An assessment of two decades of contaminant monitoring in the Nation’s Coastal Zone.

Executive Summary: Information found in this report covers the years 1986 through 2005. Mussel Watch began monitoring a suite of trace metals and organic contaminants such as DDT, PCBs and PAHs. Through time additional chemicals were added, and today approximately 140 analytes are monitored. The Mussel Watch Program is the longest running estuarine and coastal pollutant monitoring effort conducted in the United States that is national in scope each year. Hundreds of scientific journal articles and technical reports based on Mussel Watch data have been written; however, this report is the first that presents local, regional and national findings across all years in a Quick Reference format, suitable for use by policy makers, scientists, resource managers and the general public. Pollution often starts at the local scale where high concentrations point to a specific source of contamination, yet some contaminants such as PCBs are atmospherically transported across regional and national scales, resulting in contamination far from their origin. Findings presented here showed few national trends for trace metals and decreasing trends for most organic contaminants; however, a wide variety of trends, both increasing and decreasing, emerge at regional and local levels. For most organic contaminants, trends have resulted from state and federal regulation. The highest concentrations for both metal and organic contaminants are found near urban and industrial areas. In addition to monitoring throughout the nation’s coastal shores and Great Lakes, Mussel Watch samples are stored in a specimen bank so that trends can be determined retrospectively for new and emerging contaminants of concern. For example, there is heightened awareness of a group of flame retardants that are finding their way into the marine environment. These compounds, known as polybrominated diphenyl ethers (PBDEs), are now being studied using historic samples from the specimen bank and current samples to determine their spatial distribution. We will continue to use this kind of investigation to assess new contaminant threats. We hope you find this document to be valuable, and that you continue to look towards the Mussel Watch Program for information on the condition of your coastal waters. (PDF contains 118 pages

EEMP Summary for NIF shot: N101004-002-999

Abstract not provide

Computers Play the Beer Game: Can Artificial Agents Manage Supply Chains?

We model an electronic supply chain managed by artificial agents. We investigate whether artificial agents do better than humans when playing the MIT Beer Game. Can the artificial agents discover good and effective business strategies in supply chains both in stationary and non-stationary environments? Can the artificial agents discover policies that mitigate the Bullwhip effect? In particular, we study the following questions: Can agents learn reasonably good policies in the face of deterministic demand with fixed lead time? Can agents cope reasonably well in the face of stochastic demand with stochastic lead time? Can agents learn and adapt in various contexts to play the game? Can agents cooperate across the supply chain

UNLV New Horizons Band & UNLV Community Concert Band

Program listing performers and works performed

A Search for Trypanosomes in Mourning Doves

Diamond (1954) described a technique for the detection of trypanosomes in geese. We used a similar technique in the search for trypanosomes in each of 64 mourning doves (Zenaidura macroura) collected on September 1-2, 1960, 4 miles west of Celina, Denton County, Texas. The condylar surfaces of the femur, sterilized with alcohol, were removed with sterile scissors, and the marrow, forced from the femur with a hemostat, was collected with a sterile nichrome wire. The inoculum was incubated in the blood agar, broth overlay medium described by Diamond. One sample of the culture was stained on the 6th day of incubation, and a second sample was stained on the 14th day

Nasal Mites of the Mourning Dove

Crossley (1952) described a species of nasal mite, Neonyssus zenaidurae, from the mourning dove (Zenaidura macroura) collected in Texas and Georgia. In his study mites were obtained from 10 of 19 doves examined. Owen (1958) found this species of mite in mourning doves collected in Alabama. He reported an infestation of 4 out of 10 birds (average: 1.5 mites per dove), for one county; and 3 of 10 birds (average: 2.6 mites per dove) for another county. Our method of recovery was similar to that described by Owen. The nasal cavities were separated sagitally, with scissors, from the tip of the beak to the anterior region of the brain. Each half was examined under a wide-field microscope. The parasites when present were found embedded in the mucous secretions and upon the tissues of the nasal cavities. Dissecting needles were used to extricate the specimens and to place them in 70% alcohol. The mites were macerated in 20% KOH for 24 hours to remove adhering tissues. Hoyer\u27s medium is recommended for mounting; if the specimen is mounted in Hoyer\u27s medium and heated soon after the mounting procedures are complete, maceration in KOH is unnecessary

Infanticide and Human Self Domestication

Our hypothesis, which is largely complementary to Wrangham, is that band elders engaged in infanticide and direct and indirect child homicide against the offspring of reactive aggressive adults through decisions during the foraging period of the Middle and Upper Pleistocene. We hypothesize that elders may have targeted the offspring of reactively aggressive males (and females) as retaliation for behaviors that were not good for the elders or their offspring and because surreptitiously killing the offspring of violent males was much less dangerous to the elders than killing the violent males. Such retaliation could have selected against reactive aggression as a genetic consequence. In other words, infanticide could have been Wrangham\u27s “different stimulus” initiating HSD. Our argument is that the earliest language of single words (kill), and certainly the crude compounds, “kill-baby or “like father” and “like son,” would be enough to organize the “execution of an infant” in a relatively secluded birthing site. Infanticide effectively becomes a second moment of mate choice. Such an action could have been relatively safely concealed since an infant dying in childbirth in forager socio-ecological conditions was likely not unusual (see below). The relative simplicity of the language capacities necessary for infanticide contrasts with the more sophisticated language necessary to organize a safe coup and execution of a reactively aggressive alpha male

Learning the Designer's Preferences to Drive Evolution

This paper presents the Designer Preference Model, a data-driven solution that pursues to learn from user generated data in a Quality-Diversity Mixed-Initiative Co-Creativity (QD MI-CC) tool, with the aims of modelling the user's design style to better assess the tool's procedurally generated content with respect to that user's preferences. Through this approach, we aim for increasing the user's agency over the generated content in a way that neither stalls the user-tool reciprocal stimuli loop nor fatigues the user with periodical suggestion handpicking. We describe the details of this novel solution, as well as its implementation in the MI-CC tool the Evolutionary Dungeon Designer. We present and discuss our findings out of the initial tests carried out, spotting the open challenges for this combined line of research that integrates MI-CC with Procedural Content Generation through Machine Learning.Comment: 16 pages, Accepted and to appear in proceedings of the 23rd European Conference on the Applications of Evolutionary and bio-inspired Computation, EvoApplications 202

On a Feasible–Infeasible Two-Population (FI-2Pop) Genetic Algorithm for Constrained Optimization: Distance Tracing and no Free Lunch

We explore data-driven methods for gaining insight into the dynamics of a two-population genetic algorithm (GA), which has been effective in tests on constrained optimization problems. We track and compare one population of feasible solutions and another population of infeasible solutions. Feasible solutions are selected and bred to improve their objective function values. Infeasible solutions are selected and bred to reduce their constraint violations. Interbreeding between populations is completely indirect, that is, only through their offspring that happen to migrate to the other population. We introduce an empirical measure of distance, and apply it between individuals and between population centroids to monitor the progress of evolution. We find that the centroids of the two populations approach each other and stabilize. This is a valuable characterization of convergence. We find the infeasible population influences, and sometimes dominates, the genetic material of the optimum solution. Since the infeasible population is not evaluated by the objective function, it is free to explore boundary regions, where the optimum is likely to be found. Roughly speaking, the No Free Lunch theorems for optimization show that all blackbox algorithms (such as Genetic Algorithms) have the same average performance over the set of all problems. As such, our algorithm would, on average, be no better than random search or any other blackbox search method. However, we provide two general theorems that give conditions that render null the No Free Lunch results for the constrained optimization problem class we study. The approach taken here thereby escapes the No Free Lunch implications, per se