The effects of site selected variables on human responses to traffic noise,part III: Community size by socio-economic status by traffic noise level

This paper reports the results of the third part of a field study of human responses to traffic noise. The influence of traffic noise level, community size, and socio-economic status were investigated in a controlled manner determined by subject selection procedures. Human responses were obtained from interviewer administered questionnaires, and were as spatially and temporally coincident with the noise measurements as possible. Noise measurements were obtained from several days of rapidly sampled digital recordings. Traffic noise level was the major predictor of the intensity of elicited responses. A number of other significant effects were observed largely related to community size. These were explained as due to parallel variations in the perceived necessity of vehicles, the annoyance with aircraft noise, and the logarithm of the vehicle flow rate. The results did demonstrate effects related to community size, and thus it is unwise to extrapolate the results of large city noise studies to small communities and rural areas.     

Rate constants for the reaction OH + CO as functions of temperature and water concentration

Rate constants for the reaction OH + CO have been measured as functions of temperature (340–1220 K) and water concentration in the presence of 1 atm of argon. Results at zero water concentration yield the expression, log k_? (cm³ molecule^?1 S^?1) = ?12.96 + 4.7 × 10^?4 T, for the reaction rate constant as a function of temperature. These results are in very good agreement with previous direct measurements and in reasonable agreement with flame and shock tube measurements. Explanations are offered for the involvement of the water molecule in the present experiments and earlier measurements from this laboratory throughout the entire temperature range. Results are consistent with previous results showing little, if any, pressure effect of Ar on the reaction up to 1 atm of Ar.     

Intensity Capping: a simple method to improve cross-correlation PIV results

A common source of error in particle image velocimetry (PIV) is the presence of bright spots within the images. These bright spots are characterized by grayscale intensities much greater than the mean intensity of the image and are typically generated by intense scattering from seed particles. The displacement of bright spots can dominate the cross-correlation calculation within an interrogation window, and may thereby bias the resulting velocity vector. An efficient and easy-to-implement image-enhancement procedure is described to improve PIV results when bright spots are present. The procedure, called Intensity Capping, imposes a user-specified upper limit to the grayscale intensity of the images. The displacement calculation then better represents the displacement of all particles in an interrogation window and the bias due to bright spots is reduced. Four PIV codes and a large set of experimental and simulated images were used to evaluate the performance of Intensity Capping. The results indicate that Intensity Capping can significantly increase the number of valid vectors from experimental image pairs and reduce displacement error in the analysis of simulated images. A comparison with other PIV image-enhancement techniques shows that Intensity Capping offers competitive performance, low computational cost, ease of implementation, and minimal modification to the images.     

Understanding the electronic structure of 4d metal complexes: from molecular spinors to L-edge spectra of a di-Ru catalyst

L(2,3)-edge X-ray absorption spectroscopy (XAS) has demonstrated unique capabilities for the analysis of the electronic structure of di-Ru complexes such as the blue dimer cis,cis-[Ru(III)(2)O(H(2)O)(2)(bpy)(4)](4+) water oxidation catalyst. Spectra of the blue dimer and the monomeric [Ru(NH(3))(6)](3+) model complex show considerably different splitting of the Ru L(2,3) absorption edge, which reflects changes in the relative energies of the Ru 4d orbitals caused by hybridization with a bridging ligand and spin-orbit coupling effects. To aid the interpretation of spectroscopic data, we developed a new approach, which computes L(2,3)-edges XAS spectra as dipole transitions between molecular spinors of 4d transition metal complexes. This allows for careful inclusion of the spin-orbit coupling effects and the hybridization of the Ru 4d and ligand orbitals. The obtained theoretical Ru L(2,3)-edge spectra are in close agreement with experiment. Critically, existing single-electron methods (FEFF, FDMNES) broadly used to simulate XAS could not reproduce the experimental Ru L-edge spectra for the [Ru(NH(3))(6)](3+) model complex nor for the blue dimer, while charge transfer multiplet (CTM) calculations were not applicable due to the complexity and low symmetry of the blue dimer water oxidation catalyst. We demonstrated that L-edge spectroscopy is informative for analysis of bridging metal complexes. The developed computational approach enhances L-edge spectroscopy as a tool for analysis of the electronic structures of complexes, materials, catalysts, and reactive intermediates with 4d transition metals.     

Synthetic studies toward spiroleucettadine

Synthetic hydroxydienone precursors to spiroleucettadine and to an isomer thereof resist cyclization to the orthoamide-type functionality present in the proposed structure of the natural product.     

Orienteering for electioneering

In this paper, we introduce a combinatorial optimization problem that models the investment decision a political candidate faces when treating his or her opponents’ campaign plans as given. Our formulation accounts for both the time cost of traveling between districts and the time expended while campaigning within districts. We describe a polynomial-time algorithm that computes a $(2+?)$-approximation to the optimal solution of a discrete version of our problem by reducing the problem to another combinatorial optimization problem known as Orienteering.     

Stretch‐Induced Drug Delivery from Superhydrophobic Polymer Composites: Use of Crack Propagation Failure Modes for Controlling Release Rates

The concept of using crack propagation in polymeric materials to control drug release and its first demonstration are reported. The composite drug delivery system consists of highly‐textured superhydrophobic electrosprayed microparticle coatings, composed of biodegradable and biocompatible polymers poly(caprolactone) and poly(glycerol monostearate carbonate‐co‐caprolactone), and a cellulose/polyester core. The release of entrapped agents is controlled by the magnitude of applied strain, resulting in a graded response from water infiltration through the propagating patterned cracks in the coating. Strain‐dependent delivery of the anticancer agents cisplatin and 7‐ethyl‐10‐hydroxycamptothecin to esophageal cancer cells (OE33) in vitro is observed. Finally the device is integrated with an esophageal stent to demonstrate delivery of fluorescein diacetate, using applied tension, to an ex vivo esophagus.     

Stochastic modeling of tire–snow interaction using a polynomial chaos approach

Developing accurate models to simulate the interaction between pneumatic tires and unprepared terrain is a demanding task. Such tire–terrain contact models are often used to analyze the mobility of a wheeled vehicle on a given type of soil, or to predict the vehicle performance under specified operational conditions (as related to the vehicle and tires, as well as to the running support). Due to the complex nature of the interaction between a tire and off-road environment, one usually needs to make simplifying assumptions when modeling such an interaction. It is often assumed that the tire–terrain interaction can be captured using a deterministic approach, which means that one assumes fixed values for several vehicle or tire parameters, and expects exact responses from the system. While this is rarely the case in real life, it is nevertheless a necessary step in the modeling process of a deterministic framework. In reality, the external excitations affecting the system, as well as the values of the vehicle and terrain parameters, do not have fixed values, but vary in time or space. Thus, although a deterministic model may capture the response of the system given one set of deterministic values for the system parameters, inputs, etc., this is in fact only one possible realization of the multitude of responses that could occur in reality. The goal of our study is to develop a mathematically sound methodology to improve the prediction of the tire–snow interaction by considering the variability of snow depth and snow density, which will lead to a significantly better understanding and a more realistic representation of tire–snow interaction. We constructed stochastic snow models using a polynomial chaos approach developed at Virginia Tech, to account for the variability of snow depth and of snow density. The stochastic tire–snow models developed are based on the extension of two representative deterministic tire–snow interaction models developed at the University of Alaska, including the pressure–stress deterministic model and the hybrid (on-road extended for off-road) deterministic model. Case studies of a select combination of uncertainties were conducted to quantify the uncertainties of the interfacial forces, sinkage, entry angle, and the friction ellipses as a function of wheel load, longitudinal slip, and slip angle. The simulation results of the stochastic pressure–stress model and the stochastic hybrid model are compared and analyzed to identify the most convenient tire design stage for which they are more suitable. The computational efficiency of the two models is also discussed.