Dissertation Defense Announcements

The modern economy runs with heavy reliance on the free flow of goods across the international logistic and supply chain. Advances in international freight transportation systems supported by intermodal integration, freight containerization, hub-and-spoke shipping system, and supply chain security, has reduced the distance friction of flow of goods and drastically lowered physical barriers of commercial activities. However, it is little known yet how spatial interactions of trade and shipping take place under the complex logistic chain process and what spatial phenomena ensue from such processes. In this dissertation, I study the nature of spatial interaction phenomena in the context of the contemporary state of the international transportation system. First, I study how the spatial structure of the port system is formed with intermodal integration of the modern international logistic system across land and water. Second, I explore how the hub-and-spoke system in the international transportation network contributes to the global shrinkage of space. Third, I investigate the effect of domestic armed conflicts developed by political instability on freight mobility and ensuing differential openness of regions to the global market. Results of the three pieces of research are as follows. First, the spatial structure of the port system is found to comprise interdependent collections of hinterlands, feeder and hub ports, and forelands along a logistical continuum, which mirror the functional division of logistic processes across space. Second, the hub-and-spoke shipping system reduces the distance friction of shipping flows and is the main driver of global shrinkage of space in terms of long-distance trade. Third, freight mobility is found to be greatly compromised by the lack of logistic chain security stemming from prevailing armed violence along inland transportation corridors. The findings confirm that intermodal logistic integration, hub-and-spoke distribution system and supply chain security are important key components of the modern international transportation system that determine global-scale spatial organization, shipping flow and freight mobility.

Structured light systems (SLS) have become increasingly important for three-dimensional shape measurements. A quantitative evaluation of the spatial resolution is also becoming increasingly important. The spatial frequency response of the instrument is a reasonable metric for resolution and is commonly referred to as the instrument transfer function (ITF). We used the ITF to determine the capability of a commercial SLS the EinScan-pro using a step artifact. The ITF is similar to the modulation transfer function (MTF) of an imaging system, which describes how well the system images an object as a function of spatial frequency. Similarly, ITF describes the instrument response to the spatial frequency on the surface to be measured. Many optical measurement instruments use a camera for data acquisition and the optical transfer function will necessarily impose a limit on the instrument resolution. The ITF and the MTF metrics rely on the linearity of the measurement. Only a liner and shift invariant system can be used to uniquely define ITF/MTF. In this dissertation, we describe the use of the step artifact to determine the spatial resolution of a commercial SLS the EinScan-Pro. We check the use of the ITF over the MTF of the imaging system. We present a methodology to check the combined uncertainty for the ITF measurements including a method to check the applicability of the step artifact for the ITF measurements, the impact of the use of step artifact with different surface finishes, and the effect of the tilt and disposition of the artifact during the measurement. We also, present the use of the bispectrum for the non-linearity check of any kind of measurement which is applicable for both ITF/MTF measurements.

We propose methods for functional predictor selection and the estimation of smooth functional coefficients simultaneously in a scalar-on-function regression problem under a high-dimensional multivariate functional data setting. In particular, we develop two methods for functional group-sparse regression under a generic Hilbert space of infinite dimension. We show the convergence of algorithms and the consistency of the estimation and the selection (oracle property) under infinite-dimensional Hilbert spaces. Simulation studies show the effectiveness of the methods in both the selection and the estimation of functional coefficients. The applications to functional magnetic resonance imaging (fMRI) reveal the human brain regions related to ADHD and IQ. In addition, we apply the proposed methods to an econometric data set to find the related functional covariates to GDP of a country. To extend the results, we propose numerical algorithms for more complex models, such as nonlinear (via RKHS), logistic, sparse function--on--function, and standardization of the results of the sparse scalar--on--function models before we list the applications of these extensions to the brain image data analysis.

Climate change has resulted in warming of coastal aquatic habitats around the world at almost every latitude, threatening ecosystems with a significant loss in biodiversity and occurring at a rate that may exceed species’ ability to adapt. Understanding how reef species survive in habitats that currently experience extreme temperatures will help identify the biological processes that will govern future responses to climate change. The Persian/Arabian Gulf experiences the warmest coral reef temperatures on the planet (summer maxima ~35-36°C but can exceed 37°C) and connects to the neighboring Gulf of Oman, which experiences more benign environmental conditions (summer maxima of ~30-32°C). Here, we leverage this unique environmental gradient as a natural laboratory to better understand how the keystone sea urchin Echinometra sp. EZ copes with thermal extremes. Species survival in extreme habitats is dependent on their ability to acclimate over the course of an organisms’ lifetime and adapt over the course of many generations. Two complementary mechanisms for coping with environmental change are shifts in the host-associated microbial community, which can happen on a timescale of hours to days, and classic Darwinian evolution in which selection results in different patterns of alleles between populations over many generations. Here, we identify temperature as a robust predictor of community-level microbial variation and highlight specific bacterial taxa that may be crucial for maintenance of host homeostasis during thermal extremes. Next, we show that while there is a high degree of genetic admixture between all sites and bidirectional gene flow between the two seas, there is also significant population differentiation. We describe nine candidate loci that are under putative selection, including one collagen gene. Finally, we sequence, assemble, and annotate a chromosome-level genome that will add substantial value to future functional genomic datasets. Together, the research composing my dissertation has identified the importance of novel microbiome and genomic variation in the adaptation of a dominant ecosystem engineer to the warmest marine environment on Earth. These integrative results provide a foothold for understanding shared and unique mechanisms for the adaptation of marine species to historic and ongoing climate change.