Experimental analysis of soil and dust stabilizers for controlling displacement of contaminated soils by wind tunnel experiments

During the remediation of burial grounds at the US Department of Energy's (DOE's) Hanford Site in Washington State, the dispersion of contaminated soil particles and dust is an issue that is faced by site workers on a daily basis. This contamination problem is even more of a concern when one takes into account the semi-arid characteristics of the region where the site is located. To mitigate this problem, workers at the site use a variety of engineered methods to minimize the dispersion of contaminated soil and dust (i.e. use of water and/or suppression agents that stabilizes the soil prior to soil excavation, segregation, and removal activities). A primary contributor to the dispersion of contaminated soil and dust is wind soil erosion. The erosion process occurs when the wind speed exceeds a certain threshold value which depends on a number of factors including wind force loading, particle size, surface soil moisture, and the geometry of the soil. Thus under these circumstances, the mobility of contaminated soil and generation and dispersion of particulate matter are significantly influenced by these parameters. This dependence of soil and dust movement on threshold shear velocity, fixative dilution and/or application rates, soil moisture content, and soil geometry were studied for Hanford's sandy soil through a series of wind tunnel experiments, laboratory experiments and theoretical analysis. In addition, the behavior of plutonium (Pu) powder contamination in the soil was studied by introducing a Pu simulant (cerium oxide). The results showed that soil dispersion and PM10 concentrations decreased with increasing soil moisture. Also, it was shown that the mobility of the soil was affected by increasing wind velocity. It was demonstrated that the use of fixative products greatly decreased the amount of soil and PM10 concentrations when exposed to varying wind conditions. In addition, it was shown that geometry of the soil sample affected the velocity profile and calculation of roughness surface coefficient when comparing round and flat soil samples. Finally, threshold shear velocities were calculated for soil with flat surface and their dependency on surface soil moisture was demonstrated. A theoretical framework was developed to explain these dependencies.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Comparative Analysis of State and Non-State Higher Educational Institutions in Terms of their Adaptation to New Societal Conditions in Post-Soviet Russia

The present paper investigates post-Soviet non-state and state higher educational institutions in terms of students’ perceptions of school curriculum, quality of teaching, available educational resources and overall organization in their higher educational institutions.

Timeshare Owner Preferences - An Analysis of Program and Service Relationships during Recessionary Times

Since the 1970s various industry studies have indicated that the vacation ownership industry has enjoyed unprecedented growth in unit sales, resort growth, and the number of owners (American Resort Devleopment Association [ARDA], 2007; ARDA, 2009a; ARDA, 2009b). However, due to the recent economic downturn these growth metrics are no longer obtainable. This external impact has caused developers to retrench and therefore reflect upon their existing product and service offerings, financial metrics, and consumer markets (ARDA, 2010a; ARDA 2010b). The crux of these findings indicates that the industry has shifted to maintaining and enhancing product and service offerings as a reaction to changing economic conditions. The findings reported in the body of this manuscript represent product and service preferences as collected from a random data pull of their existing ownership base. The study also revealed current preferences of timeshare owners with relation to services provided and products/amenities offered. Management implications and limitations of the current study are discussed.

Quality of life and application of the transtheoretical model to diabetes self -management behaviors in older adults with type 2 diabetes

One in five adults 65 years and older has diabetes. Coping with diabetes is a lifelong task, and much of the responsibility for managing the disease falls upon the individual. Reports of non-adherence to recommended treatments are high. Understanding the additive impact of diabetes on quality of life issues is important. The purpose of this study was to investigate the quality of life and diabetes self-management behaviors in ethnically diverse older adults with type 2 diabetes. The SF-12v2 was used to measure physical and mental health quality of life. Scores were compared to general, age sub-groups, and diabetes-specific norms. The Transtheoretical Model (TTM) was applied to assess perceived versus actual behavior for three diabetes self-management tasks: dietary management, medication management, and blood glucose self-monitoring. Dietary intake and hemoglobin A1c values were measured as outcome variables. Utilizing a cross-sectional research design, participants were recruited from Elderly Nutrition Program congregate meal sites (n = 148, mean age 75). ^ Results showed that mean scores of the SF-12v2 were significantly lower in the study sample than the general norms for physical health (p < .001), mental health (p < .01), age sub-group norms (p < .05), and diabetes-specific norms for physical health (p < .001). A multiple regression analysis found that adherence to an exercise plan was significantly associated with better physical health (p < .001). Transtheoretical Model multiple regression analyses explained 68% of the variance for % Kcal from fat, 41% for fiber, 70% for % Kcal from carbohydrate, and 7% for hemoglobin A 1c values. Significant associations were found between TTM stage of change and dietary fiber intake (p < .01). Other significant associations related to diet included gender (p < .01), ethnicity (p < .05), employment (p < .05), type of insurance (p < .05), adherence to an exercise plan (p < .05), number of doctor visits/year ( p < .01), and physical health (p < .05). Significant associations were found between hemoglobin A1c values and age ( p < .05), being non-Hispanic Black (p < .01), income (p < .01), and eye problems (p < .05). ^ The study highlights the importance of the beneficial effects of exercise on quality of life issues. Furthermore, application of the Transtheoretical Model in conjunction with an assessment of dietary intake may be valuable in helping individuals make lifestyle changes. ^

The relationship of managers' self -reported leadership practices and their spirituality

The role of spirituality in leadership in business and other organizations has gained growing recognition. The purpose of this study was to explore the relationship between spirituality and nine selected transformational leadership practices. Community leaders (N = 138) in business, education, and other professions who were graduates of a 10-week leadership program, Leadership Fort Lauderdale, from 1994 to 2004 completed the Spirituality Assessment Scale (SAS), the Leadership Practices Inventory (LPI), and four transformational leadership items of the Multifactor Leadership Questionnaire (MLQ). ^ The predictor variables were participants' scores on the LPI and MLQ. The criterion variable was their score on the SAS. Stepwise multiple regression analysis was used to test the hypothesis: Is there a combination of nine selected transformational leadership practices that would account for a significant portion of the variance of each of two spirituality measures? The Definitive and Correlated dimensions and Total spirituality score of the SAS were used in the analysis. ^ Results showed that two of the LPI leadership practices were significantly related to spirituality. The variable Inspiring a Shared Vision accounted for 10% of the variance of the SAS Definitive dimension. The variable Encouraging the Heart accounted for 30% of the variance of the Correlated dimension. For the Total spirituality score, two models were revealed. In the first model, Encouraging the Heart accounted for 28% of the variance of the total spirituality score. In the second model, Encouraging the Heart and Inspiring a Shared Vision together accounted for 31% of the total spirituality score. None of the transformational leadership practices from the MLQ were significantly related to spirituality. ^ The data partially support the hypothesis: two of the nine leadership variables did in combination correlate with leaders' spirituality. The results also support at least a partial relationship between spirituality and certain transformational leadership practices among leaders in various spheres, such as education, business, and other professions. ^

The Life and Work of Severo Sarduy: A Conversation with Mercedes Sarduy and Catalina Quesada

This flyer promotes the event "The Life and Work of Severo Sarduy: A Conversation with Mercedes Sarduy and Catalina Quesada".

Text analytics of social media: Sentiment analysis, event detection and summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. ^ Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. ^ In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data. ^

A content analysis of food and nutrition television advertisements

Television (TV) reaches more people than any other medium which makes it an important source of health information. Since TV ads often offer information obliquely, this study investigated implied health messages found in food and nutrition TV ads. The goals were to determine the proportion of food and nutrition ads among all TV advertising and to use content analysis to identify their implied messages and health claims. A randomly selected sample of TV ads were collected over a 28-day period beginning May 8, 1987. The sample contained 3547 ads; 725 (20%) were food-related. All were analyzed. About 10% of food-related TV ads contained a health claim. Twenty-five representative ads of the 725 food ads were also reviewed by 10 dietitians to test the reliability of the instrument. Although the dietitians agreed upon whether a health claim existed in a televised food ad, their agreement was poor when evaluating the accuracy of the claim. The number of food-related ads dropped significantly on Saturday, but the number of alcohol ads rose sharply on Saturday and Sunday. Snack ads were shown more often on Thursday, but snack commercials were also numerous on Saturday morning and afternoon, as were cereal ads. Ads for snack foods accounted for the greatest proportion of ads (20%) while fast food accounted for only 7%. Alcohol constituted about 9% of all food and nutrition ads.

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Regional flood frequency analysis for Newfoundland and Labrador using the L-Moments index-flood method

The L-moments based index-flood procedure had been successfully applied for Regional Flood Frequency Analysis (RFFA) for the Island of Newfoundland in 2002 using data up to 1998. This thesis, however, considered both Labrador and the Island of Newfoundland using the L-Moments index-flood method with flood data up to 2013. For Labrador, the homogeneity test showed that Labrador can be treated as a single homogeneous region and the generalized extreme value (GEV) was found to be more robust than any other frequency distributions. The drainage area (DA) is the only significant variable for estimating the index-flood at ungauged sites in Labrador. In previous studies, the Island of Newfoundland has been considered as four homogeneous regions (A,B,C and D) as well as two Water Survey of Canada's Y and Z sub-regions. Homogeneous regions based on Y and Z was found to provide more accurate quantile estimates than those based on four homogeneous regions. Goodness-of-fit test results showed that the generalized extreme value (GEV) distribution is most suitable for the sub-regions; however, the three-parameter lognormal (LN3) gave a better performance in terms of robustness. The best fitting regional frequency distribution from 2002 has now been updated with the latest flood data, but quantile estimates with the new data were not very different from the previous study. Overall, in terms of quantile estimation, in both Labrador and the Island of Newfoundland, the index-flood procedure based on L-moments is highly recommended as it provided consistent and more accurate result than other techniques such as the regression on quantile technique that is currently used by the government.

Medical Assistance in Dying in Canada: An Ethical Analysis of Conscientious and Religious Objections

Article

Religious Liberty Laws, Religious Practices, and Discrimination

A set of clarificatory questions I wish to address are: What qualifies as a religious belief? Can corporations have such beliefs? What qualifies a practice as a religious practice? What religious practices are/should be protected by RFRA laws?

Introducing molaR: a New R Package for Quantitative Topographic Analysis of Teeth (and Other Topographic Surfaces)

© 2016 Springer Science+Business Media New YorkResearchers studying mammalian dentitions from functional and adaptive perspectives increasingly have moved towards using dental topography measures that can be estimated from 3D surface scans, which do not require identification of specific homologous landmarks. Here we present molaR, a new R package designed to assist researchers in calculating four commonly used topographic measures: Dirichlet Normal Energy (DNE), Relief Index (RFI), Orientation Patch Count (OPC), and Orientation Patch Count Rotated (OPCR) from surface scans of teeth, enabling a unified application of these informative new metrics. In addition to providing topographic measuring tools, molaR has complimentary plotting functions enabling highly customizable visualization of results. This article gives a detailed description of the DNE measure, walks researchers through installing, operating, and troubleshooting molaR and its functions, and gives an example of a simple comparison that measured teeth of the primates Alouatta and Pithecia in molaR and other available software packages. molaR is a free and open source software extension, which can be found at the doi:10.13140/RG.2.1.3563.4961(molaR v. 2.0) as well as on the Internet repository CRAN, which stores R packages.