The Inflated Chern-Simons Number in Spectator Chromo-Natural Inflation

The chromo-natural inflation (CNI) scenario predicts a potentially detectable chiral gravitational wave signal, generated by a Chern-Simons coupling between a rolling scalar axion field and an SU(2) gauge field with an isotropy-preserving classical background during inflation. However, the generation of this signal requires a very large integer Chern-Simons level, which can be challenging to explain or embed in a UV-complete model. We show that this challenge persists in the phenomenologically viable spectator field CNI (S-CNI) model. Furthermore, we show that a clockwork scenario giving rise to a large integer as a product of small integers can never produce a Chern-Simons level large enough to have successful S-CNI phenomenology. We briefly discuss other constraints on the model, both in effective field theory based on partial-wave unitarity bounds and in quantum gravity based on the Weak Gravity Conjecture, which may be relevant for further explorations of alternative UV completions.Comment: 33 pages, 3 figure

Output Consistency Scale to Standardize Ostomate Output Description in Clinical Practice and Studies

Stool descriptors have become popular due to the large diffusion of the Bristol Stool Form Scale (BSFS) via clinical studies, clinical trials, and social media. The applications have been numerous and centered around standardization of terminology that can be used by health care professionals and patients alike, as well as individuals interested in their wellness and the associated partners in the wellness industry. For a portion of the population, the digestive content is rerouted to an external manufactured pouch or bag, making the use of the BSFS visual descriptors of stool difficult. From day one post-resection surgery, ostomates are challenged with output management. The lack of standardized descriptors may hinder proper communication between the individual and the support team, as well as providing proper characterization in clinical studies and clinical trials. We propose the Lincoln Ostomy Output Consistency Scale for jejunostomy, ileostomy and colostomy (LOOCS) to overcome the limitations of the BSFS for qualifying ostomy outputs. The design was based on the need to describe perceived consistency from the ostomate point of view. We anticipate that the LOOCS scale can be effective in pediatric and adult clinical research settings, as well as self-monitoring to manage the quality of life

Rapid development of a perfusion process with high productivity

Continuous process improvement is required during a biologics process life cycle to increase process yield and reduce cost. In this poster, we will present a case study in late stage process development where everything was changed but the product quality. The following major changes were made when developing the new process: Production cell line – subclone of the original clone used. Media – from hydrolysate-containing feeds to fully chemically-defined feeds. Feeding strategy – from fixed volume/fixed schedule feeding to daily on-demand feeding. Media components were optimized through spent media analysis and mechanistic understanding to accommodate the new feeding strategy. High-throughput bioreactor systems (ambr15TM and ambr250TM) were used for rapid screening of experimental conditions, and the results were confirmed in 3 L bioreactors. As a result of the development effort, a 100% increase in peak cell density to 20-25e6 cells/mL, a 40% decrease in peak lactate level, and a 140% increase in antibody titer were achieved in the new process. Titer increase was attributed to the improved oxidative metabolism and significant increase in cumulative cell density. In the new process, final culture viability was still maintained at \u3e90%, benefiting filtration primary recovery. The process was scaled-up to a 200 L SUB without losing productivity. We show that product quality, especially N-linked glycosylation and charge variants, could be modulated by adjusting specific medium components and feeding strategy. The antibody quality attributes resulting from the new process are comparable with (or better than) those from the old process

Hunting for Significance: Bayesian Classifiers Under a Mixture Loss Function

Detecting significance in a high-dimensional sparse data structure has received a large amount of attention in modern statistics. In the current paper, we introduce a compound decision rule to simultaneously classify signals from noise. This procedure is a Bayes rule subject to a mixture loss function. The loss function minimizes the number of false discoveries while controlling the false nondiscoveries by incorporating the signal strength information. Based on our criterion, strong signals will be penalized more heavily for nondiscovery than weak signals. In constructing this classification rule, we assume a mixture prior for the parameter which adapts to the unknown sparsity. This Bayes rule can be viewed as thresholding the “local fdr” (Efron, 2007) by adaptive thresholds. Both parametric and nonparametric methods will be discussed. The nonparametric procedure adapts to the unknown data structure well and outperforms the parametric one. Performance of the procedure is illustrated by various simulation studies and a real data application