Essays in History and Spatial Economics with Big Data

This dissertation contains three essays in History and Spatial Economics with Big Data. As a part of my dissertation, I develop a modern machine-learning based approach to connect large datasets. Merging several massive databases and matching the records within them presents challenges — some straightforward and others more complex. I employ artificial intelligence and machine learning technologies to link and then analyze massive amounts of historical US federal census, Department of Labor, and Bureau of Labor Statistics data. The transformation of the US economy during this time period was remarkable, from a rural economy at the beginning of the 19th century to an industrial nation by the end. More strikingly, after lagging behind the technological frontier for most of the nineteenth century, the United States entered the twenty-first century as the global technology leader and the richest nation in the world. Results from this dissertation reveal how people lived and how the business operated. It tells us the past that led us to where we are now in terms of people, geography, prices and wages, wealth, revenue, output, capital, numbers, and types of workers, urbanization, migration, and industrialization. As a part of this endeavor, the first chapter studies how the benefits of improving urban mass transit infrastructures in cities are shared across workers with different skills. It exploits a unique historical setting to estimate the impact of urban transportation infrastructure: the introduction of mass-public transit infrastructure in the late nineteenth and twentieth-century New York City. I linked individual-level US census data to investigate how urban transit infrastructure differentially affects the welfare of workers with heterogenous skill. My second chapter measures immigrants' role in the US rise as an economic power. Especially, this chapter focuses on a potential mechanism by which immigrants might have spurred economic prosperity: the transfer of new knowledge. This is the first project to use advances in quantitative spatial theory along with advanced big-data techniques to understand the contribution of immigrants to the process of U.S. economic growth. The key benefit of this approach is to link modern theory with massive amounts of microeconomic data about individual immigrants—their locations and occupations—to address questions that are extremely difficult to assess otherwise. Specifically, the dataset will help the researchers understand the extent to which the novel ideas and expertise immigrants brought to U.S. shores drove the nation’s emergence as an industrial and technological powerhouse. My third chapter exploits advances in data digitization and machine learning to study intergenerational mobility in the United States before World War II. Using machine learning techniques, I construct a massive database for multiple generations of fathers and sons. This allows us to identify “land of opportunities": locations and times in American history where kids had chances to move up in the income ladder. I find that intergenerational mobility elasticities were relatively stable during 1880-1940; there are regional disparities in terms of giving kids opportunities to move up, and the geographic disparities of intergenerational mobility have evolved over time

The Effect of Ca-P Coated Bovine Bone Mineral on Bone Regeneration around Dental Implant in Dogs

There are many obstacles to overcome in implant dentistry. The bony defect around implant can be seen in immediate installation procedures. Following tooth extraction, however, a socket often presents dimensions that may be considerably greater than the dimensions of a conventional implant

Adiponectin is Associated with Impaired Fasting Glucose in the Non-Diabetic Population

OBJECTIVES: Adiponectin is strongly associated with diabetes in the Western population. However, whether adiponectin is independently associated with impaired fasting glucose (IFG) in the non-obese population is unknown. METHODS: The serum adiponectin, insulin resistance (IR), and waist circumference (WC) of 27,549 healthy Koreans were measured. Individuals were then classified into tertile groups by gender. IFG was defined as a fasting serum glucose of 100-125 mg/dL without diabetes. IR was calculated using the homeostasis model assessment of insulin resistance (HOMA-IR). The association of adiponectin and IFG was determined using logistic regression analysis. RESULTS: WC and adiponectin were associated with IFG in both men and women. However, the association of WC with IFG was attenuated in both men and women after adjustment for the HOMA-IR. Adiponectin was still associated with IFG after adjustment for and stratification by HOMA-IR in men and women. Strong combined associations of IR and adiponectin with IFG were observed in men and women. Multivariate adjusted odds ratios (ORs) (95% confidence interval [CI]) among those in the highest tertile of IR and the lowest tertile of adiponectin were 9.8 (7.96 to 12.07) for men and 24.1 (13.86 to 41.94) for women. CONCLUSION: These results suggest that adiponectin is strongly associated with IFG, and point to adiponectin as an additional diagnostic biomarker of IFG in the non-diabetic population.ope

Front Matter

This file contains cover for Volume II, Issue II, Editorial Board, Acknowledgements

Validity of gait parameters for hip flexor contracture in patients with cerebral palsy

Background: Psoas contracture is known to cause abnormal hip motion in patients with cerebral palsy. The authors investigated the clinical relevance of hip kinematic and kinetic parameters, and 3D modeled psoas length in terms of discriminant validty, convergent validity, and responsiveness. Methods: Twenty-four patients with cerebral palsy (mean age 6.9 years) and 28 normal children (mean age 7.6 years) were included. Kinematic and kinetic data were obtained by three dimensional gait analysis, and psoas lengths were determined using a musculoskeletal modeling technique. Validity of the hip parameters were evaluated. Results: In discriminant validity, maximum psoas length (effect size r = 0.740), maximum pelvic tilt (0.710), maximum hip flexion in late swing (0.728), maximum hip extension in stance (0.743), and hip flexor index (0.792) showed favorable discriminant ability between the normal controls and the patients. In convergent validity, maximum psoas length was not significantly correlated with maximum hip extension in stance in control group whereas it was correlated with maximum hip extension in stance (r = -0.933, p < 0.001) in the patients group. In responsiveness, maximum pelvic tilt (p = 0.008), maximum hip extension in stance (p = 0.001), maximum psoas length (p < 0.001), and hip flexor index (p < 0.001) showed significant improvement post-operatively. Conclusions: Maximum pelvic tilt, maximum psoas length, hip flexor index, and maximum hip extension in stance were found to be clinically relevant parameters in evaluating hip flexor contracture.Y

DIRECT CAROTID WALL SHEAR STRESS IN ACUTE CORONARY SYNDROME PATIENTS DECREASED AFTER ONE MONTH MEDICAL MANAGEMENT

Fuente Fuente, Carlos;Montes Gil, Antonio;Periel Piquer, Montserra

Implicative Int-Soft Filters of R

The notion of implicative int-soft filters is introduced, and related properties are investigated. A relation between an int-soft filter and an implicative int-soft filter is discussed, and conditions for an int-soft filter to be an implicative int-soft filter are provided. Characterizations of an implicative int-soft filter are considered, and a new implicative int-soft filter from an old one is displayed. The extension property of an implicative int-soft filter is established