Physical Conditions of Accreting Gas in T Tauri Star Systems

We present results from a low resolution (R~300) near-infrared spectroscopic variability survey of actively accreting T Tauri stars (TTS) in the Taurus-Auriga star forming region. Paschen and Brackett series H I recombination lines were detected in 73 spectra of 15 classical T Tauri systems. The values of the Pan/PaB, Brn/BrG, and BrG/Pan H I line ratios for all observations exhibit a scatter of < 20% about the weighted mean, not only from source to source, but also for epoch-to-epoch variations in the same source. A representative or `global' value was determined for each ratio in both the Paschen and Brackett series as well as the BrG/Pan line ratios. A comparison of observed line ratio values was made to those predicted by the temperature and electron density dependent models of Case B hydrogen recombination line theory. The measured line ratios are statistically well-fit by a tightly constrained range of temperatures (T < 2000 K) and electron densities 1e9 < n_e < 1e10 cm^-3. A comparison of the observed line ratio values to the values predicted by the optically thick and thin local thermodynamic equilibrium cases rules out these conditions for the emitting H I gas. Therefore, the emission is consistent with having an origin in a non-LTE recombining gas. While the range of electron densities is consistent with the gas densities predicted by existing magnetospheric accretion models, the temperature range constrained by the Case B comparison is considerably lower than that expected for accreting gas. The cooler gas temperatures will require a non-thermal excitation process (e.g., coronal/accretion-related X-rays and UV photons) to power the observed line emission.Comment: 12 pages, emulateapj format, Accepted for publication in Ap

A search for broad infrared recombination lines in NGC 1068

We report infrared spectroscopy of the prototypical Seyfert 2 galaxy NGC 1068, aiming at detection of broad components of hydrogen recombination lines that originate in the obscured broad-line region. Using the Short Wavelength Spectrometer on board the Infrared Space Observatory, we have observed for the first time the regions of Brackett beta 2.626um and Pfund alpha 7.460um, and present improved data for Brackett alpha 4.052um. No significant broad components are detected, implying an equivalent visual extinction to the broad-line region of at least 50 magnitudes and an obscuring column density of at least 10^23 cm^-2. While consistent with a highly obscured broad-line region, as required by the classical unified scenario, these limits are not yet significant enough to discriminate strongly between different torus models or to constrain properties of the gas causing the very large X-ray obscuration. We discuss the systematic limitations of infrared broad-line region searches and suggest that Brackett alpha may often be the most favorable transition for future searches.Comment: aastex (V4), 4 eps figures. Accepted by Ap

Management and leadership in UK universities: exploring the possibilities of change

This paper considers the case for reform of management struc- tures in UK universities and offers proposals for change. The model of top-down, performance-led management that characterises many institutions is both outmoded and ill-suited to the chal- lenges of an increasingly turbulent higher education sector. Drawing on the experiences of a university that introduced a new scheme of performance management, I explore alternative approaches to leadership and management, collaborative or part- nership working designed to improve employee voice and the need to re-evaluate approaches to Human Resource Management. I conclude with a five-point model for change

Reflections on the Formation and Growth of the SURE Network: a National Disciplinary Network to Enhance Undergraduate Research in the Sciences

The Science Undergraduate Research Experience (SURE) Network is an academic network comprised of nine Higher Education Institutions (HEI) in Ireland that seeks to enhance the profile of, and practices in, undergraduate research in the Sciences within the Technological Higher Education Sector. This paper presents the reflections of the network\u27s leaders on the formation and growth of the network over the period from 2015, just prior to its establishment, to 2020 when the network hosted its seventh undergraduate research conference, published its second undergraduate journal issue, and initiated a coordinated community of practice in response to the Covid-19 crisis. The paper presents the motivations of the leaders for establishing and joining the SURE network, their interpretation of how involvement in the network enhances practice in their own HEI, their reflections on how their own personal development was enhanced, their interpretation of the factors that have contributed to the success of the network, and the direction in which they see the network going in the future. The collective reflections of the leaders of the SURE Network, as presented in this paper, provide importance guidance for those seeking to establish similar academic networks, both in the area of undergraduate research and elsewhere

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho

From Data to Software to Science with the Rubin Observatory LSST

editorial reviewedThe Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)