Characterizing the Viscoelastic Behavior of PDMS/PDPS Copolymers

Viscoelasticity is the property of materials that exhibits both viscous and elastic characteristics when undergoing deformation. In polymeric materials, the mechani- cal behavior is dominated by this viscoelastic phenomenon. Creating computational models for these materials can be quite complicated due to their frequency depen- dent and temperature dependent material properties. The research presented in this paper will use state of the art methods to fully develop a material model for a filled polydimethylsiloxane-polydiphenynlsiloxane (PDMS/PDPS) copolymer foam that has yet to be characterized. Mechanical properties of PDMS/PDPS copoly- mers are currently being studied to assess engineering performance, and to provide accurate models that can be used to gain a fundamental understanding of the ma- terial behavior. The properties for this material have been measured using multiple experiments. All of the parameters required to populate the Simplified Potential Energy Clock (SPEC) model were measured. The SPEC model can now be used to accurately predict the behavior of the material under different shock and loading environments

Alien Registration- Small, Eltha E. (Lubec, Washington County)

https://digitalmaine.com/alien_docs/1879/thumbnail.jp

Alien Registration- Small, Victor E. (Portland, Cumberland County)

https://digitalmaine.com/alien_docs/22073/thumbnail.jp

Alien Registration- Small, Victor E. (Portland, Cumberland County)

https://digitalmaine.com/alien_docs/22073/thumbnail.jp

Discrete Optimization for Interpretable Study Populations and Randomization Inference in an Observational Study of Severe Sepsis Mortality

Motivated by an observational study of the effect of hospital ward versus intensive care unit admission on severe sepsis mortality, we develop methods to address two common problems in observational studies: (1) when there is a lack of covariate overlap between the treated and control groups, how to define an interpretable study population wherein inference can be conducted without extrapolating with respect to important variables; and (2) how to use randomization inference to form confidence intervals for the average treatment effect with binary outcomes. Our solution to problem (1) incorporates existing suggestions in the literature while yielding a study population that is easily understood in terms of the covariates themselves, and can be solved using an efficient branch-and-bound algorithm. We address problem (2) by solving a linear integer program to utilize the worst case variance of the average treatment effect among values for unobserved potential outcomes that are compatible with the null hypothesis. Our analysis finds no evidence for a difference between the sixty day mortality rates if all individuals were admitted to the ICU and if all patients were admitted to the hospital ward among less severely ill patients and among patients with cryptic septic shock. We implement our methodology in R, providing scripts in the supplementary material

Multi-Player Diffusion Games on Graph Classes

We study competitive diffusion games on graphs introduced by Alon et al. [1] to model the spread of influence in social networks. Extending results of Roshanbin [8] for two players, we investigate the existence of pure Nash equilibria for at least three players on different classes of graphs including paths, cycles, grid graphs and hypercubes; as a main contribution, we answer an open question proving that there is no Nash equilibrium for three players on (m x n) grids with min(m, n) >= 5. Further, extending results of Etesami and Basar [3] for two players, we prove the existence of pure Nash equilibria for four players on every d-dimensional hypercube.Comment: Extended version of the TAMC 2015 conference version now discussing hypercube results (added details for the proof of Proposition 1

A revised radiometric normalisation standard for SAR

Improved geometric accuracy in SAR sensors implies that more complex models of the Earth may be used not only to geometrically rectify imagery, but also to more robustly calibrate their radiometry. Current beta, sigma, and gamma nought SAR radiometry conventions all assume a simple “flat as Kansas” Earth ellipsoid model. We complement these simple models with improved radiometric calibration that accounts for local terrain variations. In the era of ERS-1 and RADARSAT-1, image geolocation accuracy was in the order of multiple samples, and tiepointfree establishment of the relationship between radar and map geometries was not possible. Newer sensors such as ASAR, PALSAR, and TerraSAR-X all support accurate geolocation based on product annotations alone. We show that high geolocation accuracy, combined with availability of high-resolution accurate elevation models, enables a more robust radiometric calibration standard for modern SAR sensors that is based on gamma nought normalised using an Earth terrain-model