Application of cupuassu shell as biosorbent for the removal of textile dyes from aqueous solution

The cupuassu shell (Theobroma grandiflorum) which is a food residue was used in its natural form as biosorbent for the removal of C.I. Reactive Red 194 and C.I. Direct Blue 53 dyes from aqueous solutions. This biosorbent was characterized by infrared spectroscopy, scanning electron microscopy, and nitrogen adsorption/desorption curves. The effects of pH, biosorbent dosage and shaking time on biosorption capacities were studied. In acidic pH region (pH 2.0) the biosorption of the dyes were favorable. The contact time required to obtain the equilibrium was 8 and 18 h at 298 K, for Reactive Red 194 and Direct Blue 53, respectively. The Avrami fractionary-order kinetic model provided the best fit to experimental data compared with pseudo-first-order, pseudo-second-order and chemisorption kinetic adsorption models. The equilibrium data were fitted to Langmuir, Freundlich, Sips and Radke-Prausnitz isotherm models. For both dyes the equilibrium data were best fitted to the Sips isotherm model.     

Improvements in anisotropic models of single tree effects in Cartesian coordinates

For anisotropic density functions of e.g. fruit or leaf dispersal, most mathematical research is only done in polar coordinates. However, in software solutions aiming to derive inverse models for real world dispersal data, Cartesian coordinates may be preferred for several reasons. Thus, we introduce an anisotropic model in Cartesian coordinates following the approach in Wälder et al. (2009) with the von Mises approach. By introducing a correction factor, we thereby consider the fundamental attribute, that the integral over a density function with respect to the Cartesian coordinates has to be equal 1. It may have been overlooked so far that guaranteeing for this attribute needs different approaches whether working in polar or Cartesian coordinates. One result is that our approach can be used also for other anisotropic models rather than models from the von Mises approach.     

A contingency model of union commitment and participation: Meta‐analysis of the antecedents of militant and nonmilitant activities

Correlation estimates from a meta‐analysis of 108 studies including 126 independent samples and nearly 70 000 participants were used to test multiple path models of the antecedents of militant and nonmilitant union participation. Variables moderating the relationship between union commitment and participation were examined. The magnitude of the relationship between commitment and militant participation was moderated by status‐based group membership (i.e., white collar versus blue collar), supporting a contingency model of union participation. Results updated and further developed an integrative model of union participation. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of a Regional Monitoring Program’s Statistical Power to Detect Temporal Trends in Forest Health Indicators

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year^?1 for all indicators and is appropriate for detecting a 1 % trend·year^?1 in most indicators.     

Enhancing older driver safety: A driving survey and evaluation of the CarFit program

Objective

To evaluate CarFit, an educational program designed to promote optimal alignment of driver with vehicle.

Methods

A driving activity survey was sent to 727 randomly selected participants living in retirement communities. Drivers (n = 195) were assigned randomly to CarFit intervention (n = 83, M age = 78.1) or Comparison (n = 112, M age = 79.6) groups. After 6 months, participants completed a post-test of driving activity and CarFit recommendations.

Results

Nonconsenting drivers were older and participated in fewer driving activities. CarFit participation was moderate (71%) with 86% of the participants receiving recommendations. 60% followed the recommendations at the 6-month re-evaluation). The CarFit (67.6%) and Comparison (59.3%) groups reported at least one type of self-regulation of driving activity at baseline. There was no significant change in the driving behaviors at the six-month follow-up.

Conclusion

CarFit was able to detect addressable opportunities that may contribute to the safety of older drivers.

Impact on industry

CarFit recommendations may need stronger reinforcement in order to be enacted by a participant.     

Grouping Lakes for Water Quality Assessment and Monitoring: The Roles of Regionalization and Spatial Scale

Regionalization frameworks cluster geographic data to create contiguous regions of similar climate, geology and hydrology by delineating land into discrete regions, such as ecoregions or watersheds, often at several spatial scales. Although most regionalization schemes were not originally designed for aquatic ecosystem classification or management, they are often used for such purposes, with surprisingly few explicit tests of the relative ability of different regionalization frameworks to group lakes for water quality monitoring and assessment. We examined which of 11 different lake grouping schemes at two spatial scales best captures the maximum amount of variation in water quality among regions for total nutrients, water clarity, chlorophyll, overall trophic state, and alkalinity in 479 lakes in Michigan (USA). We conducted analyses on two data sets: one that included all lakes and one that included only minimally disturbed lakes. Using hierarchical linear models that partitioned total variance into within-region and among-region components, we found that ecological drainage units and 8-digit hydrologic units most consistently captured among-region heterogeneity at their respective spatial scales using all lakes (variation among lake groups = 3% to 50% and 12% to 52%, respectively). However, regionalization schemes capture less among-region variance for minimally disturbed lakes. Diagnostics of spatial autocorrelation provided insight into the relative performance of regionalization frameworks but also demonstrated that region size is only partly responsible for capturing variation among lakes. These results suggest that regionalization schemes can provide useful frameworks for lake water quality assessment and monitoring but that we must identify the appropriate spatial scale for the questions being asked, the type of management applied, and the metrics being assessed.     

Investigating activated sludge flocs using microanalytical techniques: demonstration of environmental scanning electron microscopy and time-of-flight secondary ion mass spectrometry for wastewater applications.

Environmental scanning electron microscopy (ESEM) with an energy-dispersive X-ray spectrometer (EDS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) were demonstrated to be useful analytical tools for investigating surface and bulk components of individual floc particles from both full- and bench-scale activated sludge systems. Detailed surface imaging of various hydrated biological floc particles by ESEM revealed substantial differences in surface features between treatment systems, while EDS identified spatial differences in the iron and the aluminum distributions. The ToF-SIMS spectra had signature fragments of protein and polysaccharide material from the floc surface, suggesting that this technique is capable of surface profiling extracellular polymeric substances. Principal-component analysis of the positive ion ToF-SIMS spectra from the mixed-liquor-suspended solid (MLSS) samples and reference aquatic organic materials found slight differences between the full- and bench-scale MLSS surface properties but substantial differences among MLSS and treated effluent from the same facility.