Fast Algorithms Using Minimal Data Structures for Common Topological Relationships in Large, Irregularly-spaced Topographic Data Sets

Digital terrain models (DTM) typically contain large numbers of postings, from hundreds of thousands to billions. Many algorithms that run on DTMs require topological knowledge of the postings, such as finding nearest neighbors, finding the posting closest to a chosen location, etc. If the postings are arranged irregu- larly, topological information is costly to compute and to store. This paper offers a practical approach to organizing and searching irregularly-space data sets by presenting a collection of efficient algorithms (O(N),O(lgN)) that compute important topological relationships with only a simple supporting data structure. These relationships include finding the postings within a window, locating the posting nearest a point of interest, finding the neighborhood of postings nearest a point of interest, and ordering the neighborhood counter-clockwise. These algorithms depend only on two sorted arrays of two-element tuples, holding a planimetric coordinate and an integer identification number indicating which posting the coordinate belongs to. There is one array for each planimetric coordinate (eastings and northings). These two arrays cost minimal overhead to create and store but permit the data to remain arranged irregularly.

The Value of Waiting: Foreign Direct Investment with Uncertainty and Imperfect Local Knowledge

This paper examines the role of uncertainty and imperfect local knowledge in foreign direct investment. The main idea comes from the literature on investment under uncertainty, such as Pindyck (1991) and Dixit and Pindyck (1994). We empirically test .the value of waiting. with a dataset on foreign direct investment (FDI). Many factors (e.g., political and economic regulations) as well as uncertainty and the risks due to imperfect local knowledge, determine the attractiveness of FDI. The uncertainty and irreversibility of FDI links the time interval between permission and actual execution of such FDI with explanatory variables, including information on foreign (home) countries and domestic industries. Common factors, such as regulatory change and external shocks, may affect the uncertainty when foreign investors make irreversible FDI decisions. We derive testable hypotheses from models of investment under uncertainty to determine those possible factors that induce delays in FDI, using Korean data over 1962 to 2001.

Trends in health information seeking among cancer and non-cancer adults between 2003 and 2005: A descriptive analysis of Health Information National Trends Survey (HINTS) data

Cancer is the second leading cause of death in the United States. With the advent of new technologies, changes in health care delivery, and multiplicity of provider types that patients must see, cancer care management has become increasingly complex. The availability of cancer health information has been shown to help cancer patients cope with the management and effects of their cancers. As a result, more cancer patients are using the internet to find resources that can aid in decision-making and recovery. ^ The Health Information National Trends Survey (HINTS) is a nationally representative survey designed to collect information about the experiences of cancer and non-cancer adults with health information sources. The HINTS survey focused on both conventional sources as well as newer technologies, particularly the internet. This study is a descriptive analysis of the HINTS 2003 and HINTS 2005 survey data. The purpose of the research is to explore the general trends in health information seeking and use by US adults, and especially by cancer patients. ^ From 2003 to 2005, internet use for various health-related activities appears to have increased among adults with and without cancer. Differences were found between the groups in the general trust in information media, particularly the internet. Non-cancer respondents tended to have greater trust in information media than cancer respondents. ^ The latter portion of this work examined characteristics of HINTS respondents that were thought to be relevant to how much trust individuals placed in the internet as a source of health information. Trust in health information from the internet was significantly greater among younger adults, higher-earning households, internet users, online seekers of health or cancer information, and those who found online cancer information useful. ^

The relationship between risk perception and ethnicity as an explanation for late stage skin cancer diagnosis in Black and Hispanic populations: An analysis using data from the 2005 Health Information and National Trends Survey

Objective. The purpose of this study was to determine the relationship between ethnicity and skin cancer risk perception while controlling for other risk factors: education, gender, age, access to healthcare, family history of skin cancer, fear, and worry. ^ Methods. This study utilized the Health Information National Trends Survey (HINTS) dataset, a nationally representative sample of 5,586 individuals 18 years of age or older. One third of the respondents were chosen at random and asked questions involving skin cancer. Analysis was based on questions that identified skin cancer risk perception, fear of finding skin cancer, and frequency of worry about skin cancer and a variety of sociodemographic factors. ^ Results. Ethnicity had a significant impact on risk perception scores while controlling for other risk factors. Other risk factors that also had a significant impact on risk perception scores included family history of skin cancer, age, and worry. ^

Smoke free restaurant ordinance, compliance with the regulation to reduce exposure to environmental tobacco smoke while dining at local restaurants in San Antonio, Texas

This study is a secondary analysis of a survey developed by Dr. Jimmy Perkins and administered by San Antonio/Bexar County Metropolitan Health District. The survey was developed subsequent to the implementation of the city smoking ordinance effective January 1, 2004. The survey had a multi-purpose plan to establish the number of restaurants having smoke free status prior to and following the ordinance, determine compliance as it relates to a necessary smoking section and proper signage, and expose the rationale for restaurants to become smoke free. The data resulting from the survey was presented to the San Antonio/Bexar County Metropolitan Health District. The summary presented the types of establishments surveyed, smoking status of the establishment, reasons for the establishment becoming smoke free, compliance with smoking sections, compliance with signage requirements, awareness of ordinance, and chain status of the establishment. ^ The results of this study display the relationships among the variables previously mentioned. The following relationships have been examined and the outcomes have determined whether each is significant. After careful analysis, knowledge translates into compliance with signage regulations, which then translate into ordinance compliance. Size does matter as it relates to an establishment's number of employees and seating capacity. The smaller the establishment the more likely the establishment is to have become smoke free before the ordinance went into effect. Restaurants, rather than fast food establishments most commonly cited their reason for becoming smoke free was to comply with the ordinance and only ten percent of restaurants gave policy as the main reason for becoming smoke free. ^ This study is important for public health because the negative health effects of environmental tobacco smoke (ETS) are still an overwhelming problem in the United States (3). ETS is a Known Human Group A Carcinogen (5). The Environmental Protection Agency (EPA) has estimated that around 3,000 non-smoking Americans die every year from lung cancer caused by ETS (6). This information illustrates the importance of providing smoke free establishments, especially to non-smoking patrons. ^

A project to improve the information seeking skills and increase the use of evidence-based research in public health practice

The ability of public health practitioners (PHPs) to work efficiently and effectively is negatively impacted by their lack of knowledge of the broad range of evidence-based practice information resources and tools that can be utilized to guide them in their development of health policies and programs. This project, a three-hour continuing education hands-on workshop with supporting resources, was designed to increase knowledge and skills of these resources. The workshop was presented as a pre-conference continuing education program for the Texas Public Health Association (TPHA) 2008 Annual Conference. Topics included: identification of evidence-based practice resources to aid in the development of policies and programs; identification of sources of publicly available data; utilization of data for community assessments; and accessing and searching the literature through a collection of databases available to all citizens of Texas. Supplemental resources included a blog that served as a gateway to the resources explored during the presentation, a community assessment workbook that incorporates both Healthy People 2010 objectives and links to reliable sources of data, and handouts providing additional instruction on the use of the resources covered during the workshop.^ Before- and after-workshop surveys based on Kirkpatrick's 4-level model of evaluation and the Theory of Planned Behavior were administered. Of the questions related to the trainer, the workshop, and the usefulness of the workshop, participants gave "Good" to "Excellent" responses to all one question. Confidence levels overall increased a statistically significant amount; measurements of attitude, social norms, and control showed no significant differences before and after the workshop. Lastly, participants indicated they were likely to use resources shown during the workshop within a one to three month time period on average. ^ The workshop and creation of supplemental resources served as a pilot for a funded project that will be continued with the development and delivery of four 4-week long webinar-based training sessions to be completed by December 2008. ^

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^