Cahillbusch4931

BubbleUp is a tool that lets DevOps teams-data analysts who specialize in building and maintaining online systems-rapidly figure out why anomalous data have gone wrong. We developed BubbleUp with an iterative, human-centered design approach. Through multiple rounds of feedback, we were able to build a tool that presents a paired-histogram view to help make high-dimensional data make sense.Data visualization is hard to master because of the inherent complexities that characterize the challenge of facilitating understanding. Competence with data visualization is gaining in recognition as an essential capability and thus fostering the necessary skills is paramount to prepare students for their future professional activity in this field; yet, it is a challenge for educators to design programs that cover all facets. This article presents a framework that profiles the range of different capability "ingredients" which form the recipe of expertise in data visualization, from the point of view of an experienced practitioner.Our world is a complex ecosystem of interdependent processes. Geoscientists collect individual datasets addressing hyperspecific questions, which seek to probe these deeply intertwined processes. Scientists are beginning to explore how investigating relationships between disciplines can foster richer and more holistic research, but visualization tools are conventionally designed to address hyperspecific, rather than holistic, analysis. Bridging the vast wealth of available data will require new tools. Visualization has the potential to support holistic cross-disciplinary analysis to understand the complex innerworkings of our world, but doing so requires a paradigm shift to understand how visualization might enable lines of inquiry transcending traditional disciplinary boundaries. We present challenges for visualization in fostering such holistic geoscience analyses.Climate simulations belong to the most data-intensive scientific disciplines and are-in relation to one of humankind's largest challenges, i.e., facing anthropogenic climate change-ever more important. Not only are the outputs generated by current models increasing in size, due to an increase in resolution and the use of ensembles, but the complexity is also rising as a result of maturing models that are able to better describe the intricacies of our climate system. This article focuses on developments and trends in the scientific workflow for the analysis and visualization of climate simulation data, as well as on changes in the visualization techniques and tools that are available.High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth's many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. The impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise.Public awareness and concern about climate change often do not match the magnitude of its threat to humans and our environment. One reason for this disagreement is that it is difficult to mentally simulate the effects of a process as complex as climate change and to have a concrete representation of the impact that our individual actions will have on our own future, especially if the consequences are long term and abstract. To overcome these challenges, we propose to use cutting-edge artificial intelligence (AI) approaches to develop an interactive personalized visualization tool, the AI climate impact visualizer. It will allow a user to enter an address-be it their house, their school, or their workplace--and it will provide them with an AI-imagined possible visualization of the future of this location in 2050 following the detrimental effects of climate change such as floods, storms, and wildfires. This image will be accompanied by accessible information regarding the science behind climate change, i.e., why extreme weather events are becoming more frequent and what kinds of changes are happening on a local and global scale.Smokers without airflow obstruction have reduced exercise capacity, but the underlying physiological mechanisms are not fully understood. We aimed to compare quadriceps function assessed using nonvolitional measures and ventilatory requirements during exercise, between smokers without airway obstruction and never-smoker controls. Adult smokers (n = 20) and never-smoker controls (n = 16) aged 25-50 yr with normal spirometry, underwent incremental cycle cardiopulmonary exercise testing to exhaustion with measurement of symptoms and dynamic lung volumes. Quadriceps strength and endurance were assessed nonvolitionally using single and repetitive magnetic stimulation. Quadriceps bulk was assessed using ultrasound, as rectus-femoris cross-sectional area. Physical activity level was quantified using the SenseWear armband worn for 5 days. Smokers had lower peak exercise workload, peak oxygen consumption, and anaerobic threshold than controls (170 ± 46 vs. 256 ± 57 W, 2.20 ± 0.56 vs. 3.18 ± 0.72 L/min, 1.38 ± 0.33 vs.unctions to reduced exercise capacity are unclear. We found that non-COPD smokers had decreased exercise capacity and muscle endurance although strength was preserved compared with never-smoking controls. Exercise endurance was associated with quadriceps endurance and CO transfer factor. Despite similar physical activity levels, smokers developed leg fatigue, breathlessness, and displayed increased ventilation with reduced ventilatory efficiency at lower workloads, without exhibiting ventilatory constraint.Increased consumption of added sucrose and high-fructose corn syrup in the human diet has been associated with increasing incidence of obesity and metabolic disease. There are currently no reliable, objective biomarkers for added sugar intake that could be used in individuals or population settings. 13C is a stable isotope of carbon, and measurement of blood 13C content has been proposed as a marker of added sugar consumption. This study aimed to determine if breath 13CO2 could represent an alternative, noninvasive biomarker to monitor added sugar intake. see more We undertook retrospective analyses of eight preclinical and human 13C-breath studies to define baseline breath 13CO2 characteristics. All samples were analyzed using isotope ratio mass spectrometry, and breath 13CO2 was expressed as the delta value, δ expressed as parts per thousand (‰). All data are expressed as mean ± SEM, with statistical significance considered at P less then 0.05. Breath δ13CO2 was significantly elevated in a cumulative manner in rats and mice that consumed a diet containing at least 15% sucrose.