Bayesian Analysis of Deterministic Time Trend and Changes in Persistence Using a Generalised Stochastic Unit Root Model

This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model estimation and model comparison techniques to investigate the presence of a deterministic time trend in economic series. The model is specified to allow for changes in persistence over time, such as shifts from stationarity I(0) to nonstationarity I(1) or vice versa. This uncertainty raises the crucial question about how sure one can be that an economic time series has a deterministic trend when there is a change in the underlying properties. Empirical analysis indicates that the GSTUR model could provide new insights on time series studies.Stochastic Unit Root; MCMC; Bayesian

Have Betting Exchanges Corrupted Horse Racing?

Betting exchanges allow punters to bet on a horse to lose a race. This, many argue, has opened up the sport to a new form of corruption, where races will be deliberately lost in order to profit from betting. We examine whether anecdotal evidence of the fixing of horses to lose—of which there are many examples—is indicative of wider corruption. Following a “forensic economics” approach, we build an asymmetric information model of exchange betting and take it to betting data on 9,560 races run in 2013/2014. We find no evidence of the widespread corruption of horse racing by the betting exchanges

Bayesian Inference in a Stochastic Volatility Nelson-Siegel Model

In this paper, we develop and apply Bayesian inference for an extended Nelson- Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov chain Monte Carlo (MCMC) algorithm to efficiently estimate the SVNS model using simulation-based inference. Applying the SVNS model to monthly U.S. zero-coupon yields, we find significant evidence for time-varying volatility in the yield factors. This is mostly true for the level and slope volatility revealing also the highest persistence. It turns out that the inclusion of stochastic volatility improves the model's goodness-of-fit and clearly reduces the forecasting uncertainty particularly in low-volatility periods. The proposed approach is shown to work efficiently and is easily adapted to alternative specifications of dynamic factor models revealing (multivariate) stochastic volatility.term structure of interest rates, stochastic volatility, dynamic factor model, Markov chain Monte Carlo

Bayesian Estimation and Model Selection in the Generalised Stochastic Unit Root Model

We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic Unit Root (GSTUR) model. This allows us to investigate the presence of a deterministic time trend in economic series, while allowing the degree of persistence to change over time. In particular the model allows for shifts from stationarity I(0) to nonstationarity I(1) or vice versa. The empirical analysis demonstrates that the GSTUR model provides new insights on the properties of some macroeconomic time series such as stock market indices, in ation and ex- change rates.Stochastic Unit Root, MCMC, Bayesian

Development and Applications of Similarity Measures for Spatial-Temporal Event and Setting Sequences

Similarity or distance measures between data objects are applied frequently in many fields or domains such as geography, environmental science, biology, economics, computer science, linguistics, logic, business analytics, and statistics, among others. One area where similarity measures are particularly important is in the analysis of spatiotemporal event sequences and associated environs or settings. This dissertation focuses on developing a framework of modeling, representation, and new similarity measure construction for sequences of spatiotemporal events and corresponding settings, which can be applied to different event data types and used in different areas of data science. The first core part of this dissertation presents a matrix-based spatiotemporal event sequence representation that unifies punctual and interval-based representation of events. This framework supports different event data types and provides support for data mining and sequence classification and clustering. The similarity measure is based on the modified Jaccard index with temporal order constraints and accommodates different event data types. This approach is demonstrated through simulated data examples and the performance of the similarity measures is evaluated with a k-nearest neighbor algorithm (k-NN) classification test on synthetic datasets. These similarity measures are incorporated into a clustering method and successfully demonstrate the usefulness in a case study analysis of event sequences extracted from space time series of a water quality monitoring system. This dissertation further proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been considered. While modeling event setting sequences, spatial and temporal scales are considered to define the bounds of the setting and incorporate dynamic variables along with static variables. Using a matrix-based representation and an extended Jaccard index, new similarity measures are developed to allow for the use of all variable data types. With these similarity measures coupled with other multivariate statistical analysis approaches, results from a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, support the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. To test the scalability of STES similarity measure in a larger dataset and an extended application in different fields, this dissertation compares and contrasts the prospective space-time scan statistic with the STES similarity approach for identifying COVID-19 hotspots. The COVID-19 pandemic has highlighted the importance of detecting hotspots or clusters of COVID-19 to provide decision makers at various levels with better information for managing distribution of human and technical resources as the outbreak in the USA continues to grow. The prospective space-time scan statistic has been used to help identify emerging disease clusters yet results from this approach can encounter strategic limitations imposed by the spatial constraints of the scanning window. The STES-based approach adapted for this pandemic context computes the similarity of evolving normalized COVID-19 daily cases by county and clusters these to identify counties with similarly evolving COVID-19 case histories. This dissertation analyzes the spread of COVID-19 within the continental US through four periods beginning from late January 2020 using the COVID-19 datasets maintained by John Hopkins University, Center for Systems Science and Engineering (CSSE). Results of the two approaches can complement with each other and taken together can aid in tracking the progression of the pandemic. Overall, the dissertation highlights the importance of developing similarity measures for analyzing spatiotemporal event sequences and associated settings, which can be applied to different event data types and used for data mining, sequence classification, and clustering

Correct prosody or faster articulation? Exploring the factors impacting student L2 listening comprehension

Given that many EFL learners tend to struggle with understanding spoken English, some scholars identified the pedagogical potential of shadowing and visual shadowing for improving listening comprehension. This paper explores whether dif ferent ar ticulation rates for visual shadowing af fect the improvement in EFL learners’ top-down and/or bottom-up processing, and how other factors such as improvement in prosody or articulation rates influence student English listening comprehension. Given that some research findings from this study （i.e. shadowing helped both higher and lower proficiency learners） contradict the major research findings on shadowing, the author analyzes the potential factors that led to these discrepancies

Query Processing In Location-based Services

With the advances in wireless communication technology and advanced positioning systems, a variety of Location-Based Services (LBS) become available to the public. Mobile users can issue location-based queries to probe their surrounding environments. One important type of query in LBS is moving monitoring queries over mobile objects. Due to the high frequency in location updates and the expensive cost of continuous query processing, server computation capacity and wireless communication bandwidth are the two limiting factors for large-scale deployment of moving object database systems. To address both of the scalability factors, distributed computing has been considered. These schemes enable moving objects to participate as a peer in query processing to substantially reduce the demand on server computation, and wireless communications associated with location updates. In the first part of this dissertation, we propose a distributed framework to process moving monitoring queries over moving objects in a spatial network environment. In the second part of this dissertation, in order to reduce the communication cost, we leverage both on-demand data access and periodic broadcast to design a new hybrid distributed solution for moving monitoring queries in an open space environment. Location-based services make our daily life more convenient. However, to receive the services, one has to reveal his/her location and query information when issuing locationbased queries. This could lead to privacy breach if these personal information are possessed by some untrusted parties. In the third part of this dissertation, we introduce a new privacy protection measure called query l-diversity, and provide two cloaking algorithms to achieve both location kanonymity and query l-diversity to better protect user privacy. In the fourth part of this dissertation, we design a hybrid three-tier architecture to help reduce privacy exposure. In the fifth part of this dissertation, we propose to use Road Network Embedding technique to process privacy protected queries

Localization of Expansin Expression During Adventitious and Lateral Rooting in Response to Auxin in Loblolly Pine

Loblolly Pine is the most important and widely cultivated timber species in the southern United States. Due to its fast growth, it is extensively planted for lumber and pulpwood. Vegetative propagation will enhance gains from genetic improvement of tree species. Rooted-cutting is at present the most reliable non-somatic embryogenesis method for cloning specific genotypes. However, an abrupt decline of adventitious rooting capacity has hindered the application of vegetative propagation in loblolly pine. Unraveling the rooting mechanism may facilitate a way to overcome this barrier. Regulation of lateral and adventitious root formation by auxin has been demonstrated through the application of exogenous auxin to roots. Natural lateral root initiation may depend on the localization and redistribution of IAA at the root tip. We studied spatial and temporal responses of lateral root formation to exogenous NAA (1- naphthaleneacetic acid) on the primary roots of loblolly pine seedlings. A significant increase in the frequency and the growth of lateral root primordium (LRP) in response to NAA pulses could be detected at 24 and 48 h. The region 0.5-2.0 cm behind from root tip responds to auxin treatments, but the most responsive region is 0.5-1.5 cm with the largest number of LRPs at both 24 and 48 h. Four poles of primary xylem are often seen in loblolly pine roots. Positioning of successive LRP formation in a given vascular pole is not random. The probability that the next LRP will develop in the same file is nearly 0. Treatment with an exogenous pulse of NAA increases the probability that the next primordium will form in the same file, which suggests that LRP formation may deplete the local auxin concentration in the vascular pole, lowering the probability of successive LRP forming close by. In loblolly pine, there exists a stepwise decrease in auxin-induced rooting response from root, hypocotyl, to epicotyl in young seedlings. Competence to organize root meristems is normally confined to cells in pericycle or vascular parenchyma located centrifbgal to primary xylem poles. Auxin can induce cellular reorganization and cell division in all parts of the seedling, but does not always promote the organization of root meristems in epicotyls. Expansins were found to be auxin-inducible while searching for auxin-induced genes specific to adventitious rooting. To investigate the localization and time course of expansin expression during adventitious and lateral root formation, 25- day-old hypocotyls, 50-day-old hypocotyls and epicotyls, and 10-day-old primary roots were treated with auxin at different concentrations. Non-radioactive in situ localization of expansin mRNA using digoxigenin-labeled probes was used to compare expansin expression at the cellular level in different parts of the seedling. Expansin expression was observed in the auxin-treated hypocotyl and epicotyl tissue, but no or a very weak signal was observed in the untreated tissue. In addition, the auxin-induced increase of expansin mRNA in 25-day-old hypocotyls and primary roots was highly localized to the region of the parenchyma from which adventitious roots will form. In the lateral rooting zone of primary root, strong expression, without auxin treatment, occurred in the pericycle cells prior to lateral root primordium organization. Different patterns of expansin gene expression in response to auxin were found between hypocotyl and epicotyl cuttings. Relatively strong and localized expression in vascular parenchyma of hypocotyls contrasts with relatively weak and diffuse expression in cortex cells in epicotyl cuttings. A preliminary Western blot, detected the expansin protein in hypocotyls at both 24 and 48 h after auxin treatment but not in epicotyls. Collective results suggest auxin-induced expansin expression may play a role in both lateral and adventitious root formation in loblolly pine seedlings

Why reflection matters? : Reviewing the major forms of reflection and exploring their impacts on developing intercultural competence through study abroad programs

Due to the recent social expectation to educate global citizens and provide them with high English competence and intercultural communication competence, many colleges or universities have short- or long-term study abroad programs to provide students with opportunities to experience cultural differences and also improve their intercultural skills. Given that, if not interpreted appropriately, their cross-cultural experiences have a potential risk of reinforcing negative stereotypes against cultural“others”, and let students stay in their own culturally encapsulated worldviews, this paper reviews the major research after 2000 and onward to explore the role and efficiency of reflective learning for developing intercultural communication competence in study abroad programs. (105 words