Scientometric portraits of recognized scientists: a structured literature review

Scientometrics - The purpose of scientometric portraits is to recognize prominent scholars, inspire others, and guide those who dedicate their lives to scientific advancement. This study presents...     

National culture and operations management: a structured literature review

National culture has received a substantial amount of interest in the operations management literature. We present the first structured review of articles studying national culture in operations management. Our search returned 51 papers published in ten leading journals between 2000 and 2017. We sort and analyse the papers according to three focus areas of operations management (strategy, execution and improvement). We also analyse the papers according to whether they address the relevance of national culture, the impact of national culture or the actions managers can use to manage or mitigate the effects of national culture. We find that national culture appears as a relevant variable in all focus areas of operations management research but that the direction and strength of its impact remain undetermined. Only a handful of papers address how managers can actively deal with challenges related to national culture. We propose a research agenda and a guiding framework for future research.     

Modelling aspects of cancer dynamics: a review

Cancer is a complex disease in which a variety of factors interact over a wide range of spatial and temporal scales with huge datasets relating to the different scales available. However, these data do not always reveal the mechanisms underpinning the observed phenomena. In this paper, we explain why mathematics is a powerful tool for interpreting such data by presenting case studies that illustrate the types of insight that realistic theoretical models of solid tumour growth may yield. These range from discriminating between competing hypotheses for the formation of collagenous capsules associated with benign tumours to predicting the most likely stimulus for protease production in early breast cancer. We will also illustrate the benefits that may result when experimentalists and theoreticians collaborate by considering a novel anti-cancer therapy.     

Utility of R0 as a predictor of disease invasion in structured populations

Early theoretical work on disease invasion typically assumed large and well-mixed host populations. Many human and wildlife systems, however, have small groups with limited movement among groups. In these situations, the basic reproductive number, R0, is likely to be a poor predictor of a disease pandemic because it typically does not account for group structure and movement of individuals among groups. We extend recent work by combining the movement of hosts, transmission within groups, recovery from infection and the recruitment of new susceptibles into a stochastic model of disease in a host metapopulation. We focus on how recruitment of susceptibles affects disease invasion and how population structure can affect the frequency of superspreading events (SSEs). We show that the frequency of SSEs may decrease with the reduced movement and the group sizes due to the limited number of susceptible individuals available. Classification tree analysis of the model results illustrates the hierarchical nature of disease invasion in host metapopulations. First, the pathogen must effectively transmit within a group (R0>1), and then the pathogen must persist within a group long enough to allow for movement among the groups. Therefore, the factors affecting disease persistence--such as infectious period, group size and recruitment of new susceptibles--are as important as the local transmission rates in predicting the spread of pathogens across a metapopulation.     

Evolutionary dynamics of scientific collaboration networks: multi-levels and cross-time analysis

Several studies exist which use scientific literature for comparing scientific activities (e.g., productivity, and collaboration). In this study, using co-authorship data over the last 40 years, we present the evolutionary dynamics of multi level (i.e., individual, institutional and national) collaboration networks for exploring the emergence of collaborations in the research field of “steel structures”. The collaboration network of scientists in the field has been analyzed using author affiliations extracted from Scopus between 1970 and 2009. We have studied collaboration distribution networks at the micro-, meso- and macro-levels for the 40 years. We compared and analyzed a number of properties of these networks (i.e., density, centrality measures, the giant component and clustering coefficient) for presenting a longitudinal analysis and statistical validation of the evolutionary dynamics of “steel structures” collaboration networks. At all levels, the scientific collaborations network structures were central considering the closeness centralization while betweenness and degree centralization were much lower. In general networks density, connectedness, centralization and clustering coefficient were highest in marco-level and decreasing as the network size grow to the lowest in micro-level. We also find that the average distance between countries about two and institutes five and for authors eight meaning that only about eight steps are necessary to get from one randomly chosen author to another.     

Edge effects in game-theoretic dynamics of spatially structured tumours

Cancer dynamics are an evolutionary game between cellular phenotypes. A typical assumption in this modelling paradigm is that the probability of a given phenotypic strategy interacting with another depends exclusively on the abundance of those strategies without regard for local neighbourhood structure. We address this limitation by using the Ohtsuki–Nowak transform to introduce spatial structure to the go versus grow game. We show that spatial structure can promote the invasive (go) strategy. By considering the change in neighbourhood size at a static boundary—such as a blood vessel, organ capsule or basement membrane—we show an edge effect that allows a tumour without invasive phenotypes in the bulk to have a polyclonal boundary with invasive cells. We present an example of this promotion of invasive (epithelial–mesenchymal transition-positive) cells in a metastatic colony of prostate adenocarcinoma in bone marrow. Our results caution that pathologic analyses that do not distinguish between cells in the bulk and cells at a static edge of a tumour can underestimate the number of invasive cells. Although we concentrate on applications in mathematical oncology, we expect our approach to extend to other evolutionary game models where interaction neighbourhoods change at fixed system boundaries.     

Polyhedral dynamics as a tool for machine-part group formation

It has been suggested that the efficiency and economics of a flexible manufacturing system can be improved through judicious grouping of machines and parts. This paper addresses the formulation of families of parts requiring similar manufacturing with closely related machines using the topological concepts of polyhedral dynamics (i.e. q-analysis).

An introduction to the concepts of q-analysis is presented and is followed by a discussion of the application to machine-part group formation. Two examples from the literature are presented and the resulting part groupings compared. The results suggest that q-analysis not only provides part grouping capabilities equivalent to current techniques, but also provides additional qualitative information. Measures are available which provide insight into the importance of particular groupings and the strength of the interaction between the groups. The analysis also identifies machines with are potential bottlenecks, and parts whose availability may impact the manufacturing process. A measure is also available for comparing various flexible manufacturing system options in terms of process stability or controllability through a qualitative estimate of system complexity.     

Molecular dynamics simulations of fcc-to-bcc transformation in pure iron: a review

Molecular dynamics (MD) simulation has been used to study the martensitic transformation in iron at the atomic scale. The paper reviews the available interatomic interaction potentials for iron, which describe the properties of different phases present in that system. Cases on the fcc-to-bcc transformation in iron by MD simulations were included in the present paper. Factors affecting the fcc-to-bcc transformation in iron were analysed: (a) structural factors, such as grain/phase boundaries, grain sizes and stacking faults; (b) simulation conditions, such as the presence of free surfaces, external stress/strain and studied temperatures; (c) the interatomic interaction potential. The main emphasis of the present paper is on results giving insight on the mechanisms of the nucleation and growth of bcc phase in iron.

This review was submitted as part of the 2016 Materials Literature Review Prize of the Institute of Materials, Minerals and Mining run by the Editorial Board of MST. Sponsorship of the prize by TWI Ltd is gratefully acknowledged.     

Matrices of science and technology interactions and patterns of structured growth: implications for development

Scientific and other non-patent references (NPRs) in patents are important tools to analyze interactions between science and technology. This paper organizes a database with 514,894 USPTO patents granted globally in 1974, 1982, 1990, 1998 and 2006. There are 165,762 patents with at least one reference to science and engineering (S&E) literature, from a total of 1,375,503 references. Through a lexical analysis, 71.1% of this S&E literature is classified by S&E fields. These data serve as the basis for the elaboration of global and national 3-dimensional matrices (technological domains, S&E fields and number of references). Three indicators are proposed to analyze these matrices, allowing us to identify patterns of structured growth that differentiate developed and non-developed countries. This differentiation informs suggestions for public policies for development, emphasizing the need for an articulation between the industrial and technological dimension and scientific side. The intertwinement of these two dimensions is a key component of developmental policies for the twenty-first century.     

Aspiration dynamics of multi-player games in finite populations

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.     

Plug-and-play inference for disease dynamics: measles in large and small populations as a case study

Statistical inference for mechanistic models of partially observed dynamic systems is an active area of research. Most existing inference methods place substantial restrictions upon the form of models that can be fitted and hence upon the nature of the scientific hypotheses that can be entertained and the data that can be used to evaluate them. In contrast, the so-called plug-and-play methods require only simulations from a model and are thus free of such restrictions. We show the utility of the plug-and-play approach in the context of an investigation of measles transmission dynamics. Our novel methodology enables us to ask and answer questions that previous analyses have been unable to address. Specifically, we demonstrate that plug-and-play methods permit the development of a modelling and inference framework applicable to data from both large and small populations. We thereby obtain novel insights into the nature of heterogeneity in mixing and comment on the importance of including extra-demographic stochasticity as a means of dealing with environmental stochasticity and model misspecification. Our approach is readily applicable to many other epidemiological and ecological systems.     

Modelling architectures: A review of their application in structured methods for information systems specification

This paper investigates and presents views on how enterprise modelling architectures can be deployed within various stages of structured methodologies for information systems specification. The high level role of the CIMOSA and ARIS modelling architectures within the SSADM methodology for capturing the specification process is first discussed. This is to highlight the flexibility and potential applicability of these architectures in complementary roles within structured methodologies. The constructs of the CIMOSA modelling architecture are subsequently used to show the features which support the development of information system specifications for applications in manufacturing enterprises.     

Carbon nanotube–polymer interactions in nanocomposites: A review

The interaction between carbon nanotubes and polymers is critically reviewed. The interfacial characteristics directly influence the efficiency of nanotube reinforcements in improving mechanical, thermal, and electrical properties of the polymer nanocomposite. In this review, various techniques of interaction measurements, including experimental and modelling studies, are described. From the experimental approaches, wetting, spectroscopy and probe microscopy techniques are discussed in detail. Molecular dynamics, coarse grain simulation and density functional theory are also explained as the main modelling approaches in interaction measurement studies. Different methods of interaction improvement, mainly categorized under covalent and noncovalent interactions, are described afterwards. Modelling predictions of nanocomposite properties, such as Young’s modulus, are compared with the experimental results in the literature and the challenges are discussed. Finally, it is concluded that an optimum carbon nanotube–polymer interaction is a key factor towards reaching the full potential of carbon nanotubes in nanocomposites.     

Application of materials based on group VB elements in sodium-ion batteries: A review

Owing to their high redox activity, abundant resource, and low cost, compounds based on group VB elements (V, Nb, and Ta) are promising electrode materials for an array of energy storage devices. Moreover, their open structure benefits transportation and accommodation of alkali Na⁺ ions, rending them particularly appealing for cost-effective sodium-ion batteries (SIBs). In the last decade, these materials have evoked intensive investigations in SIBs, serving as either cathode, anode, or both depending on their sodiation degree and redox potential. Exciting progress has been made, but significant gaps in our knowledge still remain. Their practical application in SIBs remains unclear and thus calls for further efforts to settle several technical challenges in terms of poor conductivity, unstable cycling, and inefficient charge storage. In this perspective, a brief overview is given of recent progress on how to solve these technical issues and envision their bright future in SIBs, which may serve as a source to inspire researches on relevant topics.     

Resolution in structured illumination microscopy: a probabilistic approach

Structured illumination can be employed to extend the lateral resolution of wide-field fluorescence microscopy. Since a structured illumination microscopy image is reconstructed from a series of several acquired images, we develop a modified formulation of the imaging response of the microscope and a probabilistic analysis to assess the resolution performance. We use this model to compare the fluorescence imaging performance of structured illumination techniques to confocal microscopy. Specifically, we examine the trade-off between achievable lateral resolution and signal-to-noise ratio when photon shot noise is dominant. We conclude that for a given photon budget, structured illumination invariably achieves better lateral resolution than confocal microscopy.     

Evolutionary dynamics of morphological stability in a long‐term experiment with Escherichia coli

To investigate the questions in morphological evolution, some biologists seek to carry out evolution experiments owing to the incompleteness and uncontrollability of the fossil record and natural populations. To quantitatively analyse the morphology (cell size) evolution observed from a long‐term experiment with Escherichia coli, the authors present three mathematical approximations to the Wright–Fisher model of the morphological evolution. They firstly use a deterministic approximation, which fails to predict evolutionary dynamics of cell size and proves the importance of stochasticity in large populations. Then, they develop a stochastic approximation and derive an analytic expression for the anticipated waiting time to reach the stability of cell size. The results show that the calculation of this waiting time is in good agreement with the experimental data and that the selective advantage plays a prominent role in cell size evolution, with mutation rate and population size having less impact. Finally, they employ a multistep process to approximate the Wright–Fisher model of cell size evolution and acquire an analytical formula for the median waiting time until the stability of cell size. This median time supports the idea that the selective advantage is the dominant force for the morphological evolution in the long‐term experiment.Inspec keywords: microorganisms, cellular biophysics, evolution (biological), stochastic processesOther keywords: morphological stability, Escherichia coli, evolutionary dynamics, morphological evolution, Wright–Fisher model, deterministic approximation, stochastic approximation, mutation rate, population size, cell size evolution     

Designing low-cost modified cladding sensors: a structured approach

In this paper, a novel solution for signal conditioning, fiber illumination, and measurement is proposed for an optical fiber sensor based on a modified cladding sensing element. The presented technique has properties of compactness and low cost, due to the use of very common optoelectronic components, and flexibility, since it could be employed for different kinds of optical fiber sensors. In particular, a prototype has been realized and characterized for the measurement of liquid temperature.     

A review on rising bubble dynamics in viscosity-stratified fluids

Systems with a bubble rising in a fluid, which has a variation of viscosity in space and time can be found in various natural phenomena and industrial applications, including food processing, oil extraction, waste processing and biochemical reactors, to name a few. A review of the aspects studied in the literature on this phenomenon, the gaps that exist and the direction for further numerical and experimental studies to address these gaps is presented.