Dynamics of One-dimensional Self-gravitating Systems Using Hermite-Legendre Polynomials

The current paradigm for understanding galaxy formation in the universe depends on the existence of self-gravitating collisionless dark matter. Modeling such dark matter systems has been a major focus of astrophysicists, with much of that effort directed at computational techniques. Not surprisingly, a comprehensive understanding of the evolution of these self-gravitating systems still eludes us, since it involves the collective nonlinear dynamics of many-particle systems interacting via long-range forces described by the Vlasov equation. As a step towards developing a clearer picture of collisionless self-gravitating relaxation, we analyze the linearized dynamics of isolated one-dimensional systems near thermal equilibrium by expanding their phase space distribution functions f(x,v) in terms of Hermite functions in the velocity variable, and Legendre functions involving the position variable. This approach produces a picture of phase-space evolution in terms of expansion coefficients, rather than spatial and velocity variables. We obtain equations of motion for the expansion coefficients for both test-particle distributions and self-gravitating linear perturbations of thermal equilibrium. N-body simulations of perturbed equilibria are performed and found to be in excellent agreement with the expansion coefficient approach over a time duration that depends on the size of the expansion series used.Comment: 12 pages, accepted for publication in MNRA

Chemical modeling of Infrared Dark Clouds: the Role of Surface Chemistry

We simulate the chemistry of infrared dark clouds (IRDCs) with a model in which the physical conditions are homogeneous and time-independent. The chemistry is solved as a function of time with three networks: one purely gas-phase, one that includes accretion and desorption, and one, the complete gas-grain network, that includes surface chemistry in addition. We compare our results with observed molecular abundances for two representative IRDCs -- IRDC013.90-1 and IRDC321.73-1 -- using the molecular species N$_2$H$^+$, HC$_3$N, HNC, HCO$^+$, HCN, C$_2$H, NH$_3$ and CS. IRDC013.90-1 is a cold IRDC, with a temperature below 20 K, while IRDC321.73-1 is somewhat warmer, in the range 20 - 30 K. We find that the complete gas-grain model fits the data very well, but that the goodness-of-fit is not sharply peaked at a particular temperature. Surface processes are important for the explanation of the high gas-phase abundance of N$_2$H$^+$ in IRDC321.73-1. The general success of the 0-D model in reproducing single-dish observations of our limited sample of 8 species shows that it is probably sufficient for an explanation of this type of data. To build and justify more complicated models, including spatial temperature and density structure, contraction, and heating, we require high-resolution interferometric data.Comment: accepted for publication in Ap

Integrating hierarchical controlled vocabularies with OWL ontology: A case study from the domain of molecular interactions

Many efforts at standardising terminologies within the biological domain have resulted in the construction of hierarchical controlled vocabularies that capture domain knowledge. Vocabularies, such as the PSI-MI vocabulary, capture both deep and extensive domain knowledge, in the OBO (Open Biomedical Ontologies) format. However hierarchical vocabularies, such as PSI-MI which are represented in OBO, only represent simple parent-child relationships between terms. By contrast, ontologies constructed using the Web Ontology Language (OWL), such as BioPax, define many richer types of relationships between terms. OWL provides a semantically rich structured language for expressing classes and sub-classes of entities and properties, relationships between them and domain-specific rules or axioms that can be applied to extract new information through semantic inferencing. In order to fully exploit the domain knowledge inherent in domain-specific controlled vocabularies, they need to be represented as OWL-DL ontologies, rather than in formats such as OBO. In this paper, we describe a method for converting OBO vocabularies into OWL and class instances represented as OWL-RDF triples. This approach preserves the hierarchical arrangement of the domain knowledge whilst also making the underlying parent-child relationships available to inferencing engines. This approach also has clear advantages over existing methods which incorporate terms from external controlled vocabularies as literals stripped of the context associated with their place in the hierarchy. By preserving this context, we enable machine inferencing over the ordered domain knowledge captured in OBO controlled vocabularie

Disclosure Of EVA Use In Corporate Financial Reports: A Descriptive Analysis

This descriptive study examines a sample of 269 firms that mentioned EVA in their public disclosures.  The key findings of our study are: (1) the use of EVA is found in a cross-section of the industries; (2) the most commonly used source of disclosure is the proxy statement; (3) a majority of the firms use only EVA rather than EVA in combination with other traditional measures; (4) a majority of the sample firms apply EVA at the corporate level alone; (5) three-fourths of the sample firms use EVA as an incentive compensation tool; (6) most firms apply EVA and other metrics only at the executive level for compensation and performance evaluation; and (7) two common modes of compensation using EVA determination are bonus plans and stock options.  The results of our study indicate that firms are steadily adopting EVA as one component of their value management system.  In a related decision context, investors estimate the cost of equity capital to arrive at the intrinsic value of the firm.  Firms can help investors reduce this estimation error by reporting their own estimate of the cost of equity capital, in turn, reducing the valuation error. Our findings have implications for the Securities and Exchange Commission and the Financial Accounting Standards Board in that they should recognize the need to address this issue thereby enhancing the decision usefulness of public reporting

Telehealth Utilization in Response to the COVID-19 Pandemic: Current State of Medical Provider Training

Background: The COVID-19 pandemic accelerated the development of telehealth services and thus the need for telehealth education and training to support rapid implementation at scale. A national survey evaluating the current state of the telehealth landscape was deployed to organizational representatives, and included questions related to education and training. Materials and Methods: In the summer of 2020, 71 survey participants (31.8%) completed an online survey seeking to determine the utilization of telehealth services across institutional types and locations. This included data collected to specifically compare the rates and types of formal telehealth education provided before and during the pandemic. Results: Thirty percent of organizations reported no telehealth training before COVID-19, with those in suburban/rural settings significantly less likely to provide any training (55% vs. 82%) compared with urban. Pandemic-related training changes applied to 78% of organizations, with more change happening to those without any training before COVID-19 (95%). Generally, organizations offering training before the pandemic reported deploying COVID-19-related telehealth services, while a higher percentage of those without any training beforehand reported that they either did not plan on providing these services or were in the early planning stages. Discussion: Telehealth education is moving from elective to essential based on the need to prepare and certify the workforce to support high-quality telehealth services. Conclusions: As telehealth continues to evolve to meet the future health care service needs of patients and providers, education and training will advance to meet the needs of everyday clinical encounters and broader public health initiatives