Description: Atomic resolution images of hot-tungsten filament chemical-vapor-deposition (CVD) grown epitaxial diamond (100) films obtained in ultrahigh vacuum (UHV) with a scanning tunneling microscope (STM) are reported. A (2x1) dimer surface reconstruction and amorphous atomic regions were observed on the hydrogen terminated (100) surface. The (2x1) unit cell was measured to be 0.51"0.01 x 0.25"0.01 nm2. The amorphous regions were identified as amorphous carbon. After CVD growth, the surface of the epitaxial films was amorphous at the atomic scale. After 2 minutes of exposure to atomic hydrogen at 30 Torr and the sample temperature at 500° C, the surface was observed to consist of amorphous regions and (2x1) dimer reconstructed regions. After 5 minutes of exposure to atomic hydrogen, the surface was observed to consist mostly of (2x1) dimer reconstructed regions. These observations support a recent model for CVD diamond growth that is based on an amorphous carbon layer that is etched or converted to diamond by atomic hydrogen. With further exposure to atomic hydrogen at 500° C, etch pits were observed in the shape of inverted pyramids with {111} oriented sides. The temperature dependence of atomic hydrogen etching of the diamond (100) surface was also investigated using UHV STM, and ...

Description: The purpose of this research project is to examine the educational and job-training opportunities offered in the Lower Rio Grande Valley, and how the skills acquired from these programs assimilate with the job opportunities available in the area. Specifically, we will look at the counties of Cameron, Hidalgo, Starr, and Willacy. The central hypothesis of this project is that the Rio Grande Valley in its efforts for a more highly trained workforce may actually be enabling its workforce to seek better employment opportunities in other areas.

Description: A number of studies have been conducted on the attrition rates of undergraduate and graduate students. However, the body of knowledge concerning attrition for doctoral students, especially those who have attained the level of “all but dissertation” (ABD), is limited. The purpose of this research was to examine retention and attrition factors of doctoral candidates from a typical Higher Education Doctoral Program (Research II Public Institution) who were admitted to candidacy from 1991 through July 2000. Participation of the subject population was limited to those who had attained the level of ABD--those who had previously fulfilled the residency, coursework, foreign language or tool-subject requirements, and successfully completed the comprehensive/qualifying exams. This population included current ABDs, previously attrited ABDs, and graduates of the degree program. The research study was qualitative and intended to identify the effect of specific, predetermined factors that may have influenced or affected the progress of current, previous, and graduated students towards the doctoral degree in higher education. This study obtained responses to questions from the questionnaire/survey instrument concerning factors that affected program completion or attrition. Students had the opportunity to elaborate on factors from their dissertation, advisement, and personal, financial, and employment experiences that affected their ability ...

Description: The phenomenal growth of Information Technology requires us to elicit, store and maintain huge volumes of data. Analyzing this data for various purposes is becoming increasingly important. Data mining consists of applying data analysis and discovery algorithms that under acceptable computational efficiency limitations, produce a particular enumeration of patterns over the data. We present two techniques based on using Logic programming tools for data mining. Data mining analyzes data by extracting patterns which describe its structure and discovers co-relations in the form of rules. We distinguish analysis methods as visual and non-visual and present one application of each. We explain that our focus on the field of Logic Programming makes some of the very complex tasks related to Web based data mining and dynamic content generation, simple and easy to implement in a uniform framework.

Description: This study addresses the issue of household disaster preparedness. This work contributes two elements to disaster research. The first contribution improve the knowledge of the factors that affect household disaster preparedness. The review of literature yielded three categories of variables that can jointly explain household disaster preparedness: household structure, demographics, and risk-perception factors. In this study 19 variables compose these factors. A second contribution constitutes a theoretical exploration of the concept of disaster preparedness. In this work, four different constructs of disaster preparedness were tested. These constructs include material preparedness, preparedness activities, a combined index, and a weighted and combined index. The study presents the logic and methodology of the index construction and validation. The data used in this study came from households in the Montreal Urban Community (MUC) in Canada. A random sample of 1,003 English- and French-speaking heads of households adequately represents the 1.8 million persons within the MUC. An independent survey firm conducted the interviews in 1996. Results show that the weighted combined household disaster preparedness index constitutes the best construct to represent the concepts under study. Study results also reveal that risk-perception variables (attitudinal factors) offered the strongest explanatory power. Household structure and demographic variables collectively ...