A review of research and practice for the industrial networks of the future

Academic researchers have followed closely the interest of companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? First, it appears that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example, in assembly operations. Second, the increased tendency towards specialisation has forced other, upstream, parts of industrial networks to introduce advanced manufacturing technologies for niche markets. Third, the capital market for investments in capacity, and the trade in manufacturing as a commodity, dominates resource allocation to a larger extent than was previously the case. Fourth, there is becoming a continuous move towards more loosely connected entities that comprise manufacturing networks. Finally, in these networks, concepts for supply chain management should address collaboration and information technology that supports decentralised decision-making, in particular to address sustainable and green supply chains. More traditional concepts, such as the keiretsu and chaibol networks of some Asian economies, do not sufficiently support the demands now being placed on networks. Research should address these five fundamental challenges to prepare for the industrial networks of 2020 and beyond. © 2010 Springer-Verlag London.

Industrial networks of the future:a critical commentary on research and practice

Academia has followed the interest by companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? Firstly, it seems that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example in assembly operations. Secondly, the increased tendency to specialize forces other parts of industrial networks to introduce advanced manufacturing technologies for niche markets. Thirdly, the capital market for investments in capacity and the trade in manufacturing as a commodity dominates resource allocation to a larger extent. Fourthly, there will be a continuous move toward more loosely connected entities forming manufacturing networks. More traditional concepts, like keiretsu and chaibol networks, do not sufficiently support this transition. Research should address these fundamental challenges to prepare for the industrial networks of 2020 and beyond.

Model Construction and Research using System Compositional Approach on Natural Hierarchical Neural Networks. Development of Computer Toolbox

System compositional approach to model construction and research of informational processes, which take place in biological hierarchical neural networks, is being discussed. A computer toolbox has been successfully developed for solution of tasks from this scientific sphere. A series of computational experiments investigating the work of this toolbox on olfactory bulb model has been carried out. The well-known psychophysical phenomena have been reproduced in experiments.

Networks, space and organisational performance:a study of the determinants of industrial research income generation by universities

This paper examines the extent to which both network structure and spatial factors impact on the organizational performance of universities as measured by the generation of industrial research income. Drawing on data concerning the interactions of universities in the UK with large research and development (R&D)-intensive firms, the paper employs both social network analysis and regression analysis. It is found that the structural position of a university within networks with large R&D-intensive firms is significantly associated with the level of research income gained from industry. Spatial factors, on the other hand, are not found to be clearly associated with performance, suggesting that universities operate on a level playing field across regional environments once other factors are controlled for.

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Research-based spin-offs as agents of knowledge dissemination: evidence from the analysis of innovation networks

The paper addresses the role played by research-based spin-offs (RBSOs) as knowledge dissemination mechanisms, through their position in knowledge networks. For this purpose the paper analyses the formal networks established by the Portuguese RBSOs in the context of publicly funded research, technology and pre-commercial product development projects, and investigates their configuration along two levels. At organisational level, in order to understand whether RBSOs extend their reach beyond the academic sphere; and if they do, whether they relate with similar firms or connect to organisations located downstream in the knowledge value chain, and which is their position in networks involving both research organisations and other firms. At spatial level, in order to understand whether RBSOs extend their reach beyond the region where they are created, thus potentially acting as connectors between diverse regions. The analysis starts from the population of RBSOs created in Portugal until 2007 (387) and identifies those that have established formal technological relationships as part of projects funded by all the programmes launched in the period 1993-2012. As a result, the analysis encompasses 192 collaborative projects and involves 82 spin-offs and 281 partners, of which only 20% are research organisations, the remaining being other firms and a variety of other user organisations. The results, although still preliminary, provide some insights into the knowledge networking behaviour of the RBSOs. As expected, research organisations are a central actor in spin-offs’ networks, being the sole partner for some of them. But half of the RBSOs have moved beyond the academic sphere, being frequently a central element in tripartite technological relationships between research and other organisations and occupying an intermediation position in the network, thus potentially acting as facilitators in knowledge circulation and transformation. Also as expected, RBSOs are predominantly located in the main metropolitan areas and tend to relate with organisations similarly located. But while geographical proximity emerges as important in the choice of partners, in about half of the cases, RBSOs knowledge networks have extended beyond regional boundaries. Given their central position in the network this suggests a role as connectors across regions that will be explored in subsequent research.

Research-based spin-offs as agents of knowledge dissemination: evidence from the analysis of innovation networks

The paper addresses the role played by research-based spin-offs (RBSOs) as knowledge dissemination mechanisms, through their position in knowledge networks. For this purpose the paper analyses the formal networks established by Portuguese RBSOs, in the context of publicly funded research, technology and pre-commercial product development projects, and investigates their configuration across two levels. At organisational level, in order to understand whether RBSOs extend their reach beyond the academic sphere; and if they do, whether they connect to organisations located downstream in the knowledge value chain, and which is their position in networks involving both research organisations and other firms. At spatial level, in order to understand whether RBSOs extend their reach beyond the region where they are created, thus potentially acting as connectors between diverse regions. The analysis starts from the population of RBSOs created in Portugal until 2007 (327 firms) and identifies those that have established formal technological relationships, as part of projects funded by all the relevant programmes launched in the period 1993-2012. As a result, the analysis encompasses 192 collaborative projects and involves 82 spin-offs and 281 partners, of which only 20% are research organisations, the remaining being other firms and a variety of other downstream organisations. The results, although still preliminary, provide some insights into the knowledge networking behaviour of the RBSOs. As expected, research organisations are a central actor in spin-offs’ networks, being the sole partner for some of them. But half of the RBSOs have moved beyond the academic sphere, being frequently a central element in tripartite technological relationships between research and other organisations, and occupying an intermediation position in the network, thus potentially acting as facilitators in knowledge circulation and transformation. Also as expected, RBSOs are predominantly located in the main metropolitan areas and tend to relate with organisations similarly located. But while geographical proximity emerges as important in the choice of partners, in about half of the cases, RBSOs knowledge networks have extended beyond regional boundaries. Given their central position in the network, this suggests a role as connectors across regions that will be explored in subsequent research.

Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

INTERNATIONAL EDUCATION & RESEARCH FOR OH. Experiences of international networks for collaborative education and research using the One Health approach.

The Authors describe first-hand experiences carried out within the framework of selected International projects aimed at developing collaborative research and education using the One Health (OH) approach. Special emphasis is given to SAPUVETNET, a series of projects co-financed under the EU-ALFA program, and aimed to support an International network on Veterinary Public Health (VPH) formed by Veterinary Faculties from Latin-America (LA) and Europe (EU). SAPUVETNET has envisaged a series of objectives/activities aimed at promoting and enhancing VPH research/training and intersectoral collaboration across LA and EU using the OH approach, as well as participating in research and/or education projects/networks under the OH umbrella, namely EURNEGVEC-European Network for Neglected Vectors & Vector-Borne Infections, CYSTINET-European Network on Taeniosis/Cysticercosis, and NEOH-Network for Evaluation of One Health; the latter includes expertise in multiple disciplines (e.g. ecology, economics, human and animal health, epidemiology, social and environmental sciences, etc.) and has the primary purpose of enabling quantitative evaluation of OH initiatives by developing a standardized evaluation protocol. The Authors give also an account of the ongoing creation of OHIN-OH International Network, founded as a spin-off result of SAPUVETNET. Finally, some examples of cooperation development projects characterised by an OH approach are also briefly mentioned.

Developing a participatory impact assessment approach and action research culture within a communication for social change organisation in Nepal

Developing an effective impact evaluation framework, managing and conducting rigorous impact evaluations, and developing a strong research and evaluation culture within development communication organisations presents many challenges. This is especially so when both the community and organisational context is continually changing and the outcomes of programs are complex and difficult to clearly identify.----- This paper presents a case study from a research project being conducted from 2007-2010 that aims to address these challenges and issues, entitled Assessing Communication for Social Change: A New Agenda in Impact Assessment. Building on previous development communication projects which used ethnographic action research, this project is developing, trailing and rigorously evaluating a participatory impact assessment methodology for assessing the social change impacts of community radio programs in Nepal. This project is a collaboration between Equal Access – Nepal (EAN), Equal Access – International, local stakeholders and listeners, a network of trained community researchers, and a research team from two Australian universities. A key element of the project is the establishment of an organisational culture within EAN that values and supports the impact assessment process being developed, which is based on continuous action learning and improvement. The paper describes the situation related to monitoring and evaluation (M&E) and impact assessment before the project began, in which EAN was often reliant on time-bound studies and ‘success stories’ derived from listener letters and feedback. We then outline the various strategies used in an effort to develop stronger and more effective impact assessment and M&E systems, and the gradual changes that have occurred to date. These changes include a greater understanding of the value of adopting a participatory, holistic, evidence-based approach to impact assessment. We also critically review the many challenges experienced in this process, including:----- • Tension between the pressure from donors to ‘prove’ impacts and the adoption of a bottom-up, participatory approach based on ‘improving’ programs in ways that meet community needs and aspirations.----- • Resistance from the content teams to changing their existing M&E practices and to the perceived complexity of the approach.----- • Lack of meaningful connection between the M&E and content teams.----- • Human resource problems and lack of capacity in analysing qualitative data and reporting results.----- • The contextual challenges, including extreme poverty, wide cultural and linguistic diversity, poor transport and communications infrastructure, and political instability.----- • A general lack of acceptance of the importance of evaluation within Nepal due to accepting everything as fate or ‘natural’ rather than requiring investigation into a problem.

The influence of social communication networks on intentions to purchase on the web

Despite the increased offering of online communication channels to support web-based retail systems, there is limited marketing research that investigates how these channels act singly, or in combination with online channels, to influence an individual' s intention to purchase online. If the marketer's strategy is to encourage online transactions, this requires a focus on consumer acceptance of the web-based transaction technology, rather than the purchase of the products per se. The exploratory study reported in this paper examines normative influences from referent groups in an individual's on and offline social communication networks that might affect their intention to use online transaction facilities. The findings suggest that for non-adopters, there is no normative influence from referents in either network. For adopters, one online and one offline referent norm positively influenced this group's intentions to use online transaction facilities. The implications of these findings are discussed together with future research directions.