An integrated functional mapping and source localization platform for brain research

The premise of this dissertation is to create a highly integrated platform that combines the most current recording technologies for brain research through the development of new algorithms for three-dimensional (3D) functional mapping and 3D source localization. The recording modalities that were integrated include: Electroencephalography (EEG), Optical Topographic Maps (OTM), Magnetic Resonance Imaging (MRI), and Diffusion Tensor Imaging (DTI). This work can be divided into two parts: The first part involves the integration of OTM with MRI, where the topographic maps are mapped to both the skull and cortical surface of the brain. This integration process is made possible through the development of new algorithms that determine the probes location on the MRI head model and warping the 2D topographic maps onto the 3D MRI head/brain model. Dynamic changes of the brain activation can be visualized on the MRI head model through a graphical user interface. The second part of this research involves augmenting a fiber tracking system, by adding the ability to integrate the source localization results generated by commercial software named Curry. This task involved registering the EEG electrodes and the dipole results to the MRI data. Such Integration will allow the visualization of fiber tracts, along with the source of the EEG, in a 3D transparent brain structure. The research findings of this dissertation were tested and validated through the participation of patients from Miami Children Hospital (MCH). Such an integrated platform presented to the medical professionals in the form of a user-friendly graphical interface is viewed as a major contribution of this dissertation. It should be emphasized that there are two main aspects to this research endeavor: (1) if a dipole could be situated in time at its different positions, its trajectory may reveal additional information on the extent and nature of the brain malfunction; (2) situating such a dipole trajectory with respect to the fiber tracks could ensure the preservation of these fiber tracks (axons) during surgical interventions, preserving as a consequence these parts of the brain that are responsible for information transmission.

Three essays on labor liberalization and its effects on world economy

This dissertation consists of three theoretical essays on immigration, international trade and political economy. The first two essays analyze the political economy of immigration in developed countries. The third essay explores new ground on the effects of labor liberalization in developing countries. Trade economists have witnessed remarkable methodological developments in mathematical and game theoretical models during the last seventy years. This dissertation benefits from these advances to analyze economic issues related to immigration. The first essay applies a long run general equilibrium trade model similar to Krugman (1980), and blends it with the median voter ala-Mayer (1984) framework. The second essay uses a short run general equilibrium specific factor trade model similar to Jones (1975) and incorporates it with the median voter model similar to Benhabib (1997). The third essay employs a five stage game theoretical approach similar to Vogel (2007) and solves it by the method of backward induction. The first essay shows that labor liberalization is more likely to come about in societies that have more taste for varieties, and that workers and capital owners could share the same positive stance toward labor liberalization. In a dynamic model, it demonstrates that the median voter is willing to accept fewer immigrants in the first period in order to preserve her domestic political influence in the second period threatened by the naturalization of these immigrants. The second essay shows that the liberalization of labor depends on the host country's stock and distribution of capital, and the number of groups of skilled workers within each country. I demonstrate that the more types of goods both countries produce, the more liberal the host country is toward immigration. The third essay proposes a theory of free movement of goods and labor between two economies with imperfect labor contracts. The heart of my analysis lies in the determinants of talent development where individuals' decisions to emigrate are related to the fixed costs of emigration. Finally, free trade and labor affect income via an indirect effect on individuals' incentives to invest in the skill levels and a direct effect on the prices of goods.

Contemporary aspects of dividends: Before and during the financial crisis

The number of dividend paying firms has been on the decline since the popularity of stock repurchases in the 1980s, and the recent financial crisis has brought about a wave of dividend reductions and omissions. This dissertation examined the U.S. firms and American Depository Receipts that are listed on the U.S. equity exchanges according to their dividend paying history in the previous twelve quarters. While accounting for the state of the economy, the firm’s size, profitability, earned equity, and growth opportunities, it determines whether or not the firm will pay a dividend in the next quarter. It also examined the likelihood of a dividend change. Further, returns of firms were examined according to their dividend paying history and the state of the economy using the Fama-French three-factor model. Using forward, backward, and step-wise selection logistic regressions, the results show that firms with a history of regular and uninterrupted dividend payments are likely to continue to pay dividends, while firms that do not have a history of regular dividend payments are not likely to begin to pay dividends or continue to do so. The results of a set of generalized polytomous logistic regressions imply that dividend paying firms are more likely to reduce dividend payments during economic expansions, as opposed to recessions. Also the analysis of returns using the Fama-French three factor model reveals that dividend paying firms are earning significant abnormal positive returns. As a special case, a similar analysis of dividend payment and dividend change was applied to American Depository Receipts that trade on the NYSE, NASDAQ, and AMEX exchanges and are issued by the Bank of New York Mellon. Returns of American Depository Receipts were examined using the Fama-French two-factor model for international firms. The results of the generalized polytomous logistic regression analyses indicate that dividend paying status and economic conditions are also important for dividend level change of American Depository Receipts, and Fama-French two-factor regressions alone do not adequately explain returns for these securities.

A comprehensive study of bankruptcy prediction: Accounting ratios, market variables, and microstructure

Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

Risk factors and associations for hepatitis C infection among Hispanic/Latino intravenous drug users in Miami-Dade County, Florida

Hepatitis C infection (HCV) continues to disproportionately affect Hispanics/Latinos in the United States. Hispanic/Latino intravenous drug users (IDUs), because of their risky injection and sexual behaviors, are prone to HCV infection and rapid transmission of the virus to others via several routes. With a prevalence rate of approximately 75% among IDUs, it is imperative that transmission of HCV be prevented in this population. This study aims to examine the associations between demographic, injection and sexual risk factors to HCV infection in a group Hispanic/Latino IDUs in Miami-Dade County, Florida. Preliminary unadjusted results in this sample reveal that age (OR=4.592, p=0.004), weekly injection (OR=5.171, p=0.000), daily injection frequency (OR=3.856, p=0.000) and use of a dirty needle (OR=2.320, p= 0.006) were all significantly associated with HCV infection. Being born outside the U.S. was significantly negatively associated with HCV infection (OR=0.349, p=0.004). Additionally, having two or more sex partners in the past three months (OR=0.472, p=0.014) was negatively associated with HCV infection. After adjusting for all other variables, older age (AOR=7.470, p=0.006), weekly injection (AOR=3.238, p=0.007) and daily injection frequency (AOR=2.625, p=0.010) were all significantly associated with HCV infection. Being born outside the U.S. (AOR=0.369, p=0.019) was a significant protective factor for HCV infection, along with having two or more sex partners in the past three months (AOR=0.481, p=0.037). When analyzing the significant variables in a backward regression model, having 2 or more sex partners in the past three months was not significant at the p

Are marginalized women being left behind? A population-based study of institutional deliveries in Karnataka, India

Background While India has made significant progress in reducing maternal mortality, attaining further declines will require increased skilled birth attendance and institutional delivery among marginalized and difficult to reach populations. Methods A population-based survey was carried out among 16 randomly selected rural villages in rural Mysore District in Karnataka, India between August and September 2008. All households in selected villages were enumerated and women with children 6 years of age or younger underwent an interviewer-administered questionnaire on antenatal care and institutional delivery. Results Institutional deliveries in rural areas of Mysore District increased from 51% to 70% between 2002 and 2008. While increasing numbers of women were accessing antenatal care and delivering in hospitals, large disparities were found in uptake of these services among different castes. Mothers belonging to general castes were almost twice as likely to have an institutional birth as compared to scheduled castes and tribes. Mothers belonging to other backward caste or general castes had 1.8 times higher odds (95% CI: 1.21, 2.89) of having an institutional delivery as compared to scheduled castes and tribes. In multivariable analysis, which adjusted for inter- and intra-village variance, Below Poverty Line status, caste, and receiving antenatal care were all associated with institutional delivery. Conclusion The results of the study suggest that while the Indian Government has made significant progress in increasing antenatal care and institutional deliveries among rural populations, further success in lowering maternal mortality will likely hinge on the success of NRHM programs focused on serving marginalized groups. Health interventions which target SC/ST may also have to address both perceived and actual stigma and discrimination, in addition to providing needed services. Strategies for overcoming these barriers may include sensitization of healthcare workers, targeted health education and outreach, and culturally appropriate community-level interventions. Addressing the needs of these communities will be critical to achieving Millennium Development Goal Five by 2015.

Algorithms for efficient transaction management and consistent queries in client -server semantic object-oriented parallel databases

Large read-only or read-write transactions with a large read set and a small write set constitute an important class of transactions used in such applications as data mining, data warehousing, statistical applications, and report generators. Such transactions are best supported with optimistic concurrency, because locking of large amounts of data for extended periods of time is not an acceptable solution. The abort rate in regular optimistic concurrency algorithms increases exponentially with the size of the transaction. The algorithm proposed in this dissertation solves this problem by using a new transaction scheduling technique that allows a large transaction to commit safely with significantly greater probability that can exceed several orders of magnitude versus regular optimistic concurrency algorithms. A performance simulation study and a formal proof of serializability and external consistency of the proposed algorithm are also presented.^ This dissertation also proposes a new query optimization technique (lazy queries). Lazy Queries is an adaptive query execution scheme which optimizes itself as the query runs. Lazy queries can be used to find an intersection of sub-queries in a very efficient way, which does not require full execution of large sub-queries nor does it require any statistical knowledge about the data.^ An efficient optimistic concurrency control algorithm used in a massively parallel B-tree with variable-length keys is introduced. B-trees with variable-length keys can be effectively used in a variety of database types. In particular, we show how such a B-tree was used in our implementation of a semantic object-oriented DBMS. The concurrency control algorithm uses semantically safe optimistic virtual "locks" that achieve very fine granularity in conflict detection. This algorithm ensures serializability and external consistency by using logical clocks and backward validation of transactional queries. A formal proof of correctness of the proposed algorithm is also presented. ^

An examination of Bernard Connor's The History of Poland (1698) and its depiction of the political, religious, and cultural history of the Polish-Lithuanian commonwealth

Connor was an Irish-born member of seventeenth-century English medical society who made an impact on medicine through his use of anatomy. This forward-thinking scientist also worked as a court physician for the Polish king John III Sobieski (1629- 1696) and published a history of that country. This thesis will examine Bernard Connor's 1698 publication The History of Poland to show that the Commonwealth was considered a vision of a progressive European parliamentary government that could serve as a model for a struggling English parliamentary government, thus supporting Larry Wolff and Maria Todorova's vision of the later eighteenth-century creation of the idea of a backward "eastern Europe."

Risk Factors and Associations for Hepatitis C Infection among Hispanic/Latino Intravenous Drug Users in Miami-Dade County, Florida

Hepatitis C infection (HCV) continues to disproportionately affect Hispanics/Latinos in the United States. Hispanic/Latino intravenous drug users (IDUs), because of their risky injection and sexual behaviors, are prone to HCV infection and rapid transmission of the virus to others via several routes. With a prevalence rate of approximately 75% among IDUs, it is imperative that transmission of HCV be prevented in this population. This study aims to examine the associations between demographic, injection and sexual risk factors to HCV infection in a group Hispanic/Latino IDUs in Miami-Dade County, Florida. Preliminary unadjusted results in this sample reveal that age (OR=4.592, p=0.004), weekly injection (OR=5.171, p=0.000), daily injection frequency (OR=3.856, p=0.000) and use of a dirty needle (OR=2.320, p= 0.006) were all significantly associated with HCV infection. Being born outside the U.S. was significantly negatively associated with HCV infection (OR=0.349, p=0.004). Additionally, having two or more sex partners in the past three months (OR=0.472, p=0.014) was negatively associated with HCV infection. After adjusting for all other variables, older age (AOR=7.470, p=0.006), weekly injection (AOR=3.238, p=0.007) and daily injection frequency (AOR=2.625, p=0.010) were all significantly associated with HCV infection. Being born outside the U.S. (AOR=0.369, p=0.019) was a significant protective factor for HCV infection, along with having two or more sex partners in the past three months (AOR=0.481, p=0.037). When analyzing the significant variables in a backward regression model, having 2 or more sex partners in the past three months was not significant at the p

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.