Adenoviral Gene Painting for Use in Cardiovascular Tissue Engineering

From the Washington University Senior Honors Thesis Abstracts (WUSHTA), Spring 2018. Published by the Office of Undergraduate Research. Joy Zalis Kiefer, Director of Undergraduate Research and Associate Dean in the College of Arts & Sciences; Lindsey Paunovich, Editor; Helen Human, Programs Manager and Assistant Dean in the College of Arts and Sciences Mentor: Stacey Rentschle

Corporal Punishment in Schools: An Infringement on Constitutional Freedoms

The doctrine of in loco parentis and the right of the teacher to inflict corporal punishment has a long history of acceptance. The doctrine itself has survived for centuries with no serious challenges to its validity or acceptability. The doctrine states that a teacher stands in the place of the parent and has the right to discipline his students, including the right to inflict corporal punishment for reasonable cause and in a reasonable manner. The basis of the doctrine is an assumption of the delegation of parental authority and an assumption of the correctness of the teacher\u27s actions. A direct result of this doctrine is the passage of statutes in several states granting the teacher the right to a reasonable use of corporal punishment. The effect of statutes of this nature is the infringement of two very basic fundamental rights: the right of a parent to bring up his child as he sees fit, and the right of a child to be free from invasions of the dignity and integrity of his person

An artificial neural network for estimating haplotype frequencies

The problem of estimating haplotype frequencies from population data has been considered by numerous investigators, resulting in a wide variety of possible algorithmic and statistical solutions. We propose a relatively unique approach that employs an artificial neural network (ANN) to predict the most likely haplotype frequencies from a sample of population genotype data. Through an innovative ANN design for mapping genotype patterns to diplotypes, we have produced a prototype that demonstrates the feasibility of this approach, with provisional results that correlate well with estimates produced by the expectation maximization algorithm for haplotype frequency estimation. Given the computational demands of estimating haplotype frequencies for 20 or more single-nucleotide polymorphisms, the ANN approach is promising because its design fits well with parallel computing architectures

Big data driven co-occurring evidence discovery in chronic obstructive pulmonary disease patients

© 2017, The Author(s). Background: Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung disease that affects airflow to the lungs. Discovering the co-occurrence of COPD with other diseases, symptoms, and medications is invaluable to medical staff. Building co-occurrence indexes and finding causal relationships with COPD can be difficult because often times disease prevalence within a population influences results. A method which can better separate occurrence within COPD patients from population prevalence would be desirable. Large hospital systems may potentially have tens of millions of patient records spanning decades of collection and a big data approach that is scalable is desirable. The presented method, Co-Occurring Evidence Discovery (COED), presents a methodology and framework to address these issues. Methods: Natural Language Processing methods are used to examine 64,371 deidentified clinical notes and discover associations between COPD and medical terms. Apache cTAKES is leveraged to annotate and structure clinical notes. Several extensions to cTAKES have been written to parallelize the annotation of large sets of clinical notes. A co-occurrence score is presented which can penalize scores based on term prevalence, as well as a baseline method traditionally used for finding co-occurrence. These scoring systems are implemented using Apache Spark. Dictionaries of ground truth terms for diseases, medications, and symptoms have been created using clinical domain knowledge. COED and baseline methods are compared using precision, recall, and F1 score. Results: The highest scoring diseases using COED are lung and respiratory diseases. In contrast, baseline methods for co-occurrence rank diseases with high population prevalence highest. Medications and symptoms evaluated with COED share similar results. When evaluated against ground truth dictionaries, the maximum improvements in recall for symptoms, diseases, and medications were 0.212, 0.130, and 0.174. The maximum improvements in precision for symptoms, diseases, and medications were 0.303, 0.333, and 0.180. Median increase in F1 score for symptoms, diseases, and medications were 38.1%, 23.0%, and 17.1%. A paired t-test was performed and F1 score increases were found to be statistically significant, where p < 0.01. Conclusion: Penalizing terms which are highly frequent in the corpus results in better precision and recall performance. Penalizing frequently occurring terms gives a better picture of the diseases, symptoms, and medications co-occurring with COPD. Using a mathematical and computational approach rather than purely expert driven approach, large dictionaries of COPD related terms can be assembled in a short amount of time

Teaching students how to tailor messages: lessons learned from a technical communication course

Indiana University-Purdue University Indianapolis (IUPUI)Tailoring messages is the process of customizing messages that are more relevant for the receiver, with the aim of improving the recipient’s engagement with and understanding about information in the message. Little research has been done to look at tailored messages in technical communication about healthcare technology, even though the use of technology in healthcare, and the complexity of that technology, continues to increase. Research was performed to investigate if students who plan to work in the healthcare technology field can demonstrate an understanding about tailoring messages and can tailor messages in their technical communication. A four-phase Action Research Cycle for inquiry into teaching and learning was used to modify course materials and analyze work for six assignments submitted by 14 students enrolled in Technical Communication for the Health Care Professions, TCM 38000, during the 2015 spring semester. Although TCM 38000 has always been open to students in other majors, the majority of students who take the course are in the Health Engineering Technology Management (HETM) program at Purdue’s School of Engineering and Technology on the campus of Indiana University Purdue University Indianapolis (IUPUI) in Indianapolis. Overall, the modifications made to TCM 38000 were successful in helping students begin to learn about tailoring messages and create messages tailored for a specific end-user in their technical communication developed for some course assignments. In their Reflections for a User Manual assignment, the majority of students explained that they used what they learned through course materials and discussions to reach beyond their learning and come up with techniques for tailoring messages on their own. Students used word choice, information content and role-play techniques to determine the end-user’s information needs and then to tailor messages in their manuals to address those needs. After reflecting on the results of the research, some course materials will be modified so that students can gain a deeper understanding about tailoring messages and can have more opportunities to practice writing tailored messages in course assignments. Research implications expand beyond the classroom into workplace training for organizations that have both technical and non-technical employees that must effectively communicate

Level-Up your Learning – Introducing a Framework for Gamified Educational Conversational Agents

Driven by circumstances like the global pandemic many learners and educators realize the importance and value of self-regulated digital learning. To better support self-regulated learning, conversational agents have become more relevant. Conversational agents can act as tutor or as learning mate for learners. Although conversational agents have potential to better support self-regulated learning processes, challenges exist requiring implications about how to make these interactions more engaging and supportive. This study discusses the value of gamified conversational learning chatbots that use game elements to engage learners to guide researchers and practitioners to design conversational agents that effectively motivate learners and provide self-regulated learning at the same time. Therefore, we propose a systematically developed framework for gamifying educational conversational agents and contribute to theory by consolidating several theories about games, digital learning, and conversational agents and support practitioners by providing implications about what to care about when gamifying conversational agents

Influence of Playing Standard on Upper- and Lower-Body Strength, Power, and Velocity Characteristics of Elite Rugby League Players

From MDPI via Jisc Publications RouterHistory: accepted 2019-04-11, pub-electronic 2019-04-17Publication status: PublishedBackground: To compare load–velocity and load–power relationships among first grade (n = 26, age 22.9 ± 4.3 years), academy (n = 23, age 17.1 ± 1.0 years), and scholarship (n = 16, age 15.4 ± 0.5 years) Super League rugby league players. Methods: Participants completed assessments of maximal upper- and lower-body strength (1RM) and peak velocity and power at 20, 40, 60, and 80 kg during bench press and squat exercises, in a randomised order. Results: Bench press and squat 1RM were highest for first grade players compared with other standards (effect size (ES) = −0.43 to −3.18). Peak velocities during bench and squat were greater in the higher playing standards (ES = −0.39 to −3.72 range), except for the squat at 20 and 40 kg. Peak power was higher in the better playing standards for all loads and exercises. For all three groups, velocity was correlated to optimal bench press power (r = 0.514 to 0.766), but only 1RM was related to optimal power (r = 0.635) in the scholarship players. Only squat 1RM in the academy was related to optimal squat power (r = 0.505). Conclusions: Peak velocity and power are key physical qualities to be developed that enable progression from junior elite rugby league to first grade level. Resistance training should emphasise both maximal strength and velocity components, in order to optimise upper- and lower-body power in professional rugby league players