Bayesian Model-building in Phylogenetics

DNA sequencing costs have decreased dramatically over recent decades, resulting in a flood of phylogenetic information available to researchers. While it is often assumed that additional data will lead to more accurate conclusions, it also raises a number of problems for phylogeneticists, including mundane computational issues such as data management and complex statistical problems such as obtaining a single species tree from multiple conflicting gene trees. Developing new methods to make better use of existing data and probe the causes of conflicting signal will be necessary to confidently resolve phylogenies in the genomic era. Here, we examine two current problems in statistical phylogenetics and attempt to address them in a Bayesian framework. The first problem involves inflated tree lengths in Bayesian phylogenies, which can be an order of magnitude longer than maximum likelihood estimates. We developed EmpPrior, a program which queries TreeBASE for datasets similar to the focal data, then estimates parameters from each dataset to inform priors on the focal data. This approach greatly improves the tree length credible intervals in four exemplar datasets and, when combined with other approaches such as the use of a compound Dirichlet prior on tree length, can nearly eliminate the problem of inflated trees. The second problem involves incongruence between morphological and molecular phylogenies in squamates. Here, we use posterior prediction with inferential test statistics to investigate whether systematic error may be biasing inference in the molecular data. While we detected some model violation in most of the 44 genes, the genes with the most model violation were more distant from the molecular phylogeny. This suggests that model violation is not a major source of error in the molecular data. Hence, the source of incongruence between the molecular and morphological squamate topologies remains unknown. In both problems, we found that incorporating tools such as informed priors and posterior prediction from Bayesian statistical literature into phylogenetic analyses can improve results and help uncover why different datasets lead to conflicting topologies. As phylogenetic datasets continue to grow, using methodological best practices will only become more important if we want to have confidence in our conclusions

Topological Interpretations of GPT-3

This is an experiential study of investigating a consistent method for deriving the correlation between sentence vector and semantic meaning of a sentence. We first used three state-of-the-art word/sentence embedding methods including GPT-3, Word2Vec, and Sentence-BERT, to embed plain text sentence strings into high dimensional spaces. Then we compute the pairwise distance between any possible combination of two sentence vectors in an embedding space and map them into a matrix. Based on each distance matrix, we compute the correlation of distances of a sentence vector with respect to the other sentence vectors in an embedding space. Then we compute the correlation of each pair of the distance matrices. We observed correlations of the same sentence in different embedding spaces and correlations of different sentences in the same embedding space. These observations are consistent with our hypothesis and take us to the next stage.Comment: 70 page

Adaptive locomotion of artificial microswimmers

Bacteria can exploit mechanics to display remarkable plasticity in response to locally changing physical and chemical conditions. Compliant structures play a striking role in their taxis behavior, specifically for navigation inside complex and structured environments. Bioinspired mechanisms with rationally designed architectures capable of large, nonlinear deformation present opportunities for introducing autonomy into engineered small-scale devices. This work analyzes the effect of hydrodynamic forces and rheology of local surroundings on swimming at low Reynolds number, identifies the challenges and benefits of utilizing elastohydrodynamic coupling in locomotion, and further develops a suite of machinery for building untethered microrobots with self-regulated mobility. We demonstrate that coupling the structural and magnetic properties of artificial microswimmers with the dynamic properties of the fluid leads to adaptive locomotion in the absence of on-board sensors

Relationship between social support, quality of life, and Th2 cytokines in a biobehavioral cancer survivorship trial.

ObjectiveBenefits of social support (SS) during cancer survivorship are complex. This study examines change in SS over time in cervical cancer (CXCA) survivors who have completed definitive treatment and how changing SS impacts quality of life (QOL) and T-helper type 2 (Th2) cytokines.MethodsWe conducted a randomized trial in 204 CXCA survivors to test if psychosocial telephone counseling (PTC) could improve QOL compared to usual care (UC). Although PTC did not target SS, data were collected at baseline, 4 and 9 months post-enrollment using the Medical Outcomes Survey Social Support scale. Biospecimens were collected to investigate associations with patient-reported outcomes. Data were analyzed using multivariate linear models and stepwise regression.ResultsParticipants' mean age was 43. PTC participants experienced increasing SS compared to UC at 4 months (PTC-UC = 5.1; p = 0.055) and 9 months (PTC-UC = 6.0; p = 0.046). Higher baseline SS and increasing SS were independently associated with improved QOL at 4 and 9 months after adjusting for patient characteristics (p < 0.05). Differences between study arms were not statistically significant. Improvements in QOL at 4 months were observed with increases in emotional/informational and tangible SS. Increasing SS predicted significant longitudinal decreases in IL-4 and IL-13 at 4 months that were larger in the PTC arm (interactions p = 0.041 and p = 0.057, respectively).ConclusionImproved SS was significantly associated with improved QOL independent of patient characteristics and study arm. Decreasing Th2 cytokines with increasing SS and QOL are consistent with a biobehavioral paradigm in which modulation of the chronic stress response is associated with shifts in immune stance