4 resultados para base-age invariant dynamic equation

em Duke University


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A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

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How do infants learn word meanings? Research has established the impact of both parent and child behaviors on vocabulary development, however the processes and mechanisms underlying these relationships are still not fully understood. Much existing literature focuses on direct paths to word learning, demonstrating that parent speech and child gesture use are powerful predictors of later vocabulary. However, an additional body of research indicates that these relationships don’t always replicate, particularly when assessed in different populations, contexts, or developmental periods.

The current study examines the relationships between infant gesture, parent speech, and infant vocabulary over the course of the second year (10-22 months of age). Through the use of detailed coding of dyadic mother-child play interactions and a combination of quantitative and qualitative data analytic methods, the process of communicative development was explored. Findings reveal non-linear patterns of growth in both parent speech content and child gesture use. Analyses of contingency in dyadic interactions reveal that children are active contributors to communicative engagement through their use of gestures, shaping the type of input they receive from parents, which in turn influences child vocabulary acquisition. Recommendations for future studies and the use of nuanced methodologies to assess changes in the dynamic system of dyadic communication are discussed.

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Nucleic acids (DNA and RNA) play essential roles in the central dogma of biology for the storage and transfer of genetic information. The unique chemical and conformational structures of nucleic acids – the double helix composed of complementary Watson-Crick base pairs, provide the structural basis to carry out their biological functions. DNA double helix can dynamically accommodate Watson-Crick and Hoogsteen base-pairing, in which the purine base is flipped by ~180° degrees to adopt syn rather than anti conformation as in Watson-Crick base pairs. There is growing evidence that Hoogsteen base pairs play important roles in DNA replication, recognition, damage or mispair accommodation and repair. Here, we constructed a database for existing Hoogsteen base pairs in DNA duplexes by a structure-based survey from the Protein Data Bank, and structural analyses based on the resulted Hoogsteen structures revealed that Hoogsteen base pairs occur in a wide variety of biological contexts and can induce DNA kinking towards the major groove. As there were documented difficulties in modeling Hoogsteen or Watson-Crick by crystallography, we collaborated with the Richardsons’ lab and identified potential Hoogsteen base pairs that were mis-modeled as Watson-Crick base pairs which suggested that Hoogsteen can be more prevalent than it was thought to be. We developed solution NMR method combined with the site-specific isotope labeling to characterize the formation of, or conformational exchange with Hoogsteen base pairs in large DNA-protein complexes under solution conditions, in the absence of the crystal packing force. We showed that there are enhanced chemical exchange, potentially between Watson-Crick and Hoogsteen, at a sharp kink site in the complex formed by DNA and the Integration Host Factor protein. In stark contrast to B-form DNA, we found that Hoogsteen base pairs are strongly disfavored in A-form RNA duplex. Chemical modifications N1-methyl adenosine and N1-methyl guanosine that block Watson-Crick base-pairing, can be absorbed as Hoogsteen base pairs in DNA, but rather potently destabilized A-form RNA and caused helix melting. The intrinsic instability of Hoogsteen base pairs in A-form RNA endows the N1-methylation as a functioning post-transcriptional modification that was known to facilitate RNA folding, translation and potentially play roles in the epitranscriptome. On the other hand, the dynamic property of DNA that can accommodate Hoogsteen base pairs could be critical to maintaining the genome stability.

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INTRODUCTION: Upper airway measurement can be important for the diagnosis of breathing disorders. Acoustic reflection (AR) is an accepted tool for studying the airway. Our objective was to investigate the differences between cone-beam computed tomography (CBCT) and AR in calculating airway volumes and areas. METHODS: Subjects with prescribed CBCT images as part of their records were also asked to have AR performed. A total of 59 subjects (mean age, 15 ± 3.8 years) had their upper airway (5 areas) measured from CBCT images, acoustic rhinometry, and acoustic pharyngometry. Volumes and minimal cross-sectional areas were extracted and compared with software. RESULTS: Intraclass correlation on 20 randomly selected subjects, remeasured 2 weeks apart, showed high reliability (r >0.77). Means of total nasal volume were significantly different between the 2 methods (P = 0.035), but anterior nasal volume and minimal cross-sectional area showed no differences (P = 0.532 and P = 0.066, respectively). Pharyngeal volume showed significant differences (P = 0.01) with high correlation (r = 0.755), whereas pharyngeal minimal cross-sectional area showed no differences (P = 0.109). The pharyngeal volume difference may not be considered clinically significant, since it is 758 mm3 for measurements showing means of 11,000 ± 4000 mm3. CONCLUSIONS: CBCT is an accurate method for measuring anterior nasal volume, nasal minimal cross-sectional area, pharyngeal volume, and pharyngeal minimal cross-sectional area.