181 research outputs found
The politics of accelerating low-carbon transitions: towards a new research agenda
Meeting the climate change targets in the Paris Agreement implies a substantial and rapid acceleration of low-carbon transitions. Combining insights from political science, policy analysis and socio-technical transition studies, this paper addresses the politics of deliberate acceleration by taking stock of emerging examples, mobilizing relevant theoretical approaches, and articulating a new research agenda. Going beyond routine appeals for more ‘political will’, it organises ideas and examples under three themes: 1) the role of coalitions in supporting and hindering acceleration; 2) the role of feedbacks, through which policies may shape actor preferences which, in turn, create stronger policies; and 3) the role of broader contexts (political economies, institutions, cultural norms, and technical systems) in creating more (or less) favourable conditions for deliberate acceleration. We discuss the importance of each theme, briefly review previous research and articulate new research questions. Our concluding section discusses the current and potential future relationship between transitions theory and political science
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Navigating tensions between rapid and just low-carbon transitions
In this Perspective, we suggest that research on just transitions and energy justice needs to better attend to the increasingly important trade-offs arising from issues related to speed and acceleration of low-carbon transitions. We identify and elaborate two important tensions that policymakers face when they want to simultaneously achieve both just and rapid low-carbon transitions. First, the way in which participatory processes may increase justice but slow the speed of action; and second the way in which incumbent mobilization can accelerate transitions but entrench injustices. Such an analysis shifts the focus from mapping justice dimensions to acknowledging the inevitable trade-offs and winners and losers produced by transition processes as a first step to better navigating them
Collaboration scripts - a conceptual analysis
This article presents a conceptual analysis of collaboration scripts used in face-to-face and computer-mediated collaborative learning. Collaboration scripts are scaffolds that aim to improve collaboration through structuring the interactive processes between two or more learning partners. Collaboration scripts consist of at least five components: (a) learning objectives, (b) type of activities, (c) sequencing, (d) role distribution, and (e) type of representation. These components serve as a basis for comparing prototypical collaboration script approaches for face-to-face vs. computer-mediated learning. As our analysis reveals, collaboration scripts for face-to-face learning often focus on supporting collaborators in engaging in activities that are specifically related to individual knowledge acquisition. Scripts for computer-mediated collaboration are typically concerned with facilitating communicative-coordinative processes that occur among group members. The two lines of research can be consolidated to facilitate the design of collaboration scripts, which both support participation and coordination, as well as induce learning activities closely related to individual knowledge acquisition and metacognition. In addition, research on collaboration scripts needs to consider the learners’ internal collaboration scripts as a further determinant of collaboration behavior. The article closes with the presentation of a conceptual framework incorporating both external and internal collaboration scripts
Saturn's equinoctial auroras
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95061/1/grl26673.pd
The Freshman, vol. 4, no. 9 [issue misnumbered]
The Freshman was a weekly, student newsletter issued on Mondays throughout the academic year. The newsletter included calendar notices, coverage of campus social events, lectures, and athletic teams. The intent of the publication was to create unity, a sense of community, and class spirit among first year students. National politics become a focus in this issue. The Class of 1937 run of The Freshman featured original cover art by sketch artist Jack Frost (John Edward Frost, 1915-1997), who was born in Eastport, Maine. He attended the University of Maine for only a single academic year before moving to Massachusetts to work for the Boston Herald. Frost later became a columnist and illustrator for the Boston Post
The Freshman, vol. 4, no. 8
The Freshman was a weekly, student newsletter issued on Mondays throughout the academic year. The newsletter included calendar notices, coverage of campus social events, lectures, and athletic teams. The intent of the publication was to create unity, a sense of community, and class spirit among first year students. The annual tradition of Rushing fraternities is discussed in this issue. The Class of 1937 run of The Freshman featured original cover art by sketch artist Jack Frost (John Edward Frost, 1915-1997), who was born in Eastport, Maine. He attended the University of Maine for only a single academic year before moving to Massachusetts to work for the Boston Herald. Frost later became a columnist and illustrator for the Boston Post
Patient-centred tuberculosis treatment delivery under programmatic conditions in Tanzania: a cohort study
<p>Abstract</p> <p>Background</p> <p>Directly observed therapy (DOT) remains the cornerstone of the global tuberculosis (TB) control strategy. Tanzania, one of the 22 high-burden countries regarding TB, changed the first-line treatment regimen to contain rifampicin-containing fixed-dose combination for the full 6 months of treatment. As daily health facility-based DOT for this long period is not feasible for the patient, nor for the health system, Tanzania introduced patient centred treatment (PCT). PCT allows patients to choose for daily DOT at a health facility or at their home by a supporter of choice. The introduction of fixed dose combinations in the intensive and continuation phase made PCT feasible by eliminating the risk of selective drug taking by patients and reducing the number of tablets to be taken. The approach was tested in three districts with the objective to assess the effect of this strategy on TB treatment outcomes</p> <p>Methods</p> <p>Cohort analysis comparing patients treated under the PCT strategy (registered April-September 2006) with patients treated under health-facility-based DOT (registered April-September 2005). The primary outcome was the cure rate. Differences were assessed by calculating the risk ratios. Associations between characteristics of the supporters and treatment outcomes in the group of patients opting for home-based DOT were assessed through logistic regression.</p> <p>Results</p> <p>In the PCT cohort there were 1208 patients and 1417 were included in the historic cohort. There was no significant difference in cure rates between the cohorts (risk ratio [RR]: 1.06; 95% confidence interval [CI]: 0.96-1.16). In the PCT cohort, significantly more patients had successful treatment (cure or treatment completed; RR: 1.10; 95%CI: 1.01-1.15). There were no characteristics of supporters that were associated with treatment outcome.</p> <p>Conclusion</p> <p>The PCT approach showed similar cure rates and better treatment success rates compared to daily health-facility DOT. The results indicate that there are no specific prerequisites for the supporter chosen by the patient. The programmatic setting of the study lends strong support for scaling-up of TB treatment observation outside the health facility.</p
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Toward a next generation particle precipitation model: Mesoscale prediction through machine learning (a case study and framework for progress)
We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning tools to gain utility from those data. We have compiled, curated, analyzed, and made available a new and more capable database of particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by machine learning approaches to appropriately utilize diverse information from the solar wind and geomagnetic activity and, importantly, their time histories. With a more capable representation of the organizing parameters and the target electron energy flux observations, PrecipNet achieves a 50\% reduction in errors from a current state-of-the-art model (OVATION Prime), better captures the dynamic changes of the auroral flux, and provides evidence that it can capably reconstruct mesoscale phenomena. We create and apply a new framework for space weather model evaluation that culminates previous guidance from across the solar-terrestrial research community. The research approach and results are representative of the `new frontier' of space weather research at the intersection of traditional and data science-driven discovery and provides a foundation for future efforts
Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications
A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”
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