Drainage flow over complex terrain

Model calculations even carried in order to simulate tracer release experiments at the Geysers Area. Comparisons with the experimental data provide a test of current ability to model pollutant transport. The calculations were carried out with a windfield code (ATMOS1) and an advection-diffusion code (ATMOS2). The resulting concentrations permit prediction of tracer particle collections at the measurement stations. Comparison of the observations and predictions of sequential and integrated counts shows generally good agreement, but with discrepancies in some instances. The method appears to be a useful one for pollutant transport predictions and for parametric studies

The KMOS Redshift One Spectroscopic Survey (KROSS): the Tully–Fisher relation at z ∼ 1

We present the stellar mass (M*), and K-corrected K-band absolute magnitude (MK) Tully–Fisher relations (TFRs) for subsamples of the 584 galaxies spatially resolved in H α emission by the KMOS Redshift One Spectroscopic Survey (KROSS). We model the velocity field of each of the KROSS galaxies and extract a rotation velocity, V80 at a radius equal to the major axis of an ellipse containing 80 per cent of the total integrated H α flux. The large sample size of KROSS allowed us to select 210 galaxies with well-measured rotation speeds. We extract from this sample a further 56 galaxies that are rotationally supported, using the stringent criterion V80/σ > 3, where σ is the flux weighted average velocity dispersion. We find the MK and M* TFRs for this subsample to be MK/mag=(−7.3±0.9)×[(log(V80/km s−1)−2.25]−23.4±0.2MK/mag=(−7.3±0.9)×[(log⁡(V80/km s−1)−2.25]−23.4±0.2, and log(M∗/M⊙)=(4.7±0.4)×[(log(V80/km s−1)−2.25]+10.0±0.3log⁡(M∗/M⊙)=(4.7±0.4)×[(log⁡(V80/km s−1)−2.25]+10.0±0.3, respectively. We find an evolution of the M* TFR zero-point of −0.41 ± 0.08 dex over the last ∼8 billion years. However, we measure no evolution in the MK TFR zero-point over the same period. We conclude that rotationally supported galaxies of a given dynamical mass had less stellar mass at z ∼ 1 than the present day, yet emitted the same amounts of K-band light. The ability of KROSS to differentiate, using integral field spectroscopy with KMOS, between those galaxies that are rotationally supported and those that are not explains why our findings are at odds with previous studies without the same capabilities

Time-dependent optical spectroscopy of GRB 010222: Clues to the gamma-ray burst environment

We present sequential optical spectra of the afterglow of GRB 010222 obtained 1 day apart using the Low-Resolution Imaging Spectrometer (LRIS) and the Echellette Spectrograph and Imager (ESI) on the Keck Telescopes. Three low-ionization absorption systems are spectroscopically identified at z 1 = 1.47688, z2 = 1.15628, and z3 = 0.92747. The higher resolution ESI spectrum reveals two distinct components in the highest redshift system at z1a = 1.47590 and z1b = 1.47688. We interpret the z1b = 1.47688 system as an absorption feature of the disk of the host galaxy of GRB 010222. The best-fitted power-law optical continuum and [Zn/Cr] ratio imply low dust content or a local gray dust component near the burst site. In addition, we do not detect strong signatures of vibrationally excited states of H2. If the gamma-ray burst took place in a superbubble or young stellar cluster, there are no outstanding signatures of an ionized absorber either. Analysis of the spectral time dependence at low resolution shows no significant evidence for absorption-line variability. This lack of variability is confronted with time-dependent photoionization simulations designed to apply the observed flux from GRB 010222 to a variety of assumed atomic gas densities and cloud radii. The absence of time dependence in the absorption lines implies that high-density environments are disfavored. In particular, if the GRB environment was dust free, its density was unlikely to exceed nH I = 102 cm -3. If depletion of metals onto dust is similar to Galactic values or less than solar abundances are present, then nH I ≥ 2 × 104 cm-3 is probably ruled out in the immediate vicinity of the burst

The KMOS Redshift One Spectroscopic Survey (KROSS): The origin of disc turbulence in z≈1 star-forming galaxies

We analyse the velocity dispersion properties of 472 z~0.9 star-forming galaxies observed as part of the KMOS Redshift One Spectroscopic Survey (KROSS). The majority of this sample is rotationally dominated (83 ± 5 per cent with vC/σ0 > 1) but also dynamically hot and highly turbulent. After correcting for beam smearing effects, the median intrinsic velocity dispersion for the final sample is σ0 =43.2 ± 0.8 kms-1 with a rotational velocity to dispersion ratio of vC/σ0 =2.6 ± 0.1. To explore the relationship between velocity dispersion, stellar mass, star formation rate, and redshift, we combine KROSS with data from the SAMI survey (z~0.05) and an intermediate redshift MUSE sample (z~0.5). Whilst there is, at most, a weak trend between velocity dispersion and stellar mass, at fixed mass there is a strong increase with redshift. At all redshifts, galaxies appear to follow the same weak trend of increasing velocity dispersion with star formation rate. Our results are consistent with an evolution of galaxy dynamics driven by discs that are more gas rich, and increasingly gravitationally unstable, as a function of increasing redshift. Finally, we test two analytic models that predict turbulence is driven by either gravitational instabilities or stellar feedback. Both provide an adequate description of the data, and further observations are required to rule out either model

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Readout technologies for directional WIMP Dark Matter detection

The measurement of the direction of WIMP-induced nuclear recoils is a compelling but technologically challenging strategy to provide an unambiguous signature of the detection of Galactic dark matter. Most directional detectors aim to reconstruct the dark-matter-induced nuclear recoil tracks, either in gas or solid targets. The main challenge with directional detection is the need for high spatial resolution over large volumes, which puts strong requirements on the readout technologies. In this paper we review the various detector readout technologies used by directional detectors. In particular, we summarize the challenges, advantages and drawbacks of each approach, and discuss future prospects for these technologies

Long COVID and cardiovascular disease: a prospective cohort study

Background Pre-existing cardiovascular disease (CVD) or cardiovascular risk factors have been associated with an increased risk of complications following hospitalisation with COVID-19, but their impact on the rate of recovery following discharge is not known. Objectives To determine whether the rate of patient-perceived recovery following hospitalisation with COVID-19 was affected by the presence of CVD or cardiovascular risk factors. Methods In a multicentre prospective cohort study, patients were recruited following discharge from the hospital with COVID-19 undertaking two comprehensive assessments at 5 months and 12 months. Patients were stratified by the presence of either CVD or cardiovascular risk factors prior to hospitalisation with COVID-19 and compared with controls with neither. Full recovery was determined by the response to a patient-perceived evaluation of full recovery from COVID-19 in the context of physical, physiological and cognitive determinants of health. Results From a total population of 2545 patients (38.8% women), 472 (18.5%) and 1355 (53.2%) had CVD or cardiovascular risk factors, respectively. Compared with controls (n=718), patients with CVD and cardiovascular risk factors were older and more likely to have had severe COVID-19. Full recovery was significantly lower at 12 months in patients with CVD (adjusted OR (aOR) 0.62, 95% CI 0.43 to 0.89) and cardiovascular risk factors (aOR 0.66, 95% CI 0.50 to 0.86). Conclusion Patients with CVD or cardiovascular risk factors had a delayed recovery at 12 months following hospitalisation with COVID-19. Targeted interventions to reduce the impact of COVID-19 in patients with cardiovascular disease remain an unmet need

Cognitive and psychiatric symptom trajectories 2–3 years after hospital admission for COVID-19: a longitudinal, prospective cohort study in the UK

Background COVID-19 is known to be associated with increased risks of cognitive and psychiatric outcomes after the acute phase of disease. We aimed to assess whether these symptoms can emerge or persist more than 1 year after hospitalisation for COVID-19, to identify which early aspects of COVID-19 illness predict longer-term symptoms, and to establish how these symptoms relate to occupational functioning. Methods The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study of adults (aged ≥18 years) who were hospitalised with a clinical diagnosis of COVID-19 at participating National Health Service hospitals across the UK. In the C-Fog study, a subset of PHOSP-COVID participants who consented to be recontacted for other research were invited to complete a computerised cognitive assessment and clinical scales between 2 years and 3 years after hospital admission. Participants completed eight cognitive tasks, covering eight cognitive domains, from the Cognitron battery, in addition to the 9-item Patient Health Questionnaire for depression, the Generalised Anxiety Disorder 7-item scale, the Functional Assessment of Chronic Illness Therapy Fatigue Scale, and the 20-item Cognitive Change Index (CCI-20) questionnaire to assess subjective cognitive decline. We evaluated how the absolute risks of symptoms evolved between follow-ups at 6 months, 12 months, and 2–3 years, and whether symptoms at 2–3 years were predicted by earlier aspects of COVID-19 illness. Participants completed an occupation change questionnaire to establish whether their occupation or working status had changed and, if so, why. We assessed which symptoms at 2–3 years were associated with occupation change. People with lived experience were involved in the study. Findings 2469 PHOSP-COVID participants were invited to participate in the C-Fog study, and 475 participants (191 [40·2%] females and 284 [59·8%] males; mean age 58·26 [SD 11·13] years) who were discharged from one of 83 hospitals provided data at the 2–3-year follow-up. Participants had worse cognitive scores than would be expected on the basis of their sociodemographic characteristics across all cognitive domains tested (average score 0·71 SD below the mean [IQR 0·16–1·04]; p<0·0001). Most participants reported at least mild depression (263 [74·5%] of 353), anxiety (189 [53·5%] of 353), fatigue (220 [62·3%] of 353), or subjective cognitive decline (184 [52·1%] of 353), and more than a fifth reported severe depression (79 [22·4%] of 353), fatigue (87 [24·6%] of 353), or subjective cognitive decline (88 [24·9%] of 353). Depression, anxiety, and fatigue were worse at 2–3 years than at 6 months or 12 months, with evidence of both worsening of existing symptoms and emergence of new symptoms. Symptoms at 2–3 years were not predicted by the severity of acute COVID-19 illness, but were strongly predicted by the degree of recovery at 6 months (explaining 35·0–48·8% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); by a biocognitive profile linking acutely raised D-dimer relative to C-reactive protein with subjective cognitive deficits at 6 months (explaining 7·0–17·2% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); and by anxiety, depression, fatigue, and subjective cognitive deficit at 6 months. Objective cognitive deficits at 2–3 years were not predicted by any of the factors tested, except for cognitive deficits at 6 months, explaining 10·6% of their variance. 95 of 353 participants (26·9% [95% CI 22·6–31·8]) reported occupational change, with poor health being the most common reason for this change. Occupation change was strongly and specifically associated with objective cognitive deficits (odds ratio [OR] 1·51 [95% CI 1·04–2·22] for every SD decrease in overall cognitive score) and subjective cognitive decline (OR 1·54 [1·21–1·98] for every point increase in CCI-20). Interpretation Psychiatric and cognitive symptoms appear to increase over the first 2–3 years post-hospitalisation due to both worsening of symptoms already present at 6 months and emergence of new symptoms. New symptoms occur mostly in people with other symptoms already present at 6 months. Early identification and management of symptoms might therefore be an effective strategy to prevent later onset of a complex syndrome. Occupation change is common and associated mainly with objective and subjective cognitive deficits. Interventions to promote cognitive recovery or to prevent cognitive decline are therefore needed to limit the functional and economic impacts of COVID-19. Funding National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Wolfson Foundation, MQ Mental Health Research, MRC-UK Research and Innovation, and National Institute for Health and Care Research

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification. Funding: UK Research and Innovation and National Institute for Health Research

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain–gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials