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

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