RELATIONSHIP BETWEEN ANKLE MOBILITY AND GOLF SWING KINEMATICS

The purpose of this study was to examine the relationship between ankle mobility and golf swing kinematics. Sixteen male golfers volunteered to take part. Ankle mobility was assessed using the weight bearing lunge test and three-dimensional kinematic data from 10 golf drives were collected using a Vicon motion capture system. Pearson’s correlation coefficients were calculated to identify the relationship between ankle mobility and the rotations of four segments; pelvis, shoulders, upper arm and forearm. Large positive relationships were identified for the rotations of the pelvis (r = 0.670) and shoulders (r = 0.604) in the downswing as well as for peak rotational velocities of the pelvis (r = 0.553), shoulder (r = 0.571) and upper arm (r = 0.549) segments. These results indicate that improvements in ankle joint mobility are associated with superior rotations of segments further up the kinetic chain and that the weight bearing lunge test should be used as part of golf specific movement screening

Psychology: Examining the relationship between tuition payment and academic performance through GPA.

Abstract The purpose of this study is to evaluate the correlation between whether paying for college tuition can affect individual\u27s grade point average (GPA). In previous studies, research has shown that individuals tend to perform better academically when receiving financial help vs. Individuals funded by their parents (Faulk et al., 2012). Following previous studies, most of the studies found do not focus specifically on the correlation between financial dependency when paying for college and GPA. Our study strictly focuses on the relationship between those students who do not pay for college and those who do pay for college and how those effects someone\u27s GPA. We hypothesize that participants who pay for any part of their tuition themselves will have a higher GPA and spend more time studying than those who have third parties paying for their tuition, such as scholarships, family, and grants. The individuals involved in the sample are introductory psychology students who attend Belmont University and are participating for a class credit. Participants were asked to answer specific questions regarding financial status, GPA, time spent studying, and who is currently paying for their college tuition. Results will be presented at SURS

GSK-3α Promotes Oncogenic KRAS Function in Pancreatic Cancer via TAK1–TAB Stabilization and Regulation of Noncanonical NF-κB

Mutations in KRAS drive the oncogenic phenotype in a variety of tumors of epithelial origin. The NF-κB transcription factor pathway is important for oncogenic RAS to transform cells and to drive tumorigenesis in animal models. Recently TAK1, an upstream regulator of IKK, which controls canonical NF-κB, was shown to be important for chemoresistance in pancreatic cancer and for regulating KRAS+ colorectal cancer cell growth and survival. Here we show that KRAS+ upregulates GSK-3α leading to its interaction with TAK1 to stabilize the TAK1/TAB complex to promote IKK activity. Additionally, GSK-3α is required for promoting critical non-canonical NF-κB signaling in pancreatic cancer cells. Pharmacologic inhibition of GSK-3 suppresses growth of human pancreatic tumor explants, consistent with the loss of expression of oncogenic genes such as c-myc and TERT. These data identify GSK-3α as a key downstream effector of oncogenic KRAS via its ability to coordinately regulate distinct NF-κB signaling pathways

Risk-aware graph search with dynamic edge cost discovery

In this paper, we introduce a novel algorithm for incorporating uncertainty into lookahead planning. Our algorithm searches through connected graphs with uncertain edge costs represented by known probability distributions. As a robot moves through the graph, the true edge costs of adjacent edges are revealed to the planner prior to traversal. This locally revealed information allows the planner to improve performance by predicting the benefit of edge costs revealed in the future and updating the plan accordingly in an online manner. Our proposed algorithm, risk-aware graph search (RAGS), selects paths with high probability of yielding low costs based on the probability distributions of individual edge traversal costs. We analyze RAGS for its correctness and computational complexity and provide a bounding strategy to reduce its complexity. We then present results in an example search domain and report improved performance compared with traditional heuristic search techniques. Lastly, we implement the algorithm in both simulated missions and field trials using satellite imagery to demonstrate the benefits of risk-aware planning through uncertain terrain for low-flying unmanned aerial vehicles

Impacting Student Satisfaction, Engagement and Motivation in Online and Traditional Classrooms

The COVID-19 pandemic altered the higher education landscape in a number of ways. It, specifically, made the online/distance learning environment more prominent among institutions as 96% of colleges and universities in the U.S. shifted at least some of their course offerings online. The contrast of in-person and online teaching outcomes has become increasingly relevant due to these circumstances. Given the necessity and ubiquity of online classes, it is as important as ever to understand how to best implement an online course. The current project explored how student characteristics, instructor characteristics, and classroom characteristics in both traditional and online classes in the U.S. differed in terms of motivation, engagement, and satisfaction. Results indicate that only instructor rapport and credibility were perceived as important in online classes whereas perceived classroom interaction was important for in-person classes. Student reports of motivation, engagement, and satisfaction were higher for in-person classes than online classes

Copy number variation genotyping using family information

BACKGROUND: In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies. RESULTS: To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments. CONCLUSIONS: In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs

Copy number variation genotyping using family information

Abstract Background In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies. Results To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments. Conclusions In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs.http://deepblue.lib.umich.edu/bitstream/2027.42/112374/1/12859_2012_Article_5896.pd

Our Space: Being a Responsible Citizen of the Digital World

Our Space is a set of curricular materials designed to encourage high school students to reflect on the ethical dimensions of their participation in new media environments. Through role-playing activities and reflective exercises, students are asked to consider the ethical responsibilities of other people, and whether and how they behave ethically themselves online. These issues are raised in relation to five core themes that are highly relevant online: identity, privacy, authorship and ownership, credibility, and participation.Our Space was co-developed by The Good Play Project and Project New Media Literacies (established at MIT and now housed at University of Southern California's Annenberg School for Communications and Journalism). The Our Space collaboration grew out of a shared interest in fostering ethical thinking and conduct among young people when exercising new media skills

(Discrete) Almansi Type Decompositions: An umbral calculus framework based on osp(1∣2)\mathfrak{osp}(1|2) symmetries

We introduce the umbral calculus formalism for hypercomplex variables starting from the fact that the algebra of multivariate polynomials \BR[\underline{x}] shall be described in terms of the generators of the Weyl-Heisenberg algebra. The extension of \BR[\underline{x}] to the algebra of Clifford-valued polynomials $\mathcal{P}$ gives rise to an algebra of Clifford-valued operators whose canonical generators are isomorphic to the orthosymplectic Lie algebra $\mathfrak{osp}(1|2)$. This extension provides an effective framework in continuity and discreteness that allow us to establish an alternative formulation of Almansi decomposition in Clifford analysis (c.f. \cite{Ryan90,MR02,MAGU}) that corresponds to a meaningful generalization of Fischer decomposition for the subspaces $\ker (D')^k$. We will discuss afterwards how the symmetries of \mathfrak{sl}_2(\BR) (even part of $\mathfrak{osp}(1|2)$) are ubiquitous on the recent approach of \textsc{Render} (c.f. \cite{Render08}), showing that they can be interpreted in terms of the method of separation of variables for the Hamiltonian operator in quantum mechanics.Comment: Improved version of the Technical Report arXiv:0901.4691v1; accepted for publication @ Math. Meth. Appl. Sci http://www.mat.uc.pt/preprints/ps/p1054.pdf (Preliminary Report December 2010