Mass media and polarisation processes in the bounded confidence model of opinion dynamics

This paper presents a social simulation in which we add an additional layer of mass media communication to the social network 'bounded confidence' model of Deffuant et al (2000). A population of agents on a lattice with continuous opinions and bounded confidence adjust their opinions on the basis of binary social network interactions between neighbours or communication with a fixed opinion. There are two mechanisms for interaction. 'Social interaction' occurs between neighbours on a lattice and 'mass communication' adjusts opinions based on an agent interacting with a fixed opinion. Two new variables are added, polarisation: the degree to which two mass media opinions differ, and broadcast ratio: the number of social interactions for each mass media communication. Four dynamical regimes are observed, fragmented, double extreme convergence, a state of persistent opinion exchange leading to single extreme convergence and a disordered state. Double extreme convergence is found where agents are less willing to change opinion and mass media communications are common or where there is moderate willingness to change opinion and a high frequency of mass media communications. Single extreme convergence is found where there is moderate willingness to change opinion and a lower frequency of mass media communication. A period of persistent opinion exchange precedes single extreme convergence, it is characterized by the formation of two opposing groups of opinion separated by a gradient of opinion exchange. With even very low frequencies of mass media communications this results in a move to central opinions followed by a global drift to one extreme as one of the opposing groups of opinion dominates. A similar pattern of findings is observed for Neumann and Moore neighbourhoods.

Turning the tide: A critique of Natural Semantic Metalanguage from a translation studies perspective

Starting from the premise that human communication is predicated on translational phenomena, this paper applies theoretical insights and practical findings from Translation Studies to a critique of Natural Semantic Metalanguage (NSM), a theory of semantic analysis developed by Anna Wierzbicka. Key tenets of NSM, i.e. (1) culture-specificity of complex concepts; (2) the existence of a small set of universal semantic primes; and (3) definition by reductive paraphrase, are discussed critically with reference to the notions of untranslatability, equivalence, and intra-lingual translation, respectively. It is argued that a broad spectrum of research and theoretical reflection in Translation Studies may successfully feed into the study of cognition, meaning, language, and communication. The interdisciplinary exchange between Translation Studies and linguistics may be properly balanced, with the former not only being informed by but also informing and interrogating the latter.

Betwixt spaces: Students’ accounts of turning point experiences in first-year transitions

'Not belonging' is becoming a prevalent theme within accounts of the first-year student experience at university. In this study the notion of not belonging is extended by assuming a more active role for the idea of liminality in a student's transition into the university environments of academic and student life. In doing so, the article suggests that the transition between one place (home) and another (university) can result in an 'in-between-ness' - a betwixt space. Through an interpretative methodology, the study explores how students begin to move from this betwixt space into feeling like fully-fledged members of university life. It is concluded that there is a wide range of turning points associated with the students' betwixt transition, which shapes, alters or indeed accentuates the ways in which they make meaningful connections with university life. Moreover, transitional turning point experiences reveal a cast of characters and symbolic objects; capture contrasting motivations and evolving relationships; display multiple trajectories of interpersonal tensions and conflicts; highlight discontinuities as well as continuities; and together, simultaneously liberate and constrain the students' transition into university life.

Completely bounded disjointness preserving operators between Fourier algebras

In this paper, we characterize surjective completely bounded disjointness preserving linear operators on Fourier algebras of locally compact amenable groups. We show that such operators are given by weighted homomorphisms induced by piecewise affine proper maps. © 2011 Elsevier Inc.

Molecular dynamics simulation model for the quantitative assessment of tool wear during single point diamond turning of cubic silicon carbide

Silicon carbide (SiC) is a material of great technological interest for engineering applications concerning hostile environments where silicon-based components cannot work (beyond 623 K). Single point diamond turning (SPDT) has remained a superior and viable method to harness process efficiency and freeform shapes on this harder material. However, it is extremely difficult to machine this ceramic consistently in the ductile regime due to sudden and rapid tool wear. It thus becomes non trivial to develop an accurate understanding of tool wear mechanism during SPDT of SiC in order to identify measures to suppress wear to minimize operational cost.

In this paper, molecular dynamics (MD) simulation has been deployed with a realistic analytical bond order potential (ABOP) formalism based potential energy function to understand tool wear mechanism during single point diamond turning of SiC. The most significant result was obtained using the radial distribution function which suggests graphitization of diamond tool during the machining process. This phenomenon occurs due to the abrasive processes between these two ultra hard materials. The abrasive action results in locally high temperature which compounds with the massive cutting forces leading to sp3–sp2 order–disorder transition of diamond tool. This represents the root cause of tool wear during SPDT operation of cubic SiC. Further testing led to the development of a novel method for quantitative assessment of the progression of diamond tool wear from MD simulations.

Brittle-ductile transition during diamond turning of single crystal silicon carbide

In this experimental study, diamond turning of single crystal 6H-SiC was performed at a cutting speed of 1 m/s on an ultra-precision diamond turning machine (Moore Nanotech 350 UPL) to elucidate the microscopic origin of ductile-regime machining. Distilled water (pH value 7) was used as a preferred coolant during the course of machining in order to improve the tribological performance. A high magnification scanning electron microscope (SEM FIB- FEI Quanta 3D FEG) was used to examine the cutting tool before and after the machining. A surface finish of Ra=9.2 nm, better than any previously reported value on SiC was obtained. Also, tremendously high cutting resistance was offered by SiC resulting in the observation of significant wear marks on the cutting tool just after 1 km of cutting length. It was found out through a DXR Raman microscope that similar to other classical brittle materials (silicon, germanium, etc.) an occurrence of brittle-ductile transition is responsible for the ductile-regime machining of 6H-SiC. It has also been demonstrated that the structural phase transformations associated with the diamond turning of brittle materials which are normally considered as a prerequisite to ductile-regime machining, may not be observed during ductile-regime machining of polycrystalline materials.

The development of a surface defect machining method for hard turning processes

Hard turning (HT) is a material removal process employing a combination of a single point cutting tool and high speeds to machine hard ferrous alloys which exhibit hardness values over 45 HRC. In this paper, a surface defect machining (SDM) method for HT is proposed which harnesses the combined advantages of porosity machining and pulsed laser pre-treatment processing. From previous experimental work, this was shown to provide better controllability of the process and improved quality of the machined surface. While the experiments showed promising results, a comprehensive understanding of this new technique could only be achieved through a rigorous, in depth theoretical analysis. Therefore, an assessment of the SDM technique was carried out using both finite element method (FEM) and molecular dynamics (MD) simulations.
FEM modelling was used to compare the conventional HT of AISI 4340 steel (52 HRC) using an Al2O3 insert with the proposed SDM method. The simulations showed very good agreement with the previously published experimental results. Compared to conventional HT, SDM provided favourable machining outcomes, such as reduced shear plane angle, reduced average cutting forces, improved surface roughness, lower residual stresses on the machined surface, reduced tool–chip interface contact length and increased chip flow velocity. Furthermore, a scientific explanation of the improved surface finish was revealed using a state-of-the-art MD simulation model which suggested that during SDM, a combination of both the cutting action and rough polishing action help improve the machined surface finish.

Prediction of surface roughness during hard turning of AISI 4340 steel (69 HRC)

In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).