Best Selling Books by Hoang Nguyen

"This timely book delves into the intricate relationship between tourism and poverty with a specific focus on nature conservation areas, using case studies of island economies in a developed country, Japan, and a developing one, Vietnam. This volume is a pivotal resource for scholars in tourism, particularly those focused on teaching and researching tourism geographies and sustainable development. It holds particular significance for scholars examining emerging nations across Asia"--

Planarians, free-living flatworms, are able to regenerate complete individuals from miniscule fragments. However, little is known about the effects of regeneration on aging, or senescence, in planarians. Using an asexual strain of the planarian, Schmidtea mediterranea, we studied long-term differences in aging between the two fragments of fission, the anterior (head) and posterior (tail), by tracking fecundity and viability. Fecundity was quantified by measuring patterns in the time interval between fissions. Viability was tracked as survival rates over time. We created separate lines of successive heads and successive tails for observation. We present the first demonstration that the head and tail products of fission are not identical with respect to aging. Lines of successive heads showed aging through reduced fecundity over time; and all lines ultimately died out. Conversely, lines of successive tails showed no aging based on uniform fecundity and no recorded deaths. Furthermore, we found that all tails were equally rejuvenated regardless of the age of the original planarian at the time of fission. Thus, asexual fission can act as a mechanism for rejuvenation in tails at the cost of aging in heads.

This dissertation contains three essays exploring how macroeconomists can identify and estimate dynamic causal effects in models where researchers have doubts about identifying assumptions. Chapter 1 proposes a new Markov Chain Monte Carlo algorithm to estimate a sign-restricted structural vector autoregression on time series that are subject to regime shifts. My approach can incorporate useful prior information about both model parameters and hidden states while transparently imposing sign restrictions. I illustrate my method by revisiting the literature on asymmetric effects of conventional monetary policy during recessions and expansions. My evidence suggests that previous empirical research found asymmetric effects by questionable identification schemes and neglecting changes in the variances of structural shocks. I find little difference in the structural parameters, and thus I do not find evidence of asymmetry. Chapter 2 studies the method of instrumental variables in set-identified models. I develop a proxy structural vector autoregression in which prior information from both theory and the empirical literature is incorporated about signs and magnitudes of certain parameters and equilibrium impacts. I use my method to investigate the relevance and validity of three popular instruments for monetary policy shocks, developed by Romer and Romer (2004), Sims and Zha (2006), and Smets and Wouters (2007). I find that all of them are strongly relevant but only that of Smets and Wouters is valid. Furthermore, the empirical analysis demonstrates that my framework can combine information from a relevant and valid instrument with prior information about sign restrictions to improve inference about structural impulse-response functions. Chapter 3 develops new methods to study dynamic causal effects in a data-rich environment. Current development in high-dimensional statistics fails to address the main interest of economists: causal inference with credible assumptions. I first review the literature on high-dimensional linear regression models and dynamic factor models. Then, I develop several new Bayesian numerical algorithms that combine the techniques in high-dimensional statistics with recent advances in dynamic causal inference. In particular, I discuss how to make causal statements from a high-dimensional structural model when researchers have doubts about identifying assumptions. Finally, I extend those algorithms to the case of Markov-switching models to accommodate nonlinearities in economic time series.

Hair occlusion often causes automated melanoma diagnostic systems to fail. We present a new method to segment hair in dermoscopic images. First, all possible dark and light hairs are amplified without prejudice with a universal matched filtering kernel. We then process the filter response with a novel tracing algorithm to get a raw hair mask. This raw mask is skeletonized to contain only the centerlines of all the possible hairs. Then the centerlines are verified by applying a model checker on the response and the original images. If a centerline indeed corresponds to a hair, the hair is reconstructed; otherwise it is rejected. The result is a clean hair mask which can be used to disocclude hair. Application on real dermoscopic images yields good results for thick hair of varying colours. The algorithm also performs well on skin images with a mixture of both dark and light hair.

Financing issues play essential roles in the survival and development of entrepreneurial firms. The current study, employing the bibliometric analysis of 6,903 articles from 1970 to 2019, extracted from Web of Science database, aims to provide an overview of the discipline''s landscape and major scientific domains to facilitate scientific development within the field. Entrepreneurial finance is a young and growing field with exponential growth in the number of publications (with 19.54% per year) and rising collaboration tendency among authors. Journal of Business Venturing is the most prestigious journal, while Sustainability is noteworthy for its rapid contribution to the field. We also note a sign of Western ideological homogeneity from the collaboration networks and lists of top authors, institutions, and countries. Besides, using keyword co-occurrence analysis, seven major research domains are identified: “venture capital”, “crowdfunding”, “SMEs finance”, “social entrepreneurship finance”, “financial risk”, “microfinance”, and “human-social-financial capital”. Based on these findings, we raise the concern of lacking diversity in entrepreneurial finance research and provide several recommendations for future potential research directions.

Alzheimer''s Disease (AD) is the most common form of dementia. Chronic stress has been suggested to influence the progression of AD. Moreover, corticotropin-releasing factor (CRF) signaling in AD has been shown to be upregulated by stress and influence AD pathology such as amyloid-beta (A[beta]) accumulation. In rodent models, similar AD-related pathology and cognitive impairments are produced when exposed to either stress or exogenous CRF. Previous studies have shown that PSAPP (AD) mice treated with CRFR1 antagonist (R121919) resulted in reduced A[beta] accumulation and improvements in behavioral tests. However, the influence of stress while underdoing drug treatment is unknown. In this comparison study, we subjected cohorts of AD mice to R121919 in the presence and absence of restraint stress treatment. AD mice were aged to 6 and 12 months to investigate the pre-clinical and mature timepoints of AD pathology. Daily drug/vehicle treatment began at 2 months of age. Stress for the 6 and 12-month groups started at 2 and 6 months, respectively. Overall, R121919 treated AD mice resulted in a significant reduction of A[beta] levels. Additionally, it was shown that chronic restraint stress exacerbated A[beta] levels. This study suggests that CRFR1 antagonist treatment provides a potential preventative and disease-modifying therapy for populations subjugated to stress and at risk for AD development. Our data provides an important relationship between stress signaling in the CNS and the neuropathology of AD.

Economists, industry practitioners, and government officials have failed to observe the significance of mortgage fraud as an inherent problem related to the subprime mortgage crisis. Relying on intensive interviews with 23 subjects, previously and currently employed in the subprime lending industry, government reports, media accounts, and a variety of secondary sources, this study traces the exponential growth of mortgage fraud to loose underwriting standards, alternative loan products, and inadequate regulation and regulatory oversight of the subprime mortgage industry. The research findings detail and describe various types of financial crimes that constitute a modern form of mortgage fraud; unlike their traditional counterpart, contemporary mortgage fraud contain elements of both fraud for profit and fraud for property. Various types and patterns of mortgage fraud - "data manipulation," "data fabrication," and "concerted ignorance"--Completely altered the function of the subprime industry. Toward this end, the industry operated not only to provide bad loans to bad credit borrowers but also to provide bad loans to bad credit borrowers who fully lacked the ability to repay the loans. The social and economic implications of fraud are also explored in light of the findings. From a policy perspective, future fraud prevention and intervention strategies should incorporate a multi-faceted approach that includes strict underwriting standards, regulatory oversight, accountability, and mandatory continuous education for loan practitioners.

In the paper we consider the optimal portfolio choice problem under parameter uncertainty when the covariance matrix of asset returns is singular. Very useful stochastic representations are deduced for the characteristics of the expected utility optimal portfolio. Using these stochastic representations, we derive the moments of higher order of the estimated expected return and the estimated variance of the expected utility optimal portfolio. Another line of applications leads to their asymptotic distributions obtained in the high-dimensional setting. Via a simulation study, it is shown that the derived high-dimensional asymptotic distributions provide good approximations of the exact ones even for moderate sample sizes.