Categories, concepts and units: representing energy demand in and through time

Methods of data collection are unavoidably rooted in some sort of theoretical paradigm, and are inextricably tied to an implicit agenda or broad problem framing. These prior orientations are not always explicit, but they matter for what data is collected and how it is used. They also structure opportunities for asking new questions, for linking or bridging between existing data sets and they matter even more when data is re-purposed for uses not initially anticipated. In this paper we provide an historical and comparative review of the changing categories used in organising and collecting data on mobility/travel and time use as part of ongoing work to understand, conceptualise and describe the changing patterns of domestic and mobility related energy demand within UK society. This exercise reveals systematic differences of method and approach, for instance in units of measurement, in how issues of time/duration and periodicity are handled, and how these strategies relate to the questions such data is routinely used to address. It also points to more fundamental differences in how traditions of research into mobility, domestic energy and time use have developed. We end with a discussion of the practical implications of these diverse histories for understanding and analysing changing patterns of energy/mobility demand at different scales.

Knowledge-based design cost estimation through extending industry foundation classes

In order to overcome divergence of estimation with the same data, the proposed digital costing process adopts an integrated design of information system to design the process knowledge and costing system together. By employing and extending a widely used international standard, industry foundation classes, the system can provide an integrated process which can harvest information and knowledge of current quantity surveying practice of costing method and data. Knowledge of quantification is encoded from literatures, motivation case and standards. It can reduce the time consumption of current manual practice. The further development will represent the pricing process in a Bayesian Network based knowledge representation approach. The hybrid types of knowledge representation can produce a reliable estimation for construction project. In a practical term, the knowledge management of quantity surveying can improve the system of construction estimation. The theoretical significance of this study lies in the fact that its content and conclusion make it possible to develop an automatic estimation system based on hybrid knowledge representation approach.

Developing a knowledge management system using an ontological approach in global organisation

This paper introduces an ontology-based knowledge model for knowledge management. This model can facilitate knowledge discovery that provides users with insight for decision making. The users requiring the insight normally play different roles with different requirements in an organisation. To meet the requirements, insights are created by purposely aggregated transnational data. This involves a semantic data integration process. In this paper, we present a knowledge management system which is capable of representing knowledge requirements in a domain context and enabling the semantic data integration through ontology modeling. The knowledge domain context of United Bible Societies is used to illustrate the features of the knowledge management capabilities.

Assessing the business risk of technology obsolescence through enterprise modelling

The problem of technology obsolescence in information intensive businesses (software and hardware no longer being supported and replaced by improved and different solutions) and a cost constrained market can severely increase costs and operational, and ultimately reputation risk. Although many businesses recognise technological obsolescence, the pervasive nature of technology often means they have little information to identify the risk and location of pending obsolescence and little money to apply to the solution. This paper presents a low cost structured method to identify obsolete software and the risk of their obsolescence where the structure of a business and its supporting IT resources can be captured, modelled, analysed and the risk to the business of technology obsolescence identified to enable remedial action using qualified obsolescence information. The technique is based on a structured modelling approach using enterprise architecture models and a heatmap algorithm to highlight high risk obsolescent elements. The method has been tested and applied in practice in two consulting studies carried out by Capgemini involving three UK police forces. However the generic technique could be applied to any industry based on plans to improve it using ontology framework methods. This paper contains details of enterprise architecture meta-models and related modelling.

Foreign direct investment through acquisitions and implications for technological upgrading: case evidence from Tanzania

Using a case study approach, this paper examines the role of privatisation on the industrial landscape of Tanzania. We examine the impact of foreign direct investment (FDI) through acquisitions on technology transfer within the acquired firm as well as the development of linkages to other firms based in the host country. Our results suggest that technological upgrading has occurred following FDI, the intensity of which reflects the type of firm-specific assets of the parent multinational enterprise (MNE), as well as the pre-acquisition state of these industrial activities. Improved backward linkages are also evident with local economic agents, but their type and extent – reflecting Tanzania's comparative advantage in the primary sector – confirm that capabilities both within the acquired firms and also in the industrial base of the host country greatly influence the magnitude and intensity of technological upgrading. 'Narrower' technology gaps between the MNE affiliate and the domestic sector are more likely to result in backward linkages and determine the type of technological content of inputs sourced locally rather than within the MNE.

Towards a parallel computationally efficient approach to scaling up data stream classification

Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

The adoption of the materiality concept in social and environmental reporting assurance: a field study approach

This study investigates the logics or values that shape the social and environmental reporting (SER) and SER assurance (SERA) process. The influence of logics is observed through a study of the conceptualisation and operationalisation of the materiality concept by accounting and non-accounting assurors and their assurance statements. We gathered qualitative data from interviews with both accounting and non-accounting assurors. We analysed the interplay between old and new logics that are shaping materiality as a reporting concept in SER. SER is a rich field in which to study the dynamics of change because it is a voluntary, unregulated, qualitative reporting arena. It has a broad, stakeholder audience, where accounting and non-accounting organisations are in competition. There are three key findings. First, the introduction of a new, stakeholder logic has significantly changed the meaning and role of materiality. Second, a more versatile, performative, social understanding of materiality was portrayed by assurors, with a forward-looking rather than a historic focus. Third, competing logics have encouraged different beliefs about materiality, and practices, to develop. This influenced the way assurors theorised the concept and interpreted outcomes. A patchwork of localised understandings of materiality is developing. Policy implications both in SERA and also in financial audit are explored.

Performing knowledge requirements analysis for public organisations in a Virtual Learning Environment: a social network analysis approach

This paper describes an application of Social Network Analysis methods for identification of knowledge demands in public organisations. Affiliation networks established in a postgraduate programme were analysed. The course was executed in a distance education mode and its students worked on public agencies. Relations established among course participants were mediated through a virtual learning environment using Moodle. Data available in Moodle may be extracted using knowledge discovery in databases techniques. Potential degrees of closeness existing among different organisations and among researched subjects were assessed. This suggests how organisations could cooperate for knowledge management and also how to identify their common interests. The study points out that closeness among organisations and research topics may be assessed through affiliation networks. This opens up opportunities for applying knowledge management between organisations and creating communities of practice. Concepts of knowledge management and social network analysis provide the theoretical and methodological basis.

Mastery-approach goals eliminate retrieval-induced forgetting: the role of achievement goals in memory inhibition

The present study examined how achievement goals affect retrieval-induced forgetting. Researchers have suggested that mastery-approach goals (i.e., developing one’s own competence) promote a relational encoding, whereas performance-approach goals (i.e., demonstrating one’s ability in comparison to others) promote item-specific encoding. These different encoding processes may affect the degree to which participants integrate the exemplars within a category and, as a result, we expected that retrieval-induced forgetting may be reduced or eliminated under mastery-approach goals. Three experiments were conducted using a retrieval-practice paradigm with different stimuli, where participants’ achievement goals were manipulated through brief written instructions. A meta-analysis that synthesized the results of the three experiments showed that retrieval-induced forgetting was not statistically significant in the mastery-approach goal condition, whereas it was statistically significant in the performance-approach goal condition. These results suggest that mastery-approach goals eliminate retrieval-induced forgetting, but performance-approach goals do not, demonstrating that motivation factors can influence inhibition and forgetting.

Rainfall estimation by rain gauge-radar combination: a concurrent multiplicative-additive approach

A procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) is proposed for operational rainfall estimation using rain gauges and radar data. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on Barnes' objective analysis scheme (OAS), whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, a spatially variable adjustment with multiplicative factors, and ordinary cokriging.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.

Improved seasonal prediction of the hot summer of 2003 over Europe through better representation of uncertainty in the land surface

Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.

Towards a unified approach for the determination of the bioaccessibility of organic pollutants

Bioaccessibility studies have been widely used as a research tool to determine the potential human exposure to ingested contaminants. More recently they have been practically applied for soil borne toxic elements. This paper reviews the application of bioaccessibility tests across a range of organic pollutants and contaminated matrices. Important factors are reported to be: the physiological relevance of the test, the components in the gut media, the size fraction chosen for the test and whether it contains a sorptive sink. The bioaccessibility is also a function of the composition of the matrix (e.g. organic carbon content of soils) and the physico-chemical characteristics of the pollutant under test. Despite the widespread use of these tests, there are a large number of formats used and very few validation studies with animal models. We propose a unified format for a bioaccessibility test for organic pollutants. The robustness of this test should first be confirmed through inter laboratory comparison, then tested in-vivo.

Transformation through translation: translation policies at Amnesty International

International non-governmental organisations (NGOs) are powerful political players who aim to influence global society. In order to be effective on a global scale, they must communicate their goals and achievements in different languages. Translation and translation policy play an essential role here. Despite NGOs’ important position in politics and society, not much is known about how these organisations, who often have limited funds available, organise their translation work. This study aims to contribute to Translation Studies, and more specifically to investigating institutional translation, by exploring translation policies at Amnesty International, one of the most successful and powerful human rights NGOs around the world. Translation policy is understood as comprising three components: translation management, translation practices, and translation beliefs, based on Spolsky’s study of language policy (2004). The thesis investigates how translation is organised and what kind of policies different Amnesty offices have in place, and how this is reflected in their translation products. The thesis thus also pursues how translation and translation policy impact on the organisation’s message and voice as it is spread around the world. An ethnographic approach is used for the analysis of various data sets that were collected during fieldwork. These include policy documents, guidelines on writing and translation, recorded interviews, e-mail correspondence, and fieldnotes. The thesis at first explores Amnesty’s global translation policy, and then presents the results of a comparative analysis of local translation policies at two concrete institutions: Amnesty International Language Resource Centre in Paris (AILRC-FR) and Amnesty International Vlaanderen (AIVL). A corpus of English source texts and Dutch (AIVL) and French (AILRC-FR) target texts are analysed. The findings of the analysis of translation policies and of the translation products are then combined to illustrate how translation impacts on Amnesty’s message and voice. The research results show that there are large differences in how translation is organised depending on the local office and the language(s), and that this also influences the way in which Amnesty’s message and voice are represented. For Dutch and French specifically, translation policies and translation products differ considerably. The thesis describes how these differences are often the result of different beliefs and assumptions relating to translation, and that staff members within Amnesty are not aware of the different conceptions of translation that exist within Amnesty International as a formal institution. Organising opportunities where translation can be discussed (meetings, workshops, online platforms) can help in reducing such differences. The thesis concludes by suggesting that an increased awareness of these issues will enable Amnesty to make more effective use of translation in its fight against human rights violations.

A global proteomics approach identifies novel phosphorylated signaling proteins in GPVI-activated platelets: involvement of G6f, a novel platelet Grb2-binding membrane adapter.

Collagen-related peptide (CRP) stimulates powerful activation of platelets through the glycoprotein VI (GPVI)-FcR gamma-chain complex. We have combined proteomics and traditional biochemistry approaches to study the proteome of CRP-activated platelets, focusing in detail on tyrosine phosphorylation. In two separate approaches, phosphotyrosine immunoprecipitations followed by 1-D-PAGE, and 2-DE, were used for protein separation. Proteins were identified by MS. By following these approaches, 96 proteins were found to undergo PTM in response to CRP in human platelets, including 11 novel platelet proteins such as Dok-1, SPIN90, osteoclast stimulating factor 1, and beta-Pix. Interestingly, the type I transmembrane protein G6f was found to be specifically phosphorylated on Tyr-281 in response to platelet activation by CRP, providing a docking site for the adapter Grb2. G6f tyrosine phoshporylation was also found to take place in response to collagen, although not in response to the G protein-coupled receptor agonists, thrombin and ADP. Further, we also demonstrate for the first time that Grb2 and its homolog Gads are tyrosine-phosphorylated in CRP-stimulated platelets. This study provides new insights into the mechanism of platelet activation through the GPVI collagen receptor, helping to build the basis for the development of new drug targets for thrombotic disease.