University of Maryland, Baltimore County
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The Effects of Reading Recovery on the English Reading Development of Native Spanish-Speaking ESOL Students
No full textThis study investigated the sustained effects of Reading Recovery on the reading achievement of native Spanish-speaking English Language Learners (ELL) who received the one-to-one intervention while in the first grade. All native Spanish-speaking ELL students who received the Reading Recovery intervention during the three academic years from the fall of 2001 to the spring of 2004 were included in the study, including those students who were successful (discontinued), unsuccessful (recommended/exited), or received an incomplete program. Reading achievement data were gathered from end-of-intervention text reading levels in the first grade and from standardized test reading scores from the second and third grades. The technique of shift analysis (Lindman, 1968) was used to analyze data for each group of students to explore the degree to which reading achievement was sustained over time. It was found that all student groups showed improvement across time as 84% of the total population had moved out of the bottom quintile with regards to reading achievement by the end of the third grade. Discontinued students showed the highest level of achievement and the incomplete students showed the least growth. This study also examined the correlation between end-of-intervention text reading levels and scores on the standardized tests from the second and third grades. A positive correlation was found for all relationships explored except for one. A negative correlation was found between the text reading level and the NCE scores from the second-grade standardized test for students discontinued from Reading Recovery in the fall. However, of the eight relationships explored, only one correlation was found to be statistically significant (end-of-intervention text reading levels and second-grade standardized test scores for students discontinued in the spring)
Diffusion In Social Networks: A Model Of Member Diffusion Behavior
No full textAs more of our society participates online to perform everyday activities from shopping to socializing, the traditional methods of diffusion are changing. These changes are important, not only for individuals participating, but also for the organizations and businesses that are entering the online space. Information of new innovations and ideas spread through societies by means of interaction and communication (Rogers 1976). Understanding how diffusion functions online gives all the stake holders information that can be used to optimize their online experiences. Historically, diffusion followed orderly paths dictated by networks constructed from relationships of who had contact with whom (Bala and Goyal 1998). Today, the ability to reach others has shortcut the traditional paths. Creating communities comprised of relationship possibilities is only bounded by technologies. Diffusion in today's communities requires an understanding of the member behaviors that lead to the formation of the relationships that become the pathways enabling exchange. Based on fundamental theories about social networks and diffusion, this research proposes a Member Diffusion Behavior Model (MDB) that explains member diffusion behavior with three antecedents: Informal Sharing (IS), Promotion (Pr), and Persistent Conversation (PC). The findings of this research toile in three areas, the testing of the behavior model, the discovery of the behaviors from conversation structure, and the identification of the influence of seed members on diffusion. Hypotheses testing provides support for the IS and PC paths in the MDB model. Using a new structure based method, these two behaviors IS and PC are shown to be successfully discovered from the conversation structure. When the top defusing members identified using the structure metrics are used to seed the diffusion process, these members are found to be more effective than members selected using the traditional degree centrality method. This research contributes to the understanding of diffusion in social networks in several important ways. First, it provides a theoretical model to explain member diffusion behavior by integrating theories of diffusion and social networks. Second, it designs methods and develops metrics for measuring diffusion behavior in social networks by integrating social network analysis and information retrieval techniques. Third, it helps to gain insight into the diffusion process by exploring how members with influencing behaviors affect the network
Detection of unsafe actions in laparoscopic cholecystectomy videos
No full textLaparoscopic cholecystectomy has replaced open cholecystectomy as the first-choice of treatment for gallstones and inflammation of the gallbladder. The operation is minimally invasive and requires a camera to be inserted into patient's abdominal cavity. This limits the surgeon's view of the surgical site to the camera's projection. Due to the lack of tactile sensation and three dimensional visual feedback, there are possibilities of certain surgical injuries to the adjacent anatomical structures such as the cystic artery, common bile duct, duodenum or the small intestine. To address this challenge we have developed a system that analyzes images from the laparoscopic videos. It indicates the possibility of an injury to the cystic artery by automatically detecting the proximity of the surgical instruments with respect to the cystic artery. The system uses machine learning algorithm to classify images and warn surgeons against probable unsafe actions. The approach has been successful in classifying images with an accuracy of 90.14%
The Role of Elevated Dissolved versus Foliar Nitrogen on Leaf Litter Processing in Stream Ecosystems
No full textNutrient pollution can enrich waterways and riparian vegetation via assimilation and transformation into new biomass. Since leaf litter is the primary energy source to shaded streams and microbial immobilization of nutrients can increase its quality as a food resource, alterations could change ecosystem processing of detritus. My goal was to understand the relative importance of these nutrient sources to decomposition and the interactive role macroinvertebrates play in litter breakdown. I experimentally enriched Reed Canary grass (Phalaris arundinace
A Semantic Analysis of XML Schema Matching for B2B Systems Integration
No full textOne of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema matching, which is known to be costly and error-prone. Many automatic schema matching approaches have been proposed, but the challenge is still daunting because of the complexity of schemas and immaturity of technologies in semantic representation, measuring, and reasoning. The dissertation focuses on three challenging problems in schema matching. First, the existing approaches have often failed to sufficiently investigate and utilize semantic information imbedded in the hierarchical structure of the XML schemas. Secondly, due to synonyms and polysemies found in natural languages, the meaning of a data node in the schema cannot be determined solely by the words in its label. Thirdly, it is difficult to correctly identify the best set of matching pairs for all data nodes between two schemas. To overcome these problems, we propose new innovative approaches for XML schema matching, particularly applicable to XML schema integration and data transformation between heterogeneous e-Business systems. Our research supports two different tasks: integration task between two different component schemas; and transformation task between two business documents which confirm to different document schemas. For the integration task, we propose an approximate approach that produces the best matching candidates between global type components of two schemas, using their layer specific semantic similarities. For the transformation task, we propose another approximate approach that produces the best sets of matching pairs for all atomic nodes between two schemas, based on their linguistic and structural semantic similarities. We evaluate our approaches with the state of the art evaluation metrics and sample schema sets obtained from several e-Business standard organizations and e-Business system vendors. A variety of computer experiments have been conducted with encouraging results that show the proposed approaches are valuable for addressing difficulties in XML schema matching
On Gas Detection and Concentration Estimation via Mid-IR-based Gas Detection System Analysis Model
No full textDue to recent development in laser technology and infrared spectroscopy, Laser-based spectroscopy (LAS) has been used in a wide range of research and application fields. A particular application of interest is mid-IR laser-based gas detection systems for health and environment assessment. The NSF-ERC Mid-Infrared Technologies for Health and Environment (MIRTHE) project has engineers and researchers from different areas. As a participant in MIRTHE, we study the performance analysis and improvement possibilities of the integrated sensing system. Herein, we have improved the developed statistical analysis model, and then used our statistical analysis model for a generic mid-IR pulsed-laser gas detection system to predict trace gas detection and concentration estimation performance, and their sensitivity to system parameters. Based on PNNL (Pacific Northwest National Laboratory) data and the Beer-Lambert law, we defined three main spectral peaks of a trace gas for detecting target gas and evaluate 3-peak joint detection performance in terms of PD vs PFA. For concentration estimation we used the relationship between gas transmittance β, molar absorptivity ε, concentration c, the sample-mean measurement, xN, from the photo-detector, and number of samples, N, as the basis. Using the standard confidence interval method, we evaluated estimation reliability, and then analyzed estimation errors. Analytical gas detection and concentration estimation results are presented for 17 trace gases at 1 ppm and 1 ppb concentrations
Total Synthesis and Guanase Inhibition Studies of Azepinomycin and Its Analogs
No full textThe overall objectives of my dissertation project are to (a) provide a convenient and efficient total synthesis of the natural product azepinomycin, a known transition state analog inhibitor of the enzyme guanase, (b) separate and characterize the two enantiomers of azepinomycin, which have never been done before, (c) synthesize both heterocyclic and nucleoside analogs of azepinomycin, (d) determine the Ki of azepinomycin against an isolated mammalian guanase, which has never been done before, (e) assess the Ki's of the mentioned synthetic analogs, and (f) assess the effect of translocation of the 6-OH group of azepinomycin on the enzyme activity. Guanine deaminase (guanase) is an important enzyme involved in the nucleotide metabolism, and therefore, an important target in anticancer, antiviral, and antibacterial therapy. There have been reports of abnormally high levels of serum guanase activity in patients with liver diseases, and with multiple sclerosis. Increased levels of guanase have also been detected in cancerous kidney and breast tissue cells. These observations suggest that a potent guanase inhibitor is necessary for exploring the biochemical mechanisms of the above metabolic disorders as well to understand the specific physiological role played by guanase, and not to mention its potential therapeutic use in treating these disorders. Guanase catalyzes the hydrolysis of guanine to xanthine through an intermediate which contains a quaternary carbon at the site of hydrolysis, with a geminal hydroxy/amino functionality. While many studies on guanase inhibition have been reported in the literature, a potent guanase inhibitor with a submicromolar or nanomolar Ki has yet to be discovered. The natural product azepinomycin, a known transition state analog inhibitor of guanase, has so far been studied only in tissue culture systems. So, while its IC50 value is known, the Ki of azepinomycin against guanase has never been determined biochemically against an isolated pure enzyme. As a step forward in exploring this potent guanase inhibitor, an efficient and convenient synthetic strategy has been developed to access not only azepinomycin but also its two diastereomeric nucleoside analogs. In addition, some [5:7]-fused ring expanded heterocycles containing the imidazo[4,5-e][1,4]-diazepine-5,8-dione ring system, with appropriate substituents mimicking the transition state of the enzyme-catalyzed reaction, have also been successfully synthesized. The biochemical investigations were done to assess their Ki values of all target compounds against a mammalian guanase
Dynamic Portfolio Optimization using Sequential Quadratic Programming
No full textIn Financial Mathematics, classical Markowitz Portfolio theory provides a strategy for optimizing return on a portfolio by considering only the mean and variance of returns. However, recent theoretical and empirical studies show that it has many limitations, some of which are that it assumes a one shot allocation and Gaussianity of returns. We describe a more realistic approach which incorporates probabilities of both large gains and large losses and which is not confined to a particular type of distribution. We use a new approach in the sense that we use probabilities for the constraint and objective functions. Thus, instead of looking only at the expected return, we maximize the probability of the reward, while keeping the probability of loss small. We desire that the portfolio values a predetermined Vu and are averse to portfolio values below a predetermined value Vl. Thus, we maximize the probability of a portfolio value being above Vu subject to the constraint that the probability of portfolio value being below Vl does not exceed a given threshold Ɛ. We introduce and verify a method to optimize the return using sequential quadratic programming. We solve the optimization problem over one period using MATLAB routine fmincon. This approach involves making certain approximations. We verify the validity of these approximations using brute force calculations. We compute the expected values of objective and constraint functions by taking the sample means of large samples generated by Monte Carlo simulations. We expand our model to multi period timeframe by first considering the two period optimization problem. We use dynamic portfolio allocation, fmincon, Monte Carlo simulations, and cubic spline interpolation so solve the optimization problem. To solve the two period problem, a grid of possible portfolio returns after the first period is used. For each of the grid values then the portfolio optimization problem over one period is solved. This then enables us to solve the overall two period problem. When the two period problem is unconstrained, our approach finds a (local) optimal solution. When constraints are introduced, our method is only suboptimal. We test our approach on different types of distributions, including the lognormal, mixture of lognormals and Pareto. While we limit ourselves to two time periods and three assets, comparisons with brute force calculations suggest that our approach using fmincon produces accurate results. Our approach has been developed in a manner that it can be applied to arbitrary number of assets as well as multiple time periods
The Experience of Benzodiazepine Use and Perceived Dependence among Older Women: A Cultural Analysis
No full textExamining the use of prescription medications such as benzodiazepines (BZDs) and their abuse potential in older populations is important in light of the current statistics: older adults comprise about 13% of the population, but are prescribed approximately one-third of all medications. Despite some important research in recent years, the understanding of older BZD-using women has been neglected. This dissertation addressed the use of BZDs by women age 65 and older. The specific aims of this dissertation are to 1) qualitatively examine the experience, meaning, and interpretation of BZD use and 2) determine how culture has a role in the differential experience of BZD use in later life in a sample of community-dwelling older women. Methods Results Conclusion <</ This dissertation provides a unique look into the medication use worlds of older community-dwelling women and helps to answer previously unaddressed questions about this population. Future research is needed in several areas, including determining how to define BZD dependence in older populations and also how socially isolated older adults and persons burdened by caregiving responsibilities use psychotropic medications as coping tools
The Association of Inattention and Children's Math Development: A Longitudinal Study
No full textThis study examined the association of inattention and children's math development as children progress from elementary into middle school. Of particular interest was whether children who are consistently rated by their teachers as frequently inattentive exhibit different patterns of growth in math fact retrieval, calculation, and conceptual knowledge of place value than children who are seldom inattentive. Math tests were administered to children in third through sixth grades, and behavior rating scales to assess inattention were completed by their teachers in second through fifth grades. Growth in math skills was analyzed using both zero-order and partial correlations and latent growth curve modeling. Results indicated that children's inattention in second grade was related to lower levels of fact retrieval and calculation performance in third grade. However, with one exception, inattention was not found to be associated with year-to-year growth or overall growth in any of the three math skills evaluated. The study also investigated third grade predictors of sixth grade calculation skill. Findings indicated that children's third grade inattention was as predictive of their sixth grade calculation scores as were the third grade measures of fact retrieval, calculation skill, and conceptual knowledge of place value. In analyses conducted to screen specifically for later math calculation difficulties, fact retrieval emerged as a ""good"" screening test for the sample of children evaluated. This information has the potential for aiding the development of appropriate intervention techniques