HIV/STI AND TEEN PREGNANCY PREVENTION WITHIN MCLENNAN COUNTY TEXAS

In response to the Center for Disease Control and Prevention (CDC) funding announcement, the McLennan County Health Department proposes to implement Be Proud! Be Responsible!, an evidence-based HIV/STI and teen pregnancy prevention program into the pre-existing health curriculum of the sixth grade classes within the county. With the highest rates of chlamydia and gonorrhea within the state of Texas, and $7 million per year of teen pregnancy related costs spent in Waco, Texas alone, this intervention aims to increase HIV/STI knowledge, increase positive perceptions of safe sexual behaviors, increase parent-student communication about safe sexual behaviors, prolong first sexual initiation, and reduce frequency of risky sexual behaviors, thus contributing to a decrease in the incidence of STI rates and teen pregnancy within the county. In implementing the curriculum in to the health classes for sixth graders, we hope to educate the participating students before they have initiated sexual activity. Under the leadership of Program Director Kayla Storrs, Director of the Sexual and Reproductive Health Department within the McLennan County Health Department, and Program Coordinator, Cynthia Estrada, Associate Director of the Sexual and Reproductive Health Department, the program will be integrated into the pre-exiting curriculum of six intervention schools within the county and six control schools will be used to help evaluate the program effectiveness. Upon completion of program implementation, based on evaluation results, the program will then be implemented across the county

Content addressable memory project

A parameterized version of the tree processor was designed and tested (by simulation). The leaf processor design is 90 percent complete. We expect to complete and test a combination of tree and leaf cell designs in the next period. Work is proceeding on algorithms for the computer aided manufacturing (CAM), and once the design is complete we will begin simulating algorithms for large problems. The following topics are covered: (1) the practical implementation of content addressable memory; (2) design of a LEAF cell for the Rutgers CAM architecture; (3) a circuit design tool user's manual; and (4) design and analysis of efficient hierarchical interconnection networks

Love\u27s Touch

https://digitalcommons.library.umaine.edu/mmb-me/1129/thumbnail.jp

Intraprofessional, team-based treatment planning for oral health students in the comprehensive care clinic

published_or_final_versio

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments.

Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs' performance compares to that of non-computational "conceptual" models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., "eye") and category labels (e.g., "animal") for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features other than object parts perform relatively poorly, perhaps because DNNs more comprehensively capture the colors, textures and contours which matter to human object perception. However, categorical models outperform DNNs, suggesting that further work may be needed to bring high-level semantic representations in DNNs closer to those extracted by humans. Modern DNNs explain similarity judgments remarkably well considering they were not trained on this task, and are promising models for many aspects of human cognition

Spectroscopic Observations of New Oort Cloud Comet 2006 VZ13 and Four Other Comets

Spectral data are presented for comets 2006 VZ13 (LINEAR), 2006 K4 (NEAT), 2006 OF2 (Broughton), 2P/Encke, and 93P/Lovas I, obtained with the Cerro-Tololo Inter-American Observatory 1.5-m telescope in August 2007. Comet 2006 VZ13 is a new Oort cloud comet and shows strong lines of CN (3880 angstroms), the Swan band sequence for C_2 (4740, 5160, and 5630 angstroms), C_3 (4056 angstroms), and other faint species. Lines are also identified in the spectra of the other comets. Flux measurements of the CN, C_2 (Delta v = +1,0), and C_3 lines are recorded for each comet and production rates and ratios are derived. When considering the comets as a group, there is a correlation of C_2 and C_3 production with CN, but there is no conclusive evidence that the production rate ratios depend on heliocentric distance. The continuum is also measured, and the dust production and dust-to-gas ratios are calculated. There is a general trend, for the group of comets, between the dust-to-gas ratio and heliocentric distance, but it does not depend on dynamical age or class. Comet 2006 VZ13 is determined to be in the carbon-depleted (or Tempel 1 type) class.Comment: 8 pages, 6 figures, 6 tables; Accepted by MNRA

Fiscal Year 2003

This report discusses President Bush's 2002 requests for new funding and additional authority to provide assistance to Colombia and six regional neighbors in a continuation of the Andean Regional Initiative (ARI) launched in 2001

Andean Regional Initiative (ARI): FY2002 Assistance for Colombia and Neighbors

This report discusses the Andean Regional Initiative (ARI), implemented by the Bush Administration in 2001 to provide economic and counter-narcotics assistance for Colombia and regional neighbors. The report discusses the goals of the ARI, as well as related appropriations

Fiscal Year 2003

This report discusses President Bush's 2002 requests for new funding and additional authority to provide assistance to Colombia and six regional neighbors in a continuation of the Andean Regional Initiative (ARI) launched in 2001

Andean Regional Initiative (ARI): FY2002 Assistance for Colombia and Neighbors

This report discusses the Andean Regional Initiative (ARI), implemented by the Bush Administration in 2001 to provide economic and counter-narcotics assistance for Colombia and regional neighbors. The report discusses the goals of the ARI, as well as related appropriations