Exploring how complex solution-based capabilities (CSC) are developed and integrated in engineering companies

This paper explores how engineering companies develop and integrate solution-based capabilities for complex ‘one-off’ or small-batch production. Although there is extant literature on developing a standalone service, product and process capabilities, an integrated solution-based capability for effective execution of complex ‘design-build’ projects is currently underdeveloped. For such firms to be successful in delivering complex solutions, there is the need for organisational structured routines and processes which we conceptualise as complex solution-based capabilities (CSC). The study was based on a multiple case study using in-depth semi-structured interviews with managers and engineers. Primary data collected were complemented by documentary evidence, for triangulation and validity. The data were analysed using thematic analysis to develop a framework of CSC. The findings show that the case study companies have developed and integrated CSC through organisational routines and processes of make-to-concept approach, value creation, and strategic coordination. Implications and future research are discussed

Integrating quality control and performance management in developing complex bespoke systems

Risk and performance management are at the core of complex bespoke systems (CBSs). CBSs are developed to customer–specified requirements in terms of structure, functionality and conformance. This paper examines how risk and performance management are integrated as essential systems in the successful development of projects across multi-organisational functions in complex bespoke system (CBS) organisations. The paper argues for the development of a quality management system that consists of two sub-processes: quality control and quality development. Using three case studies from engineering companies, we provide evidence and insights of the way change control, quality development and quality performance are developed in innovating business solutions

Knowledge discovery for friction stir welding via data driven approaches: Part 2 – multiobjective modelling using fuzzy rule based systems

In this final part of this extensive study, a new systematic data-driven fuzzy modelling approach has been developed, taking into account both the modelling accuracy and its interpretability (transparency) as attributes. For the first time, a data-driven modelling framework has been proposed designed and implemented in order to model the intricate FSW behaviours relating to AA5083 aluminium alloy, consisting of the grain size, mechanical properties, as well as internal process properties. As a result, ‘Pareto-optimal’ predictive models have been successfully elicited which, through validations on real data for the aluminium alloy AA5083, have been shown to be accurate, transparent and generic despite the conservative number of data points used for model training and testing. Compared with analytically based methods, the proposed data-driven modelling approach provides a more effective way to construct prediction models for FSW when there is an apparent lack of fundamental process knowledge

Complex k band diagrams of 3D metamaterial/photonic crystals

A finite element method (FEM) for solving the complex valued k({\omega}) vs. {\omega} dispersion curve of a 3D metamaterial/photonic crystal system is presented. This 3D method is a generalization of a previously reported 2D eigenvalue method. This method is particularly convenient for analyzing periodic systems containing dispersive (e.g., plasmonic) materials, for computing isofrequency surfaces in the k-space, and for calculating the decay length of the evanescent waves. Two specific examples are considered: a photonic crystal comprised of dielectric spheres and a plasmonic fishnet structure. Hybridization and avoided crossings between Mie resonances and propagating modes are numerically demonstrated. Negative index propagation of four electromagnetic modes distinguished by their symmetry is predicted for the plasmonic fishnets. By calculating the isofrequency contours, we also demonstrate that the fishnet structure is a hyperbolic medium

X-ray Imaging of Transplanar Liquid Transport Mechanisms in Single Layer Textiles

Understanding the penetration of liquids within textile fibers is critical for the development of next-generation smart textiles. Despite substantial research on liquid penetration in the plane of the textile, little is known about how the liquid penetrates in the thickness direction. Here we report a time-resolved high-resolution X-ray measurement of the motion of the liquid–air interface within a single layer textile, as the liquid is transported across the textile thickness following the deposition of a droplet. The measurement of the time-dependent position of the liquid meniscus is made possible by the use of ultrahigh viscosity liquids (dynamic viscosity from 10⁵ to 2.5 × 10⁶ times larger than water). This approach enables imaging due to the slow penetration kinetics. Imaging results suggest a three-stage penetration process with each stage being associated with one of the three types of capillary channels existing in the textile geometry, providing insights into the effect of the textile structure on the path of the three-dimensional liquid meniscus. One dimensional kinetics studies show that our data for the transplanar penetration depth Δ<i>x</i>_L vs time do not conform to a power law, and that the measured rate of penetration for long times is smaller than that predicted by Lucas–Washburn kinetics, challenging commonly held assumptions regarding the validity of power laws when applied to relatively thin textiles

1H, 13C, and 15N resonance assignments for the tandem PHD finger motifs of human CHD4

The plant homeodomain (PHD) zinc finger is a structural motif of about 40–60 amino acid residues found in many eukaryotic proteins that are involved in chromatin-mediated gene regulation. The human chromodomain helicase DNA binding protein 4 (CHD4) is a multi-domain protein that harbours, at its N-terminal end, a pair of PHD finger motifs (dPHD) connected by a ~30 amino acid linker. This tandem PHD motif is thought to be involved in targeting CHD4 to chromatin via its interaction with histone tails. Here we report the 1H, 13C and 15N backbone and side-chain resonance assignment of the entire dPHD by heteronuclear multidimensional NMR spectroscopy. These assignments provide the starting point for the determination of the structure, dynamics and histone-binding properties of this tandem domain pair

Integration of environmental aspects in modelling and optimisation of water supply chains

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure

NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity

In Diffusion Weighted MR Imaging (DWI), the signal is affected by the biophysical properties of neuronal cells and their relative placement, as well as extra-cellular tissue compartments. Typically, microstructural indices, such as fractional anisotropy (FA) and mean diffusivity (MD), are based on a tensor model that cannot disentangle the influence of these parameters. Recently, Neurite Orientation Dispersion and Density Imaging (NODDI) has exploited multi-shell acquisition protocols to model the diffusion signal as the contribution of three tissue compartments. NODDI microstructural indices, such as intra-cellular volume fraction (ICVF) and orientation dispersion index (ODI) are directly related to neuronal density and orientation dispersion, respectively. One way of examining the neurophysiological role of these microstructural indices across neuronal fibres is to look into how they relate to brain function. Here we exploit a statistical framework based on sparse Canonical Correlation Analysis (sCCA) and randomised Lasso to identify structural connections that are highly correlated with resting-state functional connectivity measured with simultaneous EEG-fMRI. Our results reveal distinct structural fingerprints for each microstructural index that also reflect their inter-relationships

Global transcriptional response of pig brain and lung to natural infection by Pseudorabies virus.

BACKGROUND: Pseudorabies virus (PRV) is an alphaherpesviruses whose native host is pig. PRV infection mainly causes signs of central nervous system disorder in young pigs, and respiratory system diseases in the adult. RESULTS: In this report, we have analyzed native host (piglets) gene expression changes in response to acute pseudorabies virus infection of the brain and lung using a printed human oligonucleotide gene set from Illumina. A total of 210 and 1130 out of 23,000 transcript probes displayed differential expression respectively in the brain and lung in piglets after PRV infection (p-value < 0.01), with most genes displaying up-regulation. Biological process and pathways analysis showed that most of the up-regulated genes are involved in cell differentiation, neurodegenerative disorders, the nervous system and immune responses in the infected brain whereas apoptosis, cell cycle control, and the mTOR signaling pathway genes were prevalent in the infected lung. Additionally, a number of differentially expressed genes were found to map in or close to quantitative trait loci for resistance/susceptibility to pseudorabies virus in piglets. CONCLUSION: This is the first comprehensive analysis of the global transcriptional response of the native host to acute alphaherpesvirus infection. The differentially regulated genes reported here are likely to be of interest for the further study and understanding of host viral gene interactions.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202