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To present a discrete particle model for granular materials.

Starting with kinematical analysis of relative movements of two typical circular grains with different radii in contact, both the relative rolling and the relative sliding motion measurements at contact, including translational and angular velocities (displacements) are defined. Both the rolling and sliding friction tangential forces, and the rolling friction resistance moment, which are constitutively related to corresponding relative motion measurements defined, are formulated and integrated into the framework of dynamic model of the discrete element method.

Numerical results demonstrate that the importance of rolling friction resistance, including both rolling friction tangential force and rolling friction resistance moment, in correct simulations of physical behavior in particulate systems; and the capability of the proposed model in simulating the different types of failure modes, such as the landslide (shear bands), the compression cracking and the mud avalanching, in granular materials.

Each grain in the particulate system under consideration is assumed to be rigid and circular. Do not account for the effects of plastic deformation at the contact points.

To model the failure phenomena of granular materials in geo‐mechanics and geo‐technical engineering problems; and to be a component model in a combined discrete‐continuum macroscopic approach or a two‐scale discrete‐continuum micro‐ macro‐scopic approach to granular media.

This paper develops a new discrete particle model to describe granular media in several branches of engineering such as soil mechanics, power technologies or sintering processes.

This paper aims to present a new numerical model for geometric nonlinear analysis of thin-shell structures based on a combined finite-discrete element method (FDEM).

The model uses rotation-free, three-node triangular finite elements with exact formulation for large rotations, large displacements in conjunction with small strains.

The presented numerical results related to behaviour of arbitrary shaped thin shell structures under large rotations and large displacement are in a good agreement with reference solutions.

This paper presents new computationally efficient numerical model for geometric nonlinear analysis and prediction of the behaviour of thin-shell structures based on combined FDEM. The model is implemented into the open source FDEM package “Yfdem”, and is tested on simple benchmark problems.

This paper outlines a dynamic domain decomposition‐based parallel strategy for combined finite/discrete element analysis of multi‐fracturing solids and discrete systems. Attention is focused on the parallelised interaction detection between discrete objects. Two graph representation models for discrete objects in contact are proposed which lay the foundation of the current development. In addition, a load imbalance detection and re‐balancing scheme is also suggested to enhance the parallel performance. Finally, numerical examples are provided to illustrate the parallel performance achieved with the current implementation.

This chapter provides a comprehensive review of research and developments relating to the use of Web 2.0 technologies in education. As opposed to early educational uses of the Internet involving publication of static information on web pages, Web 2.0 tools offer a host of opportunities for educators to provide more interactive, collaborative, and creative online learning experiences for students. The chapter starts by defining Web 2.0 tools in terms of their ability to facilitate online creation, editing, and sharing of web content. A typology of Web 2.0 technologies is presented to illustrate the wide variety of tools at teachers’ disposal. Educational uses of Web 2.0 technologies such as wikis, blogs, and microblogging are explored, in order to showcase the variety of designs that can be utilized. Based on a review of the research literature the educational benefits of using Web 2.0 technologies are outlined, including their ability to facilitate communication, collaborative knowledge building, student-centered activity, and vicarious learning. Similarly, issues surrounding the use of Web 2.0 tools are distilled from the literature and discussed, such as the possibility of technical problems, collaboration difficulties, and plagiarism. Two case studies involving the use Web 2.0 tools to support personalized learning and small group collaboration are detailed to exemplify design possibilities in greater detail. Finally, design recommendations for learning and teaching using Web 2.0 are presented, again based on findings from the research literature.

Some issues related to effective parallel implementation of the combined finite‐discrete element approach on PC clusters are discussed. Attention is focused on the interprocessor communications. Three communication schemes suitable for different problems are presented. The worker‐to‐manager scheme is simple to implement. The neighbour‐to‐neighbour scheme is sophisticated with regard to programming, and requires extra memory space, but has good overall performance for larger problems. The mixed worker‐manager scheme can balance the difficulty in programming and the overall communication performance. The effects of subdomain buffer zone on communications are also demonstrated by numerical examples.

This chapter explores the media coverage of the 2016 Presidential campaign and reveals the corruption fantasy themes that emerged. Media coverage of corruption can uniquely affect voter attitudes and public policy formulation and implementation, as revealed in previous scholarship on media coverage of corruption. By tracing the competing narratives offered in media coverage utilizing the constant comparative method, the dramatic characters, Crooked Hillary and Corrupt Businessman Trump, are identified and their storylines are explicated. Analysis reveals these dramatic fantasy themes chained through social media, evincing and promoting the narratives that drove media coverage of our political leaders and public policy results. The chapter illustrates that the narratives involving corruption were prominent and negative, further indicating that the media’s obsession with scandal contributed to and supported the narratives that portrayed both candidates as corrupt, adding pollution to the 2016 U.S. political environment.

Research involving interorganizational relationships (IORs) has grown at an impressive rate. Several datasets have been used to understand the nature and performance implications of these relationships. Given the importance of such relationships, we describe a relatively new dataset, Bloomberg SPLC, which contains data regarding the percentage of costs and revenues attributed to suppliers and customers, as well as allows researchers to construct a comprehensive dataset of IORs of buyer–supplier networks. Because of this, Bloomberg SPLC data can be used to uncover new and exciting theoretical and empirical implications. This chapter provides background information about this dataset, guidance on how it can be leveraged, and new theoretical terrain that can be charted to better understand IORs.

Without the stories, or narratives that organisations construct, there could be no social negotiation or sense making. A problem is that the narratives are often “too straight”, too simplistic and self‐serving to be helpful representations of reality. Most stories in organisations that are used to manage change efforts are too simple, and too much believed. They foster naive optimism that soon degenerates into cynicism. Stories are maps, but are often confused with the territories themselves. Some examples of stories or accounts of organisational change efforts that are straight, and how they might have been made more “crooked”, are discussed. Some suggestions on how leaders in organisations can become more thoughtful consumers of straight stories and make those stories more helpful maps to guide organisations through the turbulence of change are offered.

Purpose: The issue of whether participation in online peer-support communities has positive or negative impacts on the psychological adjustment of cancer patients warrants further explorations from new perspectives. This research investigates the role of personality traits in moderating the impact of online participation on the psychological adjustment of cancer patients in terms of their general psychological well-being and cancer-specific well-being.

Methodology: Study participants consisted of adults diagnosed with leukemia. Questionnaires were collected from 111 participants in two leukemia-related forums in China, Baidu Leukemia Community and Bloodbbs. Information regarding the personality traits, online participation, and psychological adjustment were collected using an online questionnaire. A linear regression model was used to test the moderation effect of personality traits on the relationship between online participation and psychological adjustment.

Findings: The main effect of participation in online support communities on psychological adjustment was not statistically significant. Importantly, two personality traits (i.e., emotional stability and openness to experience) moderated the relationship between online participation and psychological adjustment to cancer. Leukemia patients with high emotional stability and high openness to experience reported better psychological adjustment as they participated more in the online community. However, this was not the case for patients with low stability and low openness, who reported worse psychological adjustment as their participation in the online support community increased.

Value: This study introduces two personality moderators into the discussion of how participation in online support communities influences the lives of cancer patients. The moderation effects help to explain why there have been contradictions in the findings of previous studies. In addition, this study adds to the current literature on online support communities as little research on this topic has been conducted outside of the US and Europe. Practically, this study not only highlights the need to evaluate the personality traits of patients who are recommended to participate in online communities, but also underlines the necessity of intervention in these communities.

Probability of Default (PD) is a crucial credit risk parameter. International accords have motivated banks and credit institutions to adopt objective systems of evaluating and monitoring the PD. This study examines retail unsecured loans of a major Greek bank during the period of the financial crisis. It focusses on the stochastic behaviour of the financial states of the loans. It is tested whether a first-order Markov chain (MC) model describes sufficiently the transitions from one state to another. Moreover, Poisson regression models are estimated in order to calculate the limiting transition matrix, the limiting state probabilities and the PD. It is proved that the MC of the financial states of loans is non-homogeneous suggesting that the transition probabilities from one financial state to another are not constant across time. From the Poisson regression models, the transition probability matrix is estimated from one state to another in alternative time periods. From the limiting transition matrix, it is shown that if a loan is delayed then it is very likely to move towards the next worst case. The findings of this research could be useful for bank management.