283 research outputs found

    Examination of Ice-Crystals by X-Rays

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    Fostering the Next Generation of Sustainability Professionals – Assessing Field-based Courses in a Sustainability Science Graduate Program

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    A growing number of educational programs in sustainability science has paralleled the rise of the field itself. The educational approach of these programs follows the problem-driven, interdisciplinary, and transdisciplinary nature of the field itself. However, its effectiveness has yet to be systematically evaluated. Similarly, while ad-hoc evaluation schemes have attempted to monitor the quality of the educational programs, there is no standard method that accounts for the particularities of sustainability science programs. This study thus addresses the need for an assessment of the problem-driven approach of educational programs in sustainability science. We have conducted student self-assessments of field courses in the Graduate Program in Sustainability Science (GPSS-GLI) at The University of Tokyo, which positions its field courses at the center of its curriculum. The self-assessments were based on five key competencies identified as particularly important for sustainability professionals. Workshops and questionnaires engaged students in a reflection of the six field courses and of their own personal development through the activities offered. Our questionnaire results indicate that the majority of participants were satisfied with how the courses furthered their personal development. While some participants expressed frustration at being unable to sufficiently address the respective field's sustainability challenges due to time constraints, students generally recognized the five key competencies as important for addressing sustainability issues after participating in the courses. Moreover, participants attributed much of their learning to their active engagement in planned field research activities, rather than to passive learning. Variations in results across different course units provide material for further analysis and development of the curriculum. This study is an initial attempt at assessment, with room for ongoing improvement and further research to address additional requirements for fostering the next generation of sustainability professionals

    Fostering the Next Generation of Sustainability Professionals - Assessing Field-based Courses in a Sustainability Science Graduate Program

    Get PDF
    A growing number of educational programs in sustainability science has paralleled the rise of the field itself. The educational approach of these programs follows the problem-driven, interdisciplinary, and transdisciplinary nature of the field itself. However, its effectiveness has yet to be systematically evaluated. Similarly, while ad-hoc evaluation schemes have attempted to monitor the quality of the educational programs, there is no standard method that accounts for the particularities of sustainability science programs. This study thus addresses the need for an assessment of the problem-driven approach of educational programs in sustainability science. We have conducted student self-assessments of field courses in the Graduate Program in Sustainability Science (GPSS-GLI) at The University of Tokyo, which positions its field courses at the center of its curriculum. The self-assessments were based on five key competencies identified as particularly important for sustainability professionals. Workshops and questionnaires engaged students in a reflection of the six field courses and of their own personal development through the activities offered. Our questionnaire results indicate that the majority of participants were satisfied with how the courses furthered their personal development. While some participants expressed frustration at being unable to sufficiently address the respective field's sustainability challenges due to time constraints, students generally recognized the five key competencies as important for addressing sustainability issues after participating in the courses. Moreover, participants attributed much of their learning to their active engagement in planned field research activities, rather than to passive learning. Variations in results across different course units provide material for further analysis and development of the curriculum. This study is an initial attempt at assessment, with room for ongoing improvement and further research to address additional requirements for fostering the next generation of sustainability professionals

    Matter Distribution around Galaxies

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    We explore the mass distribution of material associated with galaxies from the observation of gravitational weak lensing for the galaxy mass correlation function with the aid of NN-body simulations of dark matter. The latter is employed to unfold various contributions that contribute to the integrated line of sight mass density. We conclude that galaxies have no definite edges of the matter distribution, extending to the middle to neighbouring galaxies with the density profile roughly r2.4r^{-2.4} beyond the virial radius. The mass distributed beyond the virial radius (gravitationally bound radius) explains the gap seen in the mass density estimates, the global value Ωm0.27\Omega_m\sim 0.27 and typically Ωgal0.15\Omega_{\rm gal} \sim 0.15 from the luminosity density multiplied by the mass to light ratio. We suggest to use a physical method of gravitational lensing to characterise galaxy samples rather than characterise them with photometric means.Comment: 16 pages, 5 figures. ApJ accepte

    Terrain-Dependent Slip Risk Prediction for Planetary Exploration Rovers

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    Wheel slip prediction on rough terrain is crucial for secure, long-term operations of planetary exploration rovers. Although rough, unstructured terrain hampers mobility, prediction by modeling wheel–terrain interactions remains difficult owing to unclear terrain conditions and complexities of terramechanics models. This study proposes a vision-based approach with machine learning for predicting wheel slip risk by estimating the slope from 3D information and classifying terrain types from image information. It considers the slope estimation accuracy for risk prediction under sharp increases in wheel slip due to inclined ground. Experimental results obtained with a rover testbed on several terrain types validate this method
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