Construction and validation of the Disability Rights Attitude Scale: Assessing attitudes toward the Americans with Disabilities Act (ADA).

The authors constructed and validated an instrument that assesses attitudes toward the Americans With Disabilities Act (ADA), a law that protects the civil rights of individuals with disabilities. The Disability Rights Attitude Scale (DRAS) demonstrated acceptable reliability and validity with 2 samples of university students (N?=?421). Reliability analysis resulted in Cronbach's alphas of .91 (Sample 1) and .90 (Sample 2). Principal-components factor analysis indicated that the DRAS essentially consists of 1 factor that accounted for 27% (Sample 1) and 31% (Sample 2) of the total variance. Construct validity analysis resulted in predicted, significant positive correlations with other relevant measures. A stepwise multiple regression analysis revealed that sex, ethnicity, and prior contact with people with disabilities were significant predictors of attitudes toward the law. The DRAS provides a psychometrically sound means of assessing attitudes toward disability rights that may encourage or impede implementation of the ADA. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Americans With Disabilities Act Knowledge Survey: Strong psychometrics and weak knowledge.

Objectives: To construct and validate a measure that assesses knowledge of the Americans With Disabilities Act (ADA) and to examine ADA knowledge among private and public sector representatives. Study Design and Subjects: A 20-item measure was developed and administered to undergraduates (n = 210) and ADA experts (n = 34) to establish validity and reliability. Then, it was administered to 133 private and public sector representatives. Results: The ADA experts obtained a significantly higher mean than undergraduates. Reliability analysis resulted in a Cronbach's alpha of .82. Furthermore, private and public sector representatives demonstrated little ADA knowledge. Conclusions: A valid and reliable measure, the ADA Knowledge Survey may be administered to individuals who are responsible for the law's implementation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

In situ Production of Polystyrene Magnetic Nanocomposites through a Batch Suspension Polymerization Process

This work presents the synthesis of micro‐sized polystyrene magnetic beads by in situ incorporation of oleic acid‐modified Fe₃O₄ magnetic nanoparticles via a suspension polymerization process. Fe₃O₄ nanoparticles with superparamagnetic characteristics were obtained through a coprecipitation technique. These particles present an average diameter equal to 7.4 ± 4.6 nm, as determined by AFM. This result is in agreement with the crystallite size of single domains calculated by using Scherrer's equation, which was equal to 7.7 nm, based on XRD measurements. The obtained materials were also studied using TGA. The weight loss behavior was independent of the Fe₃O₄ content and the stability to the thermal degradation was also not improved by magnetic nanoparticles present in the composite. Polystyrene/Fe₃O₄ magnetic nanocomposites exhibited the same diffraction peaks observed in the pure Fe₃O₄, which indicates that nanoparticles inside the composites preserved the structure and properties of pure Fe₃O₄. It was also shown that nanosized polystyrene particles, dispersed in the aqueous phase, are obtained due to the stabilization effect of the oleic acid on the styrene droplets. A cross‐section of polystyrene magnetic particles showed empty spherical regions, attributed to the encapsulation of water microdroplets during the polymerization reaction. The obtained polymeric materials also presented good magnetic behavior, indicating that the modified Fe₃O₄ nanoparticles were successfully dispersed in the polystyrene particles.

     

Optimal design of air-conditioning systems using deep seawater

Clean Technologies and Environmental Policy - This paper presents a multi-objective mixed integer linear programming problem for the optimization of seawater air-conditioning systems using deep...     

Suitability of Chitosan Scaffolds with Carbon Nanotubes for Bone Defects Treated with Photobiomodulation

Biomaterials have been investigated as an alternative for the treatment of bone defects, such as chitosan/carbon nanotubes scaffolds, which allow cell proliferation. However, bone regeneration can be accelerated by electrotherapeutic resources that act on bone metabolism, such as low-level laser therapy (LLLT). Thus, this study evaluated the regeneration of bone lesions grafted with chitosan/carbon nanotubes scaffolds and associated with LLLT. For this, a defect (3 mm) was created in the femur of thirty rats, which were divided into 6 groups: Control (G1/Control), LLLT (G2/Laser), Chitosan/Carbon Nanotubes (G3/C+CNTs), Chitosan/Carbon Nanotubes with LLLT (G4/C+CNTs+L), Mineralized Chitosan/Carbon Nanotubes (G5/C+CNTsM) and Mineralized Chitosan/Carbon Nanotubes with LLLT (G6/C+CNTsM+L). After 5 weeks, the biocompatibility of the chitosan/carbon nanotubes scaffolds was observed, with the absence of inflammatory infiltrates and fibrotic tissue. Bone neoformation was denser, thicker and voluminous in G6/C+CNTsM+L. Histomorphometric analyses showed that the relative percentage and standard deviations (mean ± SD) of new bone formation in groups G1 to G6 were 59.93 ± 3.04a (G1/Control), 70.83 ± 1.21b (G2/Laser), 70.09 ± 4.31b (G3/C+CNTs), 81.6 ± 5.74c (G4/C+CNTs+L), 81.4 ± 4.57c (G5/C+CNTsM) and 91.3 ± 4.81d (G6/C+CNTsM+L), respectively, with G6 showing a significant difference in relation to the other groups (a ≠ b ≠ c ≠ d; p < 0.05). Immunohistochemistry also revealed good expression of osteocalcin (OC), osteopontin (OP) and vascular endothelial growth factor (VEGF). It was concluded that chitosan-based carbon nanotube materials combined with LLLT effectively stimulated the bone healing process.     

CSBF: A static ensemble fusion method based on the centrality score of complex networks

Ensemble of classifiers can improve classification accuracy by combining several models. The fusion method plays an important role in the ensemble performance. Usually, a criterion for weighting the decision of each ensemble member is adopted. Frequently, this can be done using some heuristic based on accuracy or confidence. Then, the used fusion rule must consider the established criterion for providing a most reliable ensemble output through a kind of competition among the ensemble members. This article presents a new ensemble fusion method, named centrality score-based fusion, which uses the centrality concept in the context of social network analysis (SNA) as a criterion for the ensemble decision. Centrality measures have been applied in the SNA to measure the importance of each person inside of a social network, taking into account the relationship of each person with all others. Thus, the idea is to derive the classifier weight considering the overall classifier prominence inside the ensemble network, which reflects the relationships among pairs of classifiers. We hypothesized that the prominent position of a classifier based on its pairwise relationship with the other ensemble members could be its weight in the fusion process. A robust experimental protocol has confirmed that centrality measures represent a promising strategy to weight the classifiers of an ensemble, showing that the proposed fusion method performed well against the literature.     

Optimization of the Functional Characteristics of Cleaning Products Through Experimental Design

To optimize a benchmark commercial dishwashing formulation, this paper presents a fractional factorial design procedure coupled with a mixture design in order to obtain a formulation with better properties and cost, as well as to provide an example of quick formula optimization that may also be useful for other cleaning and personal hygiene sectors. First, a fractional factorial design was performed to determine the significant effects for each response variable: viscosity, performance, foaming, and Krafft temperature. Then, a mixture design was used to determine the compositions that feature the best results for each property of interest. The determined compositions that meet the requirements with 90–95% confidence showed that improvements in the compositions can be adopted. It was possible to estimate compositions based on commercial formulations that meet the same cost per kilogram of product but with gains in detergency, foaming, and viscosity volume.     

A path conditioning method with trap avoidance

This work presents a sliding-mode method for robotic path conditioning. The proposal includes a trap avoidance algorithm in order to escape from trap situations, which are analogous to local minima in potential field-based approaches. The sliding-mode algorithm activates when the desired path is about to violate the robot workspace constraints, modifying it as much as necessary in order to fulfill all the constraints and reaching their limit surface at low speed. The proposed path conditioning algorithm can be used on-line, since it does not require a priori knowledge of the desired path, and improves the conventional conservative potential field-based approach in the sense that it fully exploits the robot workspace. The proposed approach can be easily added as an auxiliary supervisory loop to conventional robotic planning algorithms and its implementation is very easy in a few program lines of a microprocessor. The proposed path conditioning is compared through simulation with the conventional potential field-based approach in order to show the benefits of the method. Moreover, the effectiveness of the proposed trap avoidance algorithm is evaluated by simulation for various trap situations.