D-Vine Pair-Copula Models for Longitudinal Binary Data

Dependent longitudinal binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. A popular method for analyzing such data is the multivariate probit (MP) model. The motivation for this dissertation stems from the fact that the MP model fails even the binary correlations are within the feasible range. The reason being the underlying correlation matrix of the latent variables in the MP model may not be positive definite. In this dissertation, we study alternatives that are based on D-vine pair-copula models. We consider both the serial dependence modeled by the first order autoregressive (AR(1)) and the equicorrelated correlation structures. Simulation results show that our model is more effective than MP model. Some real life data analysis are presented to show usefulness of our models. We also consider a general situation where the marginal distributions are ordered multinomial. We extend the D-vine pair-copula model to handle multinomial longitudinal data, and compare the generated probability distributions with other methods that are available in R packages

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility

Multivariate Distributions of Correlated Binary Variables Generated by Pair-Copulas

Correlated binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. The generalized estimating equations (GEEs) and the multivariate probit (MP) model are two of the popular methods for analyzing such data. However, both methods have some significant drawbacks. The GEEs may not have an underlying likelihood and the MP model may fail to generate a multivariate binary distribution with specified marginals and bivariate correlations. In this paper, we study multivariate binary distributions that are based on D-vine pair-copula models as a superior alternative to these methods. We elucidate the construction of these binary distributions in two and three dimensions with numerical examples. For higher dimensions, we provide a method of constructing a multidimensional binary distribution with specified marginals and equicorrelated correlation matrix. We present a real-life data analysis to illustrate the application of our results

D-Vine Copula Model For Dependent Binary Data

High-dimensional dependent binary data are prevalent in a wide range of scientific disciplines. A popular method for analyzing such data is the Multivariate Probit (MP) model. But the MP model sometimes fails even within a feasible range of binary correlations, because the underlying correlation matrix of the latent variables may not be positive definite. In this research, we proposed pair copula models, assuming the dependence between the binary variables is first order autoregressive (AR(1))or equicorrelated structure. Also, when Archimediean copula is used, most paper converted Kendall Tau to corresponding copula parameter, there is no explicit function of Pearson’s correlation coefficient with copula parameter. Therefore, we obtain the relationship between binary variable coefficient with copula parameter in the study as well. The outline of this poster presentation is as follows: we start with the definition of the copula and pictorially illustrate the relation between the copula parameter and the binary correlation. We illustrate pair copula constructions of multivariate binary distributions using D-vines and C-vines. We show the application of our method on a real life data. Finally, we briefly discuss our ongoing research.https://digitalcommons.odu.edu/gradposters2020_sciences/1003/thumbnail.jp

Industry’s going upstairs: The innovative usage of industrial land and evaluation of its economic effects

The concept of ‘Industry’s Going Upstairs (IGU)’ represents an innovative usage of industrial land that transfers the enterprises’ production to high-rise industrial buildings. It is emerging in the developed areas of eastern China. This study discusses IGU policies to promote local economic development and conducts an empirical test using Guangdong city-level data and a differencein- differences model. Theoretical analysis shows that IGU can broaden the development space of enterprises and realise industrial and labour agglomeration under supporting policies provided by local governments. The empirical results demonstrate that IGU can improve land-use efficiency and promote local industrial development. IGU is a feasible approach for addressing the current shortage of industrial land in China and is worthy of promotion and replication in other regions

Host-guest Interaction at Molecular Interfaces: Binding of Cucurbit[7]uril on Ferrocenyl Self-assembled Monolayers on Gold

Ferrocene (Fc) encapsulated cucurbit[7]uril (CB[7]) supramolecular host-guest complex  (Fc@CB[7]) as a synthetic recognition pair has been widely adapted for coupling biomolecules and nanomaterials due to its ultra-high binding affinity. In this paper, we have explored the binding of CB[7] on binary ferrocenylundecanethiolate/octanethiolate self-assembled monolayer on gold  (FcC11S-/C8S-Au), a model system to deepen our understanding of host-guest chemistry at molecular interfaces. It has been shown that upon incubation with CB[7] solution, the redox behavior FcC11S-/C8S-Au changes remarkably, i.e., a new pair of peaks appeared at more positive potential with narrowed widths. The ease of quantitation of surface bound-redox species (Fc+/Fc and  Fc+@CB[7]/ Fc@CB[7]) enabled us to determine the thermodynamic formation constant of  Fc@CB[7] at FcC11S-/C8S-Au (7.3±1.8 × 104 M-1). With time-dependent redox responses, we were able to, for the first time, deduce both the binding and dissociation rate constants, 2.8±0.3 × 103  M-1s-1 and 0.08±0.01 s-1, respectively. These results showed substantial differences both thermodynamically and kinetically for the formation of host-guest inclusion complex at molecular interfaces with respect to solution-diffused, homogenous environments

A hydrothermal route to water-stable luminescent carbon dots as nanosensors for pH and temperature

Carbon dots (CDs) as a class of heavy-metal-free fluorescent nanomaterials has drawn increasing attention in recent years due to their high optical absorptivity, chemical stability, biocompatibility, and low toxicity. Herein, we report a facile method to prepare stable CDs by hydrothermal treatment of glucose (glc) in the presence of glutathione (GSH). With this approach, the formation and the surface passivation of CDs are carried out simultaneously, resulting in intrinsic fluorescence emission. The influence of reaction temperature, reaction time and feed ratio of GSH/glc on the photoluminescence property of CDs is studied. The as-prepared CDs are characterized by UV–Vis, photoluminescence, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy and transmission electron microscope, from which their structural information and property are interpreted. These CDs may be useful as pH sensors or as versatile nanothermometry devices based on the pronounced temperature dependence of their steady-state fluorescence emission spectra, which changes considerably over the physiological temperature range (15–60 °C).This work was supported by the National Natural Science Foundation of China (No. 50925207), the Natural Science Foundation of Jiangsu Province, China (BK20140157), Programme of Introducing Talents of Discipline to Universities (111 Project B13025), and the Fundamental Research Funds for the Central Universities (JUSRP11418)

Development of the Swimbladder Surfactant System and Biogenesis of Lysosome-Related Organelles Is Regulated by BLOS1 in Zebrafish

Hermansky-Pudlak syndrome (HPS) is a human autosomal recessive disorder that is characterized by oculocutaneous albinism and a deficiency of the platelet storage pool resulting from defective biogenesis of lysosome-related organelles (LROs). To date, 10 HPS genes have been identified, three of which belong to the octamer complex BLOC-1 (biogenesis of lysosome-related organelles complex 1). One subunit of the BLOC-1 complex, BLOS1, also participates in the BLOC-1-related complex (BORC). Due to lethality at the early embryo stage in BLOS1 knockout mice, the function of BLOS1 in the above two complexes and whether it has a novel function are unclear. Here, we generated three zebrafish mutant lines with a BLOC-1 deficiency, in which melanin and silver pigment formation was attenuated as a result of mutation of bloc1s1, bloc1s2, and dtnbp1a, suggesting that they function in the same complex. In addition, mutations of bloc1s1 and bloc1s2 caused an accumulation of clusters of lysosomal vesicles at the posterior part of the tectum, representing a BORC-specific function in zebrafish. Moreover, bloc1s1 is highly expressed in the swimbladder during postembryonic stages and is required for positively regulating the expression of the genes, which is known to govern surfactant production and lung development in mammals. Our study identified BLOS1 as a crucial regulator of the surfactant system. Thus, the zebrafish swimbladder might be an easy system to screen and study genetic modifiers that control surfactant production and homeostasis.</p

Lithium niobate-enhanced laser photoacoustic spectroscopy

In this paper, the photoacoustic spectroscopy technique based on lithium niobate crystals is initially reported, to our knowledge. A novel dual-cantilever tuning fork structure and new electrodes have been designed using Y-cut 128{\deg} blackened lithium niobate wafers. The tuning fork, with a resonant frequency of only 10.46 kHz and a prong gap of 1 mm, is engineered to achieve superior performance in photoacoustic spectroscopy. In the demonstration experiment, acetylene was detected using a 1.53 um semiconductor laser, achieving a detection limit of about 9 ppb within a one-second integration time.Comment: 8 pages, 4 figure