How Protostellar Outflows Help Massive Stars Form

We consider the effects of an outflow on radiation escaping from the infalling envelope around a massive protostar. Using numerical radiative transfer calculations, we show that outflows with properties comparable to those observed around massive stars lead to significant anisotropy in the stellar radiation field, which greatly reduces the radiation pressure experienced by gas in the infalling envelope. This means that radiation pressure is a much less significant barrier to massive star formation than has previously been thought.Comment: 4 pages, 2 figures, emulateapj, accepted for publication in ApJ Letter

Scabies: Application of the Novel Identify-Isolate-Inform Tool for Detection and Management

Scabies is a highly contagious, globally prevalent, parasitic skin infestation caused by Sarcoptes scabiei var. hominis, also known as the itch mite. There have been outbreaks not only in the developing world, but also in the developed world among refugees and asylum seekers. Once infested with scabies mites, symptomatic patients, as well as asymptomatic carriers, quickly spread the disease through direct skin-to-skin contact. Typically, symptoms of scabies are characterized by an erythematous, papular, pruritic rash associated with burrows. Treatment of scabies involves using topical or systemic scabicides and treating secondary bacterial infections, if present. Given the prevalence and contagiousness of scabies, measures to prevent its spread are essential. Through application of the novel Identify-Isolate-Inform (3I) Tool, emergency medical providers can readily identify risk factors for exposure and important symptoms of the disease, thus limiting its spread through prompt scabicide therapy; isolate the patient until after treatment; and inform local public health authorities and hospital infection prevention, when appropriate. Ultimately, these three actions can aid public health in controlling the transmission of scabies cases, thus ensuring the protection of the general public from this highly contagious skin infestation

Human Learning of Hierarchical Graphs

Humans are constantly exposed to sequences of events in the environment. Those sequences frequently evince statistical regularities, such as the probabilities with which one event transitions to another. Collectively, inter-event transition probabilities can be modeled as a graph or network. Many real-world networks are organized hierarchically and understanding how humans learn these networks is an ongoing aim of current investigations. While much is known about how humans learn basic transition graph topology, whether and to what degree humans can learn hierarchical structures in such graphs remains unknown. We investigate how humans learn hierarchical graphs of the Sierpi\'nski family using computer simulations and behavioral laboratory experiments. We probe the mental estimates of transition probabilities via the surprisal effect: a phenomenon in which humans react more slowly to less expected transitions, such as those between communities or modules in the network. Using mean-field predictions and numerical simulations, we show that surprisal effects are stronger for finer-level than coarser-level hierarchical transitions. Surprisal effects at coarser levels of the hierarchy are difficult to detect for limited learning times or in small samples. Using a serial response experiment with human participants (n=$100$), we replicate our predictions by detecting a surprisal effect at the finer-level of the hierarchy but not at the coarser-level of the hierarchy. To further explain our findings, we evaluate the presence of a trade-off in learning, whereby humans who learned the finer-level of the hierarchy better tended to learn the coarser-level worse, and vice versa. Our study elucidates the processes by which humans learn hierarchical sequential events. Our work charts a road map for future investigation of the neural underpinnings and behavioral manifestations of graph learning.Comment: 22 pages, 10 figures, 1 tabl

Routes To the Renaissance for Pittsfield, MA

The goal of the Master of Regional Planning Studio is to develop a student’s techniques for collecting, analyzing, and synthesizing spatial and non-spatial data and then presenting that collective data in a manner (i.e., report, video, presentation, and charettes) that is understandable to academics, professionals, and the public. Planning Studio allows students to integrate knowledge from coursework and research, and apply such knowledge to resolving representative planning problems. At UMASS Amherst, these problems are found in neighborhood, rural, urban, and/or regional settings. In the fall of 2015, the City of Pittsfield contracted the MRP Studio to create a vision plan to connect the goal’s of its Master Plan in 2009 to current development regulations that encourage development and redevelopment of an appropriate size, scale and design that meets the short term and long term vision of the community. The vision plan encompasses the following: Spatial and Physical Boundaries of Major Gateway Corridors: Analyze the major gateways and develop tools to make them more welcoming. Permitted Use Table and Definitions: Review, clarify, and consolidate the land-uses listed in the table to assess deficiencies and unclear definitions. Design Guidelines: Create a manual to guide architectural aesthetic standards for new retail developments. Sign Ordinance: Implement a streamlined regulation that improves sign quality. Site Plan Review: Develop thresholds to create clearer processes for review of development projects. Resolution for Split Parcels: Identify all properties that fall within two zoning districts and develop a mitigation tool. Pro Forma and Multi-Family Housing: Develop a financial model that will estimate the construction and maintenance cost of multi-family housing units and make projections for new development’s financial return

PEDSnet: a National Pediatric Learning Health System

A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network that provides the infrastructure to support a national pediatric LHS. A consortium consisting of PEDSnet, which includes eight academic medical centers, two existing disease-specific pediatric networks, and two national data partners form the initial partners in the National Pediatric Learning Health System (NPLHS). PEDSnet is implementing a flexible dual data architecture that incorporates two widely used data models and national terminology standards to support multi-institutional data integration, cohort discovery, and advanced analytics that enable rapid learning

On the Role of Massive Stars in the Support and Destruction of Giant Molecular Clouds

We argue that massive stars are the dominant sources of energy for the turbulent motions within giant molecular clouds, and that the primary agent of feedback is the expansion of H II regions within the cloud volume. This conclusion is suggested by the low efficiency of star formation and corroborated by dynamical models of H II regions. We evaluate the turbulent energy input rate in clouds more massive than one third of a million solar masses, for which gravity does not significantly affect the expansion of H II regions. Such clouds achieve a balance between the decay of turbulent energy and its regeneration in H II regions; summed over clouds, the implied ionizing luminosity and star formation rate are roughly consistent with the Galactic total. H II regions also photoevaporate their clouds: we derive cloud destruction times somewhat shorter than those estimated by Williams and McKee. The upper mass limit for molecular clouds in the Milky Way may derive from the fact that larger clouds would destroy themselves in less than one crossing time. The conditions within starburst galaxies do not permit giant molecular clouds to be supported or destroyed by H II regions. This should lead to rapid cloud collapse and the efficient formation of massive star clusters, explaining some aspects of the starburst phenomenon.Comment: 21 pages, 5 figures; ApJ, in press. Minor comment added on prior wor

The Formation of Massive Stars from Turbulent Cores

Observations indicate that massive stars form in regions of very high surface density, ~1 g cm^-2. Clusters containing massive stars and globular clusters have a comparable column density. The total pressure in clouds of such a column density is P/k~10^8-10^9 K cm^-3, far greater than that in the diffuse ISM or the average in GMCs. Observations show that massive star-forming regions are supersonically turbulent, and we show that the molecular cores out of which individual massive stars form are as well. The protostellar accretion rate in such a core is approximately equal to the instantaneous mass of the star divided by the free-fall time of the gas that is accreting onto the star (Stahler, Shu, & Taam 1980). The star-formation time in this Turbulent Core model for massive star formation is several mean free-fall timesscales of the core, but is about equal to that of the region in which the core is embedded. The typical time for a massive star to form is about 10^5 yr and the accretion rate is high enough to overcome radiation pressure due to the luminosity of the star. For the typical case we consider, in which the cores out of which the stars form have a density structure varying as r^{-1.5}, the protostellar accretion rate grows linearly with time. We calculate the evolution of the radius of a protostar and determine the accretion luminosity. At the high accretion rates that are typical in regions of massive star formation, protostars join the main sequence at about 20 solar masses. We apply these results to predict the properties of protostars thought to be powering several observed hot molecular cores, including the Orion hot core and W3(H2O). In the Appendixes, we discuss the pressure in molecular clouds and we argue that ``logatropic'' models for molecular clouds are incompatible with observation.Comment: ApJ accepted; 28 pages, some clarification of the text, results unchange

Application of combined omics platforms to accelerate biomedical discovery in diabesity

Diabesity has become a popular term to describe the specific form of diabetes that develops late in life and is associated with obesity. While there is a correlation between diabetes and obesity, the association is not universally predictive. Defining the metabolic characteristics of obesity that lead to diabetes, and how obese individuals who develop diabetes different from those who do not, are important goals. The use of large-scale omics analyses (e.g., metabolomic, proteomic, transcriptomic, and lipidomic) of diabetes and obesity may help to identify new targets to treat these conditions. This report discusses how various types of omics data can be integrated to shed light on the changes in metabolism that occur in obesity and diabetes