Social and cultural drivers of incentive effectiveness in infrastructure projects

Formal incentives systems aim to encourage improved performance by offering a reward for the achievement of project-specific goals. Despite argued benefits of incentive systems on project delivery outcomes, there remains debate over how incentive systems can be designed to encourage the formation of strong project relationships within a complex social system such as an infrastructure project. This challenge is compounded by the increasing emphasis in construction management research on the important mediating influence of technical and organisational context on project performance. In light of this challenge, the research presented in this paper focuses on the design of incentive systems in four infrastructure projects: two road reconstructions in the Netherlands and two building constructions in Australia. Based on a motivational theory frame, a cross case analysis is conducted to examine differences and similarities across social and cultural drivers impacting on the effectiveness of the incentive systems in light of infrastructure project context. Despite significant differences in case project characteristics, results indicate the projects’ experience similar social drivers impacting on incentive effectiveness. Significant value across the projects was placed on: varied performance goals and multiple opportunities to across the project team to pursue incentive rewards; fair risk allocation across contract parties; value-driven tender selection; improved design-build integration; and promotion of future work opportunities. However, differences across the contexts were identified. Results suggest future work opportunities were a more powerful social driver in upholding reputation and establishing strong project relationships in the Australian context. On the other hand, the relationship initiatives in the Dutch context seemed to be more broadly embraced resulting in a greater willingness to collaboratively manage project risk. Although there are limitations with this research in drawing generalizations across two sets of case projects, the results provide a strong base to explore the social and cultural influences on incentive effectiveness across different geographical and contextual boundaries in future research.

Secrets and lies

Secrets & Lies is an Australian drama television series that first screened on Network Ten on 3 March 2014. The series has aired in the Republic of Ireland on RTÉ TWO HD from 30 March, 2014 at 9.30pm. The series also debuted in Canada on the CBC in July 2014. It premiered in The Netherlands on RTL on 24 August 2014. Started in the UK on 23 September 2014 on Channel 5 and in France from January the 26 to February the 2 on France2. On 4 February 2014, the production company behind this version announced that a US version with the same title was in the works for ABC and would be co-produced with ABC Studios with a series penalty if the project is held back or not greenlighted by the network. The series premiered in the U.S. on 1 March 2015. Ryan Phillippe and Juliette Lewis stars in this adaptation. The series follows the story of a family man who finds the body of a young boy and quickly becomes the prime murder suspect. He has no choice but to try to find the real killer as his marriage, his kids, his reputation and his sanity are all at stake.

Polybrominated diphenyl ethers and age: analysis of pooled human blood serum from birth to over 60 years

Polybrominated diphenyl ethers (PBDEs) are considered to be a cost effective and efficient way to reduce flammability therefore reducing harm caused by fires. PBDEs are incorporated into a variety of manufactured products and are found worldwide in biological and environmental samples (e.g. Hites et al. 2004). Unlike other persistent organic pollutants there is limited data on PBDE concentrations by age and/or other population specific factors. Some studies have shown no variation in adult serum PBDE concentrations with age (e.g. Mazdai et al., 2003, Meironyte Guvenius et al., 2003) while Petreas et al. (2003) and Schecter et al. (2005) found results to be suggestive of an age trend in adult data but no statistically significant correlation was found. In addition to the data on adult concentrations there is limited data which investigates the levels of PBDEs in infants and young children. Fangström et al. (2005) showed that in seven year olds there was no difference in PBDE concentration when compared to adult concentrations. While Thomsen et al. (2002, 2005) found the concentration of PBDEs in pooled samples of blood serum from a 0-4 years age group to be higher than other age groups (4 to > 60 years). In addition, a family of four was studied in the U.S. and the concentrations were found to be greatest in the 18-month-old infant followed by the 5 year old child, then the mother and father (Fischer et al., 2006). The objectives of this study were to assess age, gender and regional trends of PBDE concentrations in a representative sample of the Australian population.

Practice-based learning in community contexts: A collaborative exploration of pedagogical principles

The primary focus of this chapter is an exploration of four pedagogical principles emerging from a practice-based learning lab. Following an overview of community engaged learning and the Lab approach, the chapter is structured around a discussion of pedagogical principles related to (1) collaboration, (2) interdisciplinarity, (3) complexity and uncertainty and (4) reflection. Through a participatory action research (PAR) framework, students, academics and community partners have worked to identify and refine what it takes to support students negotiate complexity and uncertainty inherent in problems facing communities. It also examines the pedagogical strategies employed to facilitate collaboration across disciplines and professional contexts in ways that leverage difference and challenge values and practices.

Mood enhancement using smartphone apps

The significant physical, emotional, educational and social developmental challenges faced by adolescents and young adults are associated with high levels of emotional vulnerability. Thus, the development and use of effective emotion-regulation strategies during this period is critical. Music listening is commonly used by young people to identify, express, enhance and regulate their emotions. Modern mobile technology provides an engaging, easily accessible means of assisting young people with identifying and managing emotions through music. A systematic contextual review of iPhone applications addressing emotions through music was conducted. Their quality was evaluated by two independent raters using the Mobile App Rating Scale (MARS). Three participatory design workshops (PDW; N=13, 6 males, 7 females; age 15-25) were conducted, exploring young people’s use of music to enhance wellbeing. Young people were also asked to trial existing mood and music apps and to conceptualise their ultimate mood-targeting music application. Of the identified 117 music apps, 20 met inclusion criteria (to play songs, not sounds; priced below $5.00). Characteristics and overall quality of the music apps are described and key features of the five highest- rating apps are presented. Thematic analysis of the PDW content identified the following music affect- regulation strategies: relationship building, modifying cognitions, modifying emotions, and immersing in emotions (i.e. habituation or mood enhancement). The application of key learnings from the mobile app review and PDW to the design and development of the new music eScape app will be presented. Implications for future research and for applying the new app in clinical practice are discussed.

Estimate of Lagrangian integral scales in shallow tidal water using high resolution GPS-tracked drifters

In estuaries and natural water channels, the estimate of velocity and dispersion coefficients is critical to the knowledge of scalar transport and mixing. This estimate is rarely available experimentally at sub-tidal time scale in shallow water channels where high frequency is required to capture its spatio-temporal variation. This study estimates Lagrangian integral scales and autocorrelation curves, which are key parameters for obtaining velocity fluctuations and dispersion coefficients, and their spatio-temporal variability from deployments of Lagrangian drifters sampled at 10 Hz for a 4-hour period. The power spectral densities of the velocities between 0.0001 and 0.8 Hz were well fitted with a slope of 5/3 predicted by Kolmogorov’s similarity hypothesis within the inertial subrange, and were similar to the Eulerian power spectral previously observed within the estuary. The result showed that large velocity fluctuations determine the magnitude of the integral time scale, TL. Overlapping of short segments improved the stability of the estimate of TL by taking advantage of the redundant data included in the autocorrelation function. The integral time scales were about 20 s and varied by up to a factor of 8. These results are essential inputs for spatial binning of velocities, Lagrangian stochastic modelling and single particle analysis of the tidal estuary.

Statistically assisted fluid registration algorithm - SAFIRA

In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in [2] and re-formulated using Lagrangian mechanics in [3]. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure- applied to 46 3D brain scans from healthy monozygotic twins.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

Multivariate variance-components analysis in DTI

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

Patent law and biological inventions

In response to scientific breakthroughs in biotechnology, the development of new technologies, and the demands of a hungry capitalist marketplace, patent law has expanded to accommodate a range of biological inventions. There has been much academic and public debate as to whether gene patents have a positive impact upon research and development, health-care, and the protection of the environment. In a satire of prevailing patenting practices, the English poet and part-time casino waitress, Donna MacLean, sought a patent application - GB0000180.0 - in respect of herself. She explained that she had satisfied the usual patent criteria - in that she was novel, inventive, and useful: It has taken 30 years of hard labor for me to discover and invent myself, and now I wish to protect my invention from unauthorized exploitation, genetic or otherwise. I am new: I have led a private existence and I have not made the invention of myself public. I am not obvious (2000: 18). MacLean said she had many industrial applications. 'For example, my genes can be used in medical research to extremely profitable ends - I therefore wish to have sole control of my own genetic material' (2000: 18). She observed in an interview: 'There's a kind of unpleasant, grasping, greedy atmosphere at the moment around the mapping of the human genome ... I wanted to see if a human being could protect their own genes in law' (Meek, 2000). This special issue of Law in Context charts a new era in the long-standing debate over biological inventions. In the wake of the expansion of patentable subject matter, there has been great strain placed upon patent criteria - such as 'novelty', 'inventive step', and 'utility'. Furthermore, there has been a new focus upon legal doctrines which facilitate access to patented inventions - like the defence of experimental use, the 'Bolar' exception, patent pooling, and compulsory licensing. There has been a concerted effort to renew patent law with an infusion of ethical principles dealing with informed consent and benefit sharing. There has also been a backlash against the commercialisation of biological inventions, and a call by some activists for the abolition of patents on genetic inventions. This collection considers a wide range of biological inventions - ranging from micro-organisms, plants and flowers and transgenic animals to genes, express sequence tags, and research tools, as well as genetic diagnostic tests and pharmaceutical drugs. It is thus an important corrective to much policy work, which has been limited in its purview to merely gene patents and biomedical research. This collection compares and contrasts the various approaches of a number of jurisdictions to the legal problems in respect of biological inventions. In particular, it looks at the complexities of the 1998 European Union Directive on the Legal Protection of Biotechnological Inventions, as well as decisions of member states, such as the Netherlands, and peripheral states, like Iceland. The edition considers US jurisprudence on patent law and policy, as well as recent developments in Canada. It also focuses upon recent developments in Australia - especially in the wake of parallel policy inquiries into gene patents and access to genetic resources.

Biomimicking natural nanopatterned topology by 3D laser lithography

Natural nanopatterned surfaces (nNPS) present on insect wings have demonstrated bactericidal activity [1, 2]. Fabricated nanopatterned surfaces (fNPS) derived by characterization of these wings have also shown superior bactericidal activity [2]. However bactericidal NPS topologies vary in both geometry and chemical characteristics of the individual features in different insects and fabricated surfaces, rendering it difficult to ascertain the optimum geometrical parameters underling bactericidal activity. This situation calls for the adaptation of new and emerging techniques, which are capable of fabricating and characterising comparable structures to nNPS from biocompatible materials. In this research, CAD drawn nNPS representing an area of 10 μm x10 μm was fabricated on a fused silica glass by Nanoscribe photonic professional GT 3D laser lithography system using two photon polymerization lithography. The glass was cleaned with acetone and isopropyl alcohol thrice and a drop of IP-DIP photoresist from Nanoscribe GmbH was cast onto the glass slide prior to patterning. Photosensitive IP-DIP resist was polymerized with high precision to make the surface nanopatterns using a 780 nm wavelength laser. Both moving-beam fixedsample (MBFS) and fixed-beam moving-sample (FBMS) fabrication approaches were tested during the fabrication process to determine the best approach for the precise fabrication of the required nanotopological pattern. Laser power was also optimized to fabricate the required fNPS, where this was changed from 3mW to 10mW to determine the optimum laser power for the polymerization of the photoresist for fabricating FNPS...