Influence of Silica Specific Surface Area on the Viscoelastic and Fatigue Behaviors of Silica-Filled SBR Composites.

This work aimed at studying the effect of a silica specific surface area (SSA), as determined by the nitrogen adsorption method, on the viscoelastic and fatigue behaviors of silica-filled styrene-butadiene rubber (SBR) composites. In particular, silica fillers with an SSA of 125 m2/g, 165 m2/g, and 200 m2/g were selected. Micro-computed X-ray tomography (µCT) was utilized to analyze the 3D morphology of the fillers within an SBR matrix prior to mechanical testing. It was found with this technique that the volume density of the agglomerates drastically decreased with decreasing silica SSA, indicating an increase in the silica dispersion state. The viscoelastic behavior was evaluated by dynamic mechanical analysis (DMA) and hysteresis loss experiments. The fatigue behavior was studied by cyclic tensile loading until rupture enabled the generation of Wöhler curves. Digital image correlation (DIC) was used to evaluate the volume strain upon deformation, whereas µCT was used to evaluate the volume fraction of the fatigue-induced cracks. Last, scanning electron microscopy (SEM) was used to characterize, in detail, crack mechanisms. The main results indicate that fatigue life increased with decreasing silica SSA, which was also accompanied by a decrease in hysteresis loss and storage modulus. SEM investigations showed that filler-matrix debonding and filler fracture were the mechanisms at the origin of crack initiation. Both the volume fraction of the cracks obtained by µCT and the volume strain acquired from the DIC increased with increasing SSA of silica. The results are discussed based on the prominent role of the filler network on the viscoelastic and fatigue damage behaviors of SBR composites.

Residential mobility and breast cancer in Marin County, California, USA.

Marin County (California, USA) has among the highest incidences of breast cancer in the U.S. A previously conducted case-control study found eight significant risk factors in participants enrolled from 1997-1999. These included being premenopausal, never using birth control pills, lower highest lifetime body mass index, having four or more mammograms from 1990-1994, beginning drinking alcohol after age 21, drinking an average two or more alcoholic drinks per day, being in the highest quartile of pack-years of cigarette smoking, and being raised in an organized religion. Previously conducted surveys provided residential histories; while statistic accounted for participants' residential mobility, and assessed clustering of breast cancer cases relative to controls based on the known risk factors. These identified specific cases, places, and times of excess breast cancer risk. Analysis found significant global clustering of cases localized to specific residential histories and times. Much of the observed clustering occurred among participants who immigrated to Marin County. However, persistent case-clustering of greater than fifteen years duration was also detected. Significant case-clustering among long-term residents may indicate geographically localized risk factors not accounted for in the study design, as well as uncertainty and incompleteness in the acquired addresses. Other plausible explanations include environmental risk factors and cases tending to settle in specific areas. A biologically plausible exposure or risk factor has yet to be identified.

Multiferroicity in an organic charge-transfer salt that is suggestive of electric-dipole-driven magnetism.

Multiferroics, showing simultaneous ordering of electrical and magnetic degrees of freedom, are remarkable materials as seen from both the academic and technological points of view. A prominent mechanism of multiferroicity is the spin-driven ferroelectricity, often found in frustrated antiferromagnets with helical spin order. There, as for conventional ferroelectrics, the electrical dipoles arise from an off-centre displacement of ions. However, recently a different mechanism, namely purely electronic ferroelectricity, where charge order breaks inversion symmetry, has attracted considerable interest. Here we provide evidence for ferroelectricity, accompanied by antiferromagnetic spin order, in a two-dimensional organic charge-transfer salt, thus representing a new class of multiferroics. We propose a charge-order-driven mechanism leading to electronic ferroelectricity in this material. Quite unexpectedly for electronic ferroelectrics, dipolar and spin order arise nearly simultaneously. This can be ascribed to the loss of spin frustration induced by the ferroelectric ordering. Hence, here the spin order is driven by the ferroelectricity, in marked contrast to the spin-driven ferroelectricity in helical magnets.

Forecasting the effect of the Amethyst initiative on college drinking.

BACKGROUND: A number of college presidents have endorsed the Amethyst Initiative, a call to consider lowering the minimum legal drinking age (MLDA). Our objective is to forecast the effect of the Amethyst Initiative on college drinking. METHODS: A system model of college drinking simulates MLDA changes through (i) a decrease in heavy episodic drinking (HED) because of the lower likelihood of students drinking in unsupervised settings where they model irresponsible drinking (misperception), and (ii) an increase in overall drinking among currently underage students because of increased social availability of alcohol (wetness). RESULTS: For the proportion of HEDs on campus, effects of large decreases in misperception of responsible drinking behavior were more than offset by modest increases in wetness. CONCLUSIONS: For the effect of lowering the MLDA, it appears that increases in social availability of alcohol have a stronger impact on drinking behavior than decreases in misperceptions.

Heavy episodic drinking on college campuses: does changing the legal drinking age make a difference?

OBJECTIVE: This article extends the compartmental model previously developed by Scribner et al. in the context of college drinking to a mathematical model of the consequences of lowering the legal drinking age. METHOD: Using data available from 32 U.S. campuses, the analyses separate underage and legal age drinking groups into an eight-compartment model with different alcohol availability (wetness) for the underage and legal age groups. The model evaluates the likelihood that underage students will incorrectly perceive normative drinking levels to be higher than they actually are (i.e., misperception) and adjust their drinking accordingly by varying the interaction between underage students in social and heavy episodic drinking compartments. RESULTS: The results evaluate the total heavy episodic drinker population and its dependence on the difference in misperception, as well as its dependence on underage wetness, legal age wetness, and drinking age. CONCLUSIONS: Results suggest that an unrealistically extreme combination of high wetness and low enforcement would be needed for the policies related to lowering the drinking age to be effective.

Local indicators of geocoding accuracy (LIGA): theory and application.

BACKGROUND: Although sources of positional error in geographic locations (e.g. geocoding error) used for describing and modeling spatial patterns are widely acknowledged, research on how such error impacts the statistical results has been limited. In this paper we explore techniques for quantifying the perturbability of spatial weights to different specifications of positional error. RESULTS: We find that a family of curves describes the relationship between perturbability and positional error, and use these curves to evaluate sensitivity of alternative spatial weight specifications to positional error both globally (when all locations are considered simultaneously) and locally (to identify those locations that would benefit most from increased geocoding accuracy). We evaluate the approach in simulation studies, and demonstrate it using a case-control study of bladder cancer in south-eastern Michigan. CONCLUSION: Three results are significant. First, the shape of the probability distributions of positional error (e.g. circular, elliptical, cross) has little impact on the perturbability of spatial weights, which instead depends on the mean positional error. Second, our methodology allows researchers to evaluate the sensitivity of spatial statistics to positional accuracy for specific geographies. This has substantial practical implications since it makes possible routine sensitivity analysis of spatial statistics to positional error arising in geocoded street addresses, global positioning systems, LIDAR and other geographic data. Third, those locations with high perturbability (most sensitive to positional error) and high leverage (that contribute the most to the spatial weight being considered) will benefit the most from increased positional accuracy. These are rapidly identified using a new visualization tool we call the LIGA scatterplot.Herein lies a paradox for spatial analysis: For a given level of positional error increasing sample density to more accurately follow the underlying population distribution increases perturbability and introduces error into the spatial weights matrix. In some studies positional error may not impact the statistical results, and in others it might invalidate the results. We therefore must understand the relationships between positional accuracy and the perturbability of the spatial weights in order to have confidence in a study's results.

A systems approach to college drinking: development of a deterministic model for testing alcohol control policies.

OBJECTIVE: The misuse and abuse of alcohol among college students remain persistent problems. Using a systems approach to understand the dynamics of student drinking behavior and thus forecasting the impact of campus policy to address the problem represents a novel approach. Toward this end, the successful development of a predictive mathematical model of college drinking would represent a significant advance for prevention efforts. METHOD: A deterministic, compartmental model of college drinking was developed, incorporating three processes: (1) individual factors, (2) social interactions, and (3) social norms. The model quantifies these processes in terms of the movement of students between drinking compartments characterized by five styles of college drinking: abstainers, light drinkers, moderate drinkers, problem drinkers, and heavy episodic drinkers. Predictions from the model were first compared with actual campus-level data and then used to predict the effects of several simulated interventions to address heavy episodic drinking. RESULTS: First, the model provides a reasonable fit of actual drinking styles of students attending Social Norms Marketing Research Project campuses varying by "wetness" and by drinking styles of matriculating students. Second, the model predicts that a combination of simulated interventions targeting heavy episodic drinkers at a moderately "dry" campus would extinguish heavy episodic drinkers, replacing them with light and moderate drinkers. Instituting the same combination of simulated interventions at a moderately "wet" campus would result in only a moderate reduction in heavy episodic drinkers (i.e., 50% to 35%). CONCLUSIONS: A simple, five-state compartmental model adequately predicted the actual drinking patterns of students from a variety of campuses surveyed in the Social Norms Marketing Research Project study. The model predicted the impact on drinking patterns of several simulated interventions to address heavy episodic drinking on various types of campuses.

Space-time visualization and analysis in the Cancer Atlas Viewer.

This article describes the Cancer Atlas Viewer: free, downloadable software for the exploration of United States cancer mortality data. We demonstrate the software by exploring spatio-temporal patterns in colon cancer mortality rates for African-American and white females and males in the southeastern United States over the period 1970-1995. We compare the results of two cluster statistics: the local Moran and the local G*, through time.. Overall, the two statistics reach similar conclusions for most locations, although where they disagree reveals some interesting patterns in the data. There are only two persistent clusters of colon cancer mortality, and these are clusters of low values.