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Combining social network analysis and geographic information system for communication research: an application to immigrant communities
Get PDFSocial Network Analysis and Geographic Information Systems can be combined and applied to communication research to better understand how communication networks are associated with spatial or city characteristics. We use a case study of communication networks of immigrant church members (N = 178) in New Jersey to test theories of spatial versus strategic assimilation, visualize social networks, and city racial composition. The findings demonstrate that church members seeking information from coethnic immigrant networks were more likely to live in cities with a concentration of white residents, whereas members who provided more informational support to other members were less likely to live in whiter areas. Thus, coethnic residential choice may not always be linked to immigrant network use and the case applies more to the pattern of strategic assimilation. Future communication research involving questions related to physical locations and space can benefit from combining Social Network Analysis and Geographic Information System techniques in innovative ways.Financial support was provided by the University of Oklahoma Libraries’ Open Access Fund.Ye
Identification and intervention of youth with problematic sexual behavior: a preventative approach to adult sexual offenses
Get PDFThe largest bodies of research regarding sexual offenses focus on punitive measures and intervention for adult offenders during and post-incarceration. Research concerning the sexual behavior in youth has been increasing over the past 30 years, with studies showing stark differences in recidivism rates between intervention during childhood and adults post-incarceration. As a result of this growing body of research, programs targeting childhood problematic sexual behavior have continued grow, spreading awareness of childhood sexual development and providing effective treatment for youth exhibiting sexual behavior problems. No single entity is responsible for governing or responding to childhood sexual behavior. The purpose of this project is to provide a standardized public health approach to the surveillance, monitoring, and intervention of childhood sexual behavior. The overall goal is to provide youth-facing professionals with the knowledge and skill to identify and appropriately respond to children with sexual behavior problems. The K.A.P.S. Manual for Problematic Sexual Behavior: A Guide to Building Better Futures Through Early Identification and Response to Problematic Sexual Behavior in Children includes modules on childhood development, including sexual development, identifying problematic sexual behavior, levels of responding, and continuing education opportunities
Improving Drop Size Distribution Retrieval and Rain Estimation from Polarimetric Radar Data using the Deep Neural Network
Get PDFDrop size distribution (DSD) and rain rate (R) have been estimated from polarimetric radar data are now available nationwide. DSD and R are essential in understanding rain microphysics. Past studies utilized parametrized equations or empirical formulas to estimate the parameters for DSD retrieval and R estimation. The parametrized equations and empirical formulas are relatively easy to form and provide high interpretability, but often lack flexibility, nonlinearity in linear domain, and can only partially account for observational errors. The machine learning methods are often used to address these limitations. Previous machine learning approaches have been utilized, but these efforts centered solely on rain estimation rather than DSD retrievals. This study focused on estimating both DSD parameters and R using deep learning to improve understanding of precipitation microphysics and R estimation.
The estimation accuracy degrades depending on errors in the radar measurements and estimation methods. Here, the deep neural network (DNN) approach has been utilized to improve the estimation of DSD and rain rate by mitigating these error effects. The performance of this approach was verified with the ground truth observed by two-dimensional video disdrometer (2DVD) in Kessler Farm, Oklahoma, and compared with the conventional estimation methods for the period 2006−2017. Physical parameters (mass-/volume-weighted diameter and liquid water content), rain rate, and polarimetric radar variables (including radar reflectivity and differential reflectivity) were obtained from the DSD data. The three methods physics-based inversion, empirical formula, and DNN were applied to two different temporal domains (instantaneous and rain-event-total) with three diverse error sources (fitting, measurement, and model errors). The DSD and rain estimations from the total 18 (= 3 × 2 × 3) cases were evaluated by calculating the bias and root mean squared errors (RMSE). DNN produced the best performance for most cases, up to 50% reduced RMSE when model errors existed. DSD parameters and rain estimated from the Oklahoma City polarimetric radar using the empirical and DNN methods were compared to the disdrometer observations; the number of outliers and errors reduced significantly (up to 5% bias and 40% RMSE) using DNN. The present results suggest that DNN would be useful for retrievals from radar observations
Building cluster control to enable grid reliability and efficiency support
Get PDFPower system operators are actively seeking solutions to increase electric grid power flexibility and inertia, to accommodate deeper renewable integration. Buildings account for 75% of the total electricity use in the US and have great potential for grid reliability support at various time and spatial scales. Due to the limited bidding power of individual buildings, grid services are often provided by a fleet of small buildings managed by tailored coordination strategies. This dissertation presents two families of control methods for building cluster energy management based on the control time frequency and inter-building coordination mode: (1) dictatorial load modulating control strategies formulated under a specific context of distribution voltage regulation, and (2) market-based load shifting control achieved through a game-theoretic control framework. Load modulating represents the ability to balance power supply and demand within seconds in response to the grid signal. Therefore, the load modulating can enable distribution voltage support by controlling flexible loads in the building clusters to let their power use follow volatile solar photovoltaic output, as a means to mitigate fluctuations in the net demand and maintain a stable voltage. Load shifting represents the ability to change the timing of electricity use. In load shifting the typical time duration is 1 to 4 hours, and response time is less than 1 hour. The game-theoretic control strategies allow coordinative load shifting in which individual entities determine their control actions in their own interests while coordination is achieved indirectly through a market mechanism, with the goal of flattening the total load curve of the building cluster
The effect of a non-circadian photoperiod on the growth, physiology, and production of a romaine lettuce cultivar
Get PDFThe circadian rhythm serves to match plant physiology and behavior with the environmental
cycles caused by the rotation of the planet. The circadian rhythm contributes towards the
structure and function of plants and their overall performance which is an important
consideration in agriculture. Arabidopsis has served as a model plant for understanding circadian
function, but it is important to establish if these lessons can be extrapolated to other species. This
study investigated the effect of a non-circadian light cycle on Lactuca sativa (lettuce) plants
reared from germination in those conditions. Canopy size, gas exchange, and carbohydrate
storage and use were investigated, and it was found through repeated measures ANOVA
analyses that non-circadian light cycles are indeed associated with decreases in many metrics
commonly associated with plant performance such as stomatal conductance, carbon dioxide
exchange, leaf-level sugar storage, and canopy area, but not with total canopy volume or total
biomass. This opens up the possibility of further analysis into the feasibility of using non-circadian light cycles in controlled environment agricultural settings and indicates some cross
species agreement with the effects these light cycles are found to have with the model species
Arabidopsi
On the Existence and Stability of Filiform Nilsolitons
Get PDFThis dissertation is concerned with the existence and stability of nilsoliton metrics on filiform Lie algebras. The results are presented in two major components. First, we give new results which preclude the existence of soliton metrics on rank 1 filiform algebras. Most notably, these methods circumvent the need to classify the algebras in each dimension (a major obstacle to the study, to this point). Second, we demonstrate that all soliton metrics on rank 2 filiform algebras are stable. In the course of this, we will develop new approximation techniques, and compute the full curvature tensor of rank 2 filiform algebras. The tables for these curvature tensors are contained in Appendix A
Study of Electrospinning Synthesis Parameters and Validation of a Polarized Spatial Frequency Domain Imaging Device Using Electrospun Polycaprolactone Fibers and Scanning Electron Microscopy
Get PDFScaffolds made with electrospun nanofibers are used for many applications in which mechanical properties increase with decreasing the diameter and aligning the fibers. This thesis research investigates the effects of several parameters on the diameter and orientation of fibers fabricated with our custom electrospinning device. Data are collected with SEM and pSFDI with the intent to validate pSFDI as a rapid and non-destructive method of study for microstructures. Experiments showed that a decrease in concentration, increase in tip-collector distance and in flow rate, all reduce the fiber diameter, while an increase in concentration and in flow rate, improve their alignment. The implementation of an auxiliary electrode further improved the alignment of fibers. However, as the results were not optimal and reproducible, many other parameters could be taken into account to obtain highly satisfactory scaffolds. The findings also support the use of pSFDI, but with some limitations
Three Essays in Applied Macroeconomics and Financial Economics
Get PDFThe first chapter studies the relationship between democratization and production of knowledge. Using bibliographic and patents data, we show that there is a positive and strong impact of democratization on the formation of knowledge in social sciences and business but not in other fields and patenting activity. We confirm these findings using an instrumental variable approach to correct for the endogeneity problems, originating from the unobservables that affect both innovation and democratization and from measurement errors in quantifying democracy indices. Our instrumental variable results are in line with our baseline results. In fact, they indicate that there is a downward bias in the baseline result, which is likely to stem from measurement errors in quantifying democracy indices and unobservables. Finally, our results are robust to a number of estimation methods, outliers, an alternative construction of our IV, and different measures of human capital.
In the second chapter, we examine the effect of mortgage credit market conditions on U.S. elections. During the financial crisis of 2008, the U.S economy experienced a sudden drop in mortgage credit supply. According to the previous research, voters responded to the financial crisis of 2007-2008 by punishing the incumbent party in the presidential election, meaning that the vote share of the incumbent party decreased. To further investigate the effects of the financial crisis on elections, we employ an individual-level dataset of loan application outcomes to examine the effects of the contraction in the mortgage credit market on the House and Gubernatorial elections of 2008. A two-stage approach is employed in order to estimate the impact of the mortgage market conditions on election outcomes. In the first-stage regression, a measure of the change in mortgage credit supply from 2004 to 2008 is derived by taking into account the demand for credit. In the second stage, we estimate the effects of the change in mortgage credit supply on the change in votes for the candidate of the democratic party as well as the candidate of the challenger party. We find no significant impact of the shrinkage in mortgage credits on House and Gubernatorial elections' outcomes. This finding suggests that voters only punish the president for the change in mortgage credits as they may believe lower-level officials are not responsible for this shift.
In the third chapter, we study the effects of elections on the changes in the supply of mortgage credits around elections. According to the literature, politicians have incentives to change economic policies in order to attract voters. We consider a particular type of credit offered through financial institutions and a specific kind of election: mortgage credits supply and Gubernatorial elections. We conduct a spatial regression discontinuity design and explore the financial consequences of gubernatorial elections. We focus on census tracts adjacent to one another yet in two different states. We find that census tracts in states where gubernatorial elections are held and governors have full control over both chambers of state legislatures, lending growth rates increase dramatically. Our results are robust to different specifications
Evidence of learning walks related to scorpion home burrow navigation
Get PDFThe navigation by chemo-textural familiarity hypothesis (NCFH) suggests that scorpions use their midventral pectines to gather chemical and textural information near their burrows and use this information as they subsequently return home. For NCFH to be viable, animals must somehow acquire home-directed ‘tastes’ of the substrate, such as through path integration (PI) and/or learning walks. We conducted laboratory behavioral trials using desert grassland scorpions (Paruroctonus utahensis). Animals reliably formed burrows in small mounds of sand we provided in the middle of circular, sand-lined behavioral arenas. We processed overnight infrared video recordings with a MATLAB script that tracked animal movements at 1–2 s intervals. In all, we analyzed the movements of 23 animals, representing nearly 1500 h of video recording. We found that once animals established their home burrows, they immediately made one to several short, looping excursions away from and back to their burrows before walking greater distances. We also observed similar excursions when animals made burrows in level sand in the middle of the arena (i.e. no mound provided). These putative learning walks, together with recently reported PI in scorpions, may provide the crucial home-directed information requisite for NCFH.Ye
How Managers Apply Weather and Climate Information for Decision-Making in the United States
Get PDFAs the climate continues to warm, precipitation events are projected to become more intense, leaving communities to prepare for potential increases in flooding. There is currently a wealth of weather and climate information available that practitioners can use to make decisions for their jurisdictions; however, this information can be hard to access, understand, and incorporate into standard operating procedures. To document the barriers to transitioning research into operations, the Prediction of Rainfall Extremes at Sub-seasonal to Seasonal Periods (PRES2iP) project team established connections with different groups of natural resource managers from across the United States to understand how they think about and plan for heavy precipitation events. Through a stakeholder engagement workshop and conducting semi-structured interviews, the author of this thesis examines how practitioners use weather and climate information in their positions, additional factors that influence decision-making, and what weather or climate information practitioners wish they had when making decisions. Practitioners are more likely to be familiar with short-term weather forecasts than long-term climate predictions or projections, but they are willing to learn how to interpret and apply information for long-term planning. Additionally, other factors besides weather and climate information, such as budget constraints or the power of county officials, shape how practitioners make decisions. Overall, decision-making across timescales is a complex process where managers rely on multiple types of information