A VLA Survey For Faint Compact Radio Sources in the Orion Nebula Cluster

We present Karl G. Janksy Very Large Array (VLA) 1.3 cm, 3.6 cm, and 6 cm continuum maps of compact radio sources in the Orion Nebular Cluster. We mosaicked 34 square arcminutes at 1.3 cm, 70 square arcminutes at 3.6 cm and 109 square arcminutes at 6 cm, containing 778 near-infrared detected YSOs and 190 HST-identified proplyds (with significant overlap between those characterizations). We detected radio emission from 175 compact radio sources in the ONC, including 26 sources that were detected for the first time at these wavelengths. For each detected source we fit a simple free-free and dust emission model to characterize the radio emission. We extrapolate the free-free emission spectrum model for each source to ALMA bands to illustrate how these measurements could be used to correctly measure protoplanetary disk dust masses from sub-millimeter flux measurements. Finally, we compare the fluxes measured in this survey with previously measured fluxes for our targets, as well as four separate epochs of 1.3 cm data, to search for and quantify variability of our sources.Comment: 13 pages, 6 figures, 4 tables, ApJ, in pres

Protoplanetary Disk Masses in the Young NGC 2024 Cluster

We present the results from a Submillimeter Array survey of the 887 micron continuum emission from the protoplanetary disks around 95 young stars in the young cluster NGC 2024. Emission was detected from 22 infrared sources, with flux densities from ~5 to 330 mJy; upper limits (at 3sigma) for the other 73 sources range from 3 to 24 mJy. For standard assumptions, the corresponding disk masses range from ~0.003 to 0.2Msolar, with upper limits at 0.002--0.01Msolar. The NGC 2024 sample has a slightly more populated tail at the high end of its disk mass distribution compared to other clusters, but without more information on the nature of the sample hosts it remains unclear if this difference is statistically significant or a superficial selection effect. Unlike in the Orion Trapezium, there is no evidence for a disk mass dependence on the (projected) separation from the massive star IRS2b in the NGC 2024 cluster. We suggest that this is due to either the cluster youth or a comparatively weaker photoionizing radiation field.Comment: ApJ, in pres

ALMA Observations of the Largest Proto-Planetary Disk in the Orion Nebula, 114-426: A CO Silhouette

We present ALMA observations of the largest protoplanetary disk in the Orion Nebula, 114-426. Detectable 345 GHz (856 micron) dust continuum is produced only in the 350 AU central region of the ~1000 AU diameter silhouette seen against the bright H-alpha background in HST images. Assuming optically thin dust emission at 345 GHz, a gas-to-dust ratio of 100, and a grain temperature of 20 K, the disk gas-mass is estimated to be 3.1 +/- 0.6 Jupiter masses. If most solids and ices have have been incorporated into large grains, however, this value is a lower limit. The disk is not detected in dense-gas tracers such as HCO+ J=4-3, HCN J=4-3, or CS =7-6. These results may indicate that the 114-426 disk is evolved and depleted in some light organic compounds found in molecular clouds. The CO J=3-2 line is seen in absorption against the bright 50 to 80 K background of the Orion A molecular cloud over the full spatial extent and a little beyond the dust continuum emission. The CO absorption reaches a depth of 27 K below the background CO emission at VLSR ~6.7 km/s about 0.52 arcseconds (210 AU) northeast and 12 K below the background CO emission at VLSR ~ 9.7 km/s about 0.34 arcseconds (140 AU) southwest of the suspected location of the central star, implying that the embedded star has a mass less than 1 Solar mass .Comment: 20 pages, 4 figure

Timing and Potential Causes of 19th-Century Glacier Advances in Coastal Alaska Based on Tree-Ring Dating and Historical Accounts

The Little Ice Age (LIA), ca. CE 1250–1850, was a cold period of global extent, with the nature and timing of reduced temperatures varying by region. The Gulf of Alaska (GOA) is a key location to study the climatic drivers of glacier fluctuations during the LIA because dendrochronological techniques can provide precise ages of ice advances and retreats. Here, we use dendrochronology to date the most recent advance of La Perouse Glacier in the Fairweather Range of Southeast Alaska. After maintaining a relatively contracted state since at least CE 1200, La Perouse advanced to its maximum LIA position between CE 1850 and 1895. Like many other glaciers bordering the GOA, the La Perouse Glacier reached this maximum position relatively late in the LIA compared with glaciers in other regions. This is curious because reconstructions of paleoclimate in the GOA region indicate the 19th century was not the coldest period of the LIA. Using newly available paleoclimate data, we hypothesize that a combination of moderately cool summers accompanying the Dalton Solar Minimum and exceptionally snowy winters associated with a strengthened Aleutian Low could have caused these relatively late LIA advances. Such a scenario implies that winter climate processes, which are heavily influenced by ocean-atmospheric variability in the North Pacific region, have modulated these coastal glaciers’ sensitivity to shifts in summer temperatures

Language Models (Mostly) Know What They Know

We study whether language models can evaluate the validity of their own claims and predict which questions they will be able to answer correctly. We first show that larger models are well-calibrated on diverse multiple choice and true/false questions when they are provided in the right format. Thus we can approach self-evaluation on open-ended sampling tasks by asking models to first propose answers, and then to evaluate the probability "P(True)" that their answers are correct. We find encouraging performance, calibration, and scaling for P(True) on a diverse array of tasks. Performance at self-evaluation further improves when we allow models to consider many of their own samples before predicting the validity of one specific possibility. Next, we investigate whether models can be trained to predict "P(IK)", the probability that "I know" the answer to a question, without reference to any particular proposed answer. Models perform well at predicting P(IK) and partially generalize across tasks, though they struggle with calibration of P(IK) on new tasks. The predicted P(IK) probabilities also increase appropriately in the presence of relevant source materials in the context, and in the presence of hints towards the solution of mathematical word problems. We hope these observations lay the groundwork for training more honest models, and for investigating how honesty generalizes to cases where models are trained on objectives other than the imitation of human writing.Comment: 23+17 pages; refs added, typos fixe

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

We describe our early efforts to red team language models in order to simultaneously discover, measure, and attempt to reduce their potentially harmful outputs. We make three main contributions. First, we investigate scaling behaviors for red teaming across 3 model sizes (2.7B, 13B, and 52B parameters) and 4 model types: a plain language model (LM); an LM prompted to be helpful, honest, and harmless; an LM with rejection sampling; and a model trained to be helpful and harmless using reinforcement learning from human feedback (RLHF). We find that the RLHF models are increasingly difficult to red team as they scale, and we find a flat trend with scale for the other model types. Second, we release our dataset of 38,961 red team attacks for others to analyze and learn from. We provide our own analysis of the data and find a variety of harmful outputs, which range from offensive language to more subtly harmful non-violent unethical outputs. Third, we exhaustively describe our instructions, processes, statistical methodologies, and uncertainty about red teaming. We hope that this transparency accelerates our ability to work together as a community in order to develop shared norms, practices, and technical standards for how to red team language models

A Novel Family of Toxoplasma IMC Proteins Displays a Hierarchical Organization and Functions in Coordinating Parasite Division

Apicomplexans employ a peripheral membrane system called the inner membrane complex (IMC) for critical processes such as host cell invasion and daughter cell formation. We have identified a family of proteins that define novel sub-compartments of the Toxoplasma gondii IMC. These IMC Sub-compartment Proteins, ISP1, 2 and 3, are conserved throughout the Apicomplexa, but do not appear to be present outside the phylum. ISP1 localizes to the apical cap portion of the IMC, while ISP2 localizes to a central IMC region and ISP3 localizes to a central plus basal region of the complex. Targeting of all three ISPs is dependent upon N-terminal residues predicted for coordinated myristoylation and palmitoylation. Surprisingly, we show that disruption of ISP1 results in a dramatic relocalization of ISP2 and ISP3 to the apical cap. Although the N-terminal region of ISP1 is necessary and sufficient for apical cap targeting, exclusion of other family members requires the remaining C-terminal region of the protein. This gate-keeping function of ISP1 reveals an unprecedented mechanism of interactive and hierarchical targeting of proteins to establish these unique sub-compartments in the Toxoplasma IMC. Finally, we show that loss of ISP2 results in severe defects in daughter cell formation during endodyogeny, indicating a role for the ISP proteins in coordinating this unique process of Toxoplasma replication

Rheumatoid arthritis - clinical aspects: 134. Predictors of Joint Damage in South Africans with Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) causes progressive joint damage and functional disability. Studies on factors affecting joint damage as clinical outcome are lacking in Africa. The aim of the present study was to identify predictors of joint damage in adult South Africans with established RA. Methods: A cross-sectional study of 100 black patients with RA of >5 years were assessed for joint damage using a validated clinical method, the RA articular damage (RAAD) score. Potential predictors of joint damage that were documented included socio-demographics, smoking, body mass index (BMI), disease duration, delay in disease modifying antirheumatic drug (DMARD) initiation, global disease activity as measured by the disease activity score (DAS28), erythrocyte sedimentation rate (ESR), C reactive protein (CRP), and autoantibody status. The predictive value of variables was assessed by univariate and stepwise multivariate regression analyses. A p value <0.05 was considered significant. Results: The mean (SD) age was 56 (9.8) years, disease duration 17.5 (8.5) years, educational level 7.5 (3.5) years and DMARD lag was 9 (8.8) years. Female to male ratio was 10:1. The mean (SD) DAS28 was 4.9 (1.5) and total RAAD score was 28.3 (12.8). The mean (SD) BMI was 27.2 kg/m2 (6.2) and 93% of patients were rheumatoid factor (RF) positive. More than 90% of patients received between 2 to 3 DMARDs. Significant univariate predictors of a poor RAAD score were increasing age (p = 0.001), lower education level (p = 0.019), longer disease duration (p < 0.001), longer DMARD lag (p = 0.014), lower BMI (p = 0.025), high RF titre (p < 0.001) and high ESR (p = 0.008). The multivariate regression analysis showed that the only independent significant predictors of a higher mean RAAD score were older age at disease onset (p = 0.04), disease duration (p < 0.001) and RF titre (p < 0.001). There was also a negative association between BMI and the mean total RAAD score (p = 0.049). Conclusions: Patients with longstanding established RA have more severe irreversible joint damage as measured by the clinical RAAD score, contrary to other studies in Africa. This is largely reflected by a delay in the initiation of early effective treatment. Independent of disease duration, older age at disease onset and a higher RF titre are strongly associated with more joint damage. The inverse association between BMI and articular damage in RA has been observed in several studies using radiographic damage scores. The mechanisms underlying this paradoxical association are still widely unknown but adipokines have recently been suggested to play a role. Disclosure statement: C.I. has received a research grant from the Connective Tissue Diseases Research Fund, University of the Witwatersrand. All other authors have declared no conflicts of interes

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages