Factors that influence changes in temporal and spatial accumulation of debris on an estuarine shoreline, Cliftwood beach, New Jersey, USA

A field investigation was conducted on an estuarine shoreline in Raritan Bay, New Jersey to identify the temporal and spatial distribution changes in accumulation of marine debris, and the factors that influence these changes. Methodology consists of 12-monthly collections of debris and profile data, and collection of local climatological and tide data. Debris was classified by type, length, weight, fragmentation, and probable function and weathering noted for each collected item. Wind roses were constructed to determine dominant wind speed and direction and wind characteristics for time intervals between field sampling. Plastics are the primary component of debris; glass and styrofoam are common. Debris was small, light, and fragmented, and 74.2% of plastics were consumer-related. Beach usage appears to be the main source of debris but winds may transport wrack debris \u3c 5.0 g beyond wrack lines. A cross-shore pattern of spatial distribution of debris exists due to movement by wrack lines and high onshore wind speeds and wind direction. Debris type, sub-environments, beach elevation and debris weight influence cross-shore movement. Larger quantities found in the western portion of the beach compartment may be due to beach use, longshore transport of debris or both

Enhance Dopamine Autoreceptor Functioning During Blockade of Dopamine Transporters

Dopamine autoreceptors (DARs) and dopamine transporters (DATs) influence dopamine transmission in the brain\u27s mesolimbic pathway. Prior studies have focused on how activation of DARs influences trafficking of DATs, but how DATs influence DARs remains unclear. Male and female C57BL/6J mice received daily injections of either cocaine (DAT blocker) or saline for seven days then underwent stereotaxic surgery to obtain fixed potential amperometric recordings of DAR-mediated dopamine release. All mice received a mid-surgery injection of cocaine, and DAR-mediated dopamine release was assessed once more during maximal DAT blockade. The current study found that DAR functionality was increased during peak cocaine effects, suggesting DAR work harder to maintain homeostasis. Additionally, DAT function was increased following chronic cocaine exposure, but DAR functioning was unchanged, indicating DAR may be resistant to drug-induced alterations. Understanding the neurochemical mechanisms that control dopamine signaling is critical for informing treatment efforts for addiction, ADHD, and depression

Perkin Reaction: Rapid and Efficient Process Optimization Through a Microwave/Design of Experiments Couple

Microwave chemistry and a Design of Experiments (DOE) protocol were employed together in order to rapidly and efficiently optimize a modified Perkin reaction. Microwave heating significantly reduced the reaction time, and the DOE provided a statistically significant understanding of underlying process relationships in a minimum number of experimental runs. In all, the reaction time was reduced from1hour to 2 minutes, factors important to yield were identified, an interesting cross-term interaction was discovered, and it was demonstrated that the more economical sodium acetate trihydrate catalyst was a viable alternative to the more costly anhydrous sodium acetate

On a likelihood interpretation of adjusted profile likelihoods through refined predictive densities.

In this paper a second-order link between adjusted profile likelihoods and refinements of the estimative predictive density is shown. The result provides a new straightforward interpretation for modified profile likelihoods, that complements results in Severini (1998a) and in Pace and Salvan (2006). Moreover, it outlines a form of consistency to second order between likelihood theory and prediction in frequentist inference

A Neyman-Scott phenomenon in model discrimination.

The aim of this paper is to show through simulation that a Neyman-Scott phenomenon may occur in discriminating among separate stratified models. We focus on models which are scale families in each stratum. We consider traditional model selection procedures, such as the Akaike and Takeuchi information criteria, together with procedures based on the marginal likelihood and its Laplace approximation. We perform two simulation studies. Results indicate that, when the sample size in each stratum is fixed and the number of strata increases, correct selection probabilities for traditional model selection criteria may approach zero. On the other hand, model selection based on exact or approximate marginal likelihoods, that exploit invariance, can behave far better

Likelihood theory, prediction, model selection: asymptotic connections.

Plug-in estimation and corresponding refinements involving penalisation have been considered in various areas of parametric statistical inference. One major example is adjustment of the profile likelihood for inference in the presence of nuisance parameters. Another important setting is prediction, where improved estimative predictive densities have been recently developed. A third related setting is model selection, where information criteria based on penalisation of maximised likelihood have been proposed starting from the pioneering contribution of Akaike. The seminal contributions in the last setting predate those introducing the former two classes of procedures, and pertinent portions of literature seem to have evolved quite independently. The aim of this paper is to establish some simple asymptotic connections among these classes of procedures. In particular, all the three kinds of penalisations involved can be viewed as bias corrections of plug-in estimates of theoretical target criteria which are shown to be very closely connected. As a by-product, we obtain adjusted profile likelihoods from optimal predictive densities. Links between adjusted procedures in likelihood theory and model selection procedures are also briefly enquired throuh some simulation studies

East Urban Area Corridor Analysis Daviess County, Kentucky

The need for improved highway facilities in the east urban area of Daviess County, Kentucky, is analyzed in this study. The study focuses upon the need for alternative highway routes, due to the increased travel demands generated by a new Ohio River Bridge in eastern Daviess County. Also, the east urban area is forecasted to experience population and employment growth in the next decade, further necessitating the need for improving existing highways or constructing new corridors in the area. Various alternative alignments for an expressway are examined. The feasibility of upgrading existing highways in the east urban area is also analyzed. The study utilizes numerous transportation planning techniques, including the development of traffic projections, highway capacity analysis, cost estimates and land use and environmental impacts. The study includes original research and data collection in analyzing five alternatives. An alternative for constructing a new expressway in the east urban area of Daviess County is recommended