Leader vision and diffusion of HR policy during change

Purpose – This paper utilizes diffusion of innovation theory in order to investigate and understand the relationships between HR policies on employee change-related outcomes. In addition, the aim is to explore the role of leader vision at different hierarchical levels in the organization in terms of the relationship of HR policy with employee change-related outcomes. Design/methodology/approach – This quantitative study was conducted in one large Australian government department undergoing major restructuring and cultural change. Data from 624 employees were analyzed in relation to knowledge of HR policies (awareness and clarity), leader vision (organizational and divisional), and change-related outcomes. Findings –Policy knowledge (awareness and clarity) does not have a direct impact on employee change-related outcomes. It is the implementation of policies through the divisional leader that begins to enable favorable employee outcomes. Research limitations/implications – Future research should employ a longitudinal design to investigate relationships over time, and also examine the importance of communication medium and individual preferences in relation to leader vision. Originality/value - This research extends the application of diffusion of innovation theory and leader vision theory to investigate the relationship between HR policy, leader vision, and employees’ change-related outcomes.

Creative Commons Australia and Organization for Transformative Works submission to the Australian Government’s online copyright infringement discussion paper

This submission focuses on the adverse effects that the Government’s proposals are likely to have on the legitimate use of copyright works. Copyright exists to support the production of new expression. Because new expression always builds on existing culture, any extension of copyright protection necessarily also increases the costs of creative expression. As a threshold matter, we do not believe that these further increases to the force of copyright law are justified. In recent years, the balance at the heart of copyright law has tipped too far in the direction of established producers and distributors, and now imposes unnecessary costs on ordinary creators. The available evidence does not support a further increase in the penalties and enforcement mechanisms available under copyright law.

An organization of visual and auditory fear conditioning in the lateral amygdala

Pavlovian fear conditioning is an evolutionary conserved and extensively studied form of associative learning and memory. In mammals, the lateral amygdala (LA) is an essential locus for Pavlovian fear learning and memory. Despite significant progress unraveling the cellular mechanisms responsible for fear conditioning, very little is known about the anatomical organization of neurons encoding fear conditioning in the LA. One key question is how fear conditioning to different sensory stimuli is organized in LA neuronal ensembles. Here we show that Pavlovian fear conditioning, formed through either the auditory or visual sensory modality, activates a similar density of LA neurons expressing a learning-induced phosphorylated extracellular signal-regulated kinase (p-ERK1/2). While the size of the neuron population specific to either memory was similar, the anatomical distribution differed. Several discrete sites in the LA contained a small but significant number of p-ERK1/2-expressing neurons specific to either sensory modality. The sites were anatomically localized to different levels of the longitudinal plane and were independent of both memory strength and the relative size of the activated neuronal population, suggesting some portion of the memory trace for auditory and visually cued fear conditioning is allocated differently in the LA. Presenting the visual stimulus by itself did not activate the same p-ERK1/2 neuron density or pattern, confirming the novelty of light alone cannot account for the specific pattern of activated neurons after visual fear conditioning. Together, these findings reveal an anatomical distribution of visual and auditory fear conditioning at the level of neuronal ensembles in the LA.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Importance of knowledge management processes in a project-based organization : a case study of research enterprise

Knowledge Management (KM) is vital factor to successfully undertake projects. The temporary nature of projects necessitates employing useful KM practices for tackling issues such as knowledge leakiness and rework. The Project Management Office (PMO) is a unit within organizations to facilitate and oversee organizational projects. Project Management Maturity Models (PMMM) shows the development of PMOs from immature to mature levels. The existing PMMMs have focused on discussing Project Management (PM) practices, however, the management of project knowledge is yet to be addressed, at various levels of maturity. This research project was undertaken to investigate the mentioned gap for addressing KM practices at the existing PMMMs. Due to the exploratory and inductive nature of this research, qualitative methods were chosen as the research methodology. In total, three cases selected from different industries: research; mining and government organizations, to provide broad categories for research and research questions were examined using the developed framework. This paper presents the partial findings of undertaken investigation of the research organisation with the lowest level of maturity. The result shows that knowledge creation and capturing are the most important processes, while knowledge transferring and reusing are not as important as the other two processes. In addition, it was revealed that provision of “knowledge about client” and “project management knowledge” are the most important types of knowledge that are required at this level of maturity. In conclusion, the outcomes of this paper shall provide powerful guidance to PMOs at lowest level of maturity from KM point of view.

Hierarchical deterministic Bitcoin wallets that tolerate key leakage (short paper)

A Bitcoin wallet is a set of private keys known to a user and which allow that user to spend any Bitcoin associated with those keys. In a hierarchical deterministic (HD) wallet, child private keys are generated pseudorandomly from a master private key, and the corresponding child public keys can be generated by anyone with knowledge of the master public key. These wallets have several interesting applications including Internet retail, trustless audit, and a treasurer allocating funds among departments. A specification of HD wallets has even been accepted as Bitcoin standard BIP32. Unfortunately, in all existing HD wallets---including BIP32 wallets---an attacker can easily recover the master private key given the master public key and any child private key. This vulnerability precludes use cases such as a combined treasurer-auditor, and some in the Bitcoin community have suspected that this vulnerability cannot be avoided. We propose a new HD wallet that is not subject to this vulnerability. Our HD wallet can tolerate the leakage of up to m private keys with a master public key size of O(m). We prove that breaking our HD wallet is at least as hard as the so-called "one more" discrete logarithm problem.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

A hierarchical model of social marketing

Purpose This paper aims to set out a new hierarchical and differentiated model of social marketing principles, concepts and techniques that builds on, but supersedes, the existing lists of non-equivalent and undifferentiated benchmark criteria. Design/methodology/approach This is a conceptual paper that proposes a hierarchical model of social marketing principles, concepts and techniques. Findings This new delineation of the social marketing principle, its four core concepts and five techniques, represents a new way to conceptualize and recognize the different elements that constitute social marketing. This new model will help add to and further the development of the theoretical basis of social marketing, building on the definitional work led by the International Social Marketing Association (iSMA), Australian Association of Social Marketing (AASM) and European Social Marketing Association (ESMA). Research limitations/implications This proposed model offers a foundation for future research to expand upon. Further research is recommended to empirically test the proposed model. Originality/value This paper seeks to advance the theoretical base of social marketing by making a reasoned case for the need to differentiate between principles, concepts and techniques when seeking to describe social marketing.

Exploring expectations of nonprofit management capabilities

Management capabilities have been widely researched in the private and public sectors, yet there is less evidence relating to the nonprofit sector. Increasing pressures to balance the demands of organizational values with business performance in this sector leads to a focus on the managerial capabilities required to meet these expectations. This article reports an exploratory study of capability expectations of managers within an Australian nonprofit organization. Using semistructured interviews, data were collected from 21 managers across three hierarchical levels. Findings indicate that while there is some overlap with managerial requirements in the private and public sectors, there are some unique aspects of nonprofit operations which warrant further investigation. Specifically, there was an emphasis on personal knowledge and experience (i.e., self-awareness, discipline, knowledge, and strategic thinking) and having a commitment to the nonprofit sector and values of the organization. Expectations also varied depending on the level of management within the organization.

The World Stroke Organization and nursing [Guest Editorial]

The field of neuroscience nursing and, in particular, nursing people with stroke has evolved significantly over the past two decades. Nurses working with people who have had a stroke and their families are called upon to use advanced assessment skills, apply nursing diagnoses across the whole continuum of care, and identify and implement a wide range of interventions. Indeed, in a recent Canadian study on the implementation of stroke best practices, nurses were identified as playing a leading role in many aspects of stroke care and recovery. As the volume of research evidence across disciplines mounts, nurses are challenged to “keep up on the latest”...

Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship

Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.

Sodium and lithium storage properties of spray-dried molybdenum disulfide-graphene hierarchical microspheres

Developing nano/micro-structures which can effectively upgrade the intriguing properties of electrode materials for energy storage devices is always a key research topic. Ultrathin nanosheets were proved to be one of the potential nanostructures due to their high specific surface area, good active contact areas and porous channels. Herein, we report a unique hierarchical micro-spherical morphology of well-stacked and completely miscible molybdenum disulfide (MoS2) nanosheets and graphene sheets, were successfully synthesized via a simple and industrial scale spray-drying technique to take the advantages of both MoS2 and graphene in terms of their high practical capacity values and high electronic conductivity, respectively. Computational studies were performed to understand the interfacial behaviour of MoS2 and graphene, which proves high stability of the composite with high interfacial binding energy (−2.02 eV) among them. Further, the lithium and sodium storage properties have been tested and reveal excellent cyclic stability over 250 and 500 cycles, respectively, with the highest initial capacity values of 1300 mAh g−1 and 640 mAh g−1 at 0.1 A g−1.