Enhanced supply chain tracking based on the EPC network: A Bayesian approach

Supply chain tracking information is one of the main levers for achieving operational efficiency. RFID technology and the EPC Network can deliver serial-level product information that was never before available. However, these technologies still fail to meet the managers' visibility requirements in full, since they provide information about product location at specific time instances only. This paper proposes a model that uses the data provided by the EPC Network to deliver enhanced tracking information to the final user. Following a Bayesian approach, the model produces realistic ongoing estimates about the current and future location of products across a supply network, taking into account the characteristics of the product behavior and the configuration of the data collection points. These estimates can then be used to optimize operational decisions that depend on product availability at different locations. The enhancement of tracking information quality is highlighted through an example. © 2009 IFAC.

Managing global network operations along the engineering value chain

Purpose: This paper aims to improve understanding of how to manage global network operations from an engineering perspective. Design/methodology/approach: This research adopted a theory building approach based on case studies. Grounded in the existing literature, the theoretical framework was refined and enriched through nine in-depth case studies in the industry sectors of aerospace, automotives, defence and electrics and electronics. Findings: This paper demonstrates the main value creation mechanisms of global network operations along the engineering value chain. Typical organisational features to support the value creation mechanisms are captured, and the key issues in engineering network design and operations are presented with an overall framework. Practical implications: Evidenced by a series of pilot applications, outputs of this research can help companies to improve the performance of their current engineering networks and design new engineering networks to better support their global businesses and customers in a systematic way. Originality/value: Issues about the design and operations of global engineering networks (GEN) are poorly understood in the existing literature in contrast to their apparent importance in value creation and realisation. To address this knowledge gap, this paper introduces the concept of engineering value chain to highlight the potential of a value chain approach to the exploration of engineering activities in a complex business context. At the same time, it develops an overall framework for managing GEN along the engineering value chain. This improves our understanding of engineering in industrial value chains and extends the theoretical understanding of GEN through integrating the engineering network theories and the value chain concepts. © Emerald Group Publishing Limited.

Network integration for international mergers and Acquisitions

Business activities are increasingly taking place across geographical and ownership boundaries. Post-Merger & Acquisition Integration (PMI) processes are more challenging in network organisations due to the extra complexity and interdependency associated with networks. However, network integration issues are not well addressed in the traditional M&A literature or the network organisation literature. Based on ten in-depth case studies across key industry sectors, this research identifies the essential network integration issues for international M&As with a configuration concept, and demonstrates different network integration patterns according to M&A objectives for growth and efficiency. This paper extends the theoretical understanding of PMI for network organisations. It can also provide practical guidance for managers to assess the feasibility of an M&A transition or to go through the PMI process successfully. Copyright © 2010 Inderscience Enterprises Ltd.

Perturbation of the stability of amyloid fibrils through alteration of electrostatic interactions.

The self-assembly of proteins and peptides into polymeric amyloid fibrils is a process that has important implications ranging from the understanding of protein misfolding disorders to the discovery of novel nanobiomaterials. In this study, we probe the stability of fibrils prepared at pH 2.0 and composed of the protein insulin by manipulating electrostatic interactions within the fibril architecture. We demonstrate that strong electrostatic repulsion is sufficient to disrupt the hydrogen-bonded, cross-β network that links insulin molecules and ultimately results in fibril dissociation. The extent of this dissociation correlates well with predictions for colloidal models considering the net global charge of the polypeptide chain, although the kinetics of the process is regulated by the charge state of a single amino acid. We found the fibrils to be maximally stable under their formation conditions. Partial disruption of the cross-β network under conditions where the fibrils remain intact leads to a reduction in their stability. Together, these results support the contention that a major determinant of amyloid stability stems from the interactions in the structured core, and show how the control of electrostatic interactions can be used to characterize the factors that modulate fibril stability.

The toughness of adipose tissue: measurements and physical basis.

The measured toughness J(C) of adipose and dermal porcine tissues are 4.1 and 17 kJ m(-2), respectively, via a trouser tear test. An assessment is made of the contribution to overall toughness from the microstructural elements. The analysis suggests that the toughness of adipose tissue is determined by the collagen network that surrounds the adipocytes. The volume fraction of the interlobular septa is sufficiently low for it to make a negligible contribution to the macroscopic toughness.

Dynamic learning with the EM algorithm for neural networks

In this paper, we derive an EM algorithm for nonlinear state space models. We use it to estimate jointly the neural network weights, the model uncertainty and the noise in the data. In the E-step we apply a forwardbackward Rauch-Tung-Striebel smoother to compute the network weights. For the M-step, we derive expressions to compute the model uncertainty and the measurement noise. We find that the method is intrinsically very powerful, simple and stable.

Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

EARLY FLOWERING4 recruitment of EARLY FLOWERING3 in the nucleus sustains the Arabidopsis circadian clock

The plant circadian clock is proposed to be a network of several interconnected feedback loops, and loss of any component leads to changes in oscillator speed. We previously reported that Arabidopsis thaliana EARLY FLOWERING4 (ELF4) is required to sustain this oscillator and that the elf4 mutant is arrhythmic. This phenotype is shared with both elf3 and lux. Here, we show that overexpression of either ELF3 or LUX ARRHYTHMO (LUX) complements the elf4 mutant phenotype. Furthermore, ELF4 causes ELF3 to form foci in the nucleus. We used expression data to direct a mathematical position of ELF3 in the clock network. This revealed direct effects on the morning clock gene PRR9, and we determined association of ELF3 to a conserved region of the PRR9 promoter. A cis-element in this region was suggestive of ELF3 recruitment by the transcription factor LUX, consistent with both ELF3 and LUX acting genetically downstream of ELF4. Taken together, using integrated approaches, we identified ELF4/ELF3 together with LUX to be pivotal for sustenance of plant circadian rhythms. © 2012 American Society of Plant Biologists.

Defining product-service network configurations and location roles: A current and future state analysis framework for international engineering operations

Many manufacturing firms have developed a service dimension to their product portfolio. In response to this growing trend of servitisation, organisations, often involved in complex, long-lifecycle product-service system (PSS) provision, need to reconfigure their global engineering networks to support integrated PSS offerings. Drawing on parallel concepts in 'production' networks, the idea of 'location role' now becomes increasingly complex, in terms of service delivery. As new markets develop, locations in a specific region may need to grow/adapt engineering service 'competencies' along the value chain, from design and build to support and service, in order to serve future location-specific requirements and, potentially, those requirements of the overall network. The purpose of this paper is to advance understanding of how best to design complex multi-organisational engineering service networks, through extension of the 'production' network location role concept to a PSS context, capturing both traditional engineering 'design and build' and engineering 'service' requirements. Copyright © 2012 Inderscience Enterprises Ltd.

Empathy for pain involves the affective but not sensory components of pain.

Our ability to have an experience of another's pain is characteristic of empathy. Using functional imaging, we assessed brain activity while volunteers experienced a painful stimulus and compared it to that elicited when they observed a signal indicating that their loved one--present in the same room--was receiving a similar pain stimulus. Bilateral anterior insula (AI), rostral anterior cingulate cortex (ACC), brainstem, and cerebellum were activated when subjects received pain and also by a signal that a loved one experienced pain. AI and ACC activation correlated with individual empathy scores. Activity in the posterior insula/secondary somatosensory cortex, the sensorimotor cortex (SI/MI), and the caudal ACC was specific to receiving pain. Thus, a neural response in AI and rostral ACC, activated in common for "self" and "other" conditions, suggests that the neural substrate for empathic experience does not involve the entire "pain matrix." We conclude that only that part of the pain network associated with its affective qualities, but not its sensory qualities, mediates empathy.