Bt-cotton boosts the gross margin of small-scale cotton producers in South Africa

This paper explores some of the issues involved in the Genetic Modification (GM) debate by focusing on one crop that has been modified for pest resistance, cotton (Gossypium hirsutum), and commercially released to small-scale farmers in the Makhathini Flats, KwaZulu Natal, the Republic of South Africa. This was the first commercial release of a GM variety (Bt-cotton) in Sub-Saharan Africa, and thus provides valuable and timely insights into some of the potential advantages and disadvantages of the technology for small-scale farmers in Africa. Even though there are wider concerns regarding the vulnerability of small-scale farmers in the area, the survey results suggest that Bt-cotton generated higher yields and gross margins than non-Bt-cotton. In addition, Bt-cotton significantly reduced the use of pesticide with consequent potential benefits to human health and the environment.

Innovation dynamics and capability in open collaborative cyber communities: implications for cybersecurity

Cybersecurity is a complex challenge that has emerged alongside the evolving global socio-technical environment of social networks that feature connectivity across time and space in ways unimaginable even a decade ago. This paper reports on the preliminary findings of a NATO funded project that investigates the nature of innovation in open collaborative communities and its implications for cyber security. In this paper, the authors describe the framing of relevant issues, the articulation of the research questions, and the derivation of a conceptual framework based on open collaborative innovation that has emerged from preliminary field research in Russia and the UK.

Bt cotton and production risk: Panel data evidence

The farm-level success of Bt-cotton in developing countries is well documented. However, the literature has only recently begun to recognise the importance of accounting for the effects of the technology on production risk, in addition to the mean effect estimated by previous studies. The risk effects of the technology are likely very important to smallholder farmers in the developing world due to their risk-aversion. We advance the emergent literature on Bt-cotton and production risk by using panel data methods to control for possible endogeneity of Bt-adoption. We estimate two models, the first a fixed-effects version of the Just and Pope model with additive individual and time effects, and the second a variation of the model in which inputs and variety choice are allowed to affect the variance of the time effect and its correlation with the idiosyncratic error. The models are applied to panel data on smallholder cotton production in India and South Africa. Our results suggest a risk-reducing effect of Bt-cotton in India, but an inconclusive picture in South Africa.

Impact of Bt cotton on farmer livelihoods in South Africa

The economic benefits of Genetically Modified (GM) crops in developing countries have been well documented, but little research has been undertaken to date on the impacts of GM adoption on household livelihoods. The research reported here aimed to assess the livelihood impacts of the adoption of Bt cotton in South Africa., and involved 100 interviews of resource-poor farmers growing Bt cotton in Makhathini Flats, South Africa. Some 88% of respondents reported a higher income from Bt compared to non-Bt varieties previously grown by them, and this higher income was used primarily for greater education of their children (76%), more investment in growing cotton (46%), repaying debt (28%), investment in other crops (20%) and spending money on themselves. Some 89% had increased their asset base due to Bt cotton, primarily by increasing their cultivable land. These benefits of Bt adoption appeared widespread regardless of gender or farm size.

Determinants of consumers’ willingness to accept GM foods

This paper investigates Willingness to Accept (WTA) Genetic Modification (GM) foods based on experimental auctions carried out in the USA, UK and France. It explores perceptions of risk and benefits, moral concerns and their antecedents, attitudes to the environment and technology and trust in various sources using Structural Equation Modelling (SEM). Trust in information provided by industry proved to be the most important determinant of risk/benefit perceptions and WTA followed by general attitudes to the environment and technology. Education and age are also enhance perceived benefits and lower perceived risks of GM. Perception of risk/benefit and moral concerns all have significant effects on consumers' WTA but the perceived benefits are most important. The research suggests that trust-building by industry would be the most effective in enhancing GM acceptance.

Forecast calibration and combination: a simple Bayesian approach for ENSO

This study presents a new simple approach for combining empirical with raw (i.e., not bias corrected) coupled model ensemble forecasts in order to make more skillful interval forecasts of ENSO. A Bayesian normal model has been used to combine empirical and raw coupled model December SST Niño-3.4 index forecasts started at the end of the preceding July (5-month lead time). The empirical forecasts were obtained by linear regression between December and the preceding July Niño-3.4 index values over the period 1950–2001. Coupled model ensemble forecasts for the period 1987–99 were provided by ECMWF, as part of the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction (DEMETER) project. Empirical and raw coupled model ensemble forecasts alone have similar mean absolute error forecast skill score, compared to climatological forecasts, of around 50% over the period 1987–99. The combined forecast gives an increased skill score of 74% and provides a well-calibrated and reliable estimate of forecast uncertainty.

Microfabrication of high-performance aromatic polymers as nanotubes or fibrils by in situ ring-opening polymerisation of macrocyclic precursors

Melt-phase nucleophilic ring-opening polymerisation of macrocyclic aromatic ethers and thioethers at high temperatures within the cylindrical pores of an anodic-alumina membrane, followed by dissolution of the template, enables replication of the membrane's internal pore structure and so affords high-performance aromatic polymers with well-defined fibrillar or tubular morphologies.

A framework towards a multi-modal fingerprinting scheme for multimedia assets

Fingerprinting is a well known approach for identifying multimedia data without having the original data present but instead what amounts to its essence or 'DNA'. Current approaches show insufficient deployment of various types of knowledge that could be brought to bear in providing a fingerprinting framework that remains effective, efficient and can accommodate both the whole as well as elemental protection at appropriate levels of abstraction to suit various Zones of Interest (ZoI) in an image or cross media artefact. The proposed framework aims to deliver selective composite fingerprinting that is powerfully aided by leveraging both multi-modal information as well as a rich spectrum of collateral context knowledge including both image-level collaterals and also the inevitably needed market intelligence knowledge such as customers' social networks interests profiling which we can deploy as a crucial component of our fingerprinting collateral knowledge.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Factors mediating the routinisation of e-learning within a traditional university education environment

Technology-enhanced or Computer Aided Learning (e-learning) can be institutionally integrated and supported by learning management systems or Virtual Learning Environments (VLEs) to offer efficiency gains, effectiveness and scalability of the e-leaning paradigm. However this can only be achieved through integration of pedagogically intelligent approaches and lesson preparation tools environment and VLE that is well accepted by both the students and teachers. This paper critically explores some of the issues relevant to scalable routinisation of e-learning at the tertiary level, typically first year university undergraduates, with the teaching of Relational Data Analysis (RDA), as supported by multimedia authoring, as a case study. The paper concludes that blended learning approaches which balance the deployment of e-learning with other modalities of learning delivery such as instructor–mediated group learning etc offer the most flexible and scalable route to e-learning but that this requires the graceful integration of platforms for multimedia production, distribution and delivery through advanced interactive spaces that provoke learner engagement and promote learning autonomy and group learning facilitated by a cooperative-creative learning environment that remains open to personal exploration of constructivist-constructionist pathways to learning.

Finding the point on Bezier Curves with the normal vector passing an external point

Two algorithms for finding the point on non-rational/rational Bezier curves of which the normal vector passes through a given external point are presented. The algorithms are based on Bezier curves generation algorithms of de Casteljau's algorithm for non-rational Bezier curve or Farin's recursion for rational Bezier curve, respectively. Orthogonal projections from the external point are used to guide the directional search used in the proposed iterative algorithms. Using Lyapunov's method, it is shown that each algorithm is able to converge to a local minimum for each case of non-rational/rational Bezier curves. It is also shown that on convergence the distance between the point on curves to the external point reaches a local minimum for both approaches. Illustrative examples are included to demonstrate the effectiveness of the proposed approaches.

Risk accountability in the tender process of contractors in Ghana and UK

The process of how contractors take account of risk when calculating their bids for construction work is investigated based on preliminary investigations and case studies in Ghana and UK. Ghana and UK were chosen, more or less arbitrarily, for the purpose of case studies, and to test the idea that there are systematic differences between the approaches in different places. Clear differences were found in the risk pricing approaches of contractors in the two countries. The difference appeared to emanate from the professional knowledge and competence of the bid team members, company policy, corporate accountability and the business environments in which the contractors operate. Both groups of contractors take account of risk in estimates. However, risk accountability was found to be higher on the agenda in the tender process of UK contractors, documented more systematically, and assessed and managed more rigorously with input from the whole bid team. Risk accountability takes place at three levels of the tender process and is dictated strongly by market forces and company circumstances.