We present a pilot study of the z = 2.923 radio galaxy MRC0943-242, where we combine information from ALMA and MUSE data cubes for the first time. Even with modest integration times, we disentangle ...the AGN and starburst dominated components. These data reveal a highly complex morphology as the AGN, starburst, and molecular gas components show up as widely separated sources in dust continuum, optical continuum, and CO line emission observations. CO(1−0) and CO(8−7) line emission suggest that there is a molecular gas reservoir offset from both the dust and the optical continuum that is located ~90 kpc from the AGN. The UV line emission has a complex structure in emission and absorption. The line emission is mostly due to a large scale ionisation cone energised by the AGN, and a Lyα emitting bridge of gas between the radio galaxy and a heavily star-forming set of components. Strangely, the ionisation cone has no Lyα emission. We find this is due to an optically thick layer of neutral gas with unity covering fraction spread out over a region of at least ~100 kpc from the AGN. Other less thick absorption components are associated with Lyα emitting gas within a few tens of kpc from the radio galaxy and are connected by a bridge of emission. We speculate that this linear structure of dust, Lyα and CO emission, and the redshifted absorption seen in the circum nuclear region may represent an accretion flow feeding gas into this massive AGN host galaxy.
The relevance of regional lymph node (LN) assessment to quantify the metastatic spread of cancer is well recognized in veterinary oncology. Evaluation of LNs is critical for tumour staging. However, ...sampling the correct LN may not be possible without sentinel lymph node (SLN) mapping. Methods for diagnostic imaging and intraoperative detection of SLNs are well established in human medicine, in particular, the combination of lymphoscintigraphy and intraoperative application of blue dyes. Nevertheless, alternative imaging techniques are available and have gained increasing interest. Successful implementation of these techniques in dogs have been reported in both clinical and experimental studies. This review aims to provide an overview of SLN mapping techniques in human and veterinary medicine.
•Uses multi-objective optimization and Pareto optimality to monitor geologic carbon storage sites.•Incorporates user-supplied weighting criteria to prioritize detection of the most critical leakage ...scenarios.•Uses lightweight, efficient software design to run on a typical laptop or workstation.
Designs for Risk Evaluation and Management (DREAM) is a tool developed under the National Risk Assessment Partnership (NRAP) to enhance geologic carbon storage safety and efficiency. Using potential leakage scenarios generated externally by the users preferred history-matching approach, DREAM constructs ideal combinations of sensor locations in the right place at the right time to detect as many leaks as possible, detect them as early as possible, and minimize cost. This user-friendly tool, developed in Java, features a window-based GUI for input and a 3D visualization tool for viewing the domain space and optimized monitoring plans. DREAM's latest version accommodates real-world usage by allowing for joint optimization of wellbore point sensor placements and surface geophysics survey geometries, and by using more efficient multi-objective optimization algorithms. In an example shown here, these two improvements combined allow us to support containment assurance and go from detecting 80–90 % of the potential CO2 leakage to +99.7 %, a step-change improvement that can make the deciding difference in whether a site is suitable for geologic carbon storage. Though developed for geologic carbon storage, this tool would be equally applicable in many surface or offshore environmental monitoring projects.
Surgical decision-making after SARS-CoV-2 infection is influenced by the presence of comorbidity, infection severity and whether the surgical problem is time-sensitive. Contemporary surgical policy ...to delay surgery is informed by highly heterogeneous country-specific guidance. We evaluated surgical provision in England during the COVID-19 pandemic to assess real-world practice and whether deferral remains necessary. Using the OpenSAFELY platform, we adapted the COVIDSurg protocol for a service evaluation of surgical procedures that took place within the English NHS from 17 March 2018 to 17 March 2022. We assessed whether hospitals adhered to guidance not to operate on patients within 7 weeks of an indication of SARS-CoV-2 infection. Additional outcomes were postoperative all-cause mortality (30 days, 6 months) and complications (pulmonary, cardiac, cerebrovascular). The exposure was the interval between the most recent indication of SARS-CoV-2 infection and subsequent surgery. In any 6-month window, < 3% of surgical procedures were conducted within 7 weeks of an indication of SARS-CoV-2 infection. Mortality for surgery conducted within 2 weeks of a positive test in the era since widespread SARS-CoV-2 vaccine availability was 1.1%, declining to 0.3% by 4 weeks. Compared with the COVIDSurg study cohort, outcomes for patients in the English NHS cohort were better during the COVIDSurg data collection period and the pandemic era before vaccines became available. Clinicians within the English NHS followed national guidance by operating on very few patients within 7 weeks of a positive indication of SARS-CoV-2 infection. In England, surgical patients' overall risk following an indication of SARS-CoV-2 infection is lower than previously thought.
The SECURE project investigates the design of security mechanisms for pervasive computing based on trust. It addresses how entities in unfamiliar pervasive computing environments can overcome initial ...suspicion to provide secure collaboration.
Environmental and geographical variables are known drivers of community assembly, however their influence on phylogenetic structure and phylogenetic beta diversity of lineages within different ...bioregions is not well-understood. Using Neotropical palms as a model, we investigate how environmental and geographical variables affect the assembly of lineages into bioregions across an evolutionary time scale. We also determine lineage shifts between tropical (TRF) and non-tropical (non-TRF) forests. Our results identify that distance and area explain phylogenetic dissimilarity among bioregions. Lineages in smaller bioregions are a subset of larger bioregions and contribute significantly to the nestedness component of phylogenetic dissimilarity, here interpreted as evidence for a bioregional shift. We found a significant tendency of habitat shifts occurring preferentially between TRF and non-TRF bioregions (31 shifts) than from non-TRF to TRF (24) or from TRF to TRF (11) and non-TRF to non-TRF (9). Our results also present cases where low dissimilarity is found between TRF and non-TRF bioregions. Most bioregions showed phylogenetic clustering and larger bioregions tended to be more clustered than smaller ones, with a higher species turnover component of phylogenetic dissimilarity. However, phylogenetic structure did not differ between TRF and non-TRF bioregions and diversification rates were higher in only two lineages, Attaleinae and Bactridinae, which are widespread and overabundant in both TRF and non-TRF bioregions. Area and distance significantly affected Neotropical palm community assembly and contributed more than environmental variables. Despite palms being emblematic humid forest elements, we found multiple shifts from humid to dry bioregions, showing that palms are also important components of these environments.
Individuals with autism spectrum disorder (ASD) reportedly possess preserved or superior music-processing skills compared to their typically developing counterparts. We examined auditory imagery and ...earworms (tunes that get “stuck” in the head) in adults with ASD and controls. Both groups completed a short earworm questionnaire together with the Bucknell Auditory Imagery Scale. Results showed poorer auditory imagery in the ASD group for all types of auditory imagery. However, the ASD group did not report fewer earworms than matched controls. These data suggest a possible basis in poor auditory imagery for poor prosody in ASD, but also highlight a separability between auditory imagery and control of musical memories. The separability is present in the ASD group but not in typically developing individuals.
Background:
Severe social withdrawal behaviors among young people have been a subject of public and clinical concerns.
Aims:
This study aimed to explore the prevalence of social withdrawal behaviors ...among young people aged 12–29 years in Hong Kong.
Methods:
A cross-sectional telephone-based survey was conducted with 1,010 young individuals. Social withdrawal behaviors were measured with the proposed research diagnostic criteria for hikikomori and were categorized according to the (a) international proposed duration criterion (more than 6 months), (b) local proposed criterion (less than 6 months) and (c) with withdrawal behaviors but self-perceived as non-problematic. The correlates of social withdrawal among the three groups were examined using multinomial and ordinal logistic regression analyses.
Results:
The prevalence rates of more than 6 months, less than 6 months and self-perceived non-problematic social withdrawal were 1.9%, 2.5% and 2.6%, respectively. In terms of the correlates, the internationally and locally defined socially withdrawn youths are similar, while the self-perceived non-problematic group is comparable to the comparison group.
Conclusions:
The study finds that the prevalence of severe social withdrawal in Hong Kong is comparable to that in Japan. Both groups with withdrawal behaviors for more or less than 6 months share similar characteristics and are related to other contemporary youth issues, for example, compensated dating and self-injury behavior. The self-perceived non-problematic group appears to be a distinct group and the withdrawal behaviors of its members may be discretionary.
In comparative studies, the advantage of increased sample sizes might be outweighed by detrimental effects on sample homogeneity and comparability when small numbers of hosts from a different ...demographic of the same species are included in samples. A mixed sample of sunfishes (Lepomis spp.) was subdivided in different ways and examined using cumulative performance curves to determine whether the exclusion of larger hosts from a single-species sample and/or the inclusion of hosts of the same size demographic from closely related host species would produce more homogeneous samples. The exclusion of larger hosts from the single-species samples tended to reduce the aggregation of the infrapopulation samples, and mixed-species samples of smaller fishes tended to have lower degrees of aggregation for a given sample size relative to the single-species sample. Cumulative performance curves for diversity and richness, in concert with nonmetric multidimensional scaling of the infracommunities, demonstrated sunfish size to be a more reliable determinant of infracommunity similarity than sunfish species in this particular sample. The results demonstrate that cumulative aggregation curves can be an effective tool for delineating homogeneous and comparable subsamples and that, under some circumstances, it is possible to offset the smaller sample sizes that result from the exclusion of older/larger hosts by the addition of congeneric or confamilial hosts within the same size/age classes as the stratified sample.
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•Environmental heterogeneity is a large source of soil carbon variability.•Strategic feature selection is used to identify critical, regional-scale relationships.•Precipitation, ...nitrogen, and soil moisture have the strongest association with topsoil C.•Parent material and elevation have the strongest association with subsoil C.•Approximately 2.6 Pg C are stored in the upper 1 m of production forestland soil.
The pedosphere is the largest terrestrial reservoir of organic carbon, yet soil-carbon variability and its representation in Earth system models is a large source of uncertainty for carbon-cycle science and climate projections. Much of this uncertainty is attributed to local and regional-scale variability, and predicting this variation can be challenging if variable selection is based solely on a priori assumptions due to the scale-dependent nature of environmental determinants. Data mining can optimize predictive modeling by allowing machine-learning algorithms to learn from and discover complex patterns in large datasets that may have otherwise gone unnoticed, thus increasing the potential for knowledge discovery. In this analysis, we identify important, regional-scale determinants for top- and subsoil-carbon stabilization in production forestland across the southeastern US. Specifically, we apply recursive feature elimination to a large suite of socio-environmental data to strategically select a parsimonious, yet highly predictive covariate set. This is achieved by recursively considering smaller and smaller covariate sets—or features—by first training the estimator on the full set to obtain feature importance. The least important features are pruned, and the procedure is recursively repeated until a desired number of covariates is identified. We show that although carbon ranges from 0.3 to 8.2 kg m−2 in the topsoil (0 to 20 cm), and from 0.4 to 17.6 kg m−2 in the subsoil (20 to 100 cm), this variability is predictably distributed with precipitation, soil moisture, nitrogen and sand content, gamma ray emissions, mean annual minimum temperature, and elevation. From our spatial predictions, we estimate that 2.6 Pg of soil carbon is currently stabilized in the upper 100 cm of production forestland, which covers 34.7 million ha in the southeastern US.
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