Protected species aerial survey data collection and analysis in waters underlying the R-5306A airspace: final report submitted to US Marine Corps, MCAS Cherry Point

To be in compliance with the Endangered Species Act and the Marine Mammal Protection Act, the United States Department of the Navy is required to assess the potential environmental impacts of conducting at-sea training operations on sea turtles and marine mammals. Limited recent and area-specific density data of sea turtles and dolphins exist for many of the Navy’s operations areas (OPAREAs), including the Marine Corps Air Station (MCAS) Cherry Point OPAREA, which encompasses portions of Core and Pamlico Sounds, North Carolina. Aerial surveys were conducted to document the seasonal distribution and estimated density of sea turtles and dolphins within Core Sound and portions of Pamlico Sound, and coastal waters extending one mile offshore. Sea Surface Temperature (SST) data for each survey were extracted from 1.4 km/pixel resolution Advanced Very High Resolution Radiometer remote images. A total of 92 turtles and 1,625 dolphins were sighted during 41 aerial surveys, conducted from July 2004 to April 2006. In the spring (March – May; 7.9°C to 21.7°C mean SST), the majority of turtles sighted were along the coast, mainly from the northern Core Banks northward to Cape Hatteras. By the summer (June – Aug.; 25.2°C to 30.8°C mean SST), turtles were fairly evenly dispersed along the entire survey range of the coast and Pamlico Sound, with only a few sightings in Core Sound. In the autumn (Sept. – Nov.; 9.6°C to 29.6°C mean SST), the majority of turtles sighted were along the coast and in eastern Pamlico Sound; however, fewer turtles were observed along the coast than in the summer. No turtles were seen during the winter surveys (Dec. – Feb.; 7.6°C to 11.2°C mean SST). The estimated mean surface density of turtles was highest along the coast in the summer of 2005 (0.615 turtles/km², SE = 0.220). In Core and Pamlico Sounds the highest mean surface density occurred during the autumn of 2005 (0.016 turtles/km², SE = 0.009). The mean seasonal abundance estimates were always highest in the coastal region, except in the winter when turtles were not sighted in either region. For Pamlico Sound, surface densities were always greater in the eastern than western section. The range of mean temperatures at which turtles were sighted was 9.68°C to 30.82°C. The majority of turtles sighted were within water ≥ 11°C. Dolphins were observed within estuarine waters and along the coast year-round; however, there were some general seasonal movements. In particular, during the summer sightings decreased along the coast and dolphins were distributed throughout Core and Pamlico Sounds, while in the winter the majority of dolphins were located along the coast and in southeastern Pamlico Sound. Although relative numbers changed seasonally between these areas, the estimated mean surface density of dolphins was highest along the coast in the spring of 2006 (9.564 dolphins/km², SE = 5.571). In Core and Pamlico Sounds the highest mean surface density occurred during the autumn of 2004 (0.192 dolphins/km², SE = 0.066). The estimated mean surface density of dolphins was lowest along the coast in the summer of 2004 (0.461 dolphins/km², SE = 0.294). The estimated mean surface density of dolphins was lowest in Core and Pamlico Sounds in the summer of 2005 (0.024 dolphins/km², SE = 0.011). In Pamlico Sound, estimated surface densities were greater in the eastern section except in the autumn. Dolphins were sighted throughout the entire range of mean SST (7.60°C to 30.82°C), with a tendency towards fewer dolphins sighted as water temperatures increased. Based on the findings of this study, sea turtles are most likely to be encountered within the OPAREAs when SST is ≥ 11°C. Since sea turtle distributions are generally limited by water temperature, knowing the SST of a given area is a useful predictor of sea turtle presence. Since dolphins were observed within estuarine waters year-round and throughout the entire range of mean SST’s, they likely could be encountered in the OPAREAs any time of the year. Although our findings indicated the greatest number of dolphins to be present in the winter and the least in the summer, their movements also may be related to other factors such as the availability of prey. (PDF contains 28 pages

The Spectral Correlation Function -- A New Tool for Analyzing Spectral-Line Maps

The "spectral correlation function" analysis we introduce in this paper is a new tool for analyzing spectral-line data cubes. Our initial tests, carried out on a suite of observed and simulated data cubes, indicate that the spectral correlation function [SCF] is likely to be a more discriminating statistic than other statistical methods normally applied. The SCF is a measure of similarity between neighboring spectra in the data cube. When the SCF is used to compare a data cube consisting of spectral-line observations of the ISM with a data cube derived from MHD simulations of molecular clouds, it can find differences that are not found by other analyses. The initial results presented here suggest that the inclusion of self-gravity in numerical simulations is critical for reproducing the correlation behavior of spectra in star-forming molecular clouds.Comment: 29 pages, including 4 figures (tar file submitted as source) See also: http://cfa-www.harvard.edu/~agoodman/scf/velocity_methods.htm

Numerical simulations of the Princeton magneto-rotational instability experiment with conducting axial boundaries

We investigate numerically the Princeton magneto-rotational instability (MRI) experiment and the effect of conducting axial boundaries or endcaps. MRI is identified and found to reach a much higher saturation than for insulating endcaps. This is probably due to stronger driving of the base flow by the magnetically rather than viscously coupled boundaries. Although the computations are necessarily limited to lower Reynolds numbers ($\Re$) than their experimental counterparts, it appears that the saturation level becomes independent of $\Re$ when $\Re$ is sufficiently large, whereas it has been found previously to decrease roughly as $\Re^{-1/4}$ with insulating endcaps. The much higher saturation levels will allow for the first positive detection of MRI beyond its theoretical and numerical predictions

Trends and Regional Variation in Hip, Knee and Shoulder Replacement

Analyzes patterns in underuse or overuse of joint replacements among Medicare beneficiaries by geographic regions and race/ethnicity. Explores underlying factors and highlights the need for physician and patient education and shared decision making

The Effect of Projection on Derived Mass-Size and Linewidth-Size Relationships

Power law mass-size and linewidth-size correlations, two of "Larson's laws," are often studied to assess the dynamical state of clumps within molecular clouds. Using the result of a hydrodynamic simulation of a molecular cloud, we investigate how geometric projection may affect the derived Larson relationships. We find that large scale structures in the column density map have similar masses and sizes to those in the 3D simulation (PPP). Smaller scale clumps in the column density map are measured to be more massive than the PPP clumps, due to the projection of all emitting gas along lines of sight. Further, due to projection effects, structures in a synthetic spectral observation (PPV) may not necessarily correlate with physical structures in the simulation. In considering the turbulent velocities only, the linewidth-size relationship in the PPV cube is appreciably different from that measured from the simulation. Including thermal pressure in the simulated linewidths imposes a minimum linewidth, which results in a better agreement in the slopes of the linewidth-size relationships, though there are still discrepancies in the offsets, as well as considerable scatter. Employing commonly used assumptions in a virial analysis, we find similarities in the computed virial parameters of the structures in the PPV and PPP cubes. However, due to the discrepancies in the linewidth- and mass- size relationships in the PPP and PPV cubes, we caution that applying a virial analysis to observed clouds may be misleading due to geometric projection effects. We speculate that consideration of physical processes beyond kinetic and gravitational pressure would be required for accurately assessing whether complex clouds, such as those with highly filamentary structure, are bound.Comment: 25 pages, including 7 Figures; Accepted for publication in Ap

An Interactive Knowledge-based Multi-objective Evolutionary Algorithm Framework for Practical Optimization Problems

Experienced users often have useful knowledge and intuition in solving real-world optimization problems. User knowledge can be formulated as inter-variable relationships to assist an optimization algorithm in finding good solutions faster. Such inter-variable interactions can also be automatically learned from high-performing solutions discovered at intermediate iterations in an optimization run - a process called innovization. These relations, if vetted by the users, can be enforced among newly generated solutions to steer the optimization algorithm towards practically promising regions in the search space. Challenges arise for large-scale problems where the number of such variable relationships may be high. This paper proposes an interactive knowledge-based evolutionary multi-objective optimization (IK-EMO) framework that extracts hidden variable-wise relationships as knowledge from evolving high-performing solutions, shares them with users to receive feedback, and applies them back to the optimization process to improve its effectiveness. The knowledge extraction process uses a systematic and elegant graph analysis method which scales well with number of variables. The working of the proposed IK-EMO is demonstrated on three large-scale real-world engineering design problems. The simplicity and elegance of the proposed knowledge extraction process and achievement of high-performing solutions quickly indicate the power of the proposed framework. The results presented should motivate further such interaction-based optimization studies for their routine use in practice.Comment: 15 pages, 10 figures in main document; 6 pages, 6 figures in supplementary documen