Change mechanisms of schema-centered group psychotherapy with personality disorder patients

Background This study addressed the temporal properties of personality disorders and their treatment by schema-centered group psychotherapy. It investigated the change mechanisms of psychotherapy using a novel method by which psychotherapy can be modeled explicitly in the temporal domain. Methodology and Findings 69 patients were assigned to a specific schema-centered behavioral group psychotherapy, 26 to social skills training as a control condition. The largest diagnostic subgroups were narcissistic and borderline personality disorder. Both treatments offered 30 group sessions of 100 min duration each, at a frequency of two sessions per week. Therapy process was described by components resulting from principal component analysis of patients' session-reports that were obtained after each session. These patient-assessed components were Clarification, Bond, Rejection, and Emotional Activation. The statistical approach focused on time-lagged associations of components using time-series panel analysis. This method provided a detailed quantitative representation of therapy process. It was found that Clarification played a core role in schema-centered psychotherapy, reducing rejection and regulating the emotion of patients. This was also a change mechanism linked to therapy outcome. Conclusions/Significance The introduced process-oriented methodology allowed to highlight the mechanisms by which psychotherapeutic treatment became effective. Additionally, process models depicted the actual patterns that differentiated specific diagnostic subgroups. Time-series analysis explores Granger causality, a non-experimental approximation of causality based on temporal sequences. This methodology, resting upon naturalistic data, can explicate mechanisms of action in psychotherapy research and illustrate the temporal patterns underlying personality disorders.

From 'land grabbing' to sustainable investments in land: potential contributions by land change science

This paper assesses possible contributions of land change science to the growing body of knowledge about large-scale land acquisition. Despite obvious commonalities, such as a problem-oriented and interdisciplinary approach to land change, there seems to be little overlap between the two fields thus far. We adopt a sustainability research perspective — an important feature of land change science — to review research questions about large-scale land acquisition that are currently being addressed, and to define questions for further inquiry. Possible contributions of land change science toward more sustainable land investments are based on understanding land use change not only as a consequence, but also as a cause of large-scale land acquisition and as a solution to the problems land acquisition can create.

Desertification and Global Change: Innovative Management of Scarce Resources in Semi-Arid Areas. Experiences from development and research: Challenges for a better future

While most events related to the International Year of Deserts and Desertification 2006 took mainly a problem-oriented perspective and approach, the Bern Symposium held in May 2006 tried to adopt a more positive attitude by attempting to take stock of experience as well as best and worst practices in the past, both in development practice and in research. Through this deliberate focus on potentials, positive experiences, solutions and pathways, predominant passive and reactive attitudes and hopelessness might be better overcome. The Symposium was organized by CDE, NCCR North-South and Forum SLM.

Context-Oriented Programming

Context-dependent behavior is becoming increasingly important for a wide range of application domains, from pervasive computing to common business applications. Unfortunately, mainstream programming languages do not provide mechanisms that enable software entities to adapt their behavior dynamically to the current execution context. This leads developers to adopt convoluted designs to achieve the necessary runtime flexibility. We propose a new programming technique called Context-oriented Programming (COP) which addresses this problem. COP treats context explicitly, and provides mechanisms to dynamically adapt behavior in reaction to changes in context, even after system deployment at runtime. In this paper we lay the foundations of COP, show how dynamic layer activation enables multi-dimensional dispatch, illustrate the application of COP by examples in several language extensions, and demonstrate that COP is largely independent of other commitments to programming style.

Object-Oriented Reengineering Patterns

The rapid growth of object-oriented development over the past twenty years has given rise to many object-oriented systems that are large, complex and hard to maintain. Object-Oriented Reengineering Patterns addresses the problem of understanding and reengineering such object-oriented legacy systems. This book collects and distills successful techniques in planning a reengineering project, reverse-engineering, problem detection, migration strategies and software redesign. The material in this book is presented as a set of "reengineering patterns" --- recurring solutions that experts apply while reengineering and maintaining object-oriented systems. The principles and techniques described in this book have been observed and validated in a number of industrial projects, and reflect best practice in object-oriented reengineering.

Tools for better SLM knowledge management and informed decision-making in addressing land degradation at different scales: the WOCAT–LADA–DESIRE methodology

Desertification research conventionally focuses on the problem – that is, degradation – while neglecting the appraisal of successful conservation practices. Based on the premise that Sustainable Land Management (SLM) experiences are not sufficiently or comprehensively documented, evaluated, and shared, the World Overview of Conservation Approaches and Technologies (WOCAT) initiative (www.wocat.net), in collaboration with FAO’s Land Degradation Assessment in Drylands (LADA) project (www.fao.org/nr/lada/) and the EU’s DESIRE project (http://www.desire-project.eu/), has developed standardised tools and methods for compiling and evaluating the biophysical and socio-economic knowledge available about SLM. The tools allow SLM specialists to share their knowledge and assess the impact of SLM at the local, national, and global levels. As a whole, the WOCAT–LADA–DESIRE methodology comprises tools for documenting, self-evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing and decision support in the field, at the planning level, and in scaling up identified good practices. SLM depends on flexibility and responsiveness to changing complex ecological and socioeconomic causes of land degradation. The WOCAT tools are designed to reflect and capture this capacity of SLM. In order to take account of new challenges and meet emerging needs of WOCAT users, the tools are constantly further developed and adapted. Recent enhancements include tools for improved data analysis (impact and cost/benefit), cross-scale mapping, climate change adaptation and disaster risk management, and easier reporting on SLM best practices to UNCCD and other national and international partners. Moreover, WOCAT has begun to give land users a voice by backing conventional documentation with video clips straight from the field. To promote the scaling up of SLM, WOCAT works with key institutions and partners at the local and national level, for example advisory services and implementation projects. Keywords: Sustainable Land Management (SLM), knowledge management, decision-making, WOCAT–LADA–DESIRE methodology.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

A methodology for appraising and selecting strategies to mitigate desertification based on stakeholder participation and global best practices

The main aim of the methodology presented in this paper is to provide a framework for a participatory process for the appraisal and selection of options to mitigate desertification and land degradation. This methodology is being developed within the EU project DESIRE (www.desire-project.eu/) in collaboration with WOCAT (www.wocat.org). It is used to select promising conservation strategies for test-implementation in each of the 16 degradation and desertification hotspot sites in the Mediterranean and around the world. The methodology consists of three main parts: In a first step, prevention and mitigation strategies already applied at the respective DESIRE study site are identified and listed during a workshop with representatives of different stakeholders groups (land users, policy makers, researchers). The participatory and process-oriented approach initiates a mutual learning process among the different stakeholders by sharing knowledge and jointly reflecting on current problems and solutions related to land degradation and desertification. In the second step these identified, locally applied solutions (technologies and approaches) are assessed with the help of the WOCAT methodology. Comprehensive questionnaires and a database system have been developed to document and evaluate all relevant aspects of technical measures as well as implementation approaches by teams of researchers and specialists, together with land users. This research process ensures systematic assessing and piecing together of local information, together with specific details about the environmental and socio-economic setting. The third part consists of another stakeholder workshop where promising strategies for sustainable land management in the given context are selected, based on the best practices database of WOCAT, including the evaluated locally applied strategies at the DESIRE sites. These promising strategies will be assessed with the help of a selection and decision support tool and adapted for test-implementation at the study site.