A Monte Carlo simulation study of the mechanical and conformational properties of networks of helical polymers. I. General concepts

We study the mechanical and conformational properties of networks of helical polymers with a combination of Monte Carlo simulations based on the Wang-Landau algorithm and the three-chain model. We find that the stress-strain behavior of these networks has novel features not observed in typical networks made of synthetic polymers. In particular, we find that as these networks are stretched they first strengthen, then soften and finally strengthen again. This non-monotonic behavior of the stress correlates with the one of the helical content and is rationalized by the elongation-induced formation and melting of the helical structure of the polymer. We complement these results with a study of other conformational properties of the polymer strands that clarify the molecular mechanisms behind the mechanical behavior of these networks. Finally, we present a qualitative comparison of some of our results with the theoretical ones recently reported by Kutter and Terentjev.     

The Effects of H2O, CO and CO2 on the H2 Permeance and Surface Characteristics of 1 mm Thick Pd80wt%Cu Membranes

The hydrogen permeance of 1 mm-thick Pd_80wt%Cu foils was measured in the presence of equimolar mixtures of H₂ with CO, CO₂ or H₂O over the temperature and total pressure ranges of 623–1,173 K and 0.62–2.86 MPa, respectively. In all cases, permeance losses at 623 and 738 K were very modest. At higher temperatures, more significant decreases in membrane permeance were observed with the highest reduction of about 50% occurring when macroscopic carbon deposition occurred on the membrane surface during H₂–CO exposure at 908 K. The more worrisome effects of exposure to these gases, however, were the micron-scale surface defects observed at 908 and 1,038 K. Although the 1 mm thick disk membranes retained their mechanical integrity, such defects could cause catastrophic failure of ultra-thin, Pd–Cu membranes (1–5 μm thick) deposited on porous substrates.     

Evaluation of passive microwave snow water equivalent algorithms in the depth hoar-dominated snowpack of the Kuparuk River Watershed, Alaska, USA

This research investigates the utility of passive microwave remote sensing instruments to accurately determine snow water equivalent (SWE) over large spatial extents. Three existing Special Sensor Microwave Imager (SSM/I) snow water equivalent algorithms produced by Chang, Tait and Goodison were evaluated for their ability to determine snow water equivalent in a snowpack containing substantial depth hoar, large faceted snow crystals. The Kuparuk River Watershed (8140 km²) test site on the North Slope of Alaska was chosen for its snowpack containing a think depth hoar layer and long history of ground truth data. A new regional snow water equivalent algorithm was developed to determine if it could produce better results than the existing algorithms in an area known to contain significant depth hoar. The four algorithms were tested to see how well they could determine snow water equivalent: (1) on a per pixel basis, (2) across swath-averaged spatial bands of approximately 850 km², and (3) on a watershed scale. The algorithms were evaluated to see if they captured the annual spatial distribution in snow water equivalent over the watershed. Results show that the algorithms developed by Chang and from this research are generally within 3 cm of the spatially averaged snow water equivalents over the entire watershed. The algorithms produced by Chang, Tait, and in this research were able to predict the basin-wide ground measured snow water equivalent value within a percent error range from −32.4% to 24.4% in the years with a typical snowpack. None of the algorithms produce accurate results on a pixel-by-pixel scale, with errors ranging from −26% to 308%.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Ionization of Acetylacetone in Me2SO—Water Mixtures. Reactivity—Selectivity Principle or Principle of Imperfect Synchronization?

Rate constants for the reversible deprotonation of acetylacetone were measured in carboxylate and amine buffers in water and in 50%, 90% and 95% Me₂SO at 20°C. The Brønsted plot for the carboxylate ions is curved in the Me₂SO—water mixtures, but straight in water. The curvature is in the direction predicted by the Reactivity—Selectivity Principle (RSP). However, the Brønsted plot for the reaction with primary amines is straight in all solvents. This suggests that the curvature observerd with the carboxylate ions is caused by loss of solvation of the base; this loss of solvation is ahead of bond formation in the transition state rather than being a manifestation of the RSP. (Note that all Brønsted plots are based on pK_a values measured in the respective solvents.) The intrinsic rate constant (k₀) for proton transfer increases with the addition of Me₂SO, and more so with the carboxylate buffers than with the amines. This increase in k₀ is attributed to delayed solvation of the developing enolate ion in the transition state; with the carboxylate buffers, an additional factor is the early loss of solvation of the base. The various solvation effects observed in this study can all be understood in the context of the Principle of Imperfect Synchronization (PIS).     

The role of experience in liking "read-to-drink" alcoholic beverages.

Ready-to-drinks (RTDs) are composed of an alcoholic component and a soft-drink base and are primarily consumed by a youth market. The authors explored whether liking and experience with an RTD soft-drink base predicts liking for the RTD. Participants (N=350) from ages 12 to 30 years sampled 3 RTDs and their respective soft-drink and alcoholic components. For milk- and fruit-based RTDs, liking for and familiarity with their soft-drink base was the best predictor of liking for and familiarity with the RTD itself. For the Coke-based RTD, familiarity with and liking for bourbon best predicted familiarity with and liking for the RTD. All of these effects were consistent across blind and nonblind testing. The authors' results suggest that where there is perceptual similarity between the RTD and its soft-drink base, these beverages may provide an easy transition into alcohol consumption for novice drinkers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Defining Yield from Bender Element Measurements in Triaxial Stress Probe Experiments

This paper describes the elastic response of a block sample of compressible Chicago glacial clay under a variety of stresses and its relationship with the deformation characteristics at relatively large strains. The elastic shear stiffness was obtained from bender element tests during consolidation and shearing in drained triaxial stress probe tests. An empirical correlation was established based on the elastic shear stiffness in a preyield condition. By comparing the empirical correlation with the measured elastic shear stiffness in the stress region during probing, the changes of elastic shear stiffness were investigated. The departure of elastic shear stiffness from values computed by the empirical relation based on K0 loading directly relates to the yielding characteristics of the clay. The large-scale change of soil structure at yielding alters the well-established relationship between the elastic shear stiffness and stresses in the preyield condition. The mechanical yielding response of clays can be detected based on the systematic analysis of the elastic shear wave velocities.     

A novel method for determination of polyester end-groups by NMR spectroscopy

An efficient, convenient and quantitative method for characterising polyester end-groups is described. We have found that trichloroacetyl isocyanate (TAI) reacts rapidly and quantitatively with both carboxyl [C(O)OH] and hydroxyl (OH) chain ends to form derivatives that can be readily determined by ¹H NMR spectroscopy. The TAI capped end-groups give rise to characteristic imidic NH resonances in a normally clear region of the ¹H NMR spectrum [δ∼10-11.5 for C(O)-O-C(O)-NH-C(O)CCl₃ from C(O)OH, δ∼8-9 for O-C(O)-NH-C(O)CCl₃ from OH]. The method has been successfully applied to quantitative determination of the end-groups of a wide variety of oligomeric polyesters. It has also been applied to higher molecular weight polyesters including commercial, bottle grade, poly(ethylene terephthalate) (PET) and PET based copolyesters (e.g. PETG).