The ISR and ESR scales : measures of the project manager-stakeholder relationship

In this paper, we develop two stakeholder relationships scales. These scales assess project managers’ perceived competence in establishing and maintaining high quality, effective relationships with people internal to the project as well as those stakeholders who are external to the project. We developed the scales using an online survey study of three hundred and seventy three complex project managers from a sub-set of the Australian Defence Industry. Both the internal stakeholder relationships’ scale and the external stakeholder relationships’ scale demonstrated validity and reliability. This research has implications for the interpersonal work relationships’ literature and the stakeholder management literature. We recommend future research tests these scales with multiple samples, across different project types and project industries. The stakeholder relationships’ scales should be versatile enough to be applied to project management generally but are best suited to large-scale complex project environments.

Solo3

Solo3 is and evening of solo works collaboratively created by Jenny Roche and choreographers John Jasperse (US), Jodi Melnick (US) and Liz Roche (Ireland). It was commissioned by the Dublin Dance Festival 2008 for the culmination of Jenny Roche's residency as an artist with the festival. The three works address the role of the dancer as co-creator within choreographic practice and further examine how the dancer can inhabit multiple embodiments across various choreographies leading to a plurality of selfhood in line with post-modern and poststructuralist notions of subjectivity (Deleuze and Guattari 1987). Furthermore, the oscillation of real and imagined subjectivities in performance (Emilyn Claid 2006) and the interplay of intercorporeal and intersubjective relations between choreographer and dancer (Sally Gardner 2007) are highlighted in these works.

The effects of sleep restriction on executive inhibitory control and affect in young adults

Purpose: Young adults regularly experience restricted sleep due to a range of social, educational and vocational commitments. Evidence suggests that extended periods of sleep deprivation negatively impact affective and inhibitory control mechanisms leading to behavioural consequences such as increased emotional reactivity and impulsive behaviour. It is less clear whether acute periods of restricted sleep produce the same behavioural consequences. Methods: Nineteen young adults (m = 8, f = 12) with habitual late bed-time (after 22:30 h) and wake-time (after 06:30 h) completed a range of objective and subjective measures assessing sleepiness (Psychomotor Vigilance Task, Karolinska Sleepiness Scale), inhibitory control (Emotional Go/No-go Task and a Balloon Analog Risk Task) and affect (Positive and Negative Affective Schedule). Testing was counterbalanced across participants, and occurred on two occasions once following restricted sleep and once following habitual sleep one week apart. Results: Compared to habitual sleep, sleep restriction produced significantly slower performance on the Psychomotor Vigilance Task, and higher subjective ratings of sleepiness on the Karolinska Sleepiness Scale. Sleep restriction also caused a significant decrease in positive affect, but no change in negative affect on the Affective Schedule. Inhibitory control efficiency was significantly differentiated, with participants showing an increase in risk taking on the Balloon Analog Risk Task, but there was no evidence of increased reactivity to negative stimuli on the Emotional Go/No-go task. Conclusions: Results suggest that even acute periods of sleep loss may cause deficits in affective experiences and increase impulsive and potentially high risk behaviour in young adults.

Stop-signal task difficulty and the right inferior frontal gyrus

The stop-signal paradigm is increasingly being used as a probe of response inhibition in basic and clinical neuroimaging research. The critical feature of this task is that a cued response is countermanded by a secondary ‘stop-signal’ stimulus offset from the first by a ‘stop-signal delay’. Here we explored the role of task difficulty in the stop-signal task with the hypothesis that what is critical for successful inhibition is the time available for stopping, that we define as the difference between stop-signal onset and the expected response time (approximated by reaction time from previous trial). We also used functional magnetic resonance imaging (fMRI) to examine how the time available for stopping affects activity in the putative right inferior frontal gyrus and presupplementary motor area (right IFG-preSMA) network that is known to support stopping. While undergoing fMRI scanning, participants performed a stop-signal variant where the time available for stopping was kept approximately constant across participants, which enabled us to compare how the time available for stopping affected stop-signal task difficulty both within and between subjects. Importantly, all behavioural and neuroimaging data were consistent with previous findings. We found that the time available for stopping distinguished successful from unsuccessful inhibition trials, was independent of stop-signal delay, and affected successful inhibition depending upon individual SSRT. We also found that right IFG and adjacent anterior insula were more strongly activated during more difficult stopping. These findings may have critical implications for stop-signal studies that compare different patient or other groups using fixed stop-signal delays.

An investigation into the effect of infrastructure on fly-in fly-out mining workers

Objective: To explore fly-in fly-out (FIFO) mining workers' attitudes towards the leisure time they spend in mining camps, the recreational and social aspects of mining camp culture, the camps' communal and recreational infrastructure and activities, and implications for health. Design: In-depth semistructured interviews. Setting: Individual interviews at locations convenient for each participant. Participants: A total of seven participants, one female and six males. The age group varied within 20–59 years. Marital status varied across participants. Main outcome measures: A qualitative approach was used to interview participants, with responses thematically analysed. Findings highlight how the recreational infrastructure and activities at mining camps impact participants' enjoyment of the camps and their feelings of community and social inclusion. Results: Three main areas of need were identified in the interviews, as follows: (i) on-site facilities and activities; (ii) the role of infrastructure in facilitating a sense of community; and (iii) barriers to social interaction. Conclusion: Recreational infrastructure and activities enhance the experience of FIFO workers at mining camps. The availability of quality recreational facilities helps promote social interaction, provides for greater social inclusion and improves the experience of mining camps for their temporary FIFO residents. The infrastructure also needs to allow for privacy and individual recreational activities, which participants identified as important emotional needs. Developing appropriate recreational infrastructure at mining camps would enhance social interactions among FIFO workers, improve their well-being and foster a sense of community. Introducing infrastructure to promote social and recreational activities could also reduce alcohol-related social exclusion.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA-DTI working group

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

Major project managers’ internal and external stakeholder relationships: The development and validation of measurement scales

In this paper, we detail the development of two stakeholder relationships scales. The scales measure major project managers' perceived competence in developing (establishing and maintaining) high quality, effective relationships with stakeholders who are internal and external to their organization. Our sample consists of 373 major project managers from a sub-set of the Australian defense industry. Both the internal stakeholder relationships scale and the external stakeholder relationships scale demonstrated validity and reliability. This research has implications for the interpersonal work relationships literature and the stakeholder management literature. We recommend that researchers test these scales with multiple samples, across different project types and project industries in the future. The stakeholder relationship scales should be versatile enough to be applied to project management generally but are perhaps best suited to major project environments.

Comprehending adverbs of doubt and certainty in health communication: A multidimensional scaling approach

This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.

Cross-Domain Multitask Learning with Latent Probit Models

Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain transforms and propose a latent probit model (LPM) to jointly learn the domain transforms, and the shared probit classifier in the common domain. To learn meaningful task relatedness and avoid over-fitting in classification, we introduce sparsity in the domain transforms matrices, as well as in the common classifier. We derive theoretical bounds for the estimation error of the classifier in terms of the sparsity of domain transforms. An expectation-maximization algorithm is derived for learning the LPM. The effectiveness of the approach is demonstrated on several real datasets.

Quantification of biological aging in young adults.

Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.

Does chronic illness place constraints on positive constructions of identity? Temporal comparisons and self-evaluations in people with schizophrenia

It is often suggested that people in potentially threatening situations might engage in self-enhancing temporal comparisons that allow them to view themselves and their experience in a more positive light. Data from semistructured interviews with 12 individuals in the UK diagnosed as having schizophrenia were content analyzed to explore patterns of temporal comparison. The study found that the onset of schizophrenic symptoms created a new baseline in participants' representations of their past, with different types of temporal comparisons occurring before and after this point. Although comparisons with past selves after onset supported the suggestion that people may select and construct their past in such a manner that permits them to see their present circumstances more positively and envisage a better future, comparisons with past selves before onset were more negative. The findings suggest that the Theory of Temporal Self-Appraisals (Ross I Wilson, 2000) needs to be elaborated to include people who have experienced major life changes. (c) 2004 Elsevier Ltd. All rights reserved.

Psychological management of intractable seizures in an adolescent with a learning disability

Psychological interventions aimed at seizure management are described with a 14-year-old buy with a learning disability and intractable epilepsy. Baseline records suggested that a majority of tonic seizures and 'drop attacks' were associated with going off to sleep and by environmental 'startles'. Psychological formulation implicated sudden changes in arousal levels as an underlying mechanism of action. Cognitive-behavioural countermeasures were employed to alter arousal levels and processes in different ways in different 'at-risk' situations. A multiple baseline design was used to control for non-specific effects of interventions on non-targeted seizures. Results suggested significant declines in the number of sleep onset and startle-response seizures were attained by these methods. Gains were maintained at 2-month follow-up. (C) 1999 BEA Trading Ltd.

EEG decoding of semantic category reveals distributed representations for single concepts

Achieving a clearer picture of categorial distinctions in the brain is essential for our understanding of the conceptual lexicon, but much more fine-grained investigations are required in order for this evidence to contribute to lexical research. Here we present a collection of advanced data-mining techniques that allows the category of individual concepts to be decoded from single trials of EEG data. Neural activity was recorded while participants silently named images of mammals and tools, and category could be detected in single trials with an accuracy well above chance, both when considering data from single participants, and when group-training across participants. By aggregating across all trials, single concepts could be correctly assigned to their category with an accuracy of 98%. The pattern of classifications made by the algorithm confirmed that the neural patterns identified are due to conceptual category, and not any of a series of processing-related confounds. The time intervals, frequency bands and scalp locations that proved most informative for prediction permit physiological interpretation: the widespread activation shortly after appearance of the stimulus (from 100. ms) is consistent both with accounts of multi-pass processing, and distributed representations of categories. These methods provide an alternative to fMRI for fine-grained, large-scale investigations of the conceptual lexicon. © 2010 Elsevier Inc.

Optimal wafer site selection using forward selection component analysis

Reducing wafer metrology continues to be a major target in semiconductor manufacturing efficiency initiatives due to it being a high cost, non-value added operation that impacts on cycle-time and throughput. However, metrology cannot be eliminated completely given the important role it plays in process monitoring and advanced process control. To achieve the required manufacturing precision, measurements are typically taken at multiple sites across a wafer. The selection of these sites is usually based on a priori knowledge of wafer failure patterns and spatial variability with additional sites added over time in response to process issues. As a result, it is often the case that in mature processes significant redundancy can exist in wafer measurement plans. This paper proposes a novel methodology based on Forward Selection Component Analysis (FSCA) for analyzing historical metrology data in order to determine the minimum set of wafer sites needed for process monitoring. The paper also introduces a virtual metrology (VM) based approach for reconstructing the complete wafer profile from the optimal sites identified by FSCA. The proposed methodology is tested and validated on a wafer manufacturing metrology dataset. © 2012 IEEE.