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Female Swiss-Webster mice were treated daily for 10 days with cocaine (15 mg/kg i.p.) followed by 10 days with saline or ethanol (1.6 g/kg i.p.) or the reverse; following each injection in the experimental conditions locomotion was quantified in photocell cages. In animals given cocaine first, cocaine-induced locomotion was initially high and did not increase further with successive injections. In animals given prior saline or ethanol treatments, cocaine-induced locomotion was initially low but increased with successive cocaine treatments. There was no evidence of sensitization to the locomotor-stimulating effects of ethanol or of cross-sensitization between ethanol and cocaine. With respect to subsequent cocaine sensitization, the essential feature of prior saline or ethanol treatment appeared to be the handling and injection experience itself; a control group receiving prior saline injection in the home cage also showed a low level of cocaine-induced locomotion on the first day of cocaine testing but increasing locomotion with repeated cocaine testing. Thus, cocaine sensitization, rather than a progressive augmentation of motor function, may reflect a progressive reversal of the behavioral suppression caused by habituation to aspects of the testing situation or to some form of situational anxiety that precludes normal exploratory responses.

The new Paris Agreement, approved by 195 countries under the auspice of the United Nations Framework Convention on Climate Change (UNFCCC), calls for limiting global warming to “well below" 2°Celsius. An important part of the climate agreement relates to reducing emissions from deforestation and forest degradation, and enhancing carbon stocks (REDD+) in non-Annex I (mostly developing) countries. Over the last decades the growing demand for food, fibre and fuel has accelerated the pace of forest loss. In consequence, tropical deforestation and forest degradation are responsible for a large portion of global carbon emissions to the atmosphere, and destroy an important global carbon sink that is critical in future climate change mitigation. Within the REDD+ framework, participating countries are given incentives to develop national strategies and implementation plans that reduce emissions and enhance sinks from forests and to invest in low carbon development pathways. For REDD+ activities to be effective, accurate and robust methodologies to estimate emissions from deforestation and forest degradation are crucial. Remote sensing is an essential REDD+ observation tool, and in combination with ground measurements it provides an objective, practical and cost-effective solution for developing and maintaining REDD+ monitoring systems. The remote sensing monitoring objective for REDD+ is not only to map deforestation but also to support policy formulation and implementation. Identifying and addressing drivers and activities causing forest carbon change is crucial in this respect. Despite the importance of identifying and addressing drivers, quantitative information on these drivers, and the related carbon emissions, is scarce at the national level. The main objective of this thesis is to explore the role of remote sensing for monitoring tropical forests for REDD+ in general, and for assessing land use and related carbon emissions linked to drivers of tropical deforestation in particular. To achieve this, this thesis investigates the following research questions: What is the current role and potential of remote sensing technologies and methodologies for monitoring tropical forests for REDD+ and for assessing drivers of deforestation? What is the current state of knowledge on drivers of deforestation and degradation in REDD+ countries? What are land use patterns and related carbon emissions following deforestation, capitalising on available land use and biomass remote sensing data? The research conducted in this PhD thesis contributes to the understanding of the role of remote sensing in forest monitoring for REDD+ and in the assessment of drivers of deforestation. In addition, this thesis contributes to the improvement of spatial and temporal quantification of land use and related carbon emissions linked to drivers of tropical deforestation. The results and insights described herein are valuable for ongoing REDD+ forest monitoring efforts and capacity development as REDD+ moves closer to becoming an operational mitigation mechanism.

Most global energy models are developed by institutes from developed countries, focusing primarily on issues that are important in industrialized countries. Evaluation of the results for Asia of the IPCC/SRES models shows that broad concepts of energy and development, the energy ladder and the environmental Kuznets curve, can be observed in the results of the models. However, improvements can be made in modeling the issues that underlie these concepts, like traditional fuels, electrification, economic structural change, income distribution, and informal economies. Given the rapidly growing importance of energy trajectories of developing countries for global sustainability, the challenge for the future is to develop energy models that include all these aspects of energy and development.

This paper's objective is to apply Intervention Mapping, a planning process for the systematic development of theory- and evidence-based health promotion interventions, to the development of interventions to promote energy conservation behavior. Intervention Mapping (IM) consists of six steps: needs assessment, program objectives, methods and applications, program development, planning for program implementation, and planning for program evaluation. Examples from the energy conservation field are provided to illustrate the activities associated with these steps. It is concluded that applying IM in the energy conservation field may help the development of effective behavior change interventions, and thus develop a domain specific knowledge-base for effective intervention design.

Offshore drilling accidents have triggered regulatory reforms in China. The reforms aim to explore proper regulatory approaches to supervise offshore operations and improve their health, safety and environmental (HSE) performance. This study offers a review on the roles of risk and resilience in managing offshore operations and a well-defined analysis on their integrations with Chinese laws and regulations. The study finds risk and resilience approaches can promote the effectiveness of HSE regulation for offshore operations, while both are difficult to be transposed into legally binding rules in China. To fully develop and implement risk regulation for offshore operations, the study suggests to decentralize China’s command-and-control regulatory regime and encourage self-regulation in offshore petroleum companies. Transposing resilience thinking into legal practice is also highlighted so that various regulatory powers can keep proactive and flexible to any possible changes and uncertainties.

PurposeThe article demonstrates the dangers of gerontocracy and offers solutions.Design/methodology/approachThe article combines desk research, literature review and economic analytical reasoning.FindingsGerontocracy in developed countries is a threat to financial, labour market and political sustainability of care for older people. Without actions today, the problem will become bigger every year, not least because of increased electoral weight of older people. This article proposes to handle gerontocracy in two ways. First is by using the potential of healthy retired people as volunteers, thereby mitigating the intergenerational solidarity challenges. Second is by taxing part of the windfall profits on the housing market, where older generation profited disproportionally.Originality/valueThe added value of the article is twofold. First, it signals a serious problem in affluent societies that is largely ignored, both in the academic world and in politics. Second, it offers original solutions that mitigate the problem.

Households are responsible for a significant share of global greenhouse emissions. Hence, academic and policy discourses highlight behavioral changes among households as an essential strategy for combating climate change. However, formal models used to assess economic impacts of energy policies face limitations in tracing cumulative impacts of adaptive behavior of diverse households. The past decade has witnessed a proliferation of agent-based simulation models that quantify behavioral climate change mitigation relying on social science theories and micro-level survey data. Yet, these behaviorally-rich models usually operate on a small scale of neighborhoods, towns, and small regions, ignoring macro-scale social institutions such as international markets and rarely covering large areas relevant for climate change mitigation policy. This paper presents a methodology to scale up behavioral changes among heterogeneous individuals regarding energy choices while tracing their macroeconomic and cross-sectoral impacts. To achieve this goal, we combine the strengths of top-down computable general equilibrium models and bottom-up agent-based models. We illustrate the integration process of these two alien modeling approaches by linking data-rich macroeconomic with micro-behavioral models. Following a three-step approach, we investigate the dynamics of cumulative impacts of changes in individual energy use under three behavioral scenarios. Our findings demonstrate that the regional dimension is important in a low-carbon economy transition. Heterogeneity in individual socio-demographics (e.g. education and age), structural characteristics (e.g. type and size of dwellings), behavioral and social traits (e.g. awareness and personal norms), and social interactions amplify these differences, causing nonlinearities in diffusion of green investments among households and macro-economic dynamics.