Wolf-Rayet Central Stars of Planetary Nebulae: Their Evolution and Properties

Over the past decade, the number of planetary nebula central stars (CSPN) known to exhibit the Wolf-Rayet (WR) phenomenon has grown substantially. Many of these discoveries have resulted from the Macquarie/AAO/Strasbourg Ha (MASH) PN Survey. While WR CSPN constitute a relatively rare stellar type (<10% of CS), there are indications that the proportion of PN harbouring them may increase as spectroscopy of more central stars is carried out. In addition, with new and better distances from the Ha surface brightness-radius relationship of Frew (2008), we can attempt a dynamical age sequence which may provide insight into the evolution of these stars.Comment: 4 pages, 2 figures. Presented at the Asymmetric Planetary Nebulae V Conference in Bowness-on-Windermere, UK, June 201

Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups.

Approximately 30% of the cultivated rice area in India is prone to crop damage from prolonged flooding. We use a randomized field experiment in 128 villages of Orissa India to show that Swarna-Sub1, a recently released submergence-tolerant rice variety, has significant positive impacts on rice yield when fields are submerged for 7 to 14 days with no yield penalty without flooding. We estimate that Swarna-Sub1 offers an approximate 45% increase in yields over the current popular variety when fields are submerged for 10 days. We show additionally that low-lying areas prone to flooding tend to be more heavily occupied by people belonging to lower caste social groups. Thus, a policy relevant implication of our findings is that flood-tolerant rice can deliver both efficiency gains, through reduced yield variability and higher expected yield, and equity gains in disproportionately benefiting the most marginal group of farmers

Privacy-preserving scoring of tree ensembles : a novel framework for AI in healthcare

Machine Learning (ML) techniques now impact a wide variety of domains. Highly regulated industries such as healthcare and finance have stringent compliance and data governance policies around data sharing. Advances in secure multiparty computation (SMC) for privacy-preserving machine learning (PPML) can help transform these regulated industries by allowing ML computations over encrypted data with personally identifiable information (PII). Yet very little of SMC-based PPML has been put into practice so far. In this paper we present the very first framework for privacy-preserving classification of tree ensembles with application in healthcare. We first describe the underlying cryptographic protocols that enable a healthcare organization to send encrypted data securely to a ML scoring service and obtain encrypted class labels without the scoring service actually seeing that input in the clear. We then describe the deployment challenges we solved to integrate these protocols in a cloud based scalable risk-prediction platform with multiple ML models for healthcare AI. Included are system internals, and evaluations of our deployment for supporting physicians to drive better clinical outcomes in an accurate, scalable, and provably secure manner. To the best of our knowledge, this is the first such applied framework with SMC-based privacy-preserving machine learning for healthcare

Competition, Innovation, and Product Exit

Why do products exit markets? This paper integrates rationale for product exit from a number of different literatures and compares the statistical and substantive effect of these explanations. We use a novel dataset covering every product introduced into the desktop laser printer industry since its inception. Using hedonic models, hazard rate models, and count models, this study generates three main findings. First, innovation does not drive products out of market per se. Managers do not pull products off the market when they innovate. Rather they seem to keep the incumbent products on the market and add the newer, more innovative products to the marketplace that have longer expected lives. Second, competition has a large impact on driving products out of markets. These noninnovative products remain in the product portfolios of companies until competition drive the products out of markets, not managerial decisions. Third, holding other factors constant, scale and learning have a marginal statistical and substantive effect on product exit.Center for Innovation in Product Developmen

Surviving the Gales of Creative Destruction: The Patterns of Innovative Activity in the Desktop Laser Printer Industry

In this paper, we examine the product life cycle in the desktop laser printer industry, from its inception in 1984 through 1996. During this time, the industry experienced a significant degree of innovation, as well as an enormous amount of product introduction and subsequent exit. The relative roles of market structure, innovation, and firm effects are explored in more detail using a multidimensional product space. We introduce a very detailed product-level dataset on the desktop laser printer industry. We have a number of findings: (1) product portfolios of firms are growing larger on average, as fewer firms offer more products; (2) products on the technological frontier have better survival prospects than printers behind the frontier; (3) product characteristics, such as page description language, speed, and resolution, have the largest effect on product survival rates; (4) awards granted to models and firms by leading PC publications have no effect on hazard rates of the current product portfolios of firms, but lead to much higher entry rates by the firm; and (5) while there are many similarities between dominant and fringe firms, differences in innovative and product life cycle behavior persist which is often overlooked in current studies of economic activity.Center for Innovation in Product Developmen

Design of Analog CMOS Circuits for Batteryless Implantable Telemetry Systems

A wireless biomedical telemetry system is a device that collects biomedical signal measurements and transmits data through wireless RF communication. Testing medical treatments often involves experimentation on small laboratory animals, such as genetically modified mice and rats. Using batteries as a power source results in many practical issues, such as increased size of the implant and limited operating lifetime. Wireless power harvesting for implantable biomedical devices removes the need for batteries integrated into the implant. This will reduce device size and remove the need for surgical replacement due to battery depletion. Resonant inductive coupling achieves wireless power transfer in a manner modelled by a step down transformer. With this methodology, power harvesting for an implantable device is realized with the use of a large primary coil external to the subject, and a smaller secondary coil integrated into the implant. The signal received from the secondary coil must be regulated to provide a stable direct current (DC) power supply, which will be used to power the electronics in the implantable device. The focus of this work is on development of an electronic front-end for wireless powering of an implantable biomedical device. The energy harvesting front-end circuit is comprised of a rectifier, LDO regulator, and a temperature insensitive voltage reference. Physical design of the front-end circuit is developed in 0.13um CMOS technology with careful attention to analog layout issues. Post-layout simulation results are presented for each sub-block as well as the full front-end structure. The LDO regulator operates with supply voltages in the range of 1V to 1.5V with quiescent current of 10.5uA The complete power receiver front-end has a power conversion efficiency of up to 29%

Assessing the Medical Emergency Preparedness of Dental Faculty, Residents, and Practicing Periodontists: An Exploratory Study

With the increased number of elderly and medically compromised individuals receiving dental care and the presence of systemic comorbidities and associated treatment modalities in this patient population, it is imperative that dentists be prepared to manage a variety of medical emergencies. The aim of this study was to assess the knowledge of and preparedness to manage common medical emergencies of cohorts of practicing periodontists, specialty residents, and faculty members, both for comparative purposes and as an aid to refining a dental school’s standardized case scenarios. The study, conducted in 2017, was designed for four groups of randomly selected participants with at least 20 in each group; the actual number of voluntary participants was 28 private practice periodontists, 22 residents in specialty programs, 21 specialist faculty members, and 24 general practice faculty members. Participants were asked to evaluate ten clinical emergency cases and identify the diagnosis and indicated intervention for each. Groups were also evaluated for differences among correct responses for each case. Overall, there were no statistically significant differences for number of correct diagnoses or interventions among the four groups. However, several cases had varying degrees of incorrect diagnoses and management across all groups. Participants who had recently graduated or were still in school were able to treat cases appropriately more often than the other participants. Further refinement of cases to assess provider preparedness to correctly diagnose and manage medical emergencies is needed, specifically establishing case-specific features and addressing areas of potential confusion before the cases are used for educational purposes

Application of the dual-kinetic-balance sets in the relativistic many-body problem of atomic structure

The dual-kinetic-balance (DKB) finite basis set method for solving the Dirac equation for hydrogen-like ions [V. M. Shabaev et al., Phys. Rev. Lett. 93, 130405 (2004)] is extended to problems with a non-local spherically-symmetric Dirac-Hartree-Fock potential. We implement the DKB method using B-spline basis sets and compare its performance with the widely-employed approach of Notre Dame (ND) group [W.R. Johnson and J. Sapirstein, Phys. Rev. Lett. 57, 1126 (1986)]. We compare the performance of the ND and DKB methods by computing various properties of Cs atom: energies, hyperfine integrals, the parity-non-conserving amplitude of the $6s_{1/2}-7s_{1/2}$ transition, and the second-order many-body correction to the removal energy of the valence electrons. We find that for a comparable size of the basis set the accuracy of both methods is similar for matrix elements accumulated far from the nuclear region. However, for atomic properties determined by small distances, the DKB method outperforms the ND approach. In addition, we present a strategy for optimizing the size of the basis sets by choosing progressively smaller number of basis functions for increasingly higher partial waves. This strategy exploits suppression of contributions of high partial waves to typical many-body correlation corrections.Comment: 10 page

A change of view: Homologous recombination at single-molecule resolution

Genetic recombination occurs in all organisms and is vital for genome stability. Indeed, in humans, aberrant recombination can lead to diseases such as cancer. Our understanding of homologous recombination is built upon more than a century of scientific inquiry, but achieving a more complete picture using ensemble biochemical and genetic approaches is hampered by population heterogeneity and transient recombination intermediates. Recent advances in single-molecule and super-resolution microscopy methods help to overcome these limitations and have led to new and refined insights into recombination mechanisms, including a detailed understanding of DNA helicase function and synaptonemal complex structure. The ability to view cellular processes at single-molecule resolution promises to transform our understanding of recombination and related processes.Fil: Kaniecki, Kyle. Columbia University; Estados UnidosFil: de Tullio, Luisina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Centro de Investigaciones en Química Biológica de Córdoba; ArgentinaFil: Greene, Eric C.. Columbia University; Estados Unido