Psychology and domestic violence around the world.

Psychologists around the world have made contributions in research, clinical assessment, and intervention and prevention of domestic violence. Although each country has unique factors that determine the services and resources available to battered women, children exposed to domestic violence, and abusive partners, it is the interaction among gender, political structure, religious beliefs, attitudes toward violence in general, and violence toward women, as well as state-sponsored violence, such as civil conflicts and wars, and the migration within and between countries that ultimately determine women's vulnerability and safety. This article reviews the latest psychological research and applications to intervention and prevention programs. An introduction to the various articles that compose this international perspectives section is also included. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ain't misbehavin': The effects of age and intentionality on judgments about misconduct.

In 2 person perception experiments, young and older perceivers read a scenario about a young or old female target who leaves a store without paying for a hat. In Experiment 1, the target claims she forgot she was wearing the hat when questioned by the manager. Perceivers thought the manager would have greater sympathy, less anger, and would recommend less punishment when the target was old. In Experiment 2, the target clearly forgot to pay for the hat, clearly stole it, or had ambiguous intentions. In the ambiguous condition, perceivers attributed the young target's behavior more to stealing and the old target's behavior more to forgetting. In the forget condition, young perceivers had equal sympathy for the young and old targets and held them similarly responsible, but older perceivers had greater sympathy for the forgetful old target and held her less responsible than they did the forgetful young target. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Run-Time Validation of Speculative Optimizations using CVC.

Translation validation is an approach for validating the output of optimizing compilers. Rather than verifying the compiler itself, translation validation mandates that every run of the compiler generate a formal proof that the produced target code is a correct implementation of the source code. Speculative loop optimizations are aggressive optimizations which are only correct under certain conditions which cannot be validated at compile time. We propose using an automatic theorem prover together with the translation validation framework to automatically generate run-time tests for such speculative optimizations. This run-time validation approach must not only detect the conditions under which an optimization generates incorrect code, but also provide a way to recover from the optimization without aborting the program or producing an incorrect result. In this paper, we apply the run-time validation technique to a class of speculative reordering transformations and give some initial results of run-time tests generated by the theorem prover CVC.     

Determination of absorption coefficients for chlorophyll a,phycocyanin, mineral matter and CDOM from three central Indiana reservoirs

Absorption coefficients are used in semi-empirical and bio-optical models to estimate various optically active constituents in water. This study determines the mass-specific absorption coefficients of chlorophyll a (a*_chl), phycocyanin (a*_pc), minerals (a*_m), and chromophoric dissolved organic matter (CDOM; a*_CDOM) and the absorption coefficient for CDOM (a_CDOM) for three central Indiana reservoirs. Absorption spectra were collected using a Shimadzu spectrophotometer equipped with a Spectralon coated integrating sphere. Quantitative measurements from either fluorometric (chlorophyll a, phycocyanin, CDOM) or weight-based (mineral) measurements were used to determine the mass-specific absorption coefficients tested in this study and an exponential function was used to estimate a_CDOM. While a*_chl showed minimum variability between reservoirs, a*_pc, a*_m, a*_CDOM, and a_CDOM showed statistically significant differences between reservoirs; however, for a*_m, there was greater variation within each reservoir. Variability in a*_CDOM and a_CDOM between reservoirs was likely due to different inflows. All absorption coefficients fell within previously published ranges for each constituent examined, with the exception of a*_pc. Differences in a*_pc were likely due to different techniques used in extracting and estimating phycocyanin.     

New approach to antibacterial treatment of cotton fabric with silver nanoparticle–doped silica using sol–gel process

In this study, cotton fabric was successfully modified to have an antibacterial property through use of the sol–gel process. Dodecanethiol‐capped silver nanoparticles, which have powerful antibacterial activity, were incorporated in silica sol. The starting materials were silver nitrate, tetraoctylammonium bromide, sodium borohydride, chloroform, 1‐dodecanethiol, ethanol, tetraethylorthosilicate, and water. The cotton fabric was padded with dodecanethiol‐capped silver nanoparticle–doped sol, dried at 60°C, and cured at 150°C. Scanning electron microscopy showed a uniform and continuous layer of doped sol on the fiber surface. The antibacterial effects of the treated cotton fabric against Escherichia coli were examined and found to be excellent. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101:2938–2943, 2006     

Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments,chlorophyll a and phycocyanin

Nuisance blue-green algal blooms contribute to aesthetic degradation of water resources by means of accelerated eutrophication, taste and odor problems, and the production of toxins that can have serious adverse human health effects. Current field-based methods for detecting blooms are costly and time consuming, delaying management decisions. Methods have been developed for estimating phycocyanin concentration, the accessory pigment unique to freshwater blue-green algae, in productive inland water. By employing the known optical properties of phycocyanin, researchers have evaluated the utility of field-collected spectral response patterns for determining concentrations of phycocyanin pigments and ultimately blue-green algal abundance. The purpose of this research was to evaluate field spectroscopy as a rapid cyanobacteria bloom assessment method. In-situ field reflectance spectra were collected at 54 sampling sites on two turbid reservoirs on September 6th and 7th in Indianapolis, Indiana using ASD Fieldspec (UV/VNIR) spectroradiometers. Surface water samples were analyzed for in-vitro pigment concentrations and other physical and chemical water quality parameters. Semi-empirical algorithms by Simis et al. [Simis, S., Peters, S., Gons, H. (2005). Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water. American Society of Limnology and Oceanography 50(11): 237–245] were applied to the field spectra to predict chlorophyll a and phycocyanin absorption at 665 nm and 620 nm, respectively. For estimation of phycocyanin concentration, a specific absorption coefficient of 0.0070 m² mg PC^-1 for phycocyanin at 620 nm, a_PC^?(620), was employed, yielding an r² value of 0.85 (n = 48, p < 0.0001), mean relative residual value of 0.51 (σ = 1.41) and root mean square error (RMSE) of 19.54 ppb. Results suggest this algorithm could be a robust model for estimating phycocyanin. Error is highest in water with phycocyanin concentrations of less than 10 ppb and where phycocyanin abundance is low relative to chlorophyll a. A strong correlation between measured phycocyanin concentrations and biovolume measurements of cyanobacteria was also observed (r = 0.89), while a weaker relationship (r = 0.66) resulted between chlorophyll a concentration and cyanobacterial biovolume.     

Remote Estimation of Nutrients for a Drinking Water Source Through Adaptive Modeling

Morse Reservoir, a major water supply for the Indianapolis metropolitan area, IN, USA, experiences nuisance cyanobacterial blooms due to agricultural and point source nutrient loadings. Hyperspectral remote sensing data from both in situ and airborne AISA measurements were applied to an adaptive model based on Genetic Algorithms-Partial Least Squares (GA-PLS) by relating the spectral signal with total nitrogen (TN) and phosphorus (TP) concentrations. Results indicate that GA-PLS relating in situ spectral reflectance to the nutrients yielded high coefficients of determination (TN: R ²?=?0.88; TP: R ²?=?0.91) between measured and estimated TN (RMSE?=?0.07 mg/L; Range: 0.6–1.88 mg/L), and TP (RMSE?=?0.017; Range: 0.023–0.314 mg/L). The GA-PLS model also yielded high performance with AISA imaging data, showing close correlation between measured and estimated values (TN: RMSE?=?0.11 mg/L; TP: RMSE?=?0.02 mg/L). An analysis of in situ data indicated that TN and TP were highly correlated with chlorophyll-a and suspended matter in the water column, setting a basis for remotely sensed estimates of TN and TP. Spatial correlation of TN, TP with chlorophyll-a and suspended matters further confirmed that remote quantification of nutrients for inland waters is based on the strong association of optically active constituents with nutrients. Based on these results, in situ and airborne hyperspectral remote sensors can provide both quantitative and qualitative information on the distribution and concentration of nutrients in Morse Reservoir. Our modeling approach combined with hyperspectral remote sensing is applicable to other productive waters, where algal blooms are triggered by nutrients.