Showing papers by "University of Hertfordshire published in 2021"

The GALAH+ survey: Third data release

Abstract: © 2021 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1093/mnras/stab1242

Risk factors for long covid in previously hospitalised children using the ISARIC Global follow-up protocol: A prospective cohort study.

Abstract: Background: The long-term sequelae of coronavirus disease 2019 (Covid-19) in children remain poorly characterised. This study aimed to assess long-term outcomes in children previously hospitalised with Covid-19 and associated risk factors. Methods: This is a prospective cohort study of children (≤18 years old) admitted with confirmed Covid-19. Children admitted to the hospital between April 2, 2020 and August 26, 2020, were included. Telephone interview using the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) Covid-19 Health and Wellbeing paediatric follow-up survey. Persistent symptoms (>5 months) were further categorised by system(s) involved. Findings: 518 of 853 (61%) of eligible children were available for the follow-up assessment and included in the study. Median age was 10.4 years (IQR, 3–15.2) and 270 (52.1%) were girls; median follow-up since hospital discharge was 256 (223–271) days. At the time of the follow-up interview 126 (24.3%) participants reported persistent symptoms among which fatigue (53, 10.7%), sleep disturbance (36, 6.9%,) and sensory problems (29, 5.6%) were the most common. Multiple symptoms were experienced by 44 (8.4%) participants. Risk factors for persistent symptoms were: older age “6–11 years” (odds ratio 2.74 (95% confidence interval 1.37 to 5.75) and “12–18 years” (2.68, 1.41 to 5.4); and a history of allergic diseases (1.67, 1.04 to 2.67). Interpretation: A quarter of children experienced persistent symptoms months after hospitalization with acute covid-19 infection, with almost one in ten experiencing multi-system involvement. Older age and allergic diseases were associated with higher risk of persistent symptoms at follow-up.

Gaia Early Data Release 3 - The Gaia Catalogue of Nearby Stars

Abstract: Aims. We produce a clean and well-characterised catalogue of objects within 100 pc of the Sun from the Gaia Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use.Methods. Theselection of objects within 100 pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100 pc is included in the catalogue.Results. We have produced a catalogue of 331 312 objects that we estimate contains at least 92% of stars of stellar type M9 within 100 pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100 pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of Gaia Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10 pc of the Sun.Conclusions. We provide the community with a large, well-characterised catalogue of objects in the solar neighbourhood. This is a primary benchmark for measuring and understanding fundamental parameters and descriptive functions in astronomy.

Applications of artificial intelligence in battling against covid-19: A literature review.

Abstract: Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of grave concern for every country around the world. The rapid growth of the pandemic has wreaked havoc and prompted the need for immediate reactions to curb the effects. To manage the problems, many research in a variety of area of science have started studying the issue. Artificial Intelligence is among the area of science that has found great applications in tackling the problem in many aspects. Here, we perform an overview on the applications of AI in a variety of fields including diagnosis of the disease via different types of tests and symptoms, monitoring patients, identifying severity of a patient, processing covid-19 related imaging tests, epidemiology, pharmaceutical studies, etc. The aim of this paper is to perform a comprehensive survey on the applications of AI in battling against the difficulties the outbreak has caused. Thus we cover every way that AI approaches have been employed and to cover all the research until the writing of this paper. We try organize the works in a way that overall picture is comprehensible. Such a picture, although full of details, is very helpful in understand where AI sits in current pandemonium. We also tried to conclude the paper with ideas on how the problems can be tackled in a better way and provide some suggestions for future works.

The LOFAR Two-meter Sky Survey: Deep Fields Data Release 1. I. Direction-dependent calibration and imaging

Abstract: The Low Frequency Array (LOFAR) is an ideal instrument to conduct deep extragalactic surveys. It has a large field of view and is sensitive to large-scale and compact emission. It is, however, very challenging to synthesize thermal noise limited maps at full resolution, mainly because of the complexity of the low-frequency sky and the direction dependent effects (phased array beams and ionosphere). In this first paper of a series, we present a new calibration and imaging pipeline that aims at producing high fidelity, high dynamic range images with LOFAR High Band Antenna data, while being computationally efficient and robust against the absorption of unmodeled radio emission. We apply this calibration and imaging strategy to synthesize deep images of the Bootes and Lockman Hole fields at ~150 MHz, totaling ~80 and ~100 h of integration, respectively, and reaching unprecedented noise levels at these low frequencies of ≲30 and ≲23 μ Jy beam−1 in the inner ~3 deg2 . This approach is also being used to reduce the LOTSS-wide data for the second data release.

The East Asian Paradox: An Updated Position Statement on the Challenges to the Current Antithrombotic Strategy in Patients with Cardiovascular Disease

Abstract: East Asian patients have reduced anti-ischemic benefits and increased bleeding risk during antithrombotic therapies compared with Caucasian patients. As potent P2Y12 receptor inhibitors (e.g., ticagrelor and prasugrel) and direct oral anticoagulants are commonly used in current daily practice, the unique risk–benefit trade-off in East Asians has been a topic of emerging interest. In this article, we propose updated evidence and future directions of antithrombotic treatment in East Asian patients.

Telepsychiatry and other cutting-edge technologies in COVID-19 pandemic: Bridging the distance in mental health assistance.

Abstract: Background At the end of 2019, a novel coronavirus (COVID-19) was identified in China. The high potential of human-to-human transmission led to subsequent COVID-19 global pandemic. Public health strategies including reduced social contact and lockdown have been adopted in many countries. Nonetheless, social distancing and isolation could also represent risk factors for mental disorders, resulting in loneliness, reduced social support and under-detection of mental health needs. Along with this, social distancing determines a relevant obstacle for direct access to psychiatric care services. The pandemic generates the urgent need for integrating technology into innovative models of mental healthcare. Aims In this paper, we discuss the potential role of telepsychiatry (TP) and other cutting-edge technologies in the management of mental health assistance. We narratively review the literature to examine the advantages and risks related to the extensive application of these new therapeutic settings, along with the possible limitations and ethical concerns. Results Telemental health services may be particularly feasible and appropriate for the support of patients, family members and healthcare providers during this COVID-19 pandemic. The integration of TP with other technological innovations (eg, mobile apps, virtual reality, big data and artificial intelligence (AI)) opens up interesting future perspectives for the improvement of mental health assistance. Conclusion Telepsychiatry is a promising and growing way to deliver mental health services but is still underused. The COVID-19 pandemic may serve as an opportunity to introduce and promote, among numerous mental health professionals, the knowledge of the possibilities offered by the digital era.

Polymers exhibiting lower critical solution temperatures as a route to thermoreversible gelators for healthcare

Abstract: Funding Information: M.T.C. acknowledges support from the EPSRC (EP/T00813X/1). The University of Hertfordshire are thanked for funding the research project of P.H. Publisher Copyright: © 2020 The Authors. Advanced Functional Materials published by Wiley-VCH GmbH

Remote management of covid-19 using home pulse oximetry and virtual ward support.

Abstract: ### What you need to know Low blood oxygen—technically, hypoxaemia but usually referred to as hypoxia—can be defined as a measured oxygen saturation below 94% in the absence (or below 88% in the presence) of chronic lung disease.1 In most patients who die of acute covid-19, the initial illness advances insidiously, sometimes with “silent hypoxia” (hypoxia without clinically perceptible symptoms of dyspnoea23), leading to pneumonia followed by acute respiratory distress syndrome, usually in week 2.4 The underlying pathology in covid-19 related hypoxia is probably a ventilation-perfusion mismatch,5 caused by a combination of intrapulmonary shunting, loss of lung perfusion regulation, intravascular microthrombi, and reduced lung compliance leading to alveolar collapse.267 Many patients hospitalised with acute covid-19 have severe hypoxia.478 Hypoxia, silent hypoxia, and the need for supplementary oxygen are all independent predictors of worse outcomes in covid-19.8910111213141516 Novel prognostic tools such as the 4C score have shown the importance of identifying hypoxia early,917 and there are physiological reasons for managing the complication promptly and actively.118 For all these reasons, UK guidelines recommend that assessment and monitoring of breathless, unwell, or high risk patients with suspected covid-19 should include pulse oximetry.1920 Guidance published in January 2021 by the World Health Organization includes a provisional recommendation for “use of pulse oximetry monitoring at home as part of a package of care, including patient and provider education and appropriate follow-up.”21 Home …

Urinary biomarkers in bladder cancer: A review of the current landscape and future directions.

Abstract: Aim This narrative review aims to describe established and emerging urinary biomarkers in the diagnosis and surveillance of non-muscle invasive bladder cancer. It provides a comprehensive account of classical, FDA-approved protein biomarkers and discusses their limitations. Further, we discuss the role that epigenetic, genetic, and exosomal markers can play to enhance sensitivity and specificity of the available tests. Background The initial diagnosis and surveillance of bladder cancer involves a combination of cystoscopy, upper urinary tract imaging, and urine cytology. Despite high specificity, cytology is limited by low sensitivity. There are currently 6 urinary assays approved by the FDA to enhance diagnosis and surveillance of bladder cancer. While these have improved diagnosis and surveillance when combined with cytology, these tests are still not sufficiently sensitive and false positives often occur in benign conditions which result in inflammation of the urinary tract. Advancements in laboratory techniques have produced significant advancements in epigenetic and genetic markers, as well as extracellular vesicles, with DNA- and RNA-based markers dominating the research in this area in recent years. Methods We identified relevant published data, using the PubMed/ Medline search engines as well as Google Scholar. We performed an online search using the terms “bladder cancer”, “non-muscle invasive bladder cancer” in combination with “urine biomarkers” and limited articles in English published up to February 2020. This review consolidated on all available narrative and systematic reviews published in the 5 years in this field, while also reviewing the original data of each clinical trial or observational study which led to the development of the biomarkers. Conclusion The development of laboratory techniques and understanding urine-based biomarkers in BC has fuelled the use of noninvasive liquid-based biomarkers to complement urine cytology. Nonetheless, none are sufficiently effective when used in isolation, and cytology remains the gold standard in many practices. Future efforts will be focused on using these markers in combination as a predictive signature, and moving on to validating them for use in everyday clinical practice.

Incidence and risk factors for persistent symptoms in adults previously hospitalised for COVID-19

Abstract: BACKGROUND: The long-term sequalae of COVID-19 remain poorly characterized. We assessed persistent symptoms in previously hospitalized patients with COVID-19 and assessed potential risk factors. METHODS: Data were collected from patients discharged from 4 hospitals in Moscow, Russia between 8 April and 10 July 2020. Participants were interviewed via telephone using an ISARIC Long-term Follow-up Study questionnaire. RESULTS: 2,649 of 4755 (56%) discharged patients were successfully evaluated, at median 218 (IQR 200, 236) days post-discharge. COVID-19 diagnosis was clinical in 1291 and molecular in 1358. Most cases were mild, but 902 (34%) required supplemental oxygen and 68 (2.6%) needed ventilatory support. Median age was 56 years (IQR 46, 66) and 1,353 (51.1%) were women. Persistent symptoms were reported by 1247 (47.1%) participants, with fatigue (21.2%), shortness of breath (14.5%) and forgetfulness (9.1%) the most common symptoms and chronic fatigue (25%) and respiratory (17.2%) the most common symptom categories. Female sex was associated with any persistent symptom category OR 1.83 (95% CI 1.55 to 2.17) with association being strongest for dermatological (3.26, 2.36 to 4.57) symptoms. Asthma and chronic pulmonary disease were not associated with persistent symptoms overall, but asthma was associated with neurological (1.95, 1.25 to 2.98) and mood and behavioural changes (2.02, 1.24 to 3.18), and chronic pulmonary disease was associated with chronic fatigue (1.68, 1.21 to 2.32). CONCLUSIONS: Almost half of adults admitted to hospital due to COVID-19 reported persistent symptoms 6 to 8 months after discharge. Fatigue and respiratory symptoms were most common, and female sex was associated with persistent symptoms.

Expert appraisal of criteria for assessing gaming disorder: an international Delphi study.

Abstract: Background and aims: Following the recognition of ‘internet gaming disorder’ (IGD) as a condition requiring further study by the DSM-5, ‘gaming disorder’ (GD) was officially included as a diagnostic entity by the World Health Organization (WHO) in the 11th revision of the International Classification of Diseases (ICD-11). However, the proposed diagnostic criteria for gaming disorder remain the subject of debate, and there has been no systematic attempt to integrate the views of different groups of experts. To achieve a more systematic agreement on this new disorder, this study employed the Delphi expert consensus method to obtain expert agreement on the diagnostic validity, clinical utility and prognostic value of the DSM-5 criteria and ICD-11 clinical guidelines for GD. Methods: A total of 29 international experts with clinical and/or research experience in GD completed three iterative rounds of a Delphi survey. Experts rated proposed criteria in progressive rounds until a pre-determined level of agreement was achieved. Results: For DSM-5 IGD criteria, there was an agreement both that a subset had high diagnostic validity, clinical utility and prognostic value and that some (e.g. tolerance, deception) had low diagnostic validity, clinical utility and prognostic value. Crucially, some DSM-5 criteria (e.g. escapism/mood regulation, tolerance) were regarded as incapable of distinguishing between problematic and non-problematic gaming. In contrast, ICD-11 diagnostic guidelines for GD (except for the criterion relating to diminished non-gaming interests) were judged as presenting high diagnostic validity, clinical utility and prognostic value. Conclusions: This Delphi survey provides a foundation for identifying the most diagnostically valid and clinically useful criteria for GD. There was expert agreement that some DSM-5 criteria were not clinically relevant and may pathologize non-problematic patterns of gaming, whereas ICD-11 diagnostic guidelines are likely to diagnose GD adequately and avoid pathologizing.

Communication and Virtual Visiting for Families of Patients in Intensive Care during the COVID-19 Pandemic: A UK National Survey.

Abstract: Rationale: Restriction or prohibition of family visiting intensive care units (ICUs) during the coronavirus disease (COVID-19) pandemic poses substantial barriers to communication and family- and patient-centered care. Objectives: To understand how communication among families, patients, and the ICU team was enabled during the pandemic. The secondary objectives were to understand strategies used to facilitate virtual visiting and associated benefits and barriers. Methods: A multicenter, cross-sectional, and self-administered electronic survey was sent (June 2020) to all 217 UK hospitals with at least one ICU. Results: The survey response rate was 54%; 117 of 217 hospitals (182 ICUs) responded. All hospitals imposed visiting restrictions, with visits not permitted under any circumstance in 16% of hospitals (28 ICUs); 63% (112 ICUs) of hospitals permitted family presence at the end of life. The responsibility for communicating with families shifted with decreased bedside nurse involvement. A dedicated ICU family-liaison team was established in 50% (106 ICUs) of hospitals. All but three hospitals instituted virtual visiting, although there was substantial heterogeneity in the videoconferencing platform used. Unconscious or sedated ICU patients were deemed ineligible for virtual visits in 23% of ICUs. Patients at the end of life were deemed ineligible for virtual visits in 7% of ICUs. Commonly reported benefits of virtual visiting were reducing patient psychological distress (78%), improving staff morale (68%), and reorientation of patients with delirium (47%). Common barriers to virtual visiting were related to insufficient staff time, rapid implementation of videoconferencing technology, and challenges associated with family members' ability to use videoconferencing technology or access a device. Conclusions: Virtual visiting and dedicated communication teams were common COVID-19 pandemic innovations addressing the restrictions to family ICU visiting, and they resulted in valuable benefits in terms of patient recovery and staff morale. Enhancing access and developing a more consistent approach to family virtual ICU visits could improve the quality of care, both during and outside of pandemic conditions.

Developing Kaspar: A Humanoid Robot for Children with Autism

Abstract: In the late 1990s using robotic technology to assist children with Autistic Spectrum Condition (ASD) emerged as a potentially useful area of research. Since then the field of assistive robotics for children with ASD has grown considerably with many academics trialling different robots and approaches. One such robot is the humanoid robot Kaspar that was originally developed in 2005 and has continually been built upon since, taking advantage of technological developments along the way. A key principle in the development of Kaspar since its creation has been to ensure that all of the advances to the platform are driven by the requirements of the users. In this paper we discuss the development of Kaspar’s design and explain the rationale behind each change to the platform. Designing and building a humanoid robot to interact with and help children with ASD is a multidisciplinary challenge that requires knowledge of the mechanical engineering, electrical engineering, Human–Computer Interaction (HCI), Child–Robot Interaction (CRI) and knowledge of ASD. The Kaspar robot has benefited from the wealth of knowledge accrued over years of experience in robot-assisted therapy for children with ASD. By showing the journey of how the Kaspar robot has developed we aim to assist others in the field develop such technologies further.

Outage Probability Analysis of IRS-Assisted Systems Under Spatially Correlated Channels

Abstract: This letter investigates the impact of spatial channel correlation on the outage probability of intelligent reflecting surface (IRS)-assisted single-input single-output (SISO) communication systems. In particular, we derive a novel closed-form expression of the outage probability for arbitrary phase shifts and correlation matrices of the indirect channels. To shed light on the impact of the spatial correlation, we further attain the closed-form expressions for two common scenarios met in the literature when the large-scale fading coefficients are expressed by the loss over a propagation distance. Numerical results validate the tightness and effectiveness of the closed-form expressions. Furthermore, the spatial correlation offers significant decreases in the outage probability as the direct channel is blocked.

Introducing the NEWHORIZON simulation: Galaxy properties with resolved internal dynamics across cosmic time

Abstract: Hydrodynamical cosmological simulations are increasing their level of realism by considering more physical processes and having greater resolution or larger statistics. However, usually either the statistical power of such simulations or the resolution reached within galaxies are sacrificed. Here, we introduce the NEWHORIZON project in which we simulate at high resolution a zoom-in region of ∼(16 Mpc)3 that is larger than a standard zoom-in region around a single halo and is embedded in a larger box. A resolution of up to 34 pc, which is typical of individual zoom-in, up-to-date resimulated halos, is reached within galaxies; this allows the simulation to capture the multi-phase nature of the interstellar medium and the clumpy nature of the star formation process in galaxies. In this introductory paper, we present several key fundamental properties of galaxies and their black holes, including the galaxy mass function, cosmic star formation rate, galactic metallicities, the Kennicutt–Schmidt relation, the stellar-to-halo mass relation, galaxy sizes, stellar kinematics and morphology, gas content within galaxies and its kinematics, and the black hole mass and spin properties over time. The various scaling relations are broadly reproduced by NEWHORIZON with some differences with the standard observables. Owing to its exquisite spatial resolution, NEWHORIZON captures the inefficient process of star formation in galaxies, which evolve over time from being more turbulent, gas rich, and star bursting at high redshift. These high-redshift galaxies are also more compact, and they are more elliptical and clumpier until the level of internal gas turbulence decays enough to allow for the formation of discs. The NEWHORIZON simulation gives access to a broad range of galaxy formation and evolution physics at low-to-intermediate stellar masses, which is a regime that will become accessible in the near future through surveys such as the LSST.

Management of antithrombotic therapy in patients undergoing transcatheter aortic valve implantation: a consensus document of the ESC Working Group on Thrombosis and the European Association of Percutaneous Cardiovascular Interventions (EAPCI), in collaboration with the ESC Council on Valvular Heart Disease.

Abstract: Transcatheter aortic valve implantation (TAVI) is effective in older patients with symptomatic severe aortic stenosis, while the indication has recently broadened to younger patients at lower risk. Although thromboembolic and bleeding complications after TAVI have decreased over time, such adverse events are still common. The recommendations of the latest 2017 ESC/EACTS Guidelines for the management of valvular heart disease on antithrombotic therapy in patients undergoing TAVI are mostly based on expert opinion. Based on recent studies and randomized controlled trials, this viewpoint document provides updated therapeutic insights in antithrombotic treatment during and after TAVI.

Cardiovascular disease and COVID-19: a consensus paper from the ESC Working Group on Coronary Pathophysiology & Microcirculation, ESC Working Group on Thrombosis and the Association for Acute CardioVascular Care (ACVC), in collaboration with the European Heart Rhythm Association (EHRA).

Abstract: The cardiovascular system is significantly affected in coronavirus disease-19 (COVID-19). Microvascular injury, endothelial dysfunction and thrombosis resulting from viral infection or indirectly related to the intense systemic inflammatory and immune responses are characteristic features of severe COVID-19. Pre-existing cardiovascular disease and viral load are linked to myocardial injury and worse outcomes. The vascular response to cytokine production and the interaction between SARS-CoV-2 and ACE2 receptor may lead to a significant reduction in cardiac contractility and subsequent myocardial dysfunction. In addition, a considerable proportion of patients who have been infected with SARS-CoV-2 do not fully recover and continue to experience a large number of symptoms and post-acute complications in the absence of a detectable viral infection. This conditions often referred to as "post-acute COVID-19" may have multiple causes. Viral reservoirs or lingering fragments of viral RNA or proteins contribute to the condition. Systemic inflammatory response to COVID-19 has the potential to increase myocardial fibrosis which in turn may impair cardiac remodelling. Here we summarize the current knowledge of cardiovascular injury and post-acute sequelae of COVID-19. As the pandemic continues and new variants emerge, we can advance our knowledge of the underlying mechanisms only by integrating our understanding of the pathophysiology with the corresponding clinical findings. Identification of new biomarkers of cardiovascular complications, and development of effective treatments for COVID-19 infection are of crucial importance.

The LOFAR Two-meter Sky Survey: Deep Fields Data Release 1 - II. The ELAIS-N1 LOFAR deep field

Abstract: The LOFAR Two-metre Sky Survey (LoTSS) will cover the full northern sky and, additionally, aims to observe the LoTSS deep fields to a noise level of ~10 microJy/bm over several tens of square degrees in areas that have the most extensive ancillary data. This paper presents the ELAIS-N1 deep field, the deepest of the LoTSS deep fields to date. With an effective observing time of 163.7 hours, it reaches a root mean square (RMS) noise level below 20 microJy/bm in the central region (and below 30 microJy/bm over 10 square degrees). The resolution is 6 arcsecs and 84862 radio sources were detected in the full area (68 sq. deg.) with 74127 sources in the highest quality area at less than 3 degrees from the pointing centre. The observation reaches a sky density of more than 5000 sources per sq. deg. in the central ~5 sq. deg. region. We present the calibration procedure, which addresses the special configuration of some observations and the extended bandwidth covered (115 to 177 MHz; central frequency 146.2 MHz) compared to standard LoTSS. We also describe the methods used to calibrate the flux density scale using cross-matching with sources detected by other radio surveys in the literature. We find the flux density uncertainty related to the flux density scale to be ~6.5%. By studying the variations of the flux density measurements between different epochs, we show that relative flux density calibration is reliable out to about a 3 degree radius, but that additional flux density uncertainty is present for all sources at about the 3 per cent level; this is likely to be associated with residual calibration errors, and is shown to be more significant in datasets with poorer ionosphere conditions. We also provide intra-band spectral indices, which can be useful to detect sources with unusual spectral properties. The final uncertainty in the flux densities is estimated to be ~10% for ELAIS-N1.

Gaia Early Data Release 3. Structure and properties of the Magellanic Clouds

Abstract: Context. This work is part of the Gaia Data Processing and Analysis Consortium papers published with the Gaia Early Data Release 3 (EDR3). It is one of the demonstration papers aiming to highlight the improvements and quality of the newly published data by applying them to a scientific case.Aims. We use the Gaia EDR3 data to study the structure and kinematics of the Magellanic Clouds. The large distance to the Clouds is a challenge for the Gaia astrometry. The Clouds lie at the very limits of the usability of the Gaia data, which makes the Clouds an excellent case study for evaluating the quality and properties of the Gaia data.Methods. The basis of our work are two samples selected to provide a representation as clean as possible of the stars of the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC). The selection used criteria based on position, parallax, and proper motions to remove foreground contamination from the Milky Way, and allowed the separation of the stars of both Clouds. From these two samples we defined a series of subsamples based on cuts in the colour-magnitude diagram; these subsamples were used to select stars in a common evolutionary phase and can also be used as approximate proxies of a selection by age.Results. We compared the Gaia Data Release 2 and Gaia EDR3 performances in the study of the Magellanic Clouds and show the clear improvements in precision and accuracy in the new release. We also show that the systematics still present in the data make the determination of the 3D geometry of the LMC a difficult endeavour; this is at the very limit of the usefulness of the Gaia EDR3 astrometry, but it may become feasible with the use of additional external data. We derive radial and tangential velocity maps and global profiles for the LMC for the several subsamples we defined. To our knowledge, this is the first time that the two planar components of the ordered and random motions are derived for multiple stellar evolutionary phases in a galactic disc outside the Milky Way, showing the differences between younger and older phases. We also analyse the spatial structure and motions in the central region, the bar, and the disc, providing new insightsinto features and kinematics. Finally, we show that the Gaia EDR3 data allows clearly resolving the Magellanic Bridge, and we trace the density and velocity flow of the stars from the SMC towards the LMC not only globally, but also separately for young and evolved populations. This allows us to confirm an evolved population in the Bridge that is slightly shift from the younger population. Additionally, we were able to study the outskirts of both Magellanic Clouds, in which we detected some well-known features and indications of new ones.

Thrombotic complications in 2928 patients with COVID-19 treated in intensive care: a systematic review.

Abstract: A prothrombotic state is reported with severe COVID-19 infection, which can manifest in venous and arterial thrombotic events. Coagulopathy is reflective of more severe disease and anticoagulant thromboprophylaxis is recommended in hospitalized patients. However, the prevalence of thrombosis on the intensive care unit (ICU) remains unclear, including whether this is sufficiently addressed by conventional anticoagulant thromboprophylaxis. We aimed to identify the rate of thrombotic complications in ICU-treated patients with COVID-19, to inform recommendations for diagnosis and management. A systematic review was conducted to assess the incidence of thrombotic complications in ICU-treated patients with COVID-19. Observational studies and registries reporting thrombotic complications in ICU-treated patients were included. Information extracted included patient demographics, use of thromboprophylaxis or anticoagulation, method of identifying thrombotic complications, and reported patient outcomes. In 28 studies including 2928 patients, thrombotic complications occurred in 34% of ICU-managed patients, with deep venous thrombosis reported in 16.1% and pulmonary embolism in 12.6% of patients, despite anticoagulant thromboprophylaxis, and were associated with high mortality. Studies adopting systematic screening for venous thrombosis with Duplex ultrasound reported a significantly higher incidence of venous thrombosis compared to those relying on clinical suspicion (56.3% vs. 11.0%, p < 0.001). Despite thromboprophylaxis, there is a very high incidence of thrombotic complications in patients with COVID-19 on the ICU. Systematic screening identifies many thrombotic complications that would be missed by relying on clinical suspicion and should be employed, with consideration given to increased dose anticoagulant thromboprophylaxis, whilst awaiting results of prospective trials of anticoagulation in this cohort.

Neural Bursting and Synchronization Emulated by Neural Networks and Circuits

Abstract: Nowadays, research, modeling, simulation and realization of brain-like systems to reproduce brain behaviors have become urgent requirements. In this paper, neural bursting and synchronization are imitated by modeling two neural network models based on the Hopfield neural network (HNN). The first neural network model consists of four neurons, which correspond to realizing neural bursting firings. Theoretical analysis and numerical simulation show that the simple neural network can generate abundant bursting dynamics including multiple periodic bursting firings with different spikes per burst, multiple coexisting bursting firings, as well as multiple chaotic bursting firings with different amplitudes. The second neural network model simulates neural synchronization using a coupling neural network composed of two above small neural networks. The synchronization dynamics of the coupling neural network is theoretically proved based on the Lyapunov stability theory. Extensive simulation results show that the coupling neural network can produce different types of synchronous behaviors dependent on synaptic coupling strength, such as anti-phase bursting synchronization, anti-phase spiking synchronization, and complete bursting synchronization. Finally, two neural network circuits are designed and implemented to show the effectiveness and potential of the constructed neural networks.

A better measure of relative prediction accuracy for model selection and model estimation

Abstract: Surveys show that the mean absolute percentage error (MAPE) is the most widely used measure of forecast accuracy in businesses and organizations. It is however, biased: When used to select among competing prediction methods it systematically selects those whose predictions are too low. This is not widely discussed and so is not generally known among practitioners. We explain why this happens. We investigate an alternative relative accuracy measure which avoids this bias: the log of the accuracy ratio: log (prediction / actual). Relative accuracy is particularly relevant if the scatter in the data grows as the value of the variable grows (heteroscedasticity). We demonstrate using simulations that for heteroscedastic data (modelled by a multiplicative error factor) the proposed metric is far superior to MAPE for model selection. Another use for accuracy measures is in fitting parameters to prediction models. Minimum MAPE models do not predict a simple statistic and so theoretical analysis is limited. We prove that when the proposed metric is used instead, the resulting least squares regression model predicts the geometric mean. This important property allows its theoretical properties to be understood.

A Comprehensive Phylogenomic Platform for Exploring the Angiosperm Tree of Life.

Abstract: © The Author(s) 2021. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/).