Symphony No. 4 "Immortal"

My fourth symphony, Immortal, was conceived as I viewed the busts of Roman Emperors on display at the University of Oklahoma’s Fred Jones Museum of Art. All of the figures are representative of people who are remembered and looked upon as legendary figures from history. The name of this exhibit of Roman Emperor busts, “Immortales” translates to “Immortals.” The idea of being an immortal hero or a legend is something that fascinates me, and led to the decision of writing a symphony based on the concept of forging an immortal legend. This document is a symphony presented in the traditional four movement format. The first movement is written as a dual-binary form with an additional development section in the middle. The second movement is far slower, and focuses on the contour of the harp ostinato heard at the beginning of the movement. The third movement, written as a modern version of a classical scherzo, is fast-paced, playful, and serves as a break from the more serious nature of the rest of the work. The fourth and final movement begins with a brass fanfare derived from the fanfare in movement one, and is written as an amalgamation of the previous three movements, with some of the melodic content becoming more prominent than others as the movement progresses. The heart of the entire work is between rehearsals M1 and O1. In this section, there is an extended, slow-moving ostinato that slowly reveals the original source material from movement two, rehearsal Q. This brings the listener to a sense of closure. The brass fanfare is heard again, signaling the end of movement IV, as well as the entire work. Symphony 4 concludes with the sound of the anvil continuing to forge a vision of the future

Symphony No. 5: "Westward Journey"

This document contains the score to Symphony No. 5: Westward Journey, an original composition for symphony orchestra consisting of four movements, lasting approximately twenty-eight minutes. This work is rooted in the Western European symphonic tradition utilizing a four-movement structure, which I chose in order to carry forward the symphonic tradition, as well as to allow each movement to feature different aspects of the entirety of my compositional catalogue. The lyricism and limited tonality of Movement II stem from my earliest compositions; Movement IV uses my typical strategy of re-contextualizing all previously introduced melodic and motivic material; Movement III alludes to much of my chamber music in tone and formal structure, while Movement I focuses on the re-imagining of compositional influences that have permeated my music for several years. The piece follows a traditional pattern as to form, opening with a sonata-allegro first movement, followed by a slower theme-and-variations movement, then a slow minuet-like dance movement, finally a rondo, with extended opening material. The score to the symphony is accompanied by an analytical document

Learning with Local Gradients at the Edge

To enable learning on edge devices with fast convergence and low memory, we present a novel backpropagation-free optimization algorithm dubbed Target Projection Stochastic Gradient Descent (tpSGD). tpSGD generalizes direct random target projection to work with arbitrary loss functions and extends target projection for training recurrent neural networks (RNNs) in addition to feedforward networks. tpSGD uses layer-wise stochastic gradient descent (SGD) and local targets generated via random projections of the labels to train the network layer-by-layer with only forward passes. tpSGD doesn't require retaining gradients during optimization, greatly reducing memory allocation compared to SGD backpropagation (BP) methods that require multiple instances of the entire neural network weights, input/output, and intermediate results. Our method performs comparably to BP gradient-descent within 5% accuracy on relatively shallow networks of fully connected layers, convolutional layers, and recurrent layers. tpSGD also outperforms other state-of-the-art gradient-free algorithms in shallow models consisting of multi-layer perceptrons, convolutional neural networks (CNNs), and RNNs with competitive accuracy and less memory and time. We evaluate the performance of tpSGD in training deep neural networks (e.g. VGG) and extend the approach to multi-layer RNNs. These experiments highlight new research directions related to optimized layer-based adaptor training for domain-shift using tpSGD at the edge

Chronotype, Shift Work, and Sleep Problems Among Emergency Medicine Clinicians

Introduction: Extensive research has demonstrated that shift work can be detrimental to sleep. Chronotype, the preference for time of day to sleep or be active, can influence how we function at different times of day and how shift work impacts us. This study was designed to assess the chronotype of emergency physicians (EPs) and emergency advanced practice providers (EAPPs) and examine how chronotype was related to sleep problems and shifts worked over a three-month period. Methods: A survey assessing chronotype and sleep quality was sent to 225 EPs and EAPPs in a single, large academic Department of Emergency Medicine. An archival database indicated the shifts worked during the prior three months and the percentages of day, evening, and night shifts for each practitioner were calculated. Results: 127 people completed the survey (56.4%). Of the three chronotypes (morning, intermediate, evening), most EM clinicians were categorized as intermediate chronotype (56/127, 44.1%), followed by morning type (39/127, 30.7%) and then evening type (32/127, 25.2%). Those with an evening chronotype were more likely to report daytime dysfunction (a lack of enthusiasm and propensity to fall asleep during activities) (p \u3c 0.01) and worked a greater percentage of night shifts than other chronotypes (p \u3c 0.05). Interestingly, the effect of evening chronotype on daytime dysfunction was no longer significant when controlled for the relatively greater percentage of night shifts worked, suggesting that the observed dysfunction was more likely an artifact of the night shifts worked, rather than purely chronotype driven. Conclusion: This is the first study of a large cohort of EM practitioners investigating chronotype and its influence on shift preference and sleep quality. In this pilot investigation, most of the surveyed clinicians were categorized as an intermediate chronotype. Working night shifts was associated more closely with daytime dysfunction than was chronotype, strengthening the latent literature that working night shift carries with it significant challenges to the EM clinician. Future research should evaluate the relationship between chronotype malalignment to practitioner burnout and well-being

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games

As Artificial and Robotic Systems are increasingly deployed and relied upon for real-world applications, it is important that they exhibit the ability to continually learn and adapt in dynamically-changing environments, becoming Lifelong Learning Machines. Continual/lifelong learning (LL) involves minimizing catastrophic forgetting of old tasks while maximizing a model's capability to learn new tasks. This paper addresses the challenging lifelong reinforcement learning (L2RL) setting. Pushing the state-of-the-art forward in L2RL and making L2RL useful for practical applications requires more than developing individual L2RL algorithms; it requires making progress at the systems-level, especially research into the non-trivial problem of how to integrate multiple L2RL algorithms into a common framework. In this paper, we introduce the Lifelong Reinforcement Learning Components Framework (L2RLCF), which standardizes L2RL systems and assimilates different continual learning components (each addressing different aspects of the lifelong learning problem) into a unified system. As an instantiation of L2RLCF, we develop a standard API allowing easy integration of novel lifelong learning components. We describe a case study that demonstrates how multiple independently-developed LL components can be integrated into a single realized system. We also introduce an evaluation environment in order to measure the effect of combining various system components. Our evaluation environment employs different LL scenarios (sequences of tasks) consisting of Starcraft-2 minigames and allows for the fair, comprehensive, and quantitative comparison of different combinations of components within a challenging common evaluation environment.Comment: The Second International Conference on AIML Systems, October 12--15, 2022, Bangalore, Indi

MFA11 (MFA 2011)

Catalogue of a culminating student exhibition held at the Mildred Lane Kemper Art Museum, May 6-Aug. 1, 2011. Content includes Introduction / Buzz Spector -- Patricia Olynyk -- Marshall N. Klimasewiski -- John Talbott Allen -- Meghan Bean -- Shira Berkowitz / Maggie Stanley Majors -- Darrick Byers, Bryce Olen Robinson -- Jisun Choi -- Zlatko Ćosić -- James R. Daniels -- Kara Daving -- Andrea Degener -- Kristin Fleischmann / Randi Shapiro -- William Frank / Lawrence Ypil -- Nicholas Kania -- Katherine McCullough -- Jordan McGirk / Aditi Machado -- Zachary Miller -- Esther Murphy / Maggie Stanley Majors -- Kathryn Neale -- Christopher Ottinger / Melissa Olson -- Maia Palmer -- Nicole Petrescu / Melissa Olson -- Lauren Pressler / Randi Shapiro -- Whitney Sage / Aliya A. Reich -- Donna Smith.https://openscholarship.wustl.edu/books/1005/thumbnail.jp

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of 1) Continuous Learning, 2) Transfer and Adaptation, and 3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.Comment: To appear in Neural Network

Can We Modify the Intrauterine Environment to Halt the Intergenerational Cycle of Obesity?

Child obesity is a global epidemic whose development is rooted in complex and multi-factorial interactions. Once established, obesity is difficult to reverse and epidemiological, animal model, and experimental studies have provided strong evidence implicating the intrauterine environment in downstream obesity. This review focuses on the interplay between maternal obesity, gestational weight gain and lifestyle behaviours, which may act independently or in combination, to perpetuate the intergenerational cycle of obesity. The gestational period, is a crucial time of growth, development and physiological change in mother and child. This provides a window of opportunity for intervention via maternal nutrition and/or physical activity that may induce beneficial physiological alternations in the fetus that are mediated through favourable adaptations to in utero environmental stimuli. Evidence in the emerging field of epigenetics suggests that chronic, sub-clinical perturbations during pregnancy may affect fetal phenotype and long-term human data from ongoing randomized controlled trials will further aid in establishing the science behind ones predisposition to positive energy balance

Multi-ethnic genome-wide association study for atrial fibrillation

Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF