Matching Items (471)
Description
For waste management in Asunción, Paraguay to improve, so too must the rate of public recycling participation. However, due to minimal public waste management infrastructure, it is up to individual citizens and the private sector to develop recycling solutions in the city. One social enterprise called Soluciones Ecológicas (SE) has deployed a system of drop-off recycling stations called ecopuntos, which allow residents to deposit their paper and cardboard, plastic, and aluminum. For SE to maximize the use of its ecopuntos, it must understand the perceived barriers to, and benefits of, their use. To identify these barriers and benefits, a doer on-doer survey based on the behavioral determinants outlined in the Designing for Behavior Change Framework was distributed among Asunción residents. Results showed that perceived self-efficacy, perceived social norms, and perceived positive consequences – as well as age – were influential in shaping ecopunto use. Other determinants such as perceived negative consequences, access, and universal motivators were significant predictors of gender and age. SE and other institutions looking to improve recycling can use these results to design effective behavior change interventions.
ContributorsLoPrete, Eric (Author) / Klinsky, Sonja (Contributor) / Fischer, Daniel (Contributor) / Wiek, Arnim (Contributor)
Created2020-04-24
Description
Multi-scalar, integrated and transformational solutions are necessary to address the complex problems of climate change and sustainable development. Cities are using urban living labs to develop and test such solutions; however, the pace of transformation does not yet match the urgency of the problems at hand. In business, accelerators are used to advance new and potentially transformational enterprises, giving fresh ideas an advantage over more established competition, thereby accelerating the pace of change. This article examines the accelerator model and considers its adaptation to urban living labs. From the literature, a multi-scalar business accelerator model is proposed that addresses both individual and system interventions to advance sustainability transformations. Also proposed is a formative-evaluation framework to guide effective implementation of the accelerator model. This article concludes with recommendations for scholars and practitioners working on urban living labs to utilize business accelerators to advance sustainability transformations.
ContributorsMack, Ashley (Author) / Whithycombe Keeler, Lauren (Contributor, Contributor) / Wiek, Arnim (Contributor) / von Wehrden, Henrik (Contributor)
Created2019-04-24
Description
The next generation will be better prepared to cope with the daunting sustainability challenges if education for sustainable development is being taught and learned across educational sectors. K-12 school education will play a pivotal role in this process, most prominently, the teachers serving at these schools. While pre-service teachers’ education will contribute to this transition, success will depend on effective professional development in sustainability education to teachers currently in service. Arizona State University has pioneered the development and delivery of such a programme. We present the design principles, the programme, and insights from its initial applications that involved 246 K-12 in-service teachers from across the USA. The evaluation results indicate that due to participation in the programme, sustainability knowledge, perception of self-efficacy, inclusion of sustainability in the classroom, modelling of sustainable behaviours, and linking action to content all increased. We conclude with recommendations for the widespread adopting of the programme.
ContributorsRedman, Erin (Author) / Redman, Aaron (Author) / Wiek, Arnim (Author)
Created2018-07-13
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton School of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Background
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
ContributorsSun, Qian (Author) / Muckatira, Sherin (Author) / Yuan, Lei (Author) / Ji, Shuiwang (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2013-12-03
Description
This project aims to provide a contextualized history of the Sky Harbor Neighborhood Association‟s community collective action efforts. The Sky Harbor Neighborhood (SHN) of East Phoenix is bounded on the West by 24th St., on the East by 32nd St., on the North by Roosevelt St., and the South by Washington Street. SHN is a majority Latino, low-income, working class community (U.S. Census Bureau, 2010) that faces a variety of challenges including low walkability due to inadequate pedestrian infrastructure, low tree coverage, and crime. East Van Buren St., which has a reputation for being one of Phoenix‟s red-light districts, splits the neighborhood in two. In addition, the SHN lacks some key amenities such as grocery stores and is partly considered a food desert by the United States Department of Agriculture (USDA Economic Research Service, 2012).
ContributorsPearson, Kimberly (Author) / Golub, Aaron (Thesis director) / Wiek, Arnim (Committee member) / York, Abigail (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Sustainability (Contributor)
Created2012-12
Description
Despite widespread acknowledgement of the need for transformation towards sustainability, the majority of cities appear stuck in incremental change instead of far-reaching, radical change. While there are numerous obstacles to transformational change, one critical aspect is the process of selecting impactful sustainability programs. The unique and complex nature of sustainability suggests a different approach is needed to program selection than is normal. But, to what extent are cities adapting selection processes in response to sustainability and what effect does this have on sustainable urban transformation? Could there be a more effective process to select programs with greater transformational potential? This dissertation investigates these questions using case studies and action research to add to the general knowledge of urban sustainability program selection and to develop practical knowledge (solutions) for more effective sustainable urban transformation.
The dissertation consists of three studies. Study 1 uses a case study approach to investigate existing sustainability program selection processes in three cities: Avondale, USA; Almere, the Netherlands; and Freiburg, Germany. These cities all express commitment to sustainability but have varying degrees of sustainable development experience, accomplishment, and recognition. Study 2 develops a program selection framework for urban sustainable transformation drawing extensively from the literature on sustainability assessment and related fields, and on participatory input from municipal practitioners in Avondale and Almere. Study 3 assesses the usefulness of the framework in a dual pilot study. Participatory workshops were conducted in which the framework was applied to real-world situations: (i) with the city’s sustainability working group in Avondale; and (ii) with a local energy cooperative in Almere.
Overall, findings suggest cities are not significantly adapting program selection processes in response to the challenges of sustainability. Processes are often haphazard, opportunistic, driven elite actors, and weakly aligned with sustainability principles and goals, which results in selected programs being more incremental than transformational. The proposed framework appears effective at opening up the range of program options considered, stimulating constructive deliberation among participants, and promoting higher order learning. The framework has potential for nudging program selection towards transformational outcomes and more deeply embedding sustainability within institutional culture.
The dissertation consists of three studies. Study 1 uses a case study approach to investigate existing sustainability program selection processes in three cities: Avondale, USA; Almere, the Netherlands; and Freiburg, Germany. These cities all express commitment to sustainability but have varying degrees of sustainable development experience, accomplishment, and recognition. Study 2 develops a program selection framework for urban sustainable transformation drawing extensively from the literature on sustainability assessment and related fields, and on participatory input from municipal practitioners in Avondale and Almere. Study 3 assesses the usefulness of the framework in a dual pilot study. Participatory workshops were conducted in which the framework was applied to real-world situations: (i) with the city’s sustainability working group in Avondale; and (ii) with a local energy cooperative in Almere.
Overall, findings suggest cities are not significantly adapting program selection processes in response to the challenges of sustainability. Processes are often haphazard, opportunistic, driven elite actors, and weakly aligned with sustainability principles and goals, which results in selected programs being more incremental than transformational. The proposed framework appears effective at opening up the range of program options considered, stimulating constructive deliberation among participants, and promoting higher order learning. The framework has potential for nudging program selection towards transformational outcomes and more deeply embedding sustainability within institutional culture.
ContributorsForrest, Nigel (Author) / Wiek, Arnim (Thesis advisor) / Melnick, Rob (Committee member) / Schugurensky, Daniel, 1958- (Committee member) / Arizona State University (Publisher)
Created2015
Description
Urban areas face a host of sustainability problems ranging from air and water quality, to housing affordability, and sprawl reducing returns on infrastructure investments, among many others. To address such challenges, cities have begun to envision generational sustainability transitions, and coalesce transition arenas in context to manage those transitions. Transition arenas coordinate the efforts of diverse stakeholders in a setting conducive to making evidence-based decisions that guide a transition forward. Though espoused and studied in the literature, transition arenas still require further research on the specifics of agent selection, arena setting, and decision-making facilitation. This dissertation has three related contributions related to transition arenas. First, it describes a process that took place within Phoenix that focused on identifying, recruiting, and building the capacity of potential transition agents for a transition arena. As part of this, a first draft suggestion of plausible steps to take for identifying, recruiting, and building a team of transition agents is proposed followed by a brief discussion on how this step-by-step process could be evaluated in subsequent work. Second, building on such engagement, this dissertation then offers criteria for transition agent selection based on a review of the literature that includes the setting in which a transition arena occurs, and strategies to support successful facilitation of decision-making in that setting. Third, those criteria are operationalized to evaluate the facilitation of a specific decision (draft of a new transportation plan) in a specific transition arena: the Citizens Committee for the future of Phoenix Transportation. The goal of this dissertation is to articulate a first-draft framework for guiding the development and scientific evaluation of transition arenas. Future work is required to empirically validate the framework in other real-world transition arenas. A feasible research agenda is provides to support this work.
ContributorsHarlow, John (Author) / Hekler, Eric (Thesis advisor) / Golub, Aaron (Thesis advisor) / Johnston, Erik W., 1977- (Committee member) / Wiek, Arnim (Committee member) / Arizona State University (Publisher)
Created2015
Description
Three dilemmas plague governance of scientific research and technological
innovation: the dilemma of orientation, the dilemma of legitimacy, and the dilemma of control. The dilemma of orientation risks innovation heedless of long-term implications. The dilemma of legitimacy grapples with delegation of authority in democracies, often at the expense of broader public interest. The dilemma of control poses that the undesirable implications of new technologies are hard to grasp, yet once grasped, all too difficult to remedy. That humanity has innovated itself into the sustainability crisis is a prime manifestation of these dilemmas.
Responsible innovation (RI), with foci on anticipation, inclusion, reflection, coordination, and adaptation, aims to mitigate dilemmas of orientation, legitimacy, and control. The aspiration of RI is to bend the processes of technology development toward more just, sustainable, and societally desirable outcomes. Despite the potential for fruitful interaction across RI’s constitutive domains—sustainability science and social studies of science and technology—most sustainability scientists under-theorize the sociopolitical dimensions of technological systems and most science and technology scholars hesitate to take a normative, solutions-oriented stance. Efforts to advance RI, although notable, entail one-off projects that do not lend themselves to comparative analysis for learning.
In this dissertation, I offer an intervention research framework to aid systematic study of intentional programs of change to advance responsible innovation. Two empirical studies demonstrate the framework in application. An evaluation of Science Outside the Lab presents a program to help early-career scientists and engineers understand the complexities of science policy. An evaluation of a Community Engagement Workshop presents a program to help engineers better look beyond technology, listen to and learn from people, and empower communities. Each program is efficacious in helping scientists and engineers more thoughtfully engage with mediators of science and technology governance dilemmas: Science Outside the Lab in revealing the dilemmas of orientation and legitimacy; Community Engagement Workshop in offering reflexive and inclusive approaches to control. As part of a larger intervention research portfolio, these and other projects hold promise for aiding governance of science and technology through responsible innovation.
ContributorsBernstein, Michael J. (Author) / Wiek, Arnim (Thesis advisor) / Wetmore, Jameson M. (Thesis advisor) / Grimm, Nancy (Committee member) / Anderies, John M (Committee member) / Arizona State University (Publisher)
Created2016
Description
Economic development over the last century has driven a tripling of the world's population, a twenty-fold increase in fossil fuel consumption, and a tripling of traditional biomass consumption. The associated broad income and wealth inequities are retaining over 2 billion people in poverty. Adding to this, fossil fuel combustion is impacting the environment across spatial and temporal scales and the cost of energy is outpacing all other variable costs for most industries. With 60% of world energy delivered in 2008 consumed by the commercial and industrial sector, the fragmented and disparate energy-related decision making within organizations are largely responsible for the inefficient and impacting use of energy resources. The global transition towards sustainable development will require the collective efforts of national, regional, and local governments, institutions, the private sector, and a well-informed public. The leadership role in this transition could be provided by private and public sector organizations, by way of sustainability-oriented organizations, cultures, and infrastructure. The diversity in literature exemplifies the developing nature of sustainability science, with most sustainability assessment approaches and frameworks lacking transformational characteristics, tending to focus on analytical methods. In general, some shortfalls in sustainability assessment processes include lack of: * thorough stakeholder participation in systems and stakeholder mapping, * participatory envisioning of future sustainable states, * normative aggregation of results to provide an overall measure of sustainability, and * influence within strategic decision-making processes. Specific to energy sustainability assessments, while some authors aggregate results to provide overall sustainability scores, assessments have focused solely on energy supply scenarios, while including the deficits discussed above. This paper presents a framework for supporting organizational transition processes towards sustainable energy systems, using systems and stakeholder mapping, participatory envisioning, and sustainability assessment to prepare the development of transition strategies towards realizing long-term energy sustainability. The energy system at Arizona State University's Tempe campus (ASU) in 2008 was used as a baseline to evaluate the sustainability of the current system. From interviews and participatory workshops, energy system stakeholders provided information to map the current system and measure its performance. Utilizing operationalized principles of energy sustainability, stakeholders envisioned a future sustainable state of the energy system, and then developed strategies to begin transition of the current system to its potential future sustainable state. Key findings include stakeholders recognizing that the current energy system is unsustainable as measured against principles of energy sustainability and an envisioned future sustainable state of the energy system. Also, insufficient governmental stakeholder engagement upstream within the current system could lead to added risk as regulations affect energy supply. Energy demand behavior and consumption patterns are insufficiently understood by current stakeholders, limiting participation and accountability from consumers. In conclusion, although this research study focused on the Tempe campus, ASU could apply this process to other campuses thereby improving overall ASU energy system sustainability. Expanding stakeholder engagement upstream within the energy system and better understanding energy consumption behavior can also improve long-term energy sustainability. Finally, benchmarking ASU's performance against its peer universities could expand the current climate commitment of participants to broader sustainability goals.
ContributorsBuch, Rajesh (Author) / Wiek, Arnim (Thesis advisor) / Basile, George (Thesis advisor) / Williams, Eric (Committee member) / Arizona State University (Publisher)
Created2011