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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1998. / At head of title: MIT/Draper Technology Development Partnership Program. / Includes bibliographical references (p. 103-105). / by Garrett W. Shook. / M.Eng.

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The genome-wide HaploInsufficieny Profiling (HIPHOP) technique has been validated as a method to quantify the relative abundance of uniquely tagged yeast deletion strains using a microarray readout. The massive throughput of next generation sequencing presents a new technology for assessing HIPHOP profiles. I developed a new method called Barcode analysis by Sequencing (Bar-seq) that applies deep sequencing to genome-scale fitness. I show that Bar-seq outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex genome-scale fitness assay, Bar-seq quantitatively identifies drug-targets, exceeding the performance of the microarray assay. I also established that Bar-seq is well suited to a multiplex format and provides a dramatic increase in throughput. I used the genome-wide HIPHOP assay and other functional genomics tools to explore the mechanisms underlying drug-drug synergies. Drug combination therapy, and synergistic combinations in particular, have several advantages over monotherapies. Synergistic drug combinations allow the dose of each agent to be reduced, often with the benefit of diminishing side effects while maintaining efficacy and decreasing the chances of drug resistance. I used my yeast model to identify synergistic drug combinations and found that inhibitors of ergosterol biosynthesis are highly synergistic with several agents, including those targeting other points within the same pathway. I also devised a method that enriches for synergistic interactions during screening of compound combinations. This new synergy prediction method can aid in the rapid identification of anti-proliferative combinations and can be readily applied to other organisms for further characterization and/or confirmation. Finally, I examined synergistic combination HIPHOP profiles and identified Gene Ontology enrichments that are combination-specific.

The genome-wide HaploInsufficieny Profiling (HIPHOP) technique has been validated as a method to quantify the relative abundance of uniquely tagged yeast deletion strains using a microarray readout. The massive throughput of next generation sequencing presents a new technology for assessing HIPHOP profiles. I developed a new method called Barcode analysis by Sequencing (Bar-seq) that applies deep sequencing to genome-scale fitness. I show that Bar-seq outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex genome-scale fitness assay, Bar-seq quantitatively identifies drug-targets, exceeding the performance of the microarray assay. I also established that Bar-seq is well suited to a multiplex format and provides a dramatic increase in throughput. I used the genome-wide HIPHOP assay and other functional genomics tools to explore the mechanisms underlying drug-drug synergies. Drug combination therapy, and synergistic combinations in particular, have several advantages over monotherapies. Synergistic drug combinations allow the dose of each agent to be reduced, often with the benefit of diminishing side effects while maintaining efficacy and decreasing the chances of drug resistance. I used my yeast model to identify synergistic drug combinations and found that inhibitors of ergosterol biosynthesis are highly synergistic with several agents, including those targeting other points within the same pathway. I also devised a method that enriches for synergistic interactions during screening of compound combinations. This new synergy prediction method can aid in the rapid identification of anti-proliferative combinations and can be readily applied to other organisms for further characterization and/or confirmation. Finally, I examined synergistic combination HIPHOP profiles and identified Gene Ontology enrichments that are combination-specific.

Psychological attachment to an entrepreneurial opportunity may motivate the entrepreneur to persevere but can also bias decisions made in the entrepreneurial process, especially on market entry. This thesis investigates how psychological attachment to an entrepreneur’s idea influences decision making at the commercialization stage with special emphasis on control tendencies. Data collected from 106 fourth-year students from the Engineering Design Program at a top engineering-focused Canadian university revealed some interesting results. In the model estimated, the higher the subject’s psychological attachment to the opportunity, the more control oriented the subject was. Interestingly, psychological attachment is a strong predictor of control tendency even when subjects’ perceptions of projected returns (value) are statistically controlled in the analysis. Furthermore, psychological attachment correlates with proxy measures of the level of cognitive evaluation: the indication, affective constructs like psychological attachment elicit affect-laden evaluation of outcomes in a way that is divergent from the cognitive evaluation of commercialization situations. Within a framework of financial decision making, even as subjects generally acknowledged outside investor expertise in a potential commercialization partnership, the main finding was that high levels of attachment are more likely to lead to control-oriented funding preferences over optimal financing preferences. Further, alternative research explanations for control tendency failed to hold, as individual personality-type factors were not significant in explaining the variability in control tendency. Therefore, control tendency may be dependent on attachment to the creative process as opposed to an individual’s personality construct. The results provide insight into the role that affective constructs like psychological attachment and control tendency may play in important decision making in the entrepreneurship process.

Psychological attachment to an entrepreneurial opportunity may motivate the entrepreneur to persevere but can also bias decisions made in the entrepreneurial process, especially on market entry. This thesis investigates how psychological attachment to an entrepreneur’s idea influences decision making at the commercialization stage with special emphasis on control tendencies. Data collected from 106 fourth-year students from the Engineering Design Program at a top engineering-focused Canadian university revealed some interesting results. In the model estimated, the higher the subject’s psychological attachment to the opportunity, the more control oriented the subject was. Interestingly, psychological attachment is a strong predictor of control tendency even when subjects’ perceptions of projected returns (value) are statistically controlled in the analysis. Furthermore, psychological attachment correlates with proxy measures of the level of cognitive evaluation: the indication, affective constructs like psychological attachment elicit affect-laden evaluation of outcomes in a way that is divergent from the cognitive evaluation of commercialization situations. Within a framework of financial decision making, even as subjects generally acknowledged outside investor expertise in a potential commercialization partnership, the main finding was that high levels of attachment are more likely to lead to control-oriented funding preferences over optimal financing preferences. Further, alternative research explanations for control tendency failed to hold, as individual personality-type factors were not significant in explaining the variability in control tendency. Therefore, control tendency may be dependent on attachment to the creative process as opposed to an individual’s personality construct. The results provide insight into the role that affective constructs like psychological attachment and control tendency may play in important decision making in the entrepreneurship process.

ABSTRACT Ministry of Economic Affairs (MOEA) launched technology development program in 1979 in order to develop industrial innovation technology and satisfy domestic economic development. In the Age of Knowledge Based Economics, the key factors of continuing growing up of nations are the energy of research and development (R&D) and innovation. From 1997, MOEA made technology development program open to companies, it is Industrial Technology Development Program (ITDP). In order to encourage private sector R&D and innovative activities, MOEA subsidizes companies reduce the risk and the cost of R&D and innovation. From the beginning of ITDP, it has made plenty of R&D outputs, but we have to evaluate the efficiency of R&D. In order to allocate government funds more efficient, we pay much attention to the performance of R&D projects. In order to understand government subsides industries, this thesis is trying to research the object of ITDP of MOEA. The research methodology applied to this thesis includes: the Data Envelopment Analysis (DEA) to measure the R&D efficiency; model from Charnes, Cooper & Rhodes (1978) to measure the over-efficiency; model from the Banker, Charnes & Cooper (1984) to measure the technical efficiency, input/output slacks method to analyze the extent for which non-efficiency unit could be improved by decreasing the amount of inputs or increasing the amount of outputs, and sensitivity analysis to measure the key factors of ITDP R&D Projects. According to this thesis, we can evaluate the Decision Making Units (DMUs) and suggest the information to improve performance. Using these analyses as a reference to those project executives and administrators for controlling and management the performance of R&D projects.

When aggressive aircraft performance goals are set, he integration of new, advanced technologies into next generation aircraft concepts is required to bridge the gap between current capabilities and required capabilities. A large number of technologies exists that can be pursued, and only a subset may practically be selected to reach the chosen objectives. Additionally, the appropriate numerical and physical experimentation must be identified to further develop the selected technologies. These decisions must be made under a large amount of uncertainty because developing technologies introduce phenomena that have not been previously characterized. Traditionally, technology selection decisions are made based on deterministic performance assessments that do not capture the uncertainty of the technology impacts. Model-driven environments and new, advanced uncertainty quantification techniques provide the ability to characterize technology impact uncertainties and pinpoint how they are driving the system performance, which will aid technology selection decisions. Moreover, the probabilistic assessments can be used to plan experimentation that facilitates uncertainty reduction by targeting uncertainty sources with large performance impacts. The thesis formulates and implements a process that allows for risk-informed decision making throughout technology development. It focuses on quantifying technology readiness risk and performance risk by synthesizing quantitative, probabilistic performance information with qualitative readiness assessments. The Quantitative Uncertainty Modeling, Management, and Mitigation (QuantUM3) methodology was tested through the use of an environmentally-motivated aircraft design case study based upon NASAs Environmentally Responsible Aviation (ERA) technology development program. A physics-based aircraft design environment was created that has the ability to provide quantitative system-level performance assessments and was employed to model the technology impacts as probability distributions to facilitate the development of an overall process required to enable risk-informed technology and experimentation decisions. The outcome of the experimental e orts was a detailed outline of the entire methodology and a confirmation that the methodology enables risk-informed technology development decisions with respect to both readiness risk and performance risk. Furthermore, a new process for communicating technology readiness through morphological analysis was created as well as an experiment design process that utilizes the readiness information and quantitative uncertainty analysis to simultaneously increase readiness and decrease technology performance uncertainty.

Using technology as an entry point, I employ the concept of the ecology of practice as a lens to interpret a specific food security intervention on small millets –neglected and underutilized crops important to rainfed agriculture. The “Revalorizing small millets: Enhancing the food and nutritional security of women and children in rainfed regions of South Asia using underutilized species (RESMISA)” project objectives each evoked technology to: increase production, decrease women’s drudgery, and increase the status of small millets. I examine networks of actors, ecologies and technologies in the Nepal project sites using a multi-sited ethnographic approach. Analyzing three types of technologies (seed, machines and practices), I found divergences between natural and social scientists’ perceptions on technology development. Interests differed among the worldviews of smallholder farmers that the researchers sought to engage as participants. Understanding practices in specific ecologies matters as research for development efforts seek to close the technology adoption gap.