Societal transformation in response to global environmental change: a review of emerging concepts

The study of societal transformation in response to environmental change has become established, yet little consensus exists regarding the conceptual basis of transformation. This paper aims to provide structure to the dialog on transformation, and to reflect on the challenges of social research in this area. Concepts of transformation are identified through a literature review, and examined using four analytical criteria. It is found that the term ‘transformation’ is frequently used merely as a metaphor. When transformation is not used as a metaphor, eight concepts are most frequently employed. They differ with respect to (i) system conceptualization, (ii) notions of social consciousness (deliberate/emergent), and (iii) outcome (prescriptive/descriptive). Problem-based research tends to adopt concepts of deliberate transformation with prescriptive outcome, while concepts of emergent transformation with no prescriptive outcome tend to inform descriptive-analytical research. Dialog around the complementarities of different concepts and their empirical testing are priorities for future research.

An ASIFT-based local registration method for satellite imagery

Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs) are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT) was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC) algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion). Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM) algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE) and better distribution of feature points.

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.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

High performance polyester-based materials

Biaxially oriented films produced from semi-crystalline, semi-aromatic polyesters are utilised extensively as components within various applications, including the specialist packaging, flexible electronic and photovoltaic markets. However, the thermal performance of such polyesters, specifically poly(ethylene terephthalate) (PET) and poly(ethylene-2,6-naphthalate) (PEN), is inadequate for several applications that require greater dimensional stability at higher operating temperatures. The work described in this project is therefore primarily focussed upon the copolymerisation of rigid comonomers with PET and PEN, in order to produce novel polyester-based materials that exhibit superior thermomechanical performance, with retention of crystallinity, to achieve biaxial orientation. Rigid biphenyldiimide comonomers were readily incorporated into PEN and poly(butylene-2,6-naphthalate) (PBN) via a melt-polycondensation route. For each copoly(ester-imide) series, retention of semi-crystalline behaviour is observed throughout entire copolymer composition ratios. This phenomenon may be rationalised by cocrystallisation between isomorphic biphenyldiimide and naphthalenedicarboxylate residues, which enables statistically random copolymers to melt-crystallise despite high proportions of imide sub-units being present. In terms of thermal performance, the glass transition temperature, Tg, linearly increases with imide comonomer content for both series. This facilitated the production of several high performance PEN-based biaxially oriented films, which displayed analogous drawing, barrier and optical properties to PEN. Selected PBN copoly(ester-imide)s also possess the ability to either melt-crystallise, or form a mesophase from the isotropic state depending on the applied cooling rate. An equivalent synthetic approach based upon isomorphic comonomer crystallisation was subsequently applied to PET by copolymerisation with rigid diimide and Kevlar®-type amide comonomers, to afford several novel high performance PET-based copoly(ester-imide)s and copoly(ester-amide)s that all exhibited increased Tgs. Retention of crystallinity was achieved in these copolymers by either melt-crystallisation or thermal annealing. The initial production of a semi-crystalline, PET-based biaxially oriented film with a Tg in excess of 100 °C was successful, and this material has obvious scope for further industrial scale-up and process development.