenital heart disease patients. In the second part, these modalities are discussed more detailed for moderate to complex anatomical defects. Because of the length of the paper, simple lesions were not touched on. However, imaging modalities to use for simple shunt lesions are still poorly known. One is looking for structured recommendations on which they can rely when dealing with an (undiscovered) shunt lesion. This information is lacking for the initial diagnostic process, during repair and at follow-up. Therefore, this paper will focus on atrial septal defect, ventricular septal defect, and persistent arterial duct. Pre-, intra-, and post-procedural imaging techniques will be systematically discussed. This position paper will offer algorithms that might help at a glance. The document is prepared for general cardiologists, trainees, medical students, imagers/technicians to select the most appropriate imaging modality and to detect the requested information for each specific lesion. It might serve as reference to which researchers could refer when setting up a (imaging) study. [ABSTRACT FROM AUTHOR]

The article focuses on a study which seeks to validate aerosol optical thickness (AOT) and Ångström exponent acquired with the Satellite Aerosol Retrieval (SAER) algorithm for Moderate resolution Imaging Spectroradiometer (MODIS) Aqua and Terra data over land surfaces in Europe. It performs an inter-comparison of the diverse algorithm. It explores the impact of aerosols on climate AOT.

This paper examines the ethical and legal challenges encountered during the GATEKEEPER Project and how these challenges informed the development of a comprehensive framework for future Large-Scale Pilot (LSP) projects. GATEKEEPER is a LSP Project with 48 partners conducting 30 implementation studies across Europe with 50,000 target participants grouped into 9 Reference Use Cases. The project underscored the complexity of obtaining ethical approval across various jurisdictions with divergent regulations and procedures. Through a detailed analysis of the issues faced and the strategies employed to navigate these challenges, this study proposes an ethical and legal framework. This framework, derived from a comparative analysis of ethical application forms and regulations, aims to streamline the ethical approval process for future LSP research projects. By addressing the hurdles encountered in GATEKEEPER, the proposed framework offers a roadmap for more efficient and effective project management, ensuring smoother implementation of similar projects in the future. [ABSTRACT FROM AUTHOR]

New propulsion systems in aircrafts must meet strict regulations and emission limitations. The Flightpath 2050 goals set by the Advisory Council for Aviation Research and Innovation in Europe (ACARE) include reductions of 75%, 90%, and 65% in CO2, NOx, and noise, respectively. These goals are not fully satisfied by marginal improvements in gas turbine technology or aircraft design. A novel control design procedure for the next generation of turbofan engines is proposed in this paper to improve Full Authority Digital Engine Control (FADEC) systems and reduce the emission levels to meet the Flightpath 2050 regulations. Hence, an Adaptive Network–based Fuzzy Inference System (ANFIS), nonlinear autoregressive network with exogenous inputs (NARX) techniques, and the block-structure Hammerstein–Wiener approach are used to develop a model for a turbofan engine. The Min–Max control structure is chosen as the most widely used practical control algorithm for gas turbine aero engines. The objective function is considered to minimize the emission level for the engine in a pre-defined maneuver while keeping the engine performance in different aspects. The Genetic Algorithm (GA) is applied to find the optimized control structure. The results confirm the effectiveness of the proposed approach in emission reduction for the next generation of turbofan engines. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the retrieval and validation of the aerosol optical thickness (AOT) land product at the infrared channel of Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor aboard EUMETSAT's Meteosat Second Generation (MSG) meteorological satellite. It analyzes the validity of the algorithm using ground-based measurements (AERONET) for stations in Europe. It further explores the capability of the SEVIRI product to follow the aerosol diurnal cycle.

Determining contingency aware dispatch decisions by solving a security-constrained optimal power flow (SCOPF) is challenging for real-world power systems, as the high problem dimensionality often leads to impractical computational requirements. This problem becomes more severe when the SCOPF has to be solved not only for a single instance, but for multiple periods, e.g. in the context of electricity market analyses. This paper proposes an algorithm that identifies the minimal set of constraints that exactly define the space of feasible nodal injections for a given network and contingency scenarios. By internalizing the technical limits of the nodal injections and enforcing a minimal worst-case impact of contingencies to line flows, computational effort can be further improved. The case study applies and analyzes the methods on the IEEE 118 and A&M 2000 bus systems, as well as the German and European transmission systems. In all tested cases the proposed algorithm identifies at least 95% of the network and security constraints as redundant, leading to significant SCOPF solve time reductions. Scalability and practical implementation are explicitly discussed. The code and input data of the case study is published supplementary to the paper under an open-source license. [ABSTRACT FROM AUTHOR]

Individual tree detection algorithms (ITD) are used to obtain accurate information about trees. Following the process of individual tree detection, it is possible to use additional processing tools to determine tree parameters such as tree height, crown base height, crown volume, or stem volume. However, many of the methods developed so far have focused on parameterising the algorithms based on the study area, height structure or tree species analysed. Applying the parameters of the method can be challenging in areas with dense and heterogeneous forests with a diverse stand structure. Therefore, this work aimed to develop a method to correct the results of ITD algorithms to identify individual trees more reliably, taking into account different ITD methods based on the Canopy Height Model. In the present study, we proposed a three-step approach to correct segmentation errors. In the first step, erroneous (under- and over-segmentation errors) and correct segments were classified. After classification, the second step was to refine the under-segmentation errors. The final step was to merge segments from the over-segmentation class with correct segments based on the specified conditions. The study was conducted in one of the most complex and diverse forest communities in Europe, making tree identification a major challenge. The accuracy of the segmentation improvements varied depending on the method applied and tree species group examined. Thus, based on the results, the paper advocates for the correction method due to its efficiency in mixed forest stands. Therefore, the present study offers a possible solution to reduce segmentation errors by considering different forest types and different CHM-based ITD methods for identifying individual trees. [ABSTRACT FROM AUTHOR]

In more or less noticeable ways, algorithms are pervading every sector of life. As algorithm-related activities multiply around us, it is reasonable to predict that so will accidents and, consequently, compensation claims framed as torts. Against this background, the paper investigates from a comparative perspective how legal systems in three regions of the world--the U.S., (continental) Europe, and China--could approach the rise of algorithmic torts. First, the paper sketches out the main features that might be associated with algorithm-related torts and the specific challenges that they might bring to current legal frameworks. It then presents the state-of-the-art of the legal debate about algorithmic liability in U.S., Europe, and China. Finally, the paper delves into the ways in which tort laws in these three regions might address injuries associated with algorithmic activities, reviewing in particular the criteria for grounding jurisdiction, the procedural devices applying to tort law claims, the liability regimes under which claims could be framed, the mechanisms for damage attribution and apportionment, and the type and amount of potential recoverable losses. [ABSTRACT FROM AUTHOR]

Background in 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) published a sarcopenia definition that aimed to foster advances in identifying and caring for people with sarcopenia. In early 2018, the Working Group met again (EWGSOP2) to update the original definition in order to reflect scientific and clinical evidence that has built over the last decade. This paper presents our updated findings. Objectives to increase consistency of research design, clinical diagnoses and ultimately, care for people with sarcopenia. Recommendations sarcopenia is a muscle disease (muscle failure) rooted in adverse muscle changes that accrue across a lifetime; sarcopenia is common among adults of older age but can also occur earlier in life. In this updated consensus paper on sarcopenia, EWGSOP2: (1) focuses on low muscle strength as a key characteristic of sarcopenia, uses detection of low muscle quantity and quality to confirm the sarcopenia diagnosis, and identifies poor physical performance as indicative of severe sarcopenia; (2) updates the clinical algorithm that can be used for sarcopenia case-finding, diagnosis and confirmation, and severity determination and (3) provides clear cut-off points for measurements of variables that identify and characterise sarcopenia. Conclusions EWGSOP2's updated recommendations aim to increase awareness of sarcopenia and its risk. With these new recommendations, EWGSOP2 calls for healthcare professionals who treat patients at risk for sarcopenia to take actions that will promote early detection and treatment. We also encourage more research in the field of sarcopenia in order to prevent or delay adverse health outcomes that incur a heavy burden for patients and healthcare systems. [ABSTRACT FROM AUTHOR]

Atmospheric inversions are used to derive constraints on the net sources and sinks of CO 2 and other stable atmospheric tracers from their observed concentrations. The resolution and accuracy that the fluxes can be estimated with depends, among other factors, on the quality and density of the observational coverage, on the precision and accuracy of the transport model used by the inversion to relate fluxes to observations, and on the adaptation of the statistical approach to the problem studied. In recent years, there has been an increasing demand from stakeholders for inversions at higher spatial resolution (country scale), in particular in the framework of the Paris agreement. This step up in resolution is in theory enabled by the growing availability of observations from surface in situ networks (such as ICOS in Europe) and from remote sensing products (OCO-2, GOSAT-2). The increase in the resolution of inversions is also a necessary step to provide efficient feedback to the bottom-up modeling community (vegetation models, fossil fuel emission inventories, etc.). However, it calls for new developments in the inverse models: diversification of the inversion approaches, shift from global to regional inversions, and improvement in the computational efficiency. In this context, we developed LUMIA, the Lund University Modular Inversion Algorithm. LUMIA is a Python library for inverse modeling built around the central idea of modularity: it aims to be a platform that enables users to construct and experiment with new inverse modeling setups while remaining easy to use and maintain. It is in particular designed to be transport-model-agnostic, which should facilitate isolating the transport model errors from those introduced by the inversion setup itself. We have constructed a first regional inversion setup using the LUMIA framework to conduct regional CO 2 inversions in Europe using in situ data from surface and tall-tower observation sites. The inversions rely on a new offline coupling between the regional high-resolution FLEXPART Lagrangian particle dispersion model and the global coarse-resolution TM5 transport model. This test setup is intended both as a demonstration and as a reference for comparison with future LUMIA developments. The aims of this paper are to present the LUMIA framework (motivations for building it, development principles and future prospects) and to describe and test this first implementation of regional CO 2 inversions in LUMIA. [ABSTRACT FROM AUTHOR]

Many countries have some kind of energy-system transformation either planned or ongoing for various reasons, such as to curb carbon emissions or to compensate for the phasing out of nuclear energy. One important component of these transformations is the overall reduction in energy demand. It is generally acknowledged that the domestic sector represents a large share of total energy consumption in many countries. Increased energy efficiency is one factor that reduces energy demand, but behavioral approaches (known as “sufficiency”) and their respective interventions also play important roles. In this paper, we address citizens’ heterogeneity regarding both their current behaviors and their willingness to realize their sufficiency potentials—that is, to reduce their energy consumption through behavioral change. We collaborated with three Swiss cities for this study. A survey conducted in the three cities yielded thematic sets of energy-consumption behavior that various groups of participants rated differently. Using this data, we identified four groups of participants with different patterns of both current behaviors and sufficiency potentials. The paper discusses intervention types and addresses citizens’ heterogeneity and behaviors from a city-based perspective. [ABSTRACT FROM AUTHOR]

This paper aims to provide insights into the phenomenon of knowledge flows. We study one of the main mechanisms through which these flows occur, namely, the mobility of highly-skilled individuals. We focus on the geographical mobility of inventors across European regions. Thus, patent data are used to trace the pattern of inventors' mobility across European regions, to track down focuses of attraction of talent throughout the continent, and to study their distribution across the space. To do so, we gather information from PCT patent documents and we first match the names which seemed to belong to the same inventor and then we create a new algorithm to decide whether each patent applied for under each name belongs to the same inventor. [ABSTRACT FROM AUTHOR]

Background: Elevated rates of suicidal behavior were reported during the COVID-19 pandemic. However, information is scarce on patients' profiles during this period. Studies evoke the potential adverse effects of the mandatory lockdown, but they remain relatively speculative. Methods: We monitored fluctuations in suicide attempts (SA) in six European countries. We gathered data, retrospectively for under 18-year-old SA episodes (1 January 2018 to 31 December 2021), through records of psychiatric emergency services. We collected clinical profiles individually. We extracted environmental indicators by month, as provided by Oxford COVID-19 Government Response Tracker (OxCGRT). We used the Pruned Exact Linear Time (PELT) method to identify breakpoints in SA episodes reported for each country, and logistic regressions to estimate changes in patients' characteristics after the breakpoints. Finally, we used a univariate and multivariate negative binomial model to assess the link between SA and OxCGRT indicators, accounting for the delay (lag) between the interventions and their impact on SA. Results: The study comprised 2,833 children and adolescents (mean age = 15.1 years (SD 1.6); M: F sex-ratio = 1:5.4). A significant increase in SA was found either 6 or 10 months after the beginning of the pandemic, varying by country. Patients were more likely to be girls (aOR = 1.77 [1.34; 2.34]) and used SA methods "other than self-poisoning" (aOR = 1.34 [1.05; 1.7]). In the multivariate model, an association was found between SA and the contact tracing indicator with an 11 months delay, and the number of COVID-19 deaths with a 3-months delay. Conclusions: Findings confirmed a delayed increase in SA during the COVID-19 pandemic in children and adolescents as well as changes in patients' profiles. The duration and severity of the pandemic emerged as the strongest predictor in the rise of SA. If faced with a similar pandemic in the future, the gap between the onset of pandemic and the increase in suicide attempts presents an opportunity for prevention. [ABSTRACT FROM AUTHOR]

As a result of many factors, including the European Union's aim to increase the share of electrical energy from renewable sources, the number of distributed-generation (DG) devices in Europe is significantly increasing. Increasing numbers of DG units may cause problems with power quality (PQ). In this paper, a PQ-management algorithm is presented that reduces or even solves this problem in low-voltage grids. This algorithm will be implemented as one of several software modules in a system for distributed power operation and PQ management in low-voltage grids. PQ management in this context means maintaining PQ within prescribed limits by optimizing the control of generators, storage units, and controllable loads. Significant advantages of the presented approach are that the algorithm is universal and that it adapts its control variables automatically. Therefore, a detailed analysis of the grid in advance is not necessary. Furthermore, local PQ control of distributed resources can work autonomously and continuously without triggering by external signals, which is advantageous in the case of loss of communications. Various simulations to validate the effectiveness and stable operation of the algorithm were performed and results presented that show a marked improvement in PQ. [ABSTRACT FROM AUTHOR]

The paper proposes a fully automatic algorithm approach to map burned areas from remote sensing characterized by human interpretable mapping criteria and explainable results. This approach is partially knowledge-driven and partially data-driven. It exploits active fire points to train the fusion function of factors deemed influential in determining the evidence of burned conditions from reflectance values of multispectral Sentinel-2 (S2) data. The fusion function is used to compute a map of seeds (burned pixels) that are adaptively expanded by applying a Region Growing (RG) algorithm to generate the final burned area map. The fusion function is an Ordered Weighted Averaging (OWA) operator, learnt through the application of a machine learning (ML) algorithm from a set of highly reliable fire points. Its semantics are characterized by two measures, the degrees of pessimism/optimism and democracy/monarchy. The former allows the prediction of the results of the fusion as affected by more false positives (commission errors) than false negatives (omission errors) in the case of pessimism, or vice versa; the latter foresees if there are only a few highly influential factors or many low influential ones that determine the result. The prediction on the degree of pessimism/optimism allows the expansion of the seeds to be appropriately tuned by selecting the most suited growing layer for the RG algorithm thus adapting the algorithm to the context. The paper illustrates the application of the automatic method in four study areas in southern Europe to map burned areas for the 2017 fire season. Thematic accuracy at each site was assessed by comparison to reference perimeters to prove the adaptability of the approach to the context; estimated average accuracy metrics are omission error = 0.057, commission error = 0.068, Dice coefficient = 0.94 and relative bias = 0.0046. [ABSTRACT FROM AUTHOR]

Three algorithm intercomparison experiments have recently been conducted as part of the Global Precipitation Climatology Project with the goal of (a) assessing the skill of current satellite rainfall algorithms, (b) understanding the differences between them, and (c) moving toward improved algorithms. The results of these experiments are summarized and intercompared in this paper. It was found that the skill of satellite rainfall algorithms depends on the regime being analyzed, with algorithms producing very good results in the tropical western Pacific and over Japan and its surrounding waters during summer, but relatively poor rainfall estimates over western Europe during late winter. Monthly rainfall was estimated most accurately by algorithms using geostationary infrared data, but algorithms using polar data [Advanced Very High Resolution Radiometer and Special Sensor Microwave/Imager (SSM/I)] were also able to produce good monthly rainfall estimates when data from two satellites were available. In most eases, SSM/I algorithms showed significantly greater skill than IR-based algorithms in estimating instantaneous rain rates. [ABSTRACT FROM AUTHOR]

Background: Over the past half century the global tendency for improvements in longevity has been uneven across countries. This has resulted in widening of inter-country disparities in life expectancy. Moreover, the pattern of divergence appears to be driven in part by processes at the level of country groupings defined in geopolitical terms. A systematic quantitative analysis of this phenomenon has not been possible using demographic decomposition approaches as these have not been suitably adapted for this purpose. In this paper we present an elaboration of conventional decomposition techniques to provide a toolkit for analysis of the inter-country variance, and illustrate its use by analyzing trends in life expectancy in developed countries over a 40-year period. Methods: We analyze trends in the population-weighted variance of life expectancy at birth across 36 developed countries and three country groups over the period 1970-2010. We have modified existing decomposition approaches using the stepwise replacement algorithm to compute age components of changes in the total variance as well as variance between and within groups of Established Market Economies (EME), Central and Eastern Europe (CEE), and the Former Soviet Union (FSU). The method is generally applicable to the decomposition of temporal changes in any aggregate index based on a set of populations. Results: The divergence in life expectancy between developed countries has generally increased over the study period. This tendency dominated from the beginning of 1970s to the early 2000s, and reversed only after 2005. From 1970 to 2010, the total standard deviation of life expectancy increased from 2.0 to 5.6 years among men and from 1.0 to 3.6 years among women. This was determined by the between-group effects due to polarization between the EME and the FSU. The latter contrast was largely fueled by the long-term health crisis in Russia. With respect to age, the increase in the overall divergence was attributable to between-country differences in mortality changes at ages 15-64 years compared to those aged 65 and older. The within-group variance increased, especially among women. This change was mostly produced by growing mortality differences at ages 65 and older. Conclusions: From the early 1970s to the mid-2000s, the strong divergence in life expectancy across developed countries was largely determined by the between-group variance and mortality polarization linked to the East--West geopolitical division. [ABSTRACT FROM AUTHOR]

Therapy for polymyalgia rheumatica (PMR) varies widely in clinical practice as international recommendations for PMR treatment are not currently available. In this paper, we report the 2015 European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) recommendations for the management of PMR. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology as a framework for the project. Accordingly, the direction and strength of the recommendations are based on the quality of evidence, the balance between desirable and undesirable effects, patients' and clinicians' values and preferences, and resource use. Eight overarching principles and nine specific recommendations were developed covering several aspects of PMR, including basic and follow-up investigations of patients under treatment, risk factor assessment, medical access for patients and specialist referral, treatment strategies such as initial glucocorticoid (GC) doses and subsequent tapering regimens, use of intramuscular GCs and disease modifying anti-rheumatic drugs (DMARDs), as well as the roles of non-steroidal anti-rheumatic drugs and non-pharmacological interventions. These recommendations will inform primary, secondary and tertiary care physicians about an international consensus on the management of PMR. These recommendations should serve to inform clinicians about best practices in the care of patients with PMR. [ABSTRACT FROM AUTHOR]

Background: Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop., Methods: The image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King's College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study., Results: Some algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72., Conclusions: The study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.

Algorithmic collusion has the potential to transform future markets, leading to higher prices and consumer harm. And yet, algorithmic collusion may remain undetected and unchallenged, in particular, when it is used to facilitate conscious parallelism. The risks posed by such undetected collusion have been debated within antitrust circles in Europe, the US, and beyond. Some economists, however, downplay algorithmic tacit collusion as unlikely, if not impossible. "Keep calm and carry on," they argue, as future prices will remain competitive. This paper explores the rise of algorithmic tacit collusion and responds to those who downplay it, by pointing to new emerging evidence and the gap between law and this particular economic theory. We explain why algorithmic tacit collusion is not only possible but warrants the increasing concerns of many enforcers. [ABSTRACT FROM AUTHOR]

BACKGROUND: Upper extremity function (UEF) is often compromised in multiple sclerosis (MS), although its importance is regularly underrecognized relative to ambulation. We explored the concurrent presence of impairment in UEF and ambulation by examining various aspects of UEF across different levels of ambulation. METHODS: The cohort consisted of 247 patients with clinically definite MS or clinically isolated syndrome according to the revised 2010 McDonald criteria. The Nine-Hole Peg Test and the Expanded Disability Status Scale were used to stratify patients into clinically different subgroups. For UEF, cerebellar function (finger-to-nose test), pyramidal function (pronator drift test), and the ability to perform a task of activities of daily living (drinking- from-cup test) were examined. Patient-reported limitations of UEF in daily life were assessed using the Arm Function in Multiple Sclerosis Questionnaire. RESULTS: Patients in more severely impaired ambulation groups displayed poorer performance on all UEF measures. Although most patients had normal to mild (n = 147) or moderate (n = 46) ambulatory impairment, 87.7% exhibited some level of UEF impairment as defined using the Nine-Hole Peg Test. Most patients had mild UEF impairment (n = 174), accounting for the largest proportion in all ambulation groups (51.9%-77.8%). CONCLUSIONS: A distinct pattern of impairment was found for ambulation and multiple aspects of UEF. Independent assessment of multiple aspects of disability may be helpful in treatment decision-making and could support the development of rehabilitation strategies that specifically target UEF impairment [ABSTRACT FROM AUTHOR]

The ADA and the EASD recently published a consensus statement for the medical management of hyperglycaemia in patients with type 2 diabetes. The authors advocate initial treatment with metformin monotherapy and lifestyle modification, followed by addition of basal insulin or a sulfonylurea if glycaemic goals are not met (tier 1 recommendations). All other glucose-lowering therapies are relegated to a secondary (tier 2) status and only recommended for selected clinical settings. In our view, this algorithm does not offer physicians and patients the appropriate selection of options to individualise and optimise care with a view to sustained control of blood glucose and reduction both of diabetes complications and cardiovascular risk. This paper critically assesses the basis of the ADA/EASD algorithm and the resulting tiers of treatment options.

Objectives: To examine factors influencing the rate of transmitted drug resistance (TDR) among seroconverters, with particular emphasis on 3 widely used genotypic drug resistance algorithms., Methods: The study used data from CASCADE (Concerted Action on Seroconversion to AIDS and Death in Europe), a collaboration of seroconverter cohorts in Europe and Canada. Genotypic resistance data were derived within 18 months of the last seronegative test or date of laboratory evidence of acute infection and before the initiation of antiretroviral therapy. The Stanford algorithm was used to analyze each individual's nucleotide sequence. A multivariate logistic model was used to assess independent relationships between the presence of TDR and exposure category, sex, age at seroconversion, and year of seroconversion. The paper also describes 3 alternative definitions of resistance: the Stanford algorithm, the key resistance mutations defined by the International AIDS Society, and the Agence Nationale de Recherches sur le Sida (ANRS) algorithm., Results: Forty-five of 438 patients (10.3%) seroconverting between 1987 and 2003 were infected with a drug-resistant HIV-1 variant. Forty patients (9.1%) showed resistance mutations to only 1 class of antiretroviral drugs, 2 (0.5%) to 2 classes, and 3 (0.7%) to 3 classes of antiretroviral therapy. It was suggested that individuals seroconverting later in calendar time were more likely to have TDR (relative risk 3.89 and 95% CI: 0.84 to 18.02, and relative risk 4.69 and 95% CI: 1.03 to 21.31, for 1996-1999 and 2000-2003, respectively, compared with pre-1996; P trend = 0.08). This trend was apparent regardless of the definition of TDR used. The total estimated proportion of individuals with TDR varied between 10.3% and 15.5% according to which definition was used., Conclusions: Evidence was found for the rise of TDR over time. A specific definition of what constitutes TDR rather than a simple list of mutations is needed.

In this paper, we describe the implementation of the Semi-Analytical Cloud Retrieval Algorithm (SACURA), to obtain scaled cloud optical thickness (SCOT) from satellite imagery acquired with the SEVIRI instrument and surface UV irradiance levels. In estimation of SCOT particular care is given to the proper specification of the background (i.e. cloud-free) spectral albedo and the retrieval of the cloud water phase from reflectance ratios in SEVIRI's 0.6 µm and 1.6 µm spectral bands. The SACURA scheme is then applied to daytime SEVIRI imagery over Europe, for the month of June 2006, at 15-min time increments. The resulting SCOT fields are compared with values obtained by the CloudSat experimental satellite mission, yielding a negligible bias, correlation coefficients ranging from 0.51 to 0.78, a root mean square difference of 1 to 2 SCOT increments. These findings compare favourably to results from similar intercomparison exercises reported in the literature. Based on the retrieved SCOT from SEVIRI and radiative transfer modelling approach, simple parameterisations are proposed to estimate the surface UV-A and UV-B irradiance. The validation of the modelled UV-A and UV-B irradiance against the measurements over two Belgian stations, Redu and Ostend, indicate good agreement with the high correlation, index of agreement and low bias. The SCOT fields estimated by implementing SACURA on imagery from geostationary satellite are reliable and its impact on surface UV irradiance levels is well produced. [ABSTRACT FROM AUTHOR]

This paper describes the development of the mechanistic model within a collaborative project, referred to as the Advanced REACH Tool (ART) project, to develop a tool to model inhalation exposure for workers sharing similar operational conditions across different industries and locations in Europe. The ART mechanistic model is based on a conceptual framework that adopts a source receptor approach, which describes the transport of a contaminant from the source to the receptor and defines seven independent principal modifying factors: substance emission potential, activity emission potential, localized controls, segregation, personal enclosure, surface contamination, and dispersion. ART currently differentiates between three different exposure types: vapours, mists, and dust (fumes, fibres, and gases are presently excluded). Various sources were used to assign numerical values to the multipliers to each modifying factor. The evidence used to underpin this assessment procedure was based on chemical and physical laws. In addition, empirical data obtained from literature were used. Where this was not possible, expert elicitation was applied for the assessment procedure. Multipliers for all modifying factors were peer reviewed by leading experts from industry, research institutes, and public authorities across the globe. In addition, several workshops with experts were organized to discuss the proposed exposure multipliers. The mechanistic model is a central part of the ART tool and with advancing knowledge on exposure, determinants will require updates and refinements on a continuous basis, such as the effect of worker behaviour on personal exposure, ‘best practice’ values that describe the maximum achievable effectiveness of control measures, the intrinsic emission potential of various solid objects (e.g. metal, glass, plastics, etc.), and extending the applicability domain to certain types of exposures (e.g. gas, fume, and fibre exposure). [ABSTRACT FROM AUTHOR]

This paper presents an alternative approach for time-dependent multimodal transport problem. We describe a new graph structure to abstract multimodal networks, called transfer graph, which adapts to the distributed nature of real information sources of transportation networks. A decomposition of the Shortest Path Problem in transfer graph is proposed to optimize the computation time. This approach was computationally tested in several experimental multimodal networks having different size and complexity. The approach was integrated in the multimodal transport service of the European Carlink platform, where it has been validated in real scenarios. Comparision with other related works is provided. [ABSTRACT FROM AUTHOR]

This paper explores written calculation methods for division used by pupils in England (n = 276) and the Netherlands (n = 259) at two points in the same school year. Informal strategies are analysed and progression identified towards more structured procedures that result from different teaching approaches. Comparison of the methods used by year 5 (Group 6) pupils in the two countries shows greater success in the Dutch approach, which is based on careful progression from informal strategies to more structured and efficient procedures. This success is particularly notable for the girls in the sample. For the English pupils, whose written solutions largely involved the traditional algorithm, the discontinuity between the formal computation procedure and informal solution strategies presents difficulties. [ABSTRACT FROM AUTHOR]

Indirect methods for the indirect estimation of reference intervals are increasingly being used, especially for validation of reference intervals, as they can be applied to routine patient data. In this study, we compare three statistically different indirect methods for the verification and validation of reference intervals in eight laboratories distributed throughout Europe. The RefLim method is a fast and simple approach which calculates the reference intervals by extrapolating the theoretical 95 % of non-pathological values from the central linear part of a quantile-quantile plot. The Truncated Maximum Likelihood (TML) method estimates a smoothed kernel density function for the distribution of the mixed data, for which it is assumed that the "central" part of the distribution represents the healthy population. The refineR utilizes an inverse modelling approach. This algorithm identifies a model that best explains the observed data before transforming the data with the Box-Cox transformation. We show that the different indirect methods each have their advantages but can also lead to inaccurate or ambiguous results depending on the approximation of the mathematical model to real-world data. A combination of different methodologies can improve the informative value and thus the reliability of results. Based on routine measurements of four enzymes alkaline phosphatase (ALP), total amylase (AMY), cholinesterase (CHE) and gamma-glutamyl transferase (GGT) in adult women and men, we demonstrate that some reference limits taken from the literature need to be adapted to the laboratory's particular local and population characteristics. [ABSTRACT FROM AUTHOR]

The genetic algorithm (GA) is a computational procedure that 'evolves' solutions to optimization problems by generating populations of possible solutions, and then by treating these solutions metaphorically as individuals that can 'mate' and 'compete' to 'survive' and 'reproduce'. In this paper, I explore how culturally specific notions of evolution, population, reproduction, sex/gender, and kinship inflect the ways GAs are assembled and understood. Combining the results of fieldwork among GA workers with analysis of GA texts, I contend that the picture of 'nature' embedded in GAs is resonant with the values of secularized Judeo-Christian white middle-class US-American and European heterosexual culture. I also maintain that GA formulations are accented by languages inherited from sociobiology. I argue that examining GAs can help us track how dominant meanings of 'nature' are being stabilized and refigured in an age in which exchanges of metaphor between biology and computer science are increasingly common.

Motivated by the increasing integration among electricity markets, in this paper we propose two different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we propose a deep neural network that considers features from connected markets to improve the predictive accuracy in a local market. To measure the importance of these features, we propose a novel feature selection algorithm that, by using Bayesian optimization and functional analysis of variance, evaluates the effect of the features on the algorithm performance. In addition, using market integration, we propose a second model that, by simultaneously predicting prices from two markets, improves the forecasting accuracy even further. As a case study, we consider the electricity market in Belgium and the improvements in forecasting accuracy when using various French electricity features. We show that the two proposed models lead to improvements that are statistically significant. Particularly, due to market integration, the predictive accuracy is improved from 15.7% to 12.5% sMAPE (symmetric mean absolute percentage error). In addition, we show that the proposed feature selection algorithm is able to perform a correct assessment, i.e. to discard the irrelevant features. [ABSTRACT FROM AUTHOR]

Digitization in transplantation is not a new phenomenon. Algorithms are being used, for example, to allocate organs based on medical compatibility and priority criteria. However, digitization is accelerating as computer scientists and physicians increasingly develop and use machine learning (ML) models to obtain better predictions on the chances of a successful transplant. The objective of the article is to shed light on the potential threats to equitable access to organs allocated through algorithms, whether these are the consequence of political choices made upstream of digitization or of the algorithmic design, or are produced by self-learning algorithms. The article shows that achieving equitable access requires an overall vision of the algorithmic development process and that European legal norms only partially contribute to preventing harm and addressing equality in access to organs. [ABSTRACT FROM AUTHOR]

The paper deals with the management problem how to decide on tree species suitability under changing environmental conditions. It presents an algorithm that classifies the output of a range shift model for major tree species in Europe into multiple classes that can be linked to qualities characterizing the ecological niche of the species. The classes: i) Core distribution area, ii) Extended distribution area, iii) Occasional occurrence area, and iv) No occurrence area are first theoretically developed and then statistically described. The classes are interpreted from an ecological point of view using criteria like population structure, competitive strength, site spectrum and vulnerability to biotic hazards. The functioning of the algorithm is demonstrated using the example of a generalized linear model that was fitted to a pan-European dataset of presence/absence of major tree species with downscaled climate data from a General Circulation Model (GCM). Applications of the algorithm to tree species suitability classification on a European and regional level are shown. The thresholds that are used by the algorithm are precision-based and include Cohen's Kappa. A validation of the algorithm using an independent dataset of the German National Forest Inventory shows good accordance of the statistically derived classes with ecological traits for Norway spruce, while the differentiation especially between core and extended distribution for European beech that is in the centre of its natural range in this area is less accurate. We hypothesize that for species in the core of their range regional factors like forest history superimpose climatic factors. Problems of uncertainty issued from potentially applying a multitude of modelling approaches and/or climate realizations within the range shift model are discussed and a way to deal with the uncertainty by revealing the underlying attitude towards risk of the decision maker is proposed. [Copyright &y& Elsevier]

Abstract: The algorithms used in Arabic and medieval European mathematics for extracting cube roots are studied with respect to algebraic structure and use of external memory (dust board, table, paper). They can be separated into two distinct groups. One contains methods used in the eastern regions from the 11th century, closely connected to Chinese techniques, and very uniform in structure. The other group, showing much wider variation, contains early Indian methods and techniques developed in central and western parts of the Arabic areas and in Europe. This study supports hypotheses previously formulated by Luckey and Chemla on an early scientific connection between China and Persia. [Copyright &y& Elsevier]

Abstract: The present paper addresses the issue of urban sprawl in Europe from a multidimensional point of view, identifying the most sprawled areas and characterizing them in terms of population size. The literature is reviewed to categorize and extract the most relevant six dimensions that define the concept and several indices are specified to implement them. These are then calculated for a sample of the main European cities that uses several sources to obtain the best possible dataset to measure urban sprawl. All this information is brought together using the self-organizing map (SOM) algorithm to be visualized and further studied, taking advantage of its properties as a data-reduction as well as a clustering technique. The analysis locates the hot-spots of urban sprawl in Europe in the centre of the continent, around Germany, and characterizes such urban areas as small, always half the size of the average city of the sample. [Copyright &y& Elsevier]

Abstract: This paper describes a methodology to explore the (future) spatial distribution of biofuel crops in Europe. Two main types of biofuel crops are distinguished: biofuel crops used for the production of biodiesel or bioethanol, and second-generation biofuel crops. A multi-scale, multi-model approach is used in which biofuel crops are allocated over the period 2000–2030. The area of biofuel crops at the national level is determined by a macro-economic model. A spatially explicit land use model is used to allocate the biofuel crops within the countries. Four scenarios have been prepared based on storylines influencing the extent and spatial distribution of biofuel crop cultivation. The allocation algorithm consists of two steps. In the first step, processing plants are allocated based on location factors that are dependent on the type of biofuel crop processed and scenario conditions. In the second step, biofuel crops are allocated accounting for the transportation costs to the processing plants. Both types of biofuel crops are allocated separately based on different location factors. Despite differences between the scenarios, mostly the same areas are showing growth in biofuel crop cultivation in all scenarios. These areas stand out because they have a combination of well-developed infrastructural and industrial facilities and large areas of suitable arable land. The spatially explicit results allow an assessment of the potential consequences of large-scale biofuel crop cultivation for ecology and environment. [Copyright &y& Elsevier]

The paper deals with computer aided SWOT analysis addressing the evaluation of innovation potential of Central and South-East European countries. A type of quantitative SWOT analysis was used, due to its high efficiency, leading to fast establishing a generic strategy which could be particularized with real measures able to be applied in order to reach the objectives of improving the innovation achievements. The methodology is based on number of S, W, O, T issues, the accomplishing of SWOT matrix and also establishing the quadrant with the corresponding strategy. The "national" SWOTs, entry data in the algorithm, were part of country studies which were performed by relevant partners from each Central and South-East European country within the framework of SEE-IFA-NETWORK project. The countries were grouped according to Innovation Union Scoreboard 2010 criteria related to innovation performances and relevant strategies were elaborated to improve their innovation achievements. [ABSTRACT FROM AUTHOR]

Abstract: This purposes of this paper are to: 1) demonstrate an objective overshooting top (OT) detection method using Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) infrared data, 2) produce an OT database for all operational SEVIRI data over Europe and north Africa for the six Northern Hemisphere warm seasons observed by SEVIRI to date, and 3) determine the frequency of OT detections in the vicinity of confirmed severe weather reports recorded within the European Severe Weather Database (ESWD). Algorithm performance is demonstrated for a case where numerous severe storms were present. Qualitative comparisons indicate that most OT detections correspond with the characteristic OT signature in SEVIRI 1km resolution visible channel imagery, but some OTs were left undetected due in part to relatively coarse SEVIRI spatial resolution over the European domain. The SEVIRI OT database shows a strong relationship between OT maxima and regions with high terrain. OTs are found to occur more frequently during the day over land and during the night over water. Inter- and intra-seasonal variability in OT frequency and location are also shown. An OT was found near 47% of the confirmed ESWD events. The OT–severe weather relationship is strong for large hail (53%) and severe wind (52%) events but relatively weak for tornado events (14%). The weak OT–tornado relationship may be related two factors: 1) low-level wind shear is found to be of greater importance than large CAPE and strong updrafts (i.e. OTs) in tornadic storm environments across Europe and 2) a weakening of the storm updraft and collapse of the OT region has been documented prior to tornado formation. The relatively strong overall OT–severe weather relationship suggests that OT detections can be used to increase forecaster confidence that a given storm is severe, especially in regions where frequent, ground based Doppler weather radar data is unavailable. [ABSTRACT FROM AUTHOR]

The paper addresses selected computational issues related to the challenge of dealing with poor statistics on international migration. Partial results of the on-going Eurostat-funded project on "Modelling of statistical data on migration and migrant population" (MIMOSA) are presented. The focus is on the data on population stocks by broad group of citizenship, sex and age. After a brief overview of the main problems with data on population by citizenship for 31 European countries (27 European Union countries, Iceland, Liechtenstein, Norway and Switzerland), a range of computational methods is proposed including cohort-wise interpolation, cohort-component projections, cohort-wise weights propagation and proportional fitting methods, as well as other, auxiliary methods. The algorithm for choosing the best method for estimating missing data on population stock by broad citizenship (nationals, foreigners -- EU27 citizens, foreigners -- non EU27 citizens), five-year age group (up to 85+) and sex on 1st January 2002-2006 is proposed and illustrated by examples of its application for selected countries. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes the evaluation and performance of the Medium Resolution Imaging Spectrometer (MERIS) Global Vegetation Index (MGVI) algorithm that is implemented in the MERIS ground segment as the primary land surface product. MGVI output values represent the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) which acts as an indicator of the presence and state of the vegetation canopy. The retrieval algorithm was optimized to be insensitive to the overlying atmosphere, the underlying soil as well as angular effects, using radiative transfer models. This physically based approach for retrieving land biophysical parameters can be extended to a series of sensors; the resulting algorithms are designed to deliver similar geophysical products that are directly comparable and ultimately generate long time series of FAPAR. After presenting the MGVI algorithm, we analyze actual results by inter-comparing the FAPAR values derived from MERIS to similar products derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) that have been generated at the European Commission Joint Research Centre (EC-JRC). The FAPAR products derived from MERIS and SeaWiFS are compared on several dates in 2002 when both instruments simultaneously observed the same geographical regions. The consistency and temporal continuity of the products are then evaluated by comparing the time series of FAPAR values over local sites in Europe during the year 2003 from the two instruments. Finally, multi-annual FAPAR time series obtained by merging MERIS and SeaWiFS products demonstrate the feasibility of monitoring the state of land surfaces with FAPAR products before and after the European drought event in 2003. [Copyright &y& Elsevier]

In the sparse polynomial multiplication problem, one is asked to multiply two sparse polynomials $f$ and $g$ in time that is proportional to the size of the input plus the size of the output. The polynomials are given via lists, $F$ and $G$ , of their coefficients. Cole and Hariharan (STOC 02) have given a nearly optimal algorithm when the coefficients are positive, and Arnold and Roche (ISSAC 15) devised an algorithm running in time proportional to the “structural sparsity” of the product, i.e. the set $\mathrm {supp}(F) + \mathrm {supp}(G)$. The latter algorithm is particularly efficient when there are not “too many cancellations” of coefficients in the product. In this work we give a clean, nearly optimal algorithm for the sparse polynomial multiplication problem. [ABSTRACT FROM AUTHOR]

Rain/no-rain detection error is a key source of uncertainty in regional and global precipitation products that propagates into offline hydrological and land surface modeling simulations. Such detection error is difficult to evaluate and/or filter without access to high-quality reference precipitation datasets. For cases where such access is not available, this study proposes a novel approach for improved rain/no-rain detection. Based on categorical triple collocation (CTC) and a probabilistic framework, a weighted merging algorithm (CTC-M) is developed to combine noisy, but independent, precipitation products into an optimal binary rain/no-rain time series. Compared with commonly used approaches that directly apply the best parent product for rain/no-rain detection, the superiority of CTC-M is demonstrated analytically and numerically using spatially dense precipitation measurements over Europe. Our analysis also suggests that CTC-M is tolerant to a range of cross-correlated rain/no-rain detection errors and detection biases of the parent products. As a result, CTC-M will benefit global precipitation estimation by improving the representation of precipitation occurrence in gauge-based and multisource merged precipitation products. [ABSTRACT FROM AUTHOR]

• Timeseries representational method that presents the collective trend of the data. • A user defined segmentation method of time-series data. • Probabilistic approach of forming representational building blocks for timeseries. • Unsupervised trend based hierarchical clustering of timeseries data. Time series data is a sequence of values recorded systematically over a period which are mostly used for prediction, clustering, and analysis. The two essential features of a time series data are trend and seasonality. Preprocessing of the time series data is necessary for performing prediction tasks. In most of the cases, the trend and the seasonality are removed before applying the regression algorithms. The accuracy of such algorithms depends upon the functions used for the removal of trend and seasonality. Clustering of an unlabeled time series data with the presence of trend and seasonality is challenging. In this paper, we propose a probabilistic representational learning method for grouping the time series data. We introduce five terminologies in our method of clustering namely the trendlets, uplets, downlets, equalets and trendlet string. These elements are the representational building blocks of our proposed method. Experiments on the proposed algorithm are performed with the renewable energy data on the electricity supply system of continental Europe which includes the demand and inflow of renewable energy for the term 2012 to 2014 and UCR-2018 time series archive containing 128 datasets. We compared our proposed representational method with various clustering algorithms using the silhouette score. Mini-batch k-means and agglomerative hierarchical clustering algorithms show better performance in terms of quality, logical accordance with data and time taken for clustering. [ABSTRACT FROM AUTHOR]

Air quality measures that were implemented in Europe in the 1990s resulted in reductions of ozone precursor concentrations. In this study, the effect of these reductions on ozone is investigated by analyzing surface measurements of this pollutant for the time period between 2000 and 2015. Using a nonparametric timescale decomposition methodology, the long-term, seasonal and short-term variation in ozone observations were extracted. A clustering algorithm was applied to the different timescale variations, leading to a classification of sites across Europe based on the temporal characteristics of ozone. The clustering based on the long-term variation resulted in a site-type classification, while a regional classification was obtained based on the seasonal and short-term variations. Long-term trends of deseasonalized mean and meteo-adjusted peak ozone concentrations were calculated across large parts of Europe for the time period 2000–2015. A multidimensional scheme was used for a detailed trend analysis, based on the identified clusters, which reflect precursor emissions and meteorological influence either on the inter-annual or the short-term timescale. Decreasing mean ozone concentrations at rural sites and increasing or stabilizing at urban sites were observed. At the same time, downward trends for peak ozone concentrations were detected for all site types. In addition, a reduction of the amplitude in the seasonal cycle of ozone and a shift in the occurrence of the seasonal maximum towards earlier time of the year were observed. Finally, a reduced sensitivity of ozone to temperature was identified. It was concluded that long-term trends of mean and peak ozone concentrations are mostly controlled by precursor emissions changes, while seasonal cycle trends and changes in the sensitivity of ozone to temperature are among other factors driven by regional climatic conditions. [ABSTRACT FROM AUTHOR]

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Objectives: Value of information (VOI) analysis provides information on opportunity cost of a decision in healthcare by estimating the cost of reducing parametric uncertainty and quantifying the value of generating additional evidence. This study is an application of the VOI methodology to the problem of choosing between home telemonitoring and nurse telephone support over usual care in chronic heart failure management in the Netherlands. Methods: The expected value of perfect information (EVPI) and the expected value of partially perfect information (EVPPI) analyses were based on an informal threshold of €20K per quality-adjusted life-year. These VOI-analyses were applied to a probabilistic Markov model comparing the 20-year costs and effects in three interventions. The EVPPI explored the value of decision uncertainty caused by the following group of parameters: treatment-specific transition probabilities between New York Heart Association (NYHA) defined disease states, utilities associated with the disease states, number of hospitalizations and ER visits, health state specific costs, and the distribution of patients per NYHA group. We performed the analysis for two population sizes in the Netherlands—patients in all NYHA classes of severity, and patients in NYHA IV class only. Results: The population EVPI for an effective population of 2,841,567 CHF patients in All NYHA classes of severity over the next 20 years is more than €4.5B, implying that further research is highly cost-effective. In the NYHA IV only analysis, for the effective population of 208,003 patients over next 20 years, the population EVPI at the same informal threshold is approx. €590M. The EVPPI analysis showed that the only relevant group of parameters that contribute to the overall decision uncertainty are transition probabilities, in both All NYHA and NYHA IV analyses. Conclusions: Results of our VOI exercise show that the cost of uncertainty regarding the decision on reimbursement of telehealth interventions for chronic heart failure patients is high in the Netherlands, and that future research is needed, mainly on the transition probabilities. [ABSTRACT FROM AUTHOR]

Background The article examines gender differences in happy life expectancy at age 50 (LE50) and computes the age-specific contributions of mortality and happiness effects to gender differences in happy LE50 in 16 European countries. Methods Abridged life tables and happy LE50 were calculated using conventional life tables and Sullivan's method. Age-specific death rates were calculated from deaths and population exposures in the Human Mortality Database. Happiness prevalence was estimated using the 2010–11 Survey of Health, Ageing and Retirement in Europe. Happiness was defined using a single question about life satisfaction on a scale of 0–10. A decomposition algorithm was applied to estimate the exact contributions of the differences in mortality and happiness to the overall gender gap in happy LE50. Results Gender differences in happy LE50 favour women in all countries except Portugal (0.43 years in Italy and 3.55 years in Slovenia). Generally, the contribution of the gender gap in happiness prevalence is smaller than the one in mortality. The male advantage in the prevalence of happiness partially offsets the effects of the female advantage in mortality on the total gender gap in happy LE50. Gender differences in unhappy life years make up the greatest share of the gender gap in total LE50 in all countries except Denmark, Germany, Netherlands, Slovenia and Sweden. Conclusion Countries with the largest gender gap in LE are not necessarily the countries with larger differences in happy LE50. The remaining years of life of women are expected to be spent not only in unhealthy but also in unhappy state. [ABSTRACT FROM AUTHOR]

Romani people are a significant minority in Europe counting about 10 million individuals scattered throughout the continent. They are a migratory group originating from Northwestern India. Their exodus from India occurred approximately 1000–1500 years ago. The migration route of the Romani people was reconstructed with the help of cultural anthropology, linguistics and historical records. Their migration made them through Central Asia, Middle East and the Caucasus region, prior to the arriving into Europe. Yet the significance of these regions, especially of the Caucasus, in Roma ancestry was a rather neglected topic. Contribution of the Caucasus and further affected regions to the ancestry of Roma was investigated based on genome-wide autosomal marker data. 158 European Roma samples and 41 populations from the Caucasus region, from Middle East, Central Asia and from South Asia were considered in our tests. Population structure and ancestry analysis algorithms were applied to investigate the relationship of Roma with these populations. Identical by descent DNA segment analyses and admixture linkage disequilibrium based tests were also applied. Our results suggest that the Caucasus region plays also a significant role in the genetic legacy of Romani people besides the main sources, Europe and South Asia, previously investigated by other population genetic studies. The Middle East and Central Asia seems slightly less important but far from negligible in connection with the sources of Roma ancestry. Our results point out that the Caucasus region and altogether the area of the Caspian and Black Seas had a significant role in the migration of Romani people towards Europe and contributed significantly to the genetic legacy of Roma rival to the European and Indian main sources. [ABSTRACT FROM AUTHOR]

Background: Traumatic injury is the fourth leading cause of death globally. Half of all trauma deaths are due to bleeding and most of these will occur within 6 h of injury. Haemorrhagic shock following injury has been shown to induce a clotting dysfunction within minutes, and this early trauma-induced coagulopathy (TIC) may exacerbate bleeding and is associated with higher mortality and morbidity. In spite of improved resuscitation strategies over the last decade, current transfusion therapy still fails to correct TIC during ongoing haemorrhage and evidence for the optimal management of bleeding trauma patients is lacking. Recent publications describe increasing the use of Viscoelastic Haemostatic Assays (VHAs) in trauma haemorrhage; however, there is insufficient evidence to support their superiority to conventional coagulation tests (CCTs).Methods/design: This multicentre, randomised controlled study will compare the haemostatic effect of an evidence-based VHA-guided versus an optimised CCT-guided transfusion algorithm in haemorrhaging trauma patients. A total of 392 adult trauma patients will be enrolled at major trauma centres. Participants will be eligible if they present with clinical signs of haemorrhagic shock, activate the local massive haemorrhage protocol and initiate first blood transfusion. Enrolled patients will be block randomised per centre to either VHA-guided or CCT-guided transfusion therapy in addition to that therapy delivered as part of standard care, until haemostasis is achieved. Patients will be followed until discharge or 28 days. The primary endpoint is the proportion of subjects alive and free of massive transfusion (less than 10 units of red blood cells) at 24 h. Secondary outcomes include the effect of CCT- versus VHA-guided therapy on organ failure, total hospital and intensive care lengths of stay, health care resources needed and mortality. Surviving patients will be asked to complete a quality of life questionnaire (EuroQol EQ-5DTM) at day 90.Discussion: CCTs have traditionally been used to detect TIC and monitor response to treatment in traumatic major haemorrhage. The use of VHAs is increasing, but limited evidence exists to support the superiority of these technologies (or comparatively) for patient-centred outcomes. This knowledge gap will be addressed by this trial.Trial Registration: ClinicalTrials.gov, ID: NCT02593877 . Registered on 15 October 2015. Trial sponsor Queen Mary University of London The contact person of the above sponsor organisation is: Dr. Sally Burtles, Director of Research Services and Business Development, Joint Research Management Office, QM Innovation Building, 5 Walden Street, London E1 2EF; phone: 020 7882 7260; Email: sponsorsrep@bartshealth.nhs.uk Trial sites Academic Medical Centre, Amsterdam, The Netherlands Kliniken der Stadt Köln gGmbH, Cologne, Germany Rigshospitalet (Copenhagen University Hospital), Copenhagen, Denmark John Radcliff Hospital, Oxford, United Kingdom Oslo University Hospital, Oslo, Norway The Royal London Hospital, London, United Kingdom Centre for Trauma Sciences, Blizard Institute, Queen Mary University of London, London, United Kingdom Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom Sites that are planning to start recruitment in mid/late 2017 Nottingham University Hospitals, Queen's Medical Centre, Nottingham, United Kingdom University of Kansas Hospital (UKH), Kansas City, MO, USA Protocol version: 3.0/14.03.2017 (Additional file 1). [ABSTRACT FROM AUTHOR]