The Hector Galaxy Survey is a new optical integral field spectroscopy (IFS) survey currently using the Anglo-Australian Telescope to observe up to 15 000 galaxies at low redshift ($z \lt 0.1$). The Hector instrument employs 21 optical fibre bundles feeding into two double-beam spectrographs, AAOmega and the new Spector spectrograph, to enable wide-field multi-object IFS observations of galaxies. To efficiently process the survey data, we adopt the data reduction pipeline developed for the SAMI Galaxy Survey, with significant updates to accommodate Hector’s dual-spectrograph system. These enhancements address key differences in spectral resolution and other instrumental characteristics relative to SAMI and are specifically optimised for Hector’s unique configuration. We introduce a two-dimensional arc fitting approach that reduces the root-mean-square (RMS) velocity scatter by a factor of 1.2–3.4 compared to fitting arc lines independently for each fibre. The pipeline also incorporates detailed modelling of chromatic optical distortion in the wide-field corrector, to account for wavelength-dependent spatial shifts across the focal plane. We assess data quality through a series of validation tests, including wavelength solution accuracy (1.2–2.7 km s$^{-1}$ RMS), spectral resolution (FWHM of 1.2–1.4 Å for Spector), throughput characterisation, astrometric precision ($\lesssim$ 0.03 arcsec median offset), sky subtraction residuals (1–1.6% median continuum residual), and flux calibration stability (4% systematic offset when compared to Legacy Survey fluxes). We demonstrate that Hector delivers high-fidelity, science-ready datasets, supporting robust measurements of galaxy kinematics, stellar populations, and emission-line properties and provide examples. Additionally, we address systematic uncertainties identified during the data processing and propose future improvements to enhance the precision and reliability of upcoming data releases. This work establishes a robust data reduction framework for Hector, delivering high-quality data products that support a broad range of extragalactic studies.

A recent fluorescence of geophysical and archaeological research in Catholic cemeteries illustrates the benefits and challenges of community-engaged projects. Focusing on four ongoing case studies in coastal Virginia and Maryland (the Chesapeake region)—St. Mary’s Basilica (Norfolk, Virginia); Brent Cemetery (Stafford County, Virginia); Sacred Heart Church (Prince George’s County, Maryland); and St. Nicholas Cemetery (St. Mary’s County, Maryland)—this article explores a variety of archaeological strategies in the context of community engagement. These approaches are shaped by the physical characteristics of cemetery sites, the Catholic diocesan or church communities that oversee them, and the African American descendant communities affected by them. The built environment of cemeteries highlights the way that racism and segregation have shaped both the landscape and public memory of Catholic cemeteries in the Chesapeake region.

Background: Crisp Regional Hospital (CRH) in Georgia initiated a quality improvement project to address the excessive and inappropriate urine culture orders among inpatients. The project aimed to reduce these orders by at least 30% by June 2024, targeting the prevalent issues of increased healthcare costs and antibiotic misuse stemming from unnecessary testing. Methods: Using the Institute for Healthcare Improvement (IHI) framework, the project implemented a series of multidisciplinary strategies. These included nursing education on proper urine collection, policy updates to facilitate accurate specimen collection from specific patient groups, medical staff education on appropriateness of urine test ordering and a change in reflex criteria for urine testing. Data was analyzed using statistical process control and T-tests to assess the impact of the interventions. Results: The intervention led to a reduction in urine tests from 618 to 570. Tests reflexed to culture decreased significantly from 34.63% to 18.95% (p Conclusion: The quality improvement initiative at CRH significantly reduced unnecessary urine cultures, optimized resource use, and maintained diagnostic integrity. The interventions implemented were effective and scalable, demonstrating substantial cost savings and enhanced patient care quality. Further efforts will focus on analyzing the impact of removing pre-checked orders and implementing mandatory testing indications to continue improving urine testing practices.

We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.

Objectives/Goals: Aspiration causes or aggravates lung diseases. While bedside swallow evaluations are not sensitive/specific, gold standard tests for aspiration are invasive, uncomfortable, expose patients to radiation, and are resource intensive. We propose the development and validation of an AI model that analyzes voice to noninvasively predict aspiration. Methods/Study Population: Retrospectively recorded [i] phonations from 163 unique ENT patients were analyzed for acoustic features including jitter, shimmer, harmonic to noise ratio (HNR), etc. Patients were classified into three groups: aspirators (Penetration-Aspiration Scale, PAS 6–8), probable (PAS 3–5), and non-aspirators (PAS 1–2) based on video fluoroscopic swallow (VFSS) findings. Multivariate analysis evaluated patient demographics, history of head and neck surgery, radiation, neurological illness, obstructive sleep apnea, esophageal disease, body mass index, and vocal cord dysfunction. Supervised machine learning using five folds cross-validated neural additive network modelling (NAM) was performed on the phonations of aspirator versus non-aspirators. The model was then validated using an independent, external database. Results/Anticipated Results: Aspirators were found to have quantifiably worse quality of sound with higher jitter and shimmer but lower harmonics noise ratio. NAM modeling classified aspirators and non-aspirators as distinct groups (aspirator NAM risk score 0.528+0.2478 (mean + std) vs. non-aspirator (control) risk score of 0.252+0.241 (mean + std); p Discussion/Significance of Impact: We report the use of voice as a novel, noninvasive biomarker to detect aspiration risk using machine learning techniques. This tool has the potential to be used for the safe and early detection of aspiration in a variety of clinical settings including intensive care units, wards, outpatient clinics, and remote monitoring.

Processing and extracting actionable information, such as fault or anomaly indicators originating from vibration telemetry, is both challenging and critical for an accurate assessment of mechanical system health and subsequent predictive maintenance. In the setting of predictive maintenance for populations of similar assets, the knowledge gained from any single asset should be leveraged to provide improved predictions across the entire population. In this paper, a novel approach to population-level health monitoring is presented adopting a transfer learning approach. The new methodology is applied to monitor multiple rotating plant assets in a power generation scenario. The focus is on the detection of statistical anomalies as a means of identifying deviations from the typical operating regime from a time series of telemetry data. This is a challenging task because the machine is observed under different operating regimes. The proposed methodology can effectively transfer information across different assets, automatically identifying segments with common statistical characteristics and using them to enrich the training of the local supervised learning models. The proposed solution leads to a substantial reduction in mean square error relative to a baseline model.

Through compositional inclusion or exclusion, the photograph can assert and communicate what belongs in a picture, in a landscape, in an ecosystem. It can illuminate what we deem conservation-worthy, or, on a larger scale, which extinctions are attention-worthy. Photographic practice helps to illuminate the active nature of extinction, and our choices as actors and witnesses within that process. Here, researchers from the University of Leeds’ Extinction Studies Doctoral Training Programme present individual reflections on interdisciplinary practice-led research in the Scottish Small Isles. We consider how photography, as a form of praxis, can generate new forms of knowledge surrounding extinction: its meanings, representations, and legacies, particularly through visual representation. We offer seven perspectives on contemporary image-making, from disciplines including philosophy, conservation biology, literature, sociology, geology, cultural anthropology, and palaeontology. Researchers gathered experiential, ethical, even biological meanings from considering what to include or exclude in images: from the micro to the macro, the visible to the invisible, the aesthetic to the ecological. We draw conclusions around meaning-making through the process of photography itself, and the tensions encountered through framing and decision-making in a time of mass ecological decline.

Studies show that mental health promotion is an effective strategy that can reduce the burden of mental health disorders and improve overall well-being in both children and adults. In addition to promoting high levels of mental well-being and preventing the onset of mental illness, these mental health promotion programmes, including mental illness prevention interventions, help increase levels of mental health literacy in community members. While there is evidence showing the effectiveness of mental health promotion, much of what is known about this field is informed by studies conducted in high-income countries. There is a need to gather evidence about the effectiveness of such interventions in low- and middle-income countries (LMICs) where mental health services are often inadequate. In this systematic review, we synthesised the available published primary evidence from sub-Saharan Africa (SSA) on the types and effectiveness of mental health promotion programmes for young people. We performed a search of selected global databases (PubMed, PsycINFO, ScienceDirect and Google Scholar) and regional databases (Sabinet African Journals). We included observational, mixed methods, trials, pilots and quantitative original papers published from 2013 to 2023. We used the Mixed Methods Appraisal Tool (MMAT) to evaluate the quality of methods in selected studies, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA-2020) for reporting the evidence gathered. We identified 15 types of youth mental health promotion and illness prevention interventions. Among those identified, we found that school-based interventions enhanced mental health literacy, mental health-seeking behaviours and self-assurance and confidence among young people. Family-based interventions also showed a potential to improve relationships between young people and their caregivers. Future studies should explore how to further strengthen school- and family-based interventions that promote mental health among young people.

There is considerable interest in the role of neuroimmune processes in neuropsychiatric presentations among young people seeking mental health, neurological, paediatric and rheumatological services. The increasing availability of new immunotherapies, particularly monoclonal antibodies, introduces challenges in effectively and appropriately selecting candidates for immunotherapies. Neuroimmune-mediated neuropsychiatric syndromes (NIMNPS) typically include two broad types: i) ‘autoimmune encephalitis’, characterised by acute or subacute onset, neurological signs such as seizures, delirium or motor features and severe psychotic or major mood phenomena. Anti-N-methyl-D-aspartate receptor encephalitis was a pioneering clinical example, but various other autoantibodies have since been associated with this phenotype; and ii) atypical mood or psychotic syndromes with sub-acute or insidious onset, moderately severe atypical mood or psychotic symptoms, autonomic dysregulation, narcolepsy-like features, poor response to conventional treatments and adverse (notably motor) effects from psychotropic medications. Diagnosis of NIMNPS requires clinical or laboratory evidence of direct brain involvement, though autoantibodies are not always detectable. Given the broad and controversial diagnostic criteria for NIMNPS, we propose standardised clinical criteria for identifying ‘possible cases’, followed by laboratory, neuropsychological and brain imaging tests to confirm ‘probable’ cases suitable for immunotherapy. We emphasise rapid clinical and informed co-decision-making with young people and their families and loved ones. While immunotherapy holds promise for symptom alleviation, highly-personalised approaches and long-term management are essential. Future research should validate our proposed criteria, establish optimal, standardised yet personalised immunotherapy strategies that balance between clinical benefit and risks, and identify predictive markers of treatment response.

Migrants and refugees face elevated risks for mental health problems but have limited access to services. This study compared two strategies for training and supervising nonspecialists to deliver a scalable psychological intervention, Group Problem Management Plus (gPM+), in northern Colombia. Adult women who reported elevated psychological distress and functional impairment were randomized to receive gPM+ delivered by nonspecialists who received training and supervision by: 1) a psychologist (specialized technical support); or 2) a nonspecialist who had been trained as a trainer/supervisor (nonspecialized technical support). We examined effectiveness and implementation outcomes using a mixed-methods approach. Thirteen nonspecialists were trained as gPM+ facilitators and three were trained-as-trainers. We enrolled 128 women to participate in gPM+ across the two conditions. Intervention attendance was higher in the specialized technical support condition. The nonspecialized technical support condition demonstrated higher fidelity to gPM+ and lower cost of implementation. Other indicators of effectiveness, adoption and implementation were comparable between the two implementation strategies. These results suggest it is feasible to implement mental health interventions, like gPM+, using lower-resource, community-embedded task sharing models, while maintaining safety and fidelity. Further evidence from fully powered trials is needed to make definitive conclusions about the relative cost of these implementation strategies.

Accelerating COVID-19 Treatment Interventions and Vaccines (ACTIV) was initiated by the US government to rapidly develop and test vaccines and therapeutics against COVID-19 in 2020. The ACTIV Therapeutics-Clinical Working Group selected ACTIV trial teams and clinical networks to expeditiously develop and launch master protocols based on therapeutic targets and patient populations. The suite of clinical trials was designed to collectively inform therapeutic care for COVID-19 outpatient, inpatient, and intensive care populations globally. In this report, we highlight challenges, strategies, and solutions around clinical protocol development and regulatory approval to document our experience and propose plans for future similar healthcare emergencies.

In many regions of Canada, knowledge of the distribution of insect species is far from complete. This knowledge gap, known as the Wallacean Shortfall, is often manifest by species records separated by large, often remote areas with no records. Paradoxically, these difficult-to-access areas offer the best opportunity to study unaltered native community assemblages. Such gaps in knowledge are exemplified by ground beetles, a well-known group, yet with record gaps in many unstudied areas of Canada, including Akimiski Island, Nunavut. This postglacial rebound island, located in James Bay, has no permanently occupied human dwellings and almost no human-altered habitat. Using a combination of pitfall-malaise traps, pitfall traps, and hand captures during 2008–2014, we collected 1368 ground beetles (Coleoptera: Carabidae) as part of a larger biodiversity survey. We identified 31 species, 29 of which were first territorial records for Nunavut. Our results almost double the number of Carabidae known from Nunavut and extend the known range of eight other species. Seventeen of the species that we caught cannot fly, evidence for colonists arriving on Akimiski on floating debris. Our study fills substantial range gaps and serves as baseline information to detect future change.