A psychological contract perspective to the link between non-profit organizations' management practices and volunteer sustainability

This study applies the concept of the psychological contract to the relationship between management practices and volunteers. Formalization of the voluntary sector is impacting on volunteers’ experiences and may breach the psychological contract from the volunteers’ perspective. This mixed method study interviewed 67 volunteers and volunteer coordinators/administrators, and collected mail survey information from 152 volunteer organizations. The transactional management practices of keeping formal records and not paying volunteers out of pocket expenses are negatively associated with volunteer recruitment and retention. Alternatively, publicly recognizing volunteers through a volunteer newsletter supports volunteers’ relational expectations and is positively linked to adequate volunteer numbers. Our findings have important implications for the human resource development practices of non-profit organizations in dealing with their volunteers: they suggest that the relational expectations of volunteers are an important aspect of the psychological contract, which could be used by organizations as a framework for developing management practices that fit the volunteer ethos of trust and networks.

The effects of topological inaccuracy in evolutionary trees on the phylogenetic comparative method of independent contrasts

Computer simulations were used to test the effect of increasing phylogenetic topological inaccuracy on the results obtained from correlation tests of independent contrasts. Predictably, increasing the number of disruptions in the tree increases the likelihood of significant error in the r values produced and in the statistical conclusions drawn from the analysis. However, the position of the disruption in the tree is important: Disruptions closer to the tips of the tree have a greater effect than do disruptions that are close to the root of the tree. Independent contrasts derived from inaccurate topologies are more likely to lead to erroneous conclusions when there is a true significant relationship between the variables being tested (i.e., they tend to be conservative). The results also suggest that random phylogenies perform no better than nonphylogenetic analyses and, under certain conditions, may perform even worse than analyses using raw species data. Therefore, the use of random phylogenies is not beneficial in the absence of knowledge of the true phylogeny.

Forecasting construction demand : a vector error correction model with dummy variables

Modelling the level of demand for construction is vital in policy formulation and implementation as the construction industry plays an important role in a country’s economic development process. In construction economics, research efforts on construction demand modelling and forecasting are various, but few researchers have considered the impact of global economy events in construction demand modelling. An advanced multivariate modelling technique, namely the vector error correction (VEC) model with dummy variables, was adopted to predict demand in the Australian construction market. The results of prediction accuracy tests suggest that the general VEC model and the VEC model with dummy variables are both acceptable for forecasting construction economic indicators. However, the VEC model that considers external impacts achieves higher prediction accuracy than the general VEC model. The model estimates indicate that the growth in population, changes in national income, fluctuations in interest rates and changes in householder expenditure all play significant roles when explaining variations in construction demand. The VEC model with disturbances developed can serve as an experimentation using an advanced econometrical method which can be used to analyse the effect of specific events or factors on the construction market growth.

Mobility of people with retinitis pigmentosa as a function of vision and psychological variables

We investigated the mobility performance of subjects with retinitis pigmentosa (RP) as a function of clinical measures of residual vision and psychological variables. We found a highly significant correlation between clinical measures of residual vision and mobility. Pelli-Robson contrast sensitivity and residual visual field together explained 64% of the variance in mobility performance in an indoor shopping mall. We suggest a simple new clinical method of scoring the visual field for predicting mobility performance, the RP Concentric Field Rating. The RP Concentric Field Rating alone explained 60% of the variance in mobility performance. In spite of expectations derived from reading the recent literature, we did not find a significant correlation between psychological variables and mobility performance in a group of subjects with RP.

A new hybrid method for Bayesian network learning With dependency constraints

A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Bayes net. The quantitative aspects are the net parameters. This paper develops a hybrid criterion for learning Bayes net structures that is based on both aspects. We combine model selection criteria measuring data fit with correlation information from statistical tests: Given a sample d, search for a structure G that maximizes score(G, d), over the set of structures G that satisfy the dependencies detected in d. We rely on the statistical test only to accept conditional dependencies, not conditional independencies. We show how to adapt local search algorithms to accommodate the observed dependencies. Simulation studies with GES search and the BDeu/BIC scores provide evidence that the additional dependency information leads to Bayes nets that better fit the target model in distribution and structure.

Does the burden of the experience sampling method undermine data quality in state based body image research?

Despite growing popularity of experience sampling methodology (ESM) for evaluations of state-based components of body image, there have been concerns that the frequent repeated measurement might encourage problematic responding resulting in low data quantity and/or quality. Using a sample of 105 women (mean age = 24.84), this study used multilevel modelling to investigate whether (a) there were changes in compliance or response variability across a 7-day period, and (b) whether such changes are explained by participant characteristics. Present findings suggest that demands of ESM protocol undermine quantity more so than quality of obtained data. Decline in procedural compliance across the testing period correlated with BMI and body shame, whereas reduced variability in state-based assessments did not adversely impact the strength of association between state body satisfaction ratings and other variables in the dataset. The authors make several recommendations for ensuring the quality of ESM-based data in future studies.

Link between vertical and horizontal movement patterns of cod in the North Sea

We used a geolocation method based on tidal amplitude and water depth to assess the horizontal movements of 14 cod Gadus morhua equipped with time-depth recorders (TDR) in the North Sea and English Channel. Tracks ranged from 40 to 468 d and showed horizontal movements of up to 455 km and periods of continuous localised residence of up to 360 d. Cod spent time both in midwater (43% of total time) and near the seabed (57% of total time). A variety of common vertical movement patterns were seen within periods of both residence and directed horizontal movement. Hence particular patterns of vertical movement could not unequivocally define periods of migration or localised residence. After long horizontal movements, cod tended to adopt resident behaviour for several months and then return to broadly the same location where they were tagged, indicating a geospatial instinct. The results suggest that residence and homing behaviour are important features of Atlantic cod behaviour.

Is there a link between motor performance variability and social-communicative impairment in children with ADHD-CT : a kinematic study using an upper limb Fitts’ aiming task

 Objective: This study investigated the relationship between motor performance and social-communicative impairment in children with ADHD-combined type (ADHD-CT). Method: An upper limb Fitts’ aiming task was used as a measure of motor performance and the Social Responsiveness Scale as a measure of social-communicative/autistic impairment in the following groups: ADHD-CT (n = 11) and typically developing (TD) controls (n = 10). Results: Children with ADHD-CT displayed greater variability in their movements, reflected in increased error variance over repeated aiming trials compared with TD controls. Motor performance variability was associated with social-communicative deficits in the ADHD-CT but not in the TD group. Conclusion: Social-communicative impairments further complicate the clinical picture of ADHD-CT; therefore, further research in this area is warranted to ascertain whether a particular pattern of motor disturbance in children with ADHD-CT may be clinically useful in identifying and assessing children with a more complex ADHD presentation. © 2012 SAGE Publications.

A hazardous substance exposure prevention rating method for intervention needs assessment and effectiveness evaluation: the small business exposure index

Aims This paper describes the refinement and adaptation to small business of a previously developed method for systematically prioritizing needs for intervention on hazardous substance exposures in manufacturing worksites, and evaluating intervention effectiveness. Methods We developed a checklist containing six unique sets of yes/no variables organized in a 2 × 3 matrix of exposure potential versus exposure protection at three levels corresponding to a simplified hierarchy of controls: materials, processes, and human interface. Each of the six sets of indicator variables was reduced to a high/moderate/low rating. Ratings from the matrix were then combined to generate an exposure prevention 'Small Business Exposure Index' (SBEI) Summary score for each area. Reflecting the hierarchy of controls, material factors were weighted highest, followed by process, and then human interface. The checklist administered by an industrial hygienist during walk-through inspection (N = 149 manufacturing processes/areas in 25 small to medium-sized manufacturing worksites). One area or process per manufacturing department was assessed and rated. A second hygienist independently assessed 36 areas to evaluate inter-rater reliability. Results The SBEI Summary scores indicated that exposures were well controlled in the majority of areas assessed (58% with rating of 1 or 2 on a 6-point scale), that there was some room for improvement in roughly one-third of areas (31% of areas rated 3 or 4), and that roughly 10% of the areas assessed were urgently in need of intervention (rated as 5 or 6). Inter-rater reliability of EP ratings was good to excellent (e.g., for SBEI Summary scores, weighted kappa = 0.73, 95% CI 0.52–0.93). Conclusion The SBEI exposure prevention rating method is suitable for use in small/medium enterprises, has good discriminatory power and reliability, offers an inexpensive method for intervention needs assessment and effectiveness evaluation, and complements quantitative exposure assessment with an upstream prevention focus.

An exposure prevention rating method for intervention needs assessment and effectiveness evaluation

This article describes a new method for (1) systematically prioritizing needs for intervention on hazardous substance exposures in manufacturing work sites, and (2) evaluating intervention effectiveness. We developed a checklist containing six unique sets of yes/no variables organized in a 2 × 3 matrix of exposure potential versus protection (two columns) at the levels of materials, processes, and human interface (three rows). The three levels correspond to a simplified hierarchy of controls. Each of the six sets of indicator variables was reduced to a high/moderate/low rating. Ratings from the matrix were then combined to generate a single overall exposure prevention rating for each area. Reflecting the hierarchy of controls, material factors were weighted highest, followed by process, and then human interface. The checklist was filled out by an industrial hygienist while conducting a walk-through inspection (N = 131 manufacturing processes/areas in 17 large work sites). One area or process per manufacturing department was assessed and rated. Based on the resulting Exposure Prevention ratings, we concluded that exposures were well controlled in the majority of areas assessed (64% with rating of 1 or 2 on a 6-point scale), that there is some room for improvement in 26 percent of areas (rating of 3 or 4), and that roughly 10 percent of the areas assessed are urgently in need of intervention (rated as 5 or 6). A second hygienist independently assessed a subset of areas to evaluate inter-rater reliability. The reliability of the overall exposure prevention ratings was excellent (weighted kappa = 0.84). The rating scheme has good discriminatory power and reliability and shows promise as a broadly applicable and inexpensive tool for intervention needs assessment and effectiveness evaluation. Validation studies are needed as a next step. This assessment method complements quantitative exposure assessment with an upstream prevention focus.

A method for extending planar axis-symmetric parallel manipulators to spatial mechanisms

This paper investigates axis-symmetric parallel manipulators, composed of a central base column and an arm system able to rotate around this column. The arm system includes several actuated upper arms, each connected to a manipulated platform by one or more lower arm linkages. Such manipulators feature an extensive positional workspace in relation to the manipulator footprint and equal manipulator properties in all radial half-planes defined by the common rotation-axis of the upper arms. The similarities between planar manipulators exclusively employing 2-degrees-of-freedom (2-DOF) lower arm linkages and lower mobility spatial manipulators only utilising 5-DOF lower arm linkages are analysed. The 2-DOF linkages are composed of a link with a 1-DOF hinge on both ends whilst the 5-DOF linkages utilise 3-DOF spherical joints and 2-DOF universal joints. By employing a proposed linkage substitution scheme, it is shown how a wide range of spatial axis-symmetric parallel manipulators can be derived from a limited range of planar manipulators of the same type.

An interval type-2 fuzzy logic system-based method for prediction interval construction

This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.

Satellite imagery as a single source of predictor variables for habitat suitability modelling: how Landsat can inform the conservation of a critically endangered lemur

1. Statistical modelling of habitat suitability is an important tool for planning conservation interventions, particularly for areas where species distribution data are expensive or hard to collect. Sometimes however the predictor variables typically used in habitat suitability modelling are themselves difficult to obtain or not meaningful at the geographical extent of the study, as is the case for the Alaotran gentle lemur Hapalemur alaotrensis, a critically endangered lemur confined to the marshes of Lake Alaotra in Madagascar.2. We developed a habitat suitability model where all predictor variables, including vegetation indices and image texture measures at different scales (as surrogates for habitat structure), were derived from Landsat7 satellite imagery. Using relatively few presence records, the maximum entropy (Maxent) approach and AUC were used to assess the performance of candidate predictor variables, for studying the effect of scale, model selection and mapping suitable habitat.3. This study demonstrated the utility of satellite imagery as a single source of predictor variables for a Maxent habitat suitability model at the landscape level, within a restricted geographical extent and with a fine grain, in a case where predictor variables typically used at the macro-scale level (e.g. climatic and topographic) were not applicable.4. In the case of H. alaotrensis, the methodology generated a habitat suitability map to inform conservation management in Lake Alaotra and a replicable protocol to allow rapid updates to habitat suitability maps in the future. The exploration of candidate predictor variables allowed the identification of scales that appear ecologically relevant for the species.5. Synthesis and applications. This study presents a cost-effective combination of maximum entropy habitat suitability modelling and satellite imagery, where all predictor variables are derived solely from Landsat7 images. With a habitat modelling method like Maxent that shows good performance with few presence samples and Landsat images now freely available, the methodology can play an important role in rapid assessments of the status of species at the landscape level in data-poor regions, when typical macro-scale environmental predictors are of little use or difficult to obtain.

Searching Baxter's URDF robot joint and link tree for active serial chains

Teleoperation is integral to society's uptake of modern robotic systems. Given the wide array of readily available robots, ranging from simple mobile platforms and UAVs to advanced humanoid robots such as ASIMO and PR2, teleoperation is required in many different forms. The recent advances in virtual reality systems, interactive input controls and even haptic devices facilitate a wide range of new approaches to teleoperation control. This paper considers a dynamic user interface for improving the operator's ability to teleoperate heterogeneous robotic systems in dynamic and challenging environments. In order to achieve the proposed dynamic user interface the robot(s) comprising the heterogeneous robotic system and their active components need to be categorized. The recent uptake of ROS means that many robots are now represented within the standardized Unified Robot Descriptive Format (URDF), and this paper proposes a method for searching the URDF for active serial chains in individual robot systems. Results demonstrate the ability of the approach to determine active serial chains and associated kinematic information for the Baxter torso robot.

A convex geometry-based blind source separation method for separating nonnegative sources

This paper presents a convex geometry (CG)-based method for blind separation of nonnegative sources. First, the unaccessible source matrix is normalized to be column-sum-to-one by mapping the available observation matrix. Then, its zero-samples are found by searching the facets of the convex hull spanned by the mapped observations. Considering these zero-samples, a quadratic cost function with respect to each row of the unmixing matrix, together with a linear constraint in relation to the involved variables, is proposed. Upon which, an algorithm is presented to estimate the unmixing matrix by solving a classical convex optimization problem. Unlike the traditional blind source separation (BSS) methods, the CG-based method does not require the independence assumption, nor the uncorrelation assumption. Compared with the BSS methods that are specifically designed to distinguish between nonnegative sources, the proposed method requires a weaker sparsity condition. Provided simulation results illustrate the performance of our method.