Matching Items (48)
Description
Urban scaling analysis has introduced a new scientific paradigm to the study of cities. With it, the notions of size, heterogeneity and structure have taken a leading role. These notions are assumed to be behind the causes for why cities differ from one another, sometimes wildly. However, the mechanisms by which size, heterogeneity and structure shape the general statistical patterns that describe urban economic output are still unclear. Given the rapid rate of urbanization around the globe, we need precise and formal mathematical understandings of these matters. In this context, I perform in this dissertation probabilistic, distributional and computational explorations of (i) how the broadness, or narrowness, of the distribution of individual productivities within cities determines what and how we measure urban systemic output, (ii) how urban scaling may be expressed as a statistical statement when urban metrics display strong stochasticity, (iii) how the processes of aggregation constrain the variability of total urban output, and (iv) how the structure of urban skills diversification within cities induces a multiplicative process in the production of urban output.
ContributorsGómez-Liévano, Andrés (Author) / Lobo, Jose (Thesis advisor) / Muneepeerakul, Rachata (Thesis advisor) / Bettencourt, Luis M. A. (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
Regional differences of inventive activity and economic growth are important in economic geography. These differences are generally explained by the theory of localized knowledge spillovers, which argues that geographical proximity among economic actors fosters invention and innovation. However, knowledge production involves an increasing number of actors connecting to non-local partners. The space of knowledge flows is not tightly bounded in a given territory, but functions as a network-based system where knowledge flows circulate around alignments of actors in different and distant places. The purpose of this dissertation is to understand the dynamics of network aspects of knowledge flows in American biotechnology. The first research task assesses both spatial and network-based dependencies of biotechnology co-invention across 150 large U.S. metropolitan areas over four decades (1979, 1989, 1999, and 2009). An integrated methodology including both spatial and social network analyses are explicitly applied and compared. Results show that the network-based proximity better defines the U.S. biotechnology co-invention urban system in recent years. Co-patenting relationships of major biotechnology centers has demonstrated national and regional association since the 1990s. Associations retain features of spatial proximity especially in some Midwestern and Northeastern cities, but these are no longer the strongest features affecting co-inventive links. The second research task examines how biotechnology knowledge flows circulate over space by focusing on the structural properties of intermetropolitan co-invention networks. All analyses in this task are conducted using social network analysis. Evidence shows that the architecture of the U.S. co-invention networks reveals a trend toward more organized structures and less fragmentation over the four years of analysis. Metropolitan areas are increasingly interconnected into a large web of networked environment. Knowledge flows are less likely to be controlled by a small number of intermediaries. San Francisco, New York, Boston, and San Diego monopolize the central positions of the intermetropolitan co-invention network as major American biotechnology concentrations. The overall network-based system comes close to a relational core/periphery structure where core metropolitan areas are strongly connected to one another and to some peripheral areas. Peripheral metropolitan areas are loosely connected or even disconnected with each other. This dissertation provides empirical evidence to support the argument that technological collaboration reveals a network-based system associated with different or even distant geographical places, which is somewhat different from the conventional theory of localized knowledge spillovers that once dominated understanding of the role of geography in technological advance.
ContributorsLee, Der-Shiuan (Author) / Ó Huallacháin, Breandán (Thesis advisor) / Anselin, Luc (Committee member) / Kuby, Michael (Committee member) / Lobo, Jose (Committee member) / Arizona State University (Publisher)
Created2011
Description
Artificial Intelligence (AI) is a rapidly advancing field with the potential to impact every aspect of society, including the inventive practices of science and technology. The creation of new ideas, devices, or methods, commonly known as inventions, is typically viewed as a process of combining existing knowledge. To understand how AI can transform scientific and technological inventions, it is essential to comprehend how such combinatorial inventions have emerged in the development of AI.This dissertation aims to investigate three aspects of combinatorial inventions in AI using data-driven and network analysis methods. Firstly, how knowledge is combined to generate new scientific publications in AI; secondly, how technical com- ponents are combined to create new AI patents; and thirdly, how organizations cre- ate new AI inventions by integrating knowledge within organizational and industrial boundaries. Using an AI publication dataset of nearly 300,000 AI publications and an AI patent dataset of almost 260,000 AI patents granted by the United States Patent and Trademark Office (USPTO), this study found that scientific research related to AI is predominantly driven by combining existing knowledge in highly conventional ways, which also results in the most impactful publications. Similarly, incremental improvements and refinements that rely on existing knowledge rather than radically new ideas are the primary driver of AI patenting. Nonetheless, AI patents combin- ing new components tend to disrupt citation networks and hence future inventive practices more than those that involve only existing components.
To examine AI organizations’ inventive activities, an analytical framework called the Combinatorial Exploitation and Exploration (CEE) framework was developed to measure how much an organization accesses and discovers knowledge while working within organizational and industrial boundaries. With a dataset of nearly 500 AI organizations that have continuously contributed to AI technologies, the research shows that AI organizations favor exploitative over exploratory inventions. However, local exploitation tends to peak within the first five years and remain stable, while exploratory inventions grow gradually over time.
Overall, this dissertation offers empirical evidence regarding how inventions in AI have emerged and provides insights into how combinatorial characteristics relate to AI inventions’ quality. Additionally, the study offers tools to assess inventive outcomes and competence.
ContributorsWang, Jieshu (Author) / Maynard, Andrew (Thesis advisor) / Lobo, Jose (Committee member) / Michael, Katina (Committee member) / Motsch, Sebastien (Committee member) / Arizona State University (Publisher)
Created2023
Description
Raising future generations is a culturally diverse, universally technological human project. This research brought the everyday work of raising children into the domain of sustainability scholarship, by first proposing a model of childrearing as a globally distributed socio-technical system, and then exploring the model with participants in two nodes – an elementary and middle school, and a children’s museum. In the process, the research objective shifted towards using methods that were less academic and more relevant to childrearing agents. The focus on participatory survey data was abandoned, in favor of autoethnographic documentation of a long-term engagement with a third node of the system, a child welfare setting. This approach yielded unexpected findings that fit the proposed model, identified characteristics of a Zone of Mutual Oblivion (ZMO) that exists between childrearing and sustainability, and clarified ways in which people prioritize their own needs and responsibilities, the developmental needs of children, the potential needs and capacities of future generations, and the functional integrity of ecological systems.
ContributorsCazel-Jahn, Angela (Author) / Blue Swadener, Elizabeth (Thesis advisor) / Allenby, Braden (Committee member) / Lobo, Jose (Committee member) / Arizona State University (Publisher)
Created2019
Description
Sustainable food systems have been studied extensively in recent times and the Food-Energy-Water (FEW) nexus framework has been one of the most common frameworks used. The dissertation intends to examine and quantitatively model the food system interaction with the energy system and the water system. Traditional FEW nexus studies have focused on food production alone. While this approach is informative, it is insufficient since food is extensively traded. Various food miles studies have highlighted the extensive virtual energy and virtual water footprint of food. This highlights the need for transport, and storage needs to be considered as part of the FEW framework. The Life cycle assessment (LCA) framework is the best available option to estimate the net energy and water exchange between the food, energy, and water systems. Climate plays an important role in food production as well as food preservation. Crops are very sensitive to temperature changes and it directly impacts a crop’s productivity. Changing temperatures directly impact crop productivity, and water demand. It is important to explore the feasibility of mitigation measures to keep in check increasing agricultural water demands. Conservation technologies may be able to provide the necessary energy and water savings. Even under varying climates it might be possible to meet demand for food through trade. The complex trade network might have the capacity to compensate for the produce lost due to climate change, and hence needs to be established. Re-visualizing the FEW nexus from the consumption perspective would better inform policy on exchange of constrained resources as well as carbon footprints. This puts the FEW nexus research space a step towards recreating the FEW nexus as a network of networks, that is, FEW-e (FEW exchange) nexus.
ContributorsNatarajan, Mukunth (Author) / Chester, Mikhail (Thesis advisor) / Lobo, Jose (Committee member) / Ruddell, Benjamin (Committee member) / Fraser, Andrew (Committee member) / Arizona State University (Publisher)
Created2019
Description
Background
In 2015, the Zika arbovirus (ZIKV) began circulating in the Americas, rapidly expanding its global geographic range in explosive outbreaks. Unusual among mosquito-borne diseases, ZIKV has been shown to also be sexually transmitted, although sustained autochthonous transmission due to sexual transmission alone has not been observed, indicating the reproduction number (R0) for sexual transmission alone is less than 1. Critical to the assessment of outbreak risk, estimation of the potential attack rates, and assessment of control measures, are estimates of the basic reproduction number, R0.
Methods
We estimated the R0 of the 2015 ZIKV outbreak in Barranquilla, Colombia, through an analysis of the exponential rise in clinically identified ZIKV cases (n = 359 to the end of November, 2015).
Findings
The rate of exponential rise in cases was ρ = 0.076 days[superscript −1], with 95% CI [0.066,0.087] days[superscript −1]. We used a vector-borne disease model with additional direct transmission to estimate the R0; assuming the R0 of sexual transmission alone is less than 1, we estimated the total R0 = 3.8 [2.4,5.6], and that the fraction of cases due to sexual transmission was 0.23 [0.01,0.47] with 95% confidence.
Interpretation
This is among the first estimates of R0 for a ZIKV outbreak in the Americas, and also among the first quantifications of the relative impact of sexual transmission.
ContributorsTowers, Sherry (Author) / Brauer, Fred (Author) / Castillo-Chavez, Carlos (Author) / Falconar, Andrew K. I. (Author) / Mubayi, Anuj (Author) / Romero-Vivas, Claudia M. E. (Author) / School of Human Evolution and Social Change (Contributor) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / Mathematical and Theoretical Biology Institute (MTBI) (Contributor)
Created2016-10-17
Description
Human societies are unique in the level of cooperation among non-kin. Evolutionary models explaining this behavior typically assume pure strategies of cooperation and defection. Behavioral experiments, however, demonstrate that humans are typically conditional co-operators who have other-regarding preferences. Building on existing models on the evolution of cooperation and costly punishment, we use a utilitarian formulation of agent decision making to explore conditions that support the emergence of cooperative behavior. Our results indicate that cooperation levels are significantly lower for larger groups in contrast to the original pure strategy model. Here, defection behavior not only diminishes the public good, but also affects the expectations of group members leading conditional co-operators to change their strategies. Hence defection has a more damaging effect when decisions are based on expectations and not only pure strategies.
ContributorsJanssen, Marco (Author) / Manning, Miles (Author) / Udiani, Oyita (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2014-07-01
Description
Climate change is a well-known global threat to societal systems; however, its effects on the health of individuals are often less evident. Physicians who aim to properly treat patients holistically must be educated on the various forms of illness and disease projected to be exacerbated by climate change. Without this necessary climate education, physicians run the risk of being unable to fulfill the most sacred charge of the Hippocratic oath: Do No Harm. To ensure that physicians moving forward are prepared to face this new global health threat, the prevalence of climate change in current medical school curricula must be examined. Content analysis of publicly available medical school curricula in the Southwest U.S. was done using ChatGPT to track the frequency of climate health search terms. Medical school curricula analyzed included mandatory degree programs as well as optional dual degree programs or pathways for medical student education. Researchers found that medical schools within the Southwest region of the United States are not sufficiently preparing students to mitigate the regional effects of climate change on the health of patients. Mandatory medical degree curriculum does not sufficiently educate on climate health issues, nor is it present in Utah, New Mexico, or Colorado. Optional degrees and pathways are available to medical students to enroll in and may be sufficient to educate a medical student, but are not enticing enough to sufficiently educate all medical students. Some medical schools have recently conducted revisals of their mandatory curriculum and still show a lack of education available about climate health issues. The lack of educational resources for future providers could lead to detrimental health outcomes for patients, and medical schools in development should take the lead in educating their students about climate health issues.
ContributorsJamieson, Ann (Author) / Gutierrez, Sean (Co-author) / Vanos, Jennifer (Thesis director) / Lobo, Jose (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2023-12
Description
Climate change is a well-known global threat to societal systems; however, its effects on
the health of individuals are often less evident. Physicians who aim to properly treat patients
holistically must be educated on the various forms of illness and disease projected to be
exacerbated by climate change. Without this necessary climate education, physicians run the risk of being unable to fulfill the most sacred charge of the Hippocratic oath: Do No Harm. To
ensure that physicians moving forward are prepared to face this new global health threat, the
prevalence of climate change in current medical school curricula must be examined. Content
analysis of publicly available medical school curricula in the Southwest U.S. was done using
ChatGPT to track the frequency of climate health search terms. Medical school curricula
analyzed included mandatory degree programs as well as optional dual degree programs or
pathways for medical student education. Researchers found that medical schools within the
Southwest region of the United States are not sufficiently preparing students to mitigate the
regional effects of climate change on the health of patients. Mandatory medical degree
curriculum does not sufficiently educate on climate health issues, nor is it present in Utah, New
Mexico, or Colorado. Optional degrees and pathways are available to medical students to enroll
in and may be sufficient to educate a medical student, but are not enticing enough to sufficiently
educate all medical students. Some medical schools have recently conducted revisals of their
mandatory curriculum and still show a lack of education available about climate health issues.
The lack of educational resources for future providers could lead to detrimental health outcomes
for patients, and medical schools in development should take the lead in educating their students about climate health issues.
ContributorsGutierrez, Sean (Author) / Jamieson, Ann (Co-author) / Vanos, Jennifer (Thesis director) / Lobo, Jose (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2023-12
Description
A major conundrum in evolution is that, despite natural selection, polymorphism is still omnipresent in nature: Numerous species exhibit multiple morphs, namely several abundant values of an important trait. Polymorphism is particularly prevalent in asymmetric traits, which are beneficial to their carrier in disruptive competitive interference but at the same time bear disadvantages in other aspects, such as greater mortality or lower fecundity. Here we focus on asymmetric traits in which a better competitor disperses fewer offspring in the absence of competition. We report a general pattern in which polymorphic populations emerge when disruptive selection increases: The stronger the selection, the greater the number of morphs that evolve. This pattern is general and is insensitive to the form of the fitness function. The pattern is somewhat counterintuitive since directional selection is excepted to sharpen the trait distribution and thereby reduce its diversity (but note that similar patterns were suggested in studies that demonstrated increased biodiversity as local selection increases in ecological communities). We explain the underlying mechanism in which stronger selection drives the population towards more competitive values of the trait, which in turn reduces the population density, thereby enabling lesser competitors to stably persist with reduced need to directly compete. Thus, we believe that the pattern is more general and may apply to asymmetric traits more broadly. This robust pattern suggests a comparative, unified explanation to a variety of polymorphic traits in nature.
ContributorsLampert, Adam (Author) / Tlusty, Tsvi (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2016-02-04