How the energy sector could get it wrong with cloud computing

Cloud computing has significantly impacted a broad range of industries, but these technologies and services have been absorbed throughout the marketplace unevenly. Some industries have moved aggressively towards cloud computing, while others have moved much more slowly. For the most part, the energy sector has approached cloud computing in a measured and cautious way, with progress often in the form of private cloud solutions rather than public ones, or hybridized information technology systems that combine cloud and existing non-cloud architectures. By moving towards cloud computing in a very slow and tentative way, however, the energy industry may prevent itself from reaping the full benefit that a more complete migration to the public cloud has brought about in several other industries. This short communication is accordingly intended to offer a high-level overview of cloud computing, and to put forward the argument that the energy sector should make a more complete migration to the public cloud in order to unlock the major system-wide efficiencies that cloud computing can provide. Also, assets within the energy sector should be designed with as much modularity and flexibility as possible so that they are not locked out of cloud-friendly options in the future.

Changes in anatomical brain connectivity between ages 12 and 30: A HARDI study of 467 adolescents and adults

Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but only one study - in just 30 subjects - has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age 2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.

Test-retest reliability of graph theory measures of structural brain connectivity

The human connectome has recently become a popular research topic in neuroscience, and many new algorithms have been applied to analyze brain networks. In particular, network topology measures from graph theory have been adapted to analyze network efficiency and 'small-world' properties. While there has been a surge in the number of papers examining connectivity through graph theory, questions remain about its test-retest reliability (TRT). In particular, the reproducibility of structural connectivity measures has not been assessed. We examined the TRT of global connectivity measures generated from graph theory analyses of 17 young adults who underwent two high-angular resolution diffusion (HARDI) scans approximately 3 months apart. Of the measures assessed, modularity had the highest TRT, and it was stable across a range of sparsities (a thresholding parameter used to define which network edges are retained). These reliability measures underline the need to develop network descriptors that are robust to acquisition parameters.

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.

The role of knowledge integration in innovation and capability development

Purpose This paper investigates the interrelationships between knowledge integration (KI), product innovation and capability development to enhance our understanding of how firms can develop capability at the firm level, which in turn enhances their performance. One of the critical underlying mechanisms for capability building identified in the literature is the role of knowledge integration, which operates within product innovation projects and contributes to dynamic capability development. Therefore, the main research question is “how does the integration of knowledge across product innovation projects lead to the development of capability?” Design/methodology/approach We adopted a case-based approach and investigated the case of a successful firm that was able to sustain its performance through a series of product innovation projects. In particular this research focused on the role of KI and firm-level capability development over the course of four projects, during which the firm successfully managed the transformation of its product base and renewal of its competitive advantage. For this purpose an in-depth case study of capability development was undertaken at the Iran Khodro Company (IKCO), the key player in the Iranian auto industry transformation. Originality/value This research revealed that along with changes at each level of product architecture “design knowledge” and “design capability” have been developed at the same level of product architecture, leading to capability development at that level. It can be argued that along the step by step maturation of radical innovation across the four case projects, architectural knowledge and capability have been developed at the case company, resulting in the gradual emergence of a modular product and capability architecture across different levels of product architecture. Such findings basically add to extensive emphasis in the literature on the interrelationship of the concept of modularity with knowledge management and capability development. Practical implications Findings of this study indicate that firms manage their knowledge in accordance with the level of specialization in knowledge and capability. Furthermore, firms design appropriate knowledge integration mechanisms within and among functions in order dynamically align knowledge processes at different levels of the product architecture. Accordingly, the outcomes of this study may guide practitioners in managing their knowledge processes, through dynamically employing knowledge integration modes step-by-step and from the part level to the architectural level of product architecture across a sequence of product innovation projects to encourage learning and radical innovation.

Compositional agent-based models for electricity distribution networks

This thesis presents a novel approach to building large-scale agent-based models of networked physical systems using a compositional approach to provide extensibility and flexibility in building the models and simulations. A software framework (MODAM - MODular Agent-based Model) was implemented for this purpose, and validated through simulations. These simulations allow assessment of the impact of technological change on the electricity distribution network looking at the trajectories of electricity consumption at key locations over many years.

Medium-Coupled Bus-Based INS-GPS Sensor Fusion for Accurate and Reliable Positioning

A scheme for integration of stand-alone INS and GPS sensors is presented, with data interchange over an external bus. This ensures modularity and sensor interchangeability. Use of a medium-coupled scheme reduces data flow and computation, facilitating use in surface vehicles. Results show that the hybrid navigation system is capable of delivering high positioning accuracy.

Measuring and tracking quality factors in Free and Open Source Software projects

Free and Open Source Software (FOSS) has gained increased interest in the computer software industry, but assessing its quality remains a challenge. FOSS development is frequently carried out by globally distributed development teams, and all stages of development are publicly visible. Several product and process-level quality factors can be measured using the public data. This thesis presents a theoretical background for software quality and metrics and their application in a FOSS environment. Information available from FOSS projects in three information spaces are presented, and a quality model suitable for use in a FOSS context is constructed. The model includes both process and product quality metrics, and takes into account the tools and working methods commonly used in FOSS projects. A subset of the constructed quality model is applied to three FOSS projects, highlighting both theoretical and practical concerns in implementing automatic metric collection and analysis. The experiment shows that useful quality information can be extracted from the vast amount of data available. In particular, projects vary in their growth rate, complexity, modularity and team structure.

Shrinking Violets

Description of the work Shrinking Violets is comprised of two half scale garments in laser cut silk organza, developed with a knotting device to allow for disassembly and reassembly. The first is a jacket in layered red organza including black storm flap details. The second is a vest in jade organza with circles of pink organza attached through a pattern of knots. Research Background This practice-led fashion design research sits within the field of Design for Sustainability (DfS) in fashion that seeks to mitigate the environmental and ethical impacts of fashion consumption and production. The research explores new systems of garment construction for DfS, and examines how these systems may involve ‘designing’ new user interactions with the garments. The garments’ construction system allows them to be disassembled and recycled or reassembled by users to form a new garment. Conventional garment design follows a set process of cutting and construction, with pattern pieces permanently machine-stitched together. Garments typically contain multiple fibre types; for example a jacket may be constructed from a shell of wool/polyester, an acetate lining, fusible interlinings, and plastic buttons. These complex inputs mean that textile recycling is highly labour intensive, first to separate the garment pieces and second to sort the multiple fibre types. This difficulty results in poor quality ‘shoddy’ comprised of many fibre types and unsuitable for new apparel, or in large quantities of recyclable textile waste sent to landfill (Hawley 2011). Design-led approaches that consider the garment’s end of life in the design process are a way of addressing this problem. In Gulich’s (2006) analysis, use of single materials is the most effective way to ensure ease of recycling, with multiple materials that can be detached next in effectiveness. Given the low rate of technological innovation in most apparel manufacturing (Ruiz 2011), a challenge for effective recycling is how to develop new manufacturing methods that allow for garments to be more easily disassembled at end-of-life. Research Contribution This project addresses the research question: How can design for disassembly be considered within the fashion design process? I have employed a practice-led methodology in which my design process leads the research, making use of methods of fashion design practice including garment and construction research, fabric and colour research, textile experimentation, drape, patternmaking, and illustration as well as more recent methods such as laser cutting. Interrogating the traditional approaches to garment construction is necessarily a technical process; however fashion design is as much about the aesthetic and desirability of a garment as it is about the garment’s pragmatics or utility. This requires a balance between the technical demands of designing for disassembly with the aesthetic demands of fashion. This led to the selection of luxurious, semi-transparent fabrics in bold floral colours that could be layered to create multiple visual effects, as well as the experimentation with laser cutting for new forms of finishing and fastening the fabrics together. Shrinking Violets makes two contributions to new knowledge in the area of design for sustainability within fashion. The first is in the technical development of apparel modularity through the system of laser cut holes and knots that also become a patterning device. The second contribution lies in the design of a system for users to engage with the garment through its ability to be easily reconstructed into a new form. Research Significance Shrinking Violets was exhibited at the State Library of Queensland’s Asia Pacific Design Library, 1-5 November 2015, as part of The International Association of Societies of Design Research’s (IASDR) biannual design conference. The work was chosen for display by a panel of experts, based on the criteria of design innovation and contribution to new knowledge in design. References Gulich, B. (2006). Designing textile products that are easy to recycle. In Y. Wang (Ed.), Recycling in Textiles (pp. 25-37). London: Woodhead. Hawley, J. M. (2011). Textile recycling options: exploring what could be. In A. Gwilt & T. Rissanen (Eds.), Shaping Sustainable Fashion: Changing the way we make and use clothes (pp. 143 - 155). London: Earthscan. Ruiz, B. (2014). Global Apparel Manufacturing. Retrieved 10 August 2014, from http://clients1.ibisworld.com/reports/gl/industry/default.aspx?entid=470

Heritability of the network architecture of intrinsic brain functional connectivity

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

Transferability of Multipole Charge Density Parameters for Supramolecular Synthons: A New Tool for Quantitative Crystal Engineering

The modularity of the supramolecular synthon is used to obtain transferability of charge density derived multipolar parameters for structural fragments, thus creating an opportunity to derive charge density maps for new compounds. On the basis of high resolution X-ray diffraction data obtained at 100 K for three compounds methoxybenzoic acid, acetanilide, and 4-methyl-benzoic acid, multipole parameters for O-H center dot center dot center dot O carboxylic acid dimer and N-H center dot center dot center dot O amide infinite chain synthon fragments have been derived. The robustness associated with these supramolecular synthons has been used to model charge density derived multipolar parameters for 4-(acetylamino)benzoic acid and 4-methylacetanilide. The study provides pointers to the design and fabrication of a synthon library of high resolution X-ray diffraction data sets. It has been demonstrated that the derived charge density features can be exploited in both intra- and intermolecular space for any organic compound based on transferability of multipole parameters. The supramolecular synthon based fragments approach (SBFA) has been compared with experimental charge density data to check the reliability of use of this methodology for transferring charge density derived multipole parameters.

Determining Top K Nodes in Social Networks using the Shapley Value

In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.

Extending the Supramolecular Synthon Based Fragment Approach (SBFA) for Transferability of Multipole Charge Density Parameters to Monofluorobenzoic Acids and their Cocrystals with Isonicotinamide: Importance of C-H center dot center dot center dot O, C-H center dot center dot center dot F, and F center dot center dot center dot F Intermolecular Regions

An extension of the supramolecular synthon-based fragment approach (SBFA) method for transferability of multipole charge density parameters to include weak supramolecular synthons is proposed. In particular, the SBFA method is applied to C-H center dot center dot center dot O, C-H center dot center dot center dot F, and F center dot center dot center dot F containing synthons. A high resolution charge density study has been performed on 4-fluorobenzoic acid to build a synthon library for C-H center dot center dot center dot F infinite chain interactions. Libraries for C-H center dot center dot center dot O and F center dot center dot center dot F synthons were taken from earlier work. The SBFA methodology was applied successfully to 2- and 3-fluorobenzoic acids, data sets for which were collected in a routine manner at 100 K, and the modularity of the synthons was demonstrated. Cocrystals of isonicotinamide with all three fluorobenzoic acids were also studied with the SBFA method. The topological analysis of inter- and intramolecular interaction regions was performed using Bader's AIM approach. This study shows that the SBFA method is generally applicable to generate charge density maps using information from multiple intermolecular regions.

Halogen Bonds in Crystal Engineering: Like Hydrogen Bonds yet Different

CONSPECTUS: The halogen bond is an attractive interaction in which an electrophilic halogen atom approaches a negatively polarized species. Short halogen atom contacts in crystals have been known for around 50 years. Such contacts are found in two varieties: type I, which is symmetrical, and type II, which is bent. Both are influenced by geometric and chemical considerations. Our research group has been using halogen atom interactions as design elements in crystal engineering, for nearly 30 years. These interactions include halogen center dot center dot center dot halogen interactions (X center dot center dot center dot X) and halogen center dot center dot center dot heteroatom interactions (X center dot center dot center dot B). Many X center dot center dot center dot X and almost all X center dot center dot center dot B contacts can be classified as halogen bonds. In this Account, we illustrate examples of crystal engineering where one can build up from previous knowledge with a focus that is provided by the modern definition of the halogen bond. We also comment on the similarities and differences between halogen bonds and hydrogen bonds. These interactions are similar because the protagonist atoms halogen and hydrogen are both electrophilic in nature. The interactions are distinctive because the size of a halogen atom is of consequence when compared with the atomic sizes of, for example, C, N, and O, unlike that of a hydrogen atom. Conclusions may be drawn pertaining to the nature of X center dot center dot center dot X interactions from the Cambridge Structural Database (CSD). There is a clear geometric and chemical distinction between type I and type II, with only type II being halogen bonds. Cl/Br isostructurality is explained based on a geometric model. In parallel, experimental studies on 3,4-dichlorophenol and its congeners shed light on the nature of halogen center dot center dot center dot halogen interactions and reveal the chemical difference between Cl and Br. Variable temperature studies also show differences between type I and type II contacts. In terms of crystal design, halogen bonds offer a unique opportunity in the strength, atom size and interaction gradation; this may be used in the design of ternary cocrystals. Structural modularity in which an entire crystal structure is defined as a combination of modules is rationalized on the basis of the intermediate strength of a halogen bond. The specific directionality of the halogen bond makes it a good tool to achieve orthogonality in molecular crystals. Mechanical properties can be tuned systematically by varying these orthogonally oriented halogen center dot center dot center dot halogen interactions. In a further development, halogen bonds are shown to play a systematic role in organization of LSAMs (long range synthon aufbau module), which are bigger structural units containing multiple synthons. With a formal definition in place, this may be the right time to look at differences between halogen bonds and hydrogen bonds and exploit them in more subtle ways in crystal engineering.

Supramolecular Gating of Ion Transport in Nanochannels

Several covalent strategies towards surface charge-reversal in nanochannels have been reported with the purpose of manipulating ion transport. However, covalent routes lack dynamism, modularity and post-synthetic flexibility, and hence restrict their applicability in different environments. Here, we introduce a facile non-covalent approach towards charge-reversal in nanochannels (< 10 nm) using strong charge-transfer interactions between dicationic viologen (acceptor) and trianionic pyranine (donor). The polarity of ion transport was switched from anion selective to ambipolar to cation selective by controlling the extent of viologen bound to the pyranine. We could also regulate the ion transport with respect to pH by selecting a donor with pH-responsive functional groups. The modularity of this approach further allows facile integration of various functional groups capable of responding to stimuli such as light and temperature to modulate the transport of ions as well as molecules.