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Two flat-spectrum radio sources in the Milky Way globular cluster M22 are thought to be accreting stellar-mass black holes; the identification of two black holes in one cluster shows that the ejection of black holes from clusters is not as efficient as predicted by most models. One cluster, but two black holes The current consensus is that a typical globular star cluster can accommodate just one stellar-mass black hole. Many more will be created, but all but one will be ejected following dynamical interactions. New observations of the Milky Way globular cluster M22, however, reveal the presence of two radio sources in one cluster, with properties typical of accreting black holes each more than ten times the mass of the Sun. This suggests that the ejection of black holes is not as efficient as predicted by most models. And it may not stop there: the authors speculate that there could be a population of tens of black holes in M22, either as single black holes or in binaries where there is no mass transfer taking place. Hundreds of stellar-mass black holes probably form in a typical globular star cluster, with all but one predicted to be ejected through dynamical interactions 1 , 2 , 3 . Some observational support for this idea is provided by the lack of X-ray-emitting binary stars comprising one black hole and one other star (‘black-hole/X-ray binaries’) in Milky Way globular clusters, even though many neutron-star/X-ray binaries are known 4 . Although a few black holes have been seen in globular clusters around other galaxies 5 , 6 , the masses of these cannot be determined, and some may be intermediate-mass black holes that form through exotic mechanisms 7 . Here we report the presence of two flat-spectrum radio sources in the Milky Way globular cluster M22, and we argue that these objects are black holes of stellar mass (each ∼10–20 times more massive than the Sun) that are accreting matter. We find a high ratio of radio-to-X-ray flux for these black holes, consistent with the larger predicted masses of black holes in globular clusters compared to those outside 8 . The identification of two black holes in one cluster shows that ejection of black holes is not as efficient as predicted by most models 1 , 2 , 4 , and we argue that M22 may contain a total population of ∼5–100 black holes. The large core radius of M22 could arise from heating produced by the black holes 9 .

Collapse of hydrothermally weakened rock on the flanks of volcanic islands is a recognized cause of tsunamis generated by volcanoes. Here we use a multiphysics clustering method to derive a volcanic facies model for Whakaari/White Island, an andesite arc volcanic island in New Zealand. Through probabilistic inversion of magnetic and gravity data, combined with airborne electromagnetic data inversion we derive density, susceptibility, resistivity and saturation models of the island. Petrophysical relationships between density, P‐wave velocity and mean effective stress extends the range of physical properties mapped. A clustering algorithm identifies four clusters, that is facies, related to rock volumes characterized by varying degrees of hydrothermal alteration and saturation that occupy specific spatial locations in the edifice. Two volumes of rock (0.05–0.1 km3) in the west and north of the island, with contrasting facies properties are identified as the most hydrothermally altered or fractured parts of the island. Saturation models derived from resistivity models show the upper flanks are at low saturation, reducing their likelihood of failure. The submerged flanks become progressively more saturated with depth, in line with existing models of the hydrothermal system that show significant seawater input. The gravity and magnetic models delineate subcrater boundaries and highlight regions with different styles of alteration, including pore filling that increases rock density, and rock dissolution that decreases density. The model identifies new areas of potential slope instability, context for interpreting volcano monitoring data and quantified rock volumes for generation of scenarios which simulate tsunamis caused by volcanic landslides.

Recent studies suggest that most cases of myelodysplastic syndrome (MDS) are clonally heterogeneous, with a founding clone and multiple subclones. It is not known whether specific gene mutations typically occur in founding clones or subclones. We screened a panel of 94 candidate genes in a cohort of 157 patients with MDS or secondary acute myeloid leukemia (sAML). This included 150 cases with samples obtained at MDS diagnosis and 15 cases with samples obtained at sAML transformation (8 were also analyzed at the MDS stage). We performed whole-genome sequencing (WGS) to define the clonal architecture in eight sAML genomes and identified the range of variant allele frequencies (VAFs) for founding clone mutations. At least one mutation or cytogenetic abnormality was detected in 83% of the 150 MDS patients and 17 genes were significantly mutated (false discovery rate ⩽0.05). Individual genes and patient samples displayed a wide range of VAFs for recurrently mutated genes, indicating that no single gene is exclusively mutated in the founding clone. The VAFs of recurrently mutated genes did not fully recapitulate the clonal architecture defined by WGS, suggesting that comprehensive sequencing may be required to accurately assess the clonal status of recurrently mutated genes in MDS.

Powerful relativistic jets are one of the main ways in which accreting black holes provide kinetic feedback to their surroundings. Jets launched from or redirected by the accretion flow that powers them are expected to be affected by the dynamics of the flow, which for accreting stellar-mass black holes has shown evidence for precession 1 due to frame-dragging effects that occur when the black-hole spin axis is misaligned with the orbital plane of its companion star 2 . Recently, theoretical simulations have suggested that the jets can exert an additional torque on the accretion flow 3 , although the interplay between the dynamics of the accretion flow and the launching of the jets is not yet understood. Here we report a rapidly changing jet orientation—on a time scale of minutes to hours—in the black-hole X-ray binary V404 Cygni, detected with very-long-baseline interferometry during the peak of its 2015 outburst. We show that this changing jet orientation can be modelled as the Lense–Thirring precession of a vertically extended slim disk that arises from the super-Eddington accretion rate 4 . Our findings suggest that the dynamics of the precessing inner accretion disk could play a role in either directly launching or redirecting the jets within the inner few hundred gravitational radii. Similar dynamics should be expected in any strongly accreting black hole whose spin is misaligned with the inflowing gas, both affecting the observational characteristics of the jets and distributing the black-hole feedback more uniformly over the surrounding environment 5 , 6 . The relativistic jets associated with the black-hole X-ray binary system V404 Cygni change their orientation on time scales of minutes to hours, implying that the direction of the jets is being affected by the dynamics of the surrounding accretion flow that powers them.

Northern and tropical peatlands represent a globally significant carbon reserve accumulated over thousands of years of waterlogged conditions. It is unclear whether moderate drying predicted for northern peatlands will stimulate burning and carbon losses as has occurred in their smaller tropical counterparts where the carbon legacy has been destabilized due to severe drainage and deep peat fires. Capitalizing on a unique long-term experiment, we quantify the post-wildfire recovery of a northern peatland subjected to decadal drainage. We show that the moderate drop in water table position predicted for most northern regions triggers a shift in vegetation composition previously observed within only severely disturbed tropical peatlands. The combined impact of moderate drainage followed by wildfire converted the low productivity, moss-dominated peatland to a non-carbon accumulating shrub-grass ecosystem. This new ecosystem is likely to experience a low intensity, high frequency wildfire regime, which will further deplete the legacy of stored peat carbon.

Background Heart failure (HF) is frequently diagnosed during hospital admission, often after symptoms have been present for some time. Those diagnosed in hospital typically experience higher mortality reflecting not only possible diagnostic delay but also greater illness severity at presentation. The reasons behind delayed HF diagnosis are multifaceted and complex. This study aimed to achieve consensus on a priority list of patient, clinical, and service-level factors associated with delayed HF diagnosis, and to identify indicators that could support earlier detection of undiagnosed HF in primary care. Methods A three-round modified e-Delphi process involved patients and clinicians from primary and specialist care. Participants rated sociodemographic and clinical factors for their importance in delayed HF diagnosis and clinicians also rated service-level factors and identified indicators of undiagnosed HF. Consensus was defined as two-thirds agreement with stable opinions across rounds (McNemar p  ≥ 0.05). Indicators of undiagnosed HF required additional ranking in the top 5 by > 50% of clinicians. Results The first survey was completed by 18 patients (67% women, median age 61) and 27 clinicians (67% nurses/allied health professionals, 33% doctors). Consensus was achieved, comprising 15 factors and 5 indicators. Key sociodemographic factors were patients lacking HF knowledge, lack of access to GP/cardiologist appointments, symptom confusion, younger age (< 50), and learning difficulties. Clinical factors included multimorbidity, respiratory/mental health conditions, obesity, and depression. Service-level factors included poor HF knowledge, limited N-terminal pro–B-type Natriuretic Peptide (NT-proBNP) testing and echocardiogram access in primary care, and fragmented care. The top 5 indicators of undiagnosed HF included elevated NT-proBNP without referral, loop diuretic use, and overlapping cardiac and respiratory histories. Conclusions This study identifies critical factors and indicators that can aid earlier HF diagnosis in primary care. These indicators could be embedded into electronic health record–based alerts and used to support decision-making in primary care.

Emissions of sulfur trioxide (SO 3 ) are a key component of plume opacity and acid deposition. Consequently, these emissions need to be low enough to not cause opacity violations and acid deposition. Generally, a small fraction of sulfur (S) in coal is converted to SO 3 in coal-fired combustion devices such as electric utility boilers. The emissions of SO 3 from such a boiler depend on coal S content, combustion conditions, flue gas characteristics, and air pollution devices being used. It is well known that the catalyst used in the selective catalytic reduction (SCR) technology for nitrogen oxides control oxidizes a small fraction of sulfur dioxide in the flue gas to SO 3 . The extent of this oxidation depends on the catalyst formulation and SCR operating conditions. Gas-phase SO 3 and sulfuric acid, on being quenched in plant equipment (e.g., air preheater and wet scrubber), result in fine acidic mist, which can cause increased plume opacity and undesirable emissions. Recently, such effects have been observed at plants firing high-S coal and equipped with SCR systems and wet scrubbers. This paper investigates the factors that affect acidic mist production in coal-fired electric utility boilers and discusses approaches for mitigating emission of this mist.

The tidal disruption of a star by a supermassive black hole leads to a short-lived thermal flare. Despite extensive searches, radio follow-up observations of known thermal stellar tidal disruption flares (TDFs) have not yet produced a conclusive detection. We present a detection of variable radio emission from a thermal TDF, which we interpret as originating from a newly launched jet. The multiwavelength properties of the source present a natural analogy with accretion-state changes of stellar mass black holes, which suggests that all TDFs could be accompanied by a jet. In the rest frame of the TDF, our radio observations are an order of magnitude more sensitive than nearly all previous upper limits, explaining how these jets, if common, could thus far have escaped detection.

The associations with weather and bathing water quality on infectious intestinal disease (IID) were investigated using data from two Scottish NHS Board areas. Monthly counts of viral and non-viral gastrointestinal infections were modelled as a smooth function of temperature, relative humidity and average monthly counts of faecal indicator organisms, respectively, adjusting for season and long-term trend effects. Strong seasonal patterns were observed for each group of pathogens. Peak viral gastrointestinal infection was in May while that of non-viral gastrointestinal infections was in July. A statistically significant negative association existed between weather (temperature and humidity) and viral infection. Average levels of non-viral gastrointestinal infections increased as temperature and relative humidity increased. Increasing levels of faecal indicator organisms in bathing waters were also associated with an increase in the average number of viral and non-viral gastrointestinal infections at the ecological level. Future climate change and prolonged precipitation events may result in increasing levels of faecal indicator organisms in bathing waters leading to likely increases in IIDs.

Incorporating spatial covariance into clustering has previously been considered for functional data to identify groups of functions which are similar across space. However, in the majority of situations that have been considered until now the most appropriate metric has been Euclidean distance. Directed networks present additional challenges in terms of estimating spatial covariance due to their complex structure. Although suitable river network covariance models have been proposed for use with stream distance, where distance is computed along the stream network, these models have not been extended for contexts where the data are functional, as is often the case with environmental data. The paper develops a method of calculating spatial covariance between functions from sites along a river network and applies the measure as a weight within functional hierarchical clustering. Levels of nitrate pollution on the River Tweed in Scotland are considered with the aim of identifying groups of monitoring stations which display similar spatiotemporal characteristics.