Expanding Access to Dental Care for Patients on Suboxone

Those using Suboxone® for medication-assisted treatment for opioid dependence are at increased risk for poor oral health for a variety of reasons including lifestyle factors, effects of opioids and the direct impact of Suboxone® on the oral environment. Medication assisted addiction treatment programs do not regularly address these concerns. This project aims to educate patients about the importance of oral health, remind providers to screen for dental issues and make referrals for dental care and to promote oral health as an important aspect of well being in this vulnerable populationhttps://scholarworks.uvm.edu/fmclerk/1296/thumbnail.jp

Grammaticalization and phonological reidentification in White Hmong

The “dynamic coevolution of meaning and form” of Bybee et al. ( 1994 : 20) has been the subject of significant discussion as regards the languages of Mainland Southeast Asia. However, little work has focused on the mechanisms through which this coevolution occurs when it does surface in these languages. The current work considers phonological reidentification resulting from phonetic reduction in White Hmong (Hmong-Mien, Laos) involving four morphemes, ntshai/ntshe ‘maybe’, saib/seb ‘see if/whether; COMP.CFACT’, puag/pug ‘LOCL;INTS’, and niaj/nej ‘each, every’. These morphemes exhibit an alternation where a rime is phonologically reidentified in a manner consistent with typical phonetic underarticulation patterns, such that an exemplar-model approach (Pierrehumbert 2001 , inter alia) provides a straightforward explanation. Furthermore, the data show that the phonological reidentification patterns found in White Hmong exhibit parallels in other languages in the region, confirming that an areal approach to grammaticalization provides greater descriptive adequacy cross-linguistically as regards this phenomenon

The Hmong Medical Corpus: a biomedical corpus for a minority language

Biomedical communication is an area that increasingly benefits from natural language processing (NLP) work. Biomedical named entity recognition (NER) in particular provides a foundation for advanced NLP applications, such as automated medical question-answering and translation services. However, while a large body of biomedical documents are available in an array of languages, most work in biomedical NER remains in English, with the remainder in official national or regional languages. Minority languages so far remain an underexplored area. The Hmong language, a minority language with sizable populations in several countries and without official status anywhere, represents an exceptional challenge for effective communication in medical contexts. Taking advantage of the large number of government-produced medical information documents in Hmong, we have developed the first named entity-annotated biomedical corpus for a resource-poor minority language. The Hmong Medical Corpus contains 100,535 tokens with 4554 named entities (NEs) of three UMLS semantic types: diseases/syndromes, signs/symptoms, and body parts/organs/organ components. Furthermore, a subset of the corpus is annotated for word position and parts of speech, representing the first such gold-standard dataset publicly available for Hmong. The methodology presented provides a readily reproducible approach for the creation of biomedical NE-annotated corpora for other resource-poor languages

Re-envisioning the Resilient Individual: Reflections on the Science of Human Adaptation in Light of Paul Ricoeur and Julian of Norwich

This thesis engages the concept of resilience in light of the disciplines of social science, philosophy, and theology. Viewing resilience through these lenses presents the possibility of ‘re-envisioning’ human responses to adversity in ways that both question assumptions underlying resilience and corroborate current research. Social science data are foundational for understanding factors significant in human resilience to adversity, but may be further ‘thickened’ through narrative accounts of human being. Attention to the hermeneutic phenomenology of Paul Ricoeur provides insight into both the ‘surplus of meaning’ possible through narrative and human identity formed in relation to the Other. These take on added significance when understood in light of the narrative of the Christian Gospel that discloses meaning through relation to the self-giving God. Julian of Norwich serves as an example of the meaningfulness of the Gospel narrative, known through a personal experience of Divine love. Thus, the resilient individual may be re-envisioned through the transformative narrative of the Gospel. A renewed understanding of personhood situates responses to adversity within the meaningfulness of the ‘world’ projected by this narrative. Through participation in the narrative of the Gospel, the love of God engenders human resilience by creating meaning and connection in an environment of eschatological hope

MMAE Detection of Interference/Jamming and Spoofing in a DPGS-Aided Inertial System

Previous research at AFIT has resulted in the development of a DGPS-aided INS-based precision landing system (PLS) capable of meeting the FAA precision requirements for instrument landings. The susceptibility of DGPS transmissions to interference/jamming and spoofing must be addressed before DGPS may be used in such a safety-of-flight critical role. This thesis applies multiple model adaptive estimation (MMAE) techniques to the problem of detecting and identifying interference/jamming and spoofing failures in the DGPS signal. Such an MMAE is composed of a bank of parallel filters, each hypothesizing a different failure status, along with an evaluation of the current probability of each hypothesis being correct, to form a probability-weighted average output. Performance for a representative selection of navigation component cases is examined. For interference/jamming failures represented as increased measurement noise variance, results show that, because of the good FDI performance using MMAE, the blended navigation performance is essentially that of a single extended Kalman filter artificially informed of the actual interference noise variance. Standard MMAE is completely unable to detect spoofing failures (modelled as a bias or ramp offset signal directly added to the measurement). This thesis shows the development of a moving-bank pseudo-residual MMAE (PRMMAE) to detect and identify spoofing failures. Using the PRMMAE algorithm, the resulting navigation performance is equivalent to that of an extended Kalman filter operating in a no-fail environment