Detox your department: A stage model for achieving cultural change

Throughout this interactive session, participants will learn the stages of group formation, identify a cultural destination for their units, and engage in moderated small group activities that will help them develop their own specific stage-appropriate action strategies designed to achieve the desired cultural transformation

Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events

The High-Luminosity Large Hadron Collider at CERN will be characterized by greater pileup of events and higher occupancy, making the track reconstruction even more computationally demanding. Existing algorithms at the LHC are based on Kalman filter techniques with proven excellent physics performance under a variety of conditions. Starting in 2014, we have been developing Kalman-filter-based methods for track finding and fitting adapted for many-core SIMD processors that are becoming dominant in high-performance systems. This paper summarizes the latest extensions to our software that allow it to run on the realistic CMS-2017 tracker geometry using CMSSW-generated events, including pileup. The reconstructed tracks can be validated against either the CMSSW simulation that generated the hits, or the CMSSW reconstruction of the tracks. In general, the code's computational performance has continued to improve while the above capabilities were being added. We demonstrate that the present Kalman filter implementation is able to reconstruct events with comparable physics performance to CMSSW, while providing generally better computational performance. Further plans for advancing the software are discussed

Koinonia

Spotlight FeaturesSovereign Stumbling: My Life Journey to Date, Larry Crabb Conversations About Racism, Jessie Brown Anxiety: A Growing Problem in College Students, Steven M. Conn Thinking TheologicallyTeaching the Truth, Michael and Stephanie Santarosa Book ReviewsKingdom Triangle: Recover the Christian Mind, Renovate the Soul, Restore the Spirit\u27s Power (by J.P. Moreland), reviewed by Steve Ivester The Soul of a Christian University: A Field Guide for Educators (edited by Stephen T. Beers), reviewed by Kyle Lantz The Outrageous Idea of Academic Faithfullness (by Donald Opitz and Derek Melleby), reviewed by Nathan Geer I Once Was Lost: What Postmodern Skeptics Taught Us About Their Path to Jesus (by Don Everts and Doug Schaupp), reviewed by Andrew D. Rowell FeaturesThe President\u27s Corner Editor\u27s Deskhttps://pillars.taylor.edu/acsd_koinonia/1012/thumbnail.jp

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain

Symptom Experience and Quality of Life of Women Following Breast Cancer Treatment

Background: Few studies have examined the correlates of breast cancer-related symptoms that persist posttreatment and determined the relationship between symptoms and quality of life (QOL). Methods: A population-based sample of women in the United States with stage 0–II breast cancer (n = 1372) completed a survey including the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire and the Breast Cancer-Specific Quality of Life Questionnaire. Described are the presence and frequency of 13 symptom scales and their associations with 10 QOL dimensions. Results: All study participants had completed primary treatment (surgery and radiation and/or chemotherapy, if applicable). Mean time from initial surgical treatment to completion of the questionnaire was 7.2 months (range 0.5–14.9 months). Mean number of symptoms reported was 6.8, with the 5 most common symptom scales being systemic therapy side effects (87.7%), fatigue (81.7%), breast symptoms (72.1%), sleep disturbance (57.1%), and arm symptoms (55.6%). Younger age and poorer health status at diagnosis were associated with worse symptoms. Fatigue had the greatest impact on QOL, with significant differences between those with high and low fatigue across 7 QOL dimensions. Sociodemographic, prior health status, clinical, and treatment/diagnostic factors explained only 9%–27% of the variance in QOL outcomes. Adding symptom experience increased the variance explained to 18%–60%. Conclusions: More attention to the reduction and management of disease and treatment-related symptoms could improve QOL among women with breast cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63179/1/jwh.2006.0255.pd

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material effects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filter-based methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall efficiency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and offline reconstruction for the HL-LHC CMS tracker

Recipient mucosal-associated invariant T cells control GVHD within the colon

Mucosal-associated invariant T (MAIT) cells are a unique innate-like T cell subset that responds to a wide array of bacteria and yeast through recognition of riboflavin metabolites presented by the MHC class I–like molecule MR1. Here, we demonstrate using MR1 tetramers that recipient MAIT cells are present in small but definable numbers in graft-versus-host disease (GVHD) target organs and protect from acute GVHD in the colon following bone marrow transplantation (BMT). Consistent with their preferential juxtaposition to microbial signals in the colon, recipient MAIT cells generate large amounts of IL-17A, promote gastrointestinal tract integrity, and limit the donor alloantigen presentation that in turn drives donor Th1 and Th17 expansion specifically in the colon after BMT. Allogeneic BMT recipients deficient in IL-17A also develop accelerated GVHD, suggesting MAIT cells likely regulate GVHD, at least in part, by the generation of this cytokine. Indeed, analysis of stool microbiota and colon tissue from IL-17A–/– and MR1–/– mice identified analogous shifts in microbiome operational taxonomic units (OTU) and mediators of barrier integrity that appear to represent pathways controlled by similar, IL-17A–dependent mechanisms. Thus, MAIT cells act to control barrier function to attenuate pathogenic T cell responses in the colon and, given their very high frequency in humans, likely represent an important population in clinical BMT