Matching Items (147)
Description
College students are a niche of young adults, characterized by abnormal sleeping habits and inactive lifestyles. Many students entering college are as young as 18 years old and graduate by 22 years old, a window of time in which their bones are still accruing mineral. The purpose of this cross-sectional study was to determine whether sleep patterns and physical activity observed in college students (N= 52) 18-25 years old at Arizona State University influenced bone biomarkers, osteocalcin (OC) and N-terminal telopeptide of type 1 collagen (NTX-1) concentrations. Students completed various dietary and health history questionnaires including the International Physical Activity Questionnaire short form. Students wore an actigraphy watch for 7 consecutive nights to record sleep events including total sleep time, sleep onset latency and wake after sleep onset. Total sleep time had a significant, negative correlation with OC (r = -0.298, p-value =0.036) while sleep onset latency had a significant, positive correlation with NTX-1 serum concentration (r = 0.293, p-value = 0.037). Despite correlational findings, only sleep percent was found to be significant (beta coefficient = 0.271 p-value = 0.788) among all the sleep components assessed, after adjusting for gender, race, BMI and calcium intake in multivariate regression models. Physical activity alone was not associated with either bone biomarker. Physical activity*sleep onset latency interactions were significantly correlated with osteocalcin (r = 0.308, p-value =0.006) and NTX-1 (r = 0.286, p-value = 0.042) serum concentrations. Sleep percent*physical activity interactions were significantly correlated with osteocalcin (r = 0.280, p-value = 0.049) but not with NTX-1 serum concentrations. Interaction effects were no longer significant after adjusting for covariates in the regression models. While sleep percent was a significant component in the regression model for NTX-1, it was not clinically significant. Overall, sleep patterns and physical activity did not explain OC and NTX-1 serum concentrations in college students 18-25 years old. Future studies may need to consider objective physical activity devices including accelerometers to measure activity levels. At this time, college students should review sleep and physical activity recommendations to ensure optimal healthy habits are practiced.
ContributorsMahmood, Tara Nabil (Author) / Whisner, Corrie (Thesis advisor) / Dickinson, Jared (Committee member) / Petrov, Megan (Committee member) / Adams, Marc (Committee member) / Arizona State University (Publisher)
Created2019
Description
Background In the United States (US), first-year university students typically live on campus and purchase a meal plan. In general, meal plans allow the student a set number of meals per week or semester, or unlimited meals. Understanding how students’ use their meal plan, and barriers and facilitators to meal plan use, may help decrease nutrition-related issues.
Methods First-year students’ meal plan and residence information was provided by a large, public, southwestern university for the 2015-2016 academic year. A subset of students (n=619) self-reported their food security status. Logistic generalized estimating equations (GEEs) were used to determine if meal plan purchase and use were associated with food insecurity. Linear GEEs were used to examine several potential reasons for lower meal plan use. Logistic and Linear GEEs were used to determine similarities in meal plan purchase and use for a total of 599 roommate pairs (n=1186 students), and 557 floormates.
Results Students did not use all of the meals available to them; 7% of students did not use their meal plan for an entire month. After controlling for socioeconomic factors, compared to students on unlimited meal plans, students on the cheapest meal plan were more likely to report food insecurity (OR=2.2, 95% CI=1.2, 4.1). In Fall, 26% of students on unlimited meal plans reported food insecurity. Students on the 180 meals/semester meal plan who used fewer meals were more likely to report food insecurity (OR=0.9, 95% CI=0.8, 1.0); after gender stratification this was only evident for males. Students’ meal plan use was lower if the student worked a job (β=-1.3, 95% CI=-2.3, -0.3) and higher when their roommate used their meal plan frequently (β=0.09, 99% CI=0.04, 0.14). Roommates on the same meal plan (OR=1.56, 99% CI=1.28, 1.89) were more likely to use their meals together.
Discussion This study suggests that determining why students are not using their meal plan may be key to minimizing the prevalence of food insecurity on college campuses, and that strategic roommate assignments may result in students’ using their meal plan more frequently. Students’ meal plan information provides objective insights into students’ university transition.
Methods First-year students’ meal plan and residence information was provided by a large, public, southwestern university for the 2015-2016 academic year. A subset of students (n=619) self-reported their food security status. Logistic generalized estimating equations (GEEs) were used to determine if meal plan purchase and use were associated with food insecurity. Linear GEEs were used to examine several potential reasons for lower meal plan use. Logistic and Linear GEEs were used to determine similarities in meal plan purchase and use for a total of 599 roommate pairs (n=1186 students), and 557 floormates.
Results Students did not use all of the meals available to them; 7% of students did not use their meal plan for an entire month. After controlling for socioeconomic factors, compared to students on unlimited meal plans, students on the cheapest meal plan were more likely to report food insecurity (OR=2.2, 95% CI=1.2, 4.1). In Fall, 26% of students on unlimited meal plans reported food insecurity. Students on the 180 meals/semester meal plan who used fewer meals were more likely to report food insecurity (OR=0.9, 95% CI=0.8, 1.0); after gender stratification this was only evident for males. Students’ meal plan use was lower if the student worked a job (β=-1.3, 95% CI=-2.3, -0.3) and higher when their roommate used their meal plan frequently (β=0.09, 99% CI=0.04, 0.14). Roommates on the same meal plan (OR=1.56, 99% CI=1.28, 1.89) were more likely to use their meals together.
Discussion This study suggests that determining why students are not using their meal plan may be key to minimizing the prevalence of food insecurity on college campuses, and that strategic roommate assignments may result in students’ using their meal plan more frequently. Students’ meal plan information provides objective insights into students’ university transition.
Contributorsvan Woerden, Irene (Author) / Bruening, Meg (Thesis advisor) / Hruschka, Daniel (Committee member) / Schaefer, David (Committee member) / Vega-Lopez, Sonia (Committee member) / Adams, Marc (Committee member) / Arizona State University (Publisher)
Created2019
Description
The research on the topology and dynamics of complex networks is one of the most focused area in complex system science. The goals are to structure our understanding of the real-world social, economical, technological, and biological systems in the aspect of networks consisting a large number of interacting units and to develop corresponding detection, prediction, and control strategies. In this highly interdisciplinary field, my research mainly concentrates on universal estimation schemes, physical controllability, as well as mechanisms behind extreme events and cascading failure for complex networked systems.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
Revealing the underlying structure and dynamics of complex networked systems from observed data without of any specific prior information is of fundamental importance to science, engineering, and society. We articulate a Markov network based model, the sparse dynamical Boltzmann machine (SDBM), as a universal network structural estimator and dynamics approximator based on techniques including compressive sensing and K-means algorithm. It recovers the network structure of the original system and predicts its short-term or even long-term dynamical behavior for a large variety of representative dynamical processes on model and real-world complex networks.
One of the most challenging problems in complex dynamical systems is to control complex networks.
Upon finding that the energy required to approach a target state with reasonable precision
is often unbearably large, and the energy of controlling a set of networks with similar structural properties follows a fat-tail distribution, we identify fundamental structural ``short boards'' that play a dominant role in the enormous energy and offer a theoretical interpretation for the fat-tail distribution and simple strategies to significantly reduce the energy.
Extreme events and cascading failure, a type of collective behavior in complex networked systems, often have catastrophic consequences. Utilizing transportation and evolutionary game dynamics as prototypical
settings, we investigate the emergence of extreme events in simplex complex networks, mobile ad-hoc networks and multi-layer interdependent networks. A striking resonance-like phenomenon and the emergence of global-scale cascading breakdown are discovered. We derive analytic theories to understand the mechanism of
control at a quantitative level and articulate cost-effective control schemes to significantly suppress extreme events and the cascading process.
ContributorsChen, Yuzhong (Author) / Lai, Ying-Cheng (Thesis advisor) / Spanias, Andreas (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2016
Description
Salad bars are promoted as a means to increase fruit and vegetable consumption among school-age children; however, no study has assessed barriers to having salad bars. Further, it is not known if barriers differ across school level. This cross-sectional study investigated the barriers to having salad bars across school level among schools without salad bars in Arizona (n=177). Multivariate binominal regression models were used to determine differences between the barriers and school level, adjusting for years at current job, enrollment of school, free-reduced eligibility rate and district level clustering. The top five barriers were not enough staff (51.4%), lack of space for salad bars (49.7%), food waste concerns (37.9%), sanitation/food safety concerns (31.3%), and time to get through the lines (28.3%) Adjusted analyses indicated two significant differences between barriers across school level: time to get through lines (p=0.040) and outside caterer/vendor (p=0.018) with time to get through lines reported more often by elementary and middle school nutrition managers and outside caterer/vendor reported most often by high school nutrition managers. There were several key barriers reported and results indicate that having an outside vendor/caterer for their meal programs and time to get through the service lines varied across school level. High schools report a higher percent of the barrier outside caterer/vendors and elementary and middle schools report a higher percent of the barrier time to get through the lines. Results indicate that research determining the approximate time it takes students to get through salad bar lines will need to be considered. More research is needed to determine if the barrier time to get through the service lines is due to selection of food items or if it is due to the enrollment size of the lunch period. Future research interventions may consider investigating food safety and sanitation concerns of middle school nutrition managers. Findings may be used to guide ways to decrease barriers in schools without salad bars.
ContributorsKebric, Kelsey (Author) / Bruening, Meg (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Adams, Marc (Committee member) / Arizona State University (Publisher)
Created2016
Description
The purpose of information source detection problem (or called rumor source detection) is to identify the source of information diffusion in networks based on available observations like the states of the nodes and the timestamps at which nodes adopted the information (or called infected). The solution of the problem can be used to answer a wide range of important questions in epidemiology, computer network security, etc. This dissertation studies the fundamental theory and the design of efficient and robust algorithms for the information source detection problem.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
For tree networks, the maximum a posterior (MAP) estimator of the information source is derived under the independent cascades (IC) model with a complete snapshot and a Short-Fat Tree (SFT) algorithm is proposed for general networks based on the MAP estimator. Furthermore, the following possibility and impossibility results are established on the Erdos-Renyi (ER) random graph: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log \mu}\right\rceil+2$ and $\mu$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $
In practice, other than the nodes' states, side information like partial timestamps may also be available. Such information provides important insights of the diffusion process. To utilize the partial timestamps, the information source detection problem is formulated as a ranking problem on graphs and two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed. Extensive experimental evaluations of synthetic data of different diffusion models and real world data demonstrate the effectiveness and robustness of CR and TR compared with existing algorithms.
ContributorsZhu, Kai (Author) / Ying, Lei (Thesis advisor) / Lai, Ying-Cheng (Committee member) / Liu, Huan (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2015
Description
Conductance fluctuations associated with quantum transport through quantumdot systems are currently understood to depend on the nature of the corresponding classical dynamics, i.e., integrable or chaotic. There are a couple of interesting phenomena about conductance fluctuation and quantum tunneling related to geometrical shapes of graphene systems. Firstly, in graphene quantum-dot systems, when a magnetic field is present, as the Fermi energy or the magnetic flux is varied, both regular oscillations and random fluctuations in the conductance can occur, with alternating transitions between the two. Secondly, a scheme based on geometrical rotation of rectangular devices to effectively modulate the conductance fluctuations is presented. Thirdly, when graphene is placed on a substrate of heavy metal, Rashba spin-orbit interaction of substantial strength can occur. In an open system such as a quantum dot, the interaction can induce spin polarization. Finally, a problem using graphene systems with electron-electron interactions described by the Hubbard Hamiltonian in the setting of resonant tunneling is investigated.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
Another interesting problem in quantum transport is the effect of disorder or random impurities since it is inevitable in real experiments. At first, for a twodimensional Dirac ring, as the disorder density is systematically increased, the persistent current decreases slowly initially and then plateaus at a finite nonzero value, indicating remarkable robustness of the persistent currents, which cannot be discovered in normal metal and semiconductor rings. In addition, in a Floquet system with a ribbon structure, the conductance can be remarkably enhanced by onsite disorder.
Recent years have witnessed significant interest in nanoscale physical systems, such as semiconductor supperlattices and optomechanical systems, which can exhibit distinct collective dynamical behaviors. Firstly, a system of two optically coupled optomechanical cavities is considered and the phenomenon of synchronization transition associated with quantum entanglement transition is discovered. Another useful issue is nonlinear dynamics in semiconductor superlattices caused by its key potential application lies in generating radiation sources, amplifiers and detectors in the spectral range of terahertz. In such a system, transition to multistability, i.e., the emergence of multistability with chaos as a system parameter passes through a critical point, is found and argued to be abrupt.
ContributorsYing, Lei (Author) / Lai, Ying-Cheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Chen, Tingyong (Committee member) / Yao, Yu (Committee member) / Arizona State University (Publisher)
Created2016
Description
Background: Childhood obesity is one of the most serious public health concerns in the United States and has been associated with low levels of physical activity. Schools are ideal physical activity promotion sites but school physical activity opportunities have decreased due the increased focus on academic performance. Before-school programs provide a good opportunity for children to engage in physical activity as well as improve their readiness to learn. Purpose: The purpose of this study was to examine the effect of a before-school running/walking club on children's physical activity and on-task behavior. Methods: Participants were third and fourth grade children from two schools in the Southwestern United States who participated in a before-school running/walking club that met two times each week. The study employed a two-phase experimental design with an initial baseline phase and an alternating treatments phase. Physical activity was monitored using pedometers and on-task behavior was assessed through systematic observation. Data analysis included visual analysis, descriptive statistics, as well as multilevel modeling. Results: Children accumulated substantial amounts of physical activity within the before-school program (School A: 1731 steps, 10:02 MVPA minutes; School B: 1502 steps, 8:30 MVPA minutes) and, on average, did not compensate by decreasing their physical activity during the rest of the school day. Further, on-task behavior was significantly higher on days the children attended the before-school program than on days they did not (School A=15.78%, pseudo-R2=.34 [strong effect]; School B=14.26%, pseudo-R2=.22 [moderate effect]). Discussion: Results provide evidence for the positive impact of before-school programs on children's physical activity and on-task behavior. Such programs do not take time away from academics and may be an attractive option for schools.
ContributorsStylianou, Michalis (Author) / Kulinna, Pamela H. (Thesis advisor) / Van Der Mars, Hans (Committee member) / Amazeen, Eric (Committee member) / Adams, Marc (Committee member) / Mahar, Matthew T. (Committee member) / Arizona State University (Publisher)
Created2014
Effect of a Wii Fit® intervention on balance, muscular fitness, and bone health in middle-aged women
Description
Sustaining a fall can be hazardous for those with low bone mass. Interventions exist to reduce fall-risk, but may not retain long-term interest. "Exergaming" has become popular in older adults as a therapy, but no research has been done on its preventative ability in non-clinical populations. The purpose was to determine the impact of 12-weeks of interactive play with the Wii Fit® on balance, muscular fitness, and bone health in peri- menopausal women. METHODS: 24 peri-menopausal-women were randomized into study groups. Balance was assessed using the Berg/FICSIT-4 and a force plate. Muscular strength was measured using the isokinetic dynamometer at 60°/180°/240°/sec and endurance was assessed using 50 repetitions at 240°/sec. Bone health was tracked using dual-energy x-ray absorptiometry (DXA) for the hip/lumbar spine and qualitative ultrasound (QUS) of the heel. Serum osteocalcin was assessed by enzyme immunoassay. Physical activity was quantified using the Women's Health Initiative Physical Activity Questionnaire and dietary patterns were measured using the Nurses' Health Food Frequency Questionnaire. All measures were repeated at weeks 6 and 12, except for the DXA, which was completed pre-post. RESULTS: There were no significant differences in diet and PA between groups. Wii Fit® training did not improve scores on the Berg/FICSIT-4, but improved center of pressure on the force plate for Tandem Step, Eyes Closed (p-values: 0.001-0.051). There were no significant improvements for muscular fitness at any of the angular velocities. DXA BMD of the left femoral neck improved in the intervention group (+1.15%) and decreased in the control (-1.13%), but no other sites had significant changes. Osteocalcin indicated no differences in bone turnover between groups at baseline, but the intervention group showed increased bone turnover between weeks 6 and 12. CONCLUSIONS: Findings indicate that WiiFit® training may improve balance by preserving center of pressure. QUS, DXA and osteocalcin data confirm that those in the intervention group were experiencing more bone turnover and bone formation than the control group. In summary, twelve weeks of strength /balance training with the Wii Fit® shows promise as a preventative intervention to reduce fall and fracture risk in non-clinical middle aged women who are at risk.
ContributorsWherry, Sarah Jo (Author) / Swan, Pamela D (Thesis advisor) / Adams, Marc (Committee member) / Der Ananian, Cheryl (Committee member) / Sweazea, Karen (Committee member) / Vaughan, Linda (Committee member) / Arizona State University (Publisher)
Created2014
Description
Research indicates that adults are not acquiring enough physical activity. Increasing the use of stairs is an accessible way to weave high intensity physical activity into the daily routine. The purpose of this study is to test the effect of four environmental changes on ascending stair use in a mixed population of college students, faulty, and staff on a southwest college campus. The study design included a 10-week time series design with alternating baseline and intervention phases, including a directional cue represented by footprints on the ground, a positive prompt, a deterrent prompt and a combination phase. Data was collected with both an in-person tally and a video recording device. The study included 6,140 observations and coded variables included stair use, sex, number of bags carried, temperature, and volume. Rater reliability ranged from .81 to 1.0. Multivariate logistic regression was used to perform the statistic analysis. Stair use increased significantly from Washout 1 and the positive prompting phase with a 7% absolute increase and an odds ratio of 1.35 (95% CI 1.080-1.696). Stair use during the footprint phase, deterrent phase and combination phase did not increase significantly compared to the previous baseline or washout phases. Day of the week (Monday=reference, Tuesday CI=1.626, 95% CI 1.298-2.011, Wednesday OR=0.457, 95% CI 0.248-0.841, Thursday OR=1.434, 95% CI 1.164-1.766), sex (OR=1.376, 95% CI 1.173-1.613) and volume (OR=1.007, 95% CI 1.005-1.008) were significantly correlated to stair use. Women used the stairs more than men and higher volume situations were related to increased stair use. Temperature and baggage number were not related to stair use. The results of this study indicate that positive prompting with an environmental message theme is an effective method to increase stair use in a university setting.
ContributorsFord, Marley (Author) / Adams, Marc (Thesis advisor) / Der Ananian, Cheryl (Committee member) / Vaughan, Linda (Committee member) / Arizona State University (Publisher)
Created2015
Description
This dissertation treats a number of related problems in control and data analysis of complex networks.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
ContributorsWang, Lezhi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Papandreoou-Suppappola, Antonia (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017