Critical timescales and time intervals for coupled linear processes

In 1991, McNabb introduced the concept of mean action time (MAT) as a finite measure of the time required for a diffusive process to effectively reach steady state. Although this concept was initially adopted by others within the Australian and New Zealand applied mathematics community, it appears to have had little use outside this region until very recently, when in 2010 Berezhkovskii and coworkers rediscovered the concept of MAT in their study of morphogen gradient formation. All previous work in this area has been limited to studying single–species differential equations, such as the linear advection–diffusion–reaction equation. Here we generalise the concept of MAT by showing how the theory can be applied to coupled linear processes. We begin by studying coupled ordinary differential equations and extend our approach to coupled partial differential equations. Our new results have broad applications including the analysis of models describing coupled chemical decay and cell differentiation processes, amongst others.

A comment on "Inherited Trust and Growth"

Algan and Cahuc (2010) argue that “inherited trust” is a key factor in explaining growth rates across countries. They derive a measure of inherited trust by linking respondents’ “home countries: in the United States General Social Survey (1972-2004) and the 2000 wave of the World Values Survey. Algan and Cahuc then estimate trust levels for people born before 1910 (inherited trust in 1935) and afterwards (inherited trust in 2000). They show a strong link between economic growth rates and inherited trust. We do not challenge this result, but we do argue that: (1) The 2000 World Values Survey has many anomalous results; (2) the estimates for inherited trust in 1935 are mostly based upon tiny samples for most ethnic heritage groups in the General Social Survey; and (3) Algan and Cahuc’s findings are based upon two-tailed rather than one-tailed tests. We reestimate their model using the more reliable waves of the World Values Survey and find much weaker relationships between inherited trust in 1935 and trust in the home country. We also suggest caution in the overall measure of inherited trust in 1935.

The role of the Internet on export market growth : an empirical study in Latin America

The Internet has been shown to positively influence the export activities of firms from developed countries. However, the literature is vague as to whether the Internet has an impact on the export market growth of firms form developing countries. This paper examines of a cross-national sample of 204 firms from a Latin American country (Chile). The results show that Internet marketing activities positively influence information availability and business relationships, which lead to an increase in export market growth. The findings indicate that the Internet influences not only information availability for export performance but also business relationships generally thought to be face to face interactions in nature.

Linear adaptive channel equalization for multiuser MIMO-OFDM systems

Linear adaptive channel equalization using the least mean square (LMS) algorithm and the recursive least-squares(RLS) algorithm for an innovative multi-user (MU) MIMOOFDM wireless broadband communications system is proposed. The proposed equalization method adaptively compensates the channel impairments caused by frequency selectivity in the propagation environment. Simulations for the proposed adaptive equalizer are conducted using a training sequence method to determine optimal performance through a comparative analysis. Results show an improvement of 0.15 in BER (at a SNR of 16 dB) when using Adaptive Equalization and RLS algorithm compared to the case in which no equalization is employed. In general, adaptive equalization using LMS and RLS algorithms showed to be significantly beneficial for MU-MIMO-OFDM systems.

A non-linear dynamic analysis of heavy haul track line sleepers under wheel flat

Significant wheel-rail dynamic forces occur because of imperfections in the wheels and/or rail. One of the key responses to the transmission of these forces down through the track is impact force on the sleepers. Dynamic analysis of nonlinear systems is very complicated and does not lend itself easily to a classical solution of multiple equations. Trying to deduce the behaviour of track components from experimental data is very difficult because such data is hard to obtain and applies to only the particular conditions of the track being tested. The finite element method can be the best solution to this dilemma. This paper describes a finite element model using the software package ANSYS for various sized flat defects in the tread of a wheel rolling at a typical speed on heavy haul track. The paper explores the dynamic response of a prestressed concrete sleeper to these defects.

International entrepreneurship for SME business growth : a resource and dynamic capability view of the firm : an internet context

This research explores the relationship between international business Internet capabilities and international entrepreneurial characteristics. It has been suggested, that the accumulation of a firms Internet capability can assist international operations, especially when operating in fast changing dynamic environments. However, the international entrepreneurial characteristics which are seen as a precursor to leveraging such capabilities are still vague. Given this finding a conceptual framework is constructed and research issues are then developed in order to focus attention on the relationship between the Internet and a firm’s resource base, dynamic capabilities and international market performance.

RcppArmadillo : accelerating R with high-performance C++ linear algebra

The R statistical environment and language has demonstrated particular strengths for interactive development of statistical algorithms, as well as data modelling and visualisation. Its current implementation has an interpreter at its core which may result in a performance penalty in comparison to directly executing user algorithms in the native machine code of the host CPU. In contrast, the C++ language has no built-in visualisation capabilities, handling of linear algebra or even basic statistical algorithms; however, user programs are converted to high-performance machine code, ahead of execution. A new method avoids possible speed penalties in R by using the Rcpp extension package in conjunction with the Armadillo C++ matrix library. In addition to the inherent performance advantages of compiled code, Armadillo provides an easy-to-use template-based meta-programming framework, allowing the automatic pooling of several linear algebra operations into one, which in turn can lead to further speedups. With the aid of Rcpp and Armadillo, conversion of linear algebra centered algorithms from R to C++ becomes straightforward. The algorithms retains the overall structure as well as readability, all while maintaining a bidirectional link with the host R environment. Empirical timing comparisons of R and C++ implementations of a Kalman filtering algorithm indicate a speedup of several orders of magnitude.

Optimal distribution network reinforcement considering load growth, line loss, and reliability

In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of dispatchable distributed generators (DDG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DDG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called modified discrete particle swarm optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DDGs are included in the optimization.

Chemical vapor deposited boron carbide : growth by a vapor-liquid-solid process

Detailed analytical electron microscope (AEM) studies of yellow whiskers produced by chemical vapor deposition (CVD)1 show that two basic types of whiskers are produced at low temperatures (between 1200°C and 1400°C) and low boron to carbon gas ratios. Both whisker types show planar microstructures such as twin planes and stacking faults oriented parallel to, or at a rhombohedral angle to, the growth direction. For both whisker types, the presence of droplet-like terminations containing both Si and Ni indicate that the growth process during CVD is via a vapor-liquid-solid (VLS) mechanism.

Growth of confined cancer spheroids : a combined experimental marker, critical modelling approach

A critical step in the dissemination of ovarian cancer is the formation of multicellular spheroids from cells shed from the primary tumour. The objectives of this study were to apply bioengineered three-dimensional (3D) microenvironments for culturing ovarian cancer spheroids in vitro and simultaneously to build on a mathematical model describing the growth of multicellular spheroids in these biomimetic matrices. Cancer cells derived from human epithelial ovarian carcinoma were embedded within biomimetic hydrogels of varying stiffness and grown for up to 4 weeks. Immunohistochemistry, imaging and growth analyses were used to quantify the dependence of cell proliferation and apoptosis on matrix stiffness, long-term culture and treatment with the anti-cancer drug paclitaxel. The mathematical model was formulated as a free boundary problem in which each spheroid was treated as an incompressible porous medium. The functional forms used to describe the rates of cell proliferation and apoptosis were motivated by the experimental work and predictions of the mathematical model compared with the experimental output. This work aimed to establish whether it is possible to simulate solid tumour growth on the basis of data on spheroid size, cell proliferation and cell death within these spheroids. The mathematical model predictions were in agreement with the experimental data set and simulated how the growth of cancer spheroids was influenced by mechanical and biochemical stimuli including matrix stiffness, culture duration and administration of a chemotherapeutic drug. Our computational model provides new perspectives on experimental results and has informed the design of new 3D studies of chemoresistance of multicellular cancer spheroids.

Analytical Solution of a Walters’ Liquid B Flow Over a Linear Stretching Sheet in a Porous Medium

This chapter represents the analytical solution of two-dimensional linear stretching sheet problem involving a non-Newtonian liquid and suction by (a) invoking the boundary layer approximation and (b) using this result to solve the stretching sheet problem without using boundary layer approximation. The basic boundary layer equations for momentum, which are non-linear partial differential equations, are converted into non-linear ordinary differential equations by means of similarity transformation. The results reveal a new analytical procedure for solving the boundary layer equations arising in a linear stretching sheet problem involving a non-Newtonian liquid (Walters’ liquid B). The present study throws light on the analytical solution of a class of boundary layer equations arising in the stretching sheet problem.

Working with refugee survivors of torture and trauma : an opportunity for vicarious posttraumatic growth

Clinical work with people who have survived trauma carries a risk of vicarious traumatisation for the service provider, but also the potential for vicarious posttraumatic growth. Despite growing interest in this area, the effects of working with survivors of refugee-related trauma have remained relatively unexplored. The aim of the current study was to examine the lived experiences of people working on a daily basis with survivors of torture and trauma who had sought refuge in Australia. Seventeen clinical, administrative, and managerial staff from a not-for-profit organisation participated in a semi-structured interview that was later analysed using interpretive phenomenological analysis. Analysis of the data demonstrated that the entire sample reported symptoms of vicarious trauma (e.g., strong emotional reactions, intrusive images, shattering of existing beliefs) as well as vicarious posttraumatic growth (e.g., forming new relationships, increased self-understanding, greater appreciation of life). Moreover, effortful meaning making processes appeared to facilitate such positive changes. Reduction in the risks associated with this work, enhancement of clinician well-being, and improvement of therapeutic outcomes is a shared responsibility of the organisation and clinician. Without negating the distress of trauma work, clinicians are encouraged to more deeply consider the unique positive outcomes that supporting survivors can provide.

Mentoring as professional development: ‘growth for both’ mentor and mentee

Teachers need professional development to keep current with teaching practices, although costs for extensive professional development can be prohibitive across an education system. Mentoring provides one way for embedding cost-effective professional development. This mixed-method study includes surveying mentor teachers (n = 101) on a five-part Likert scale and interviews with experienced mentors (n = 10) to investigate professional development for mentors as a result of the mentoring process. Quantitative data were analysed through a pedagogical knowledge framework and qualitative data were collated into themes. Survey data showed that although mentoring of pedagogical knowledge was variable, mentoring pedagogical knowledge practices occurs with the majority of mentors, which requires mentors to evaluate and articulate teaching practices. Qualitative data showed that mentoring acted as professional development and led towards enhancing communication skills, developing leadership roles (problem-solving and building capacity) and advancing pedagogical knowledge. Providing professional development to teachers on mentoring can help to build capacity in two ways: quality mentoring of preservice teachers through explicit mentoring practices, and reflecting and deconstructing teaching practices for mentors’ own pedagogical advancements.

New Perspectives On Firm Growth

This insightful volume presents a collection of innovative works by two of the leading researchers of firm growth: Per Davidsson, Director, Australian Centre for Entrepreneurship Research and Professor of Entrepreneurship, Queensland University of Technology, Australia and Jönköping International Business School, Sweden and Johan Wiklund, Professor of Entrepreneurship, Syracuse University, US and Jönköping International Business School, Sweden. The studies extend previous research by providing stronger theoretical underpinnings and using longitudinal databases that can separate in time the firms’ growth from its presumed causes. They also break new ground by examining different modes of growth, such as sales growth vs. employment growth, and organic growth vs. acquisition-based expansion. Further, the studies investigate the drivers of firm growth and take a critical look at the effects, such as under what circumstances high growth is associated with high profitability. The issue of how firm growth is achieved and managed, and what consequences it has for different stakeholders is both theoretically interesting and practically important. The book will strongly appeal to academics of entrepreneurship, small business management and strategy.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.