The role of young users in determining long term care expenditure in Norway

<i>Aims</i>: In Norway, it is the responsibility of the country's 429 municipalities to provide long term care (LTC) services to their residents. Recent years have seen a sharp rise in the number of LTC users under the age of 65. This paper aims to explore the effect of this rise on LTC expenditure. <i>Methods</i>: Panel data models are used on data from municipalities from 1986 to 2011. An instrumental variable approach is also utilised to account for possible endogeneity related to the number of young users. <i>Results</i>: The number of young users appears to have a strong effect on LTC expenditure. There is also evidence of municipalities exercising discretion in defining eligibility criteria for young users in order to limit expenditure. Conclusions: The rise in the number of young LTC users presents a long-term challenge to the sustainability of LTC financing. The current budgeting system does not appear to fully compensate municipalities for expenditure on young LTC users. This may put strain on the financing of services for older users

Observational Challenges for the Standard FLRW Model

We summarise some of the main observational challenges for the standard Friedmann-Lemaitre-Robertson-Walker cosmological model and describe how results recently presented in the parallel session `Large--scale Structure and Statistics' (DE3) at the `Fourteenth Marcel Grossman Meeting on General Relativity' are related to these challenges.Comment: 17 pages; references added. Matches published version in Int. J. Mod. Phys. D; Report on Parallel Session DE3 of MG1

Efficient Bayesian estimates for discrimination among topologically different systems biology models

A major effort in systems biology is the development of mathematical models that describe complex biological systems at multiple scales and levels of abstraction. Determining the topology—the set of interactions—of a biological system from observations of the system's behavior is an important and difficult problem. Here we present and demonstrate new methodology for efficiently computing the probability distribution over a set of topologies based on consistency with existing measurements. Key features of the new approach include derivation in a Bayesian framework, incorporation of prior probability distributions of topologies and parameters, and use of an analytically integrable linearization based on the Fisher information matrix that is responsible for large gains in efficiency. The new method was demonstrated on a collection of four biological topologies representing a kinase and phosphatase that operate in opposition to each other with either processive or distributive kinetics, giving 8–12 parameters for each topology. The linearization produced an approximate result very rapidly (CPU minutes) that was highly accurate on its own, as compared to a Monte Carlo method guaranteed to converge to the correct answer but at greater cost (CPU weeks). The Monte Carlo method developed and applied here used the linearization method as a starting point and importance sampling to approach the Bayesian answer in acceptable time. Other inexpensive methods to estimate probabilities produced poor approximations for this system, with likelihood estimation showing its well-known bias toward topologies with more parameters and the Akaike and Schwarz Information Criteria showing a strong bias toward topologies with fewer parameters. These results suggest that this linear approximation may be an effective compromise, providing an answer whose accuracy is near the true Bayesian answer, but at a cost near the common heuristics.National Cancer Institute (U.S.) (U54 CA112967)National University of Singapor

Statistical uncertainty of eddy flux–based estimates of gross ecosystem carbon exchange at Howland Forest, Maine

We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest-atmosphere CO2fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However, separation of tower-based net ecosystem exchange (NEE) into its components (respiration losses and photosynthetic uptake) requires at least one application of a model, which is usually a regression model fitted to nighttime data and extrapolated for all daytime intervals. In addition, the existence of a significant amount of missing data in eddy flux time series requires a model for daytime NEE as well. Statistical approaches for analytically specifying prediction intervals associated with a regression require, among other things, constant variance of the data, normally distributed residuals, and linearizable regression models. Because the NEE data do not conform to these criteria, we used a Monte Carlo approach (bootstrapping) to quantify the statistical uncertainty of GEE estimates and present this uncertainty in the form of 90% prediction limits. We explore two examples of regression models for modeling respiration and daytime NEE: (1) a simple, physiologically based model from the literature and (2) a nonlinear regression model based on an artificial neural network. We find that uncertainty at the half-hourly timescale is generally on the order of the observations themselves (i.e., ∼100%) but is much less at annual timescales (∼10%). On the other hand, this small absolute uncertainty is commensurate with the interannual variability in estimated GEE. The largest uncertainty is associated with choice of model type, which raises basic questions about the relative roles of models and data

Performance and loads data from an outdoor hover test of a Lynx tail rotor

A Lynx tail rotor was tested in hover at the Outdoor Aerodynamic Research Facility at NASA Ames Research Center. The test objectives were to measure the isolated rotor performance to provide a baseline for subsequent testing, and to operate the rotor throughout the speed and collective envelope before testing in the NFAC 40- by 80-Foot Wind Tunnel. Rotor forces and blade bending moments were measured at ambient wind conditions from zero to 6.23 m/sec. The test envelope was limited to rotor speeds of 1550 to 1850 rpm and minus 13 deg to plus 20 deg of blade collective pitch. The isolated rotor performance and blade loads data are presented

Using Real Options in ERP-Systems for Improving Delivery Reliability

Today’s machinery and equipment industry is a highly volatile market, giving rise to frequently instable and inapprehensiblebuyer-supplier-relationships and to turbulences with respect to reliability of deliveries. With this paper we propose a minimalinvasive approach how to overcome existing capability limitations in production planning, scheduling and procurement ofERP-systems by using real options as means for coordinating the divergent interest of buyers and suppliers. Following thedesign research paradigm, we first describe how real options can be integrated in a contemporary ERP-system. In asupplemental evaluation, the attitude toward using this approach is discussed. This final discussion provides insights whethercompanies in the machinery and equipment industry are willing to adopt our real options approach, or if they prefer the use ofother, not necessarily IT-enabled, means for handling the poor delivery reliability