Search for: All records

Constructing and executing reproducible workflows is fundamental to performing research in a variety of scientific domains. Many of the current commercial and open source solutions for workflow en- gineering impose constraints—either technical or budgetary—upon researchers, requiring them to use their limited funding on expensive cloud platforms or spend valuable time acquiring knowledge of software systems and processes outside of their domain expertise. Even though many commercial solutions offer free-tier services, they often do not meet the resource and architectural requirements (memory, data storage, compute time, networking, etc) for researchers to run their workflows effectively at scale. Tapis Workflows abstracts away the complexities of workflow creation and execution behind a web-based API with a simplified workflow model comprised of only pipelines and tasks. This paper will de- tail how Tapis Workflows approaches workflow management by exploring its domain model, the technologies used, application architecture, design patterns, how organizations are leveraging Tapis Workflows to solve unique problems in their scientific workflows, and this projects’s vision for a simple, open source, extensible, and easily deployable workflow engine. 

Abstract In the mid-continental grasslands of North America, climate change is increasing the intensity and frequency of extreme weather events. Increasingly severe storms and prolonged periods of elevated temperatures can impose challenges that adversely affect an individual's condition and, ultimately, survival. However, despite mounting evidence that extreme weather events, such as heavy rain storms, can impose short-term physiological challenges, we know little regarding the putative costs of such weather events. To determine the consequences of extreme weather for small endotherms, we tested predictions of the relationships between both severe precipitation events and wet bulb temperatures (an index that combines temperature and humidity) prior to capture with body composition and hematocrit of grasshopper sparrows (Ammodramus savannarum) caught during the breeding season at the Konza Prairie Biological Station, Kansas, USA, between 2014 and 2016. We measured each individual's fat mass, lean mass and total body water using quantitative magnetic resonance in addition to their hematocrit. Individuals exposed to storms in the 24 hours prior to capture had less fat reserves, more lean mass, more water and higher hematocrit than those exposed to moderate weather conditions. Furthermore, individuals stored more fat if they experienced high wet bulb temperatures in the week prior to capture. Overall, the analysis of these data indicate that extreme weather events take a physiological toll on small endotherms, and individuals may be forced to deplete fat stores and increase erythropoiesis to meet the physiological demands associated with surviving a storm. Elucidating the potential strategies used to cope with severe weather may enable us to understand the energetic consequences of increasingly severe weather in a changing world.