Using visual analytics to develop situation awareness in astrophysics

We present a novel collaborative visual analytics application for cognitively overloaded users in the astrophysics domain. The system was developed for scientists who need to analyze heterogeneous, complex data under time pressure, and make predictions and time-critical decisions rapidly and correctly under a constant influx of changing data. The Sunfall Data Taking system utilizes several novel visualization and analysis techniques to enable a team of geographically distributed domain specialists to effectively and remotely maneuver a custom-built instrument under challenging operational conditions. Sunfall Data Taking has been in production use for 2 years by a major international astrophysics collaboration (the largest data volume supernova search currently in operation), and has substantially improved the operational efficiency of its users. We describe the system design process by an interdisciplinary team, the system architecture and the results of an informal usability evaluation of the production system by domain experts in the context of Endsley's three levels of situation awareness

Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline.

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific neuropathologies-amyloid plaques and cerebral amyloid angiopathy-in immunohistochemically-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotate > 70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieve strong plaque classification on a 10-WSI hold-out set (0.993 and 0.743 areas under the receiver operating characteristic and precision recall curve, respectively). Prediction confidence maps visualize morphology distributions at high resolution. Resulting network-derived amyloid beta (Aβ)-burden scores correlate well with established semi-quantitative scores on a 30-WSI blinded hold-out. Finally, saliency mapping demonstrates that networks learn patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologist's ability suggests a route to neuropathologic deep phenotyping

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Air quality impact of the Northern California Camp Fire of November 2018

The Northern California Camp Fire that took place in November 2018 was one of the most damaging environmental events in California history. Here, we analyze ground-based station observations of airborne particulate matter that has a diameter <2.5 µm (PM_(2.5)) across Northern California and conduct numerical simulations of the Camp Fire using the Weather Research and Forecasting model online coupled with chemistry (WRF-Chem). Simulations are evaluated against ground-based observations of PM_(2.5), black carbon, and meteorology, as well as satellite measurements, such as Tropospheric Monitoring Instrument (TROPOMI) aerosol layer height and aerosol index. The Camp Fire led to an increase in Bay Area PM_(2.5) to over 50 µg m⁻³ for nearly 2 weeks, with localized peaks exceeding 300 µg m⁻³. Using the Visible Infrared Imaging Radiometer Suite (VIIRS) high-resolution fire detection products, the simulations reproduce the magnitude and evolution of surface PM_(2.5) concentrations, especially downwind of the wildfire. The overall spatial patterns of simulated aerosol plumes and their heights are comparable with the latest satellite products from TROPOMI. WRF-Chem sensitivity simulations are carried out to analyze uncertainties that arise from fire emissions, meteorological conditions, feedback of aerosol radiative effects on meteorology, and various physical parameterizations, including the planetary boundary layer model and the plume rise model. Downwind PM2.5 concentrations are sensitive to both flaming and smoldering emissions over the fire, so the uncertainty in the satellite-derived fire emission products can directly affect the air pollution simulations downwind. Our analysis also shows the importance of land surface and boundary layer parameterization in the fire simulation, which can result in large variations in magnitude and trend of surface PM_(2.5). Inclusion of aerosol radiative feedback moderately improves PM_(2.5) simulations, especially over the most polluted days. Results of this study can assist in the development of data assimilation systems as well as air quality forecasting of health exposures and economic impact studies

Domain general learning: Infants use social and non-social cues when learning object statistics.

Previous research has shown that infants can learn from social cues. But is a social cue more effective at directing learning than a non-social cue? This study investigated whether 9-month-old infants (N = 55) could learn a visual statistical regularity in the presence of a distracting visual sequence when attention was directed by either a social cue (a person) or a non-social cue (a rectangle). The results show that both social and non-social cues can guide infants' attention to a visual shape sequence (and away from a distracting sequence). The social cue more effectively directed attention than the non-social cue during the familiarization phase, but the social cue did not result in significantly stronger learning than the non-social cue. The findings suggest that domain general attention mechanisms allow for the comparable learning seen in both conditions

Low-carbon energy: a roadmap

Technologies available today, and those expected to become competitive over the next decade, will permit a rapid decarbonization of the global energy economy. New renewable energy technologies, combined with a broad suite of energy-efficiency advances, will allow global energy needs to be met without fossil fuels and by adding only minimally to the cost of energy services The world is now in the early stages of an energy revolution that over the next few decades could be as momentous as the emergence of oiland electricity-based economies a century ago. Double-digit market growth, annual capital flows of more than $100 billion, sharp declines in technology costs, and rapid progress in the sophistication and effectiveness of government policies all herald a promising new energy era. Advanced automotive, electronics, and buildings systems will allow a substantial reduction in carbon dioxide (CO2) emissions, at negative costs once the savings in energy bills is accounted for. The savings from these measures can effectively pay for a significant portion of the additional cost of advanced renewable energy technologies to replace fossil fuels, including wind, solar, geothermal, and bioenergy. Resource estimates indicate that renewable energy is more abundant than all of the fossil fuels combined, and that well before mid-century it will be possible to run most national electricity systems with minimal fossil fuels and only 10 percent of the carbon emissions they produce today. The development of smart electricity grids, the integration of plug-in electric vehicles, and the addition of limited storage capacity will allow power to be provided without the baseload plants that are the foundation of today's electricity systems. Recent climate simulations conclude that CO2 emissions will need to peak within the next decade and decline by at least 50 to 80 percent by 2050. This challenge will be greatly complicated by the fact that China, India, and other developing countries are now rapidly developing modern energy systems. The only chance of slowing the buildup of CO2 concentrations soon enough to avoid catastrophic climate change that could take centuries to reverse is to transform the energy economies of industrial and developing countries almost simultaneously. This would have seemed nearly impossible a few years ago, but since then, the energy policies and markets of China and India have begun to change rapidly -- more rapidly than those in many industrial countries. Renewable and efficiency technologies will allow developing countries to increase their reliance on indigenous resources and reduce their dependence on expensive and unstable imported fuelsAround the world, new energy systems could become a huge engine of industrial development and job creation, opening vast new economic opportunities. Developing countries have the potential to "leapfrog" the carbon-intensive development path of the 20th century and go straight to the advanced energy systems that are possible today. Improved technology and high energy prices have created an extraordinarily favorable market for new energy systems over the past few years. But reaching a true economic tipping point will require innovative public policies and strong political leadership

The Allure of Technology: How France and California Promoted Electric Vehicles to Reduce Urban Air Pollution

All advanced industrialized societies face the problem of air pollution produced by motor vehicles. In spite of striking improvements in internal combustion engine technology, air pollution in most urban areas is still measured at levels determined to be harmful to human health. Throughout the 1990s and beyond, California and France both chose to improve air quality by means of technological innovation, adopting legislation that promoted clean vehicles, prominently among them, electric vehicles (EVs). In California, policymakers chose a technology-forcing approach, setting ambitious goals (e.g., zero emission vehicles), establishing strict deadlines and issuing penalties for non-compliance. The policy process in California called for substantial participation from the public, the media, the academic community and the interest groups affected by the regulation. The automobile and oil industries bitterly contested the regulation, in public and in the courts. In contrast, in France the policy process was non-adversarial, with minimal public participation and negligible debate in academic circles. We argue that California's stringent regulation spurred the development of innovative hybrid and fuel cell vehicles more effectively than the French approach. However, in spite of the differences, both California and France have been unable to put a substantial number of EVs on the road. Our comparison offers some broad lessons about how policy developments within a culture influence both the development of technology and the impact of humans on the environment.Environmental policy, Electric vehicles, Air pollution, Technology policy, Sustainable transport

The Allure of Technology: How France and California Promoted Electric and Hybrid Vehicles to Reduce Urban Air Pollution

All advanced industrialized societies face the problem of air pollution produced by motor vehicles. In spite of striking improvements in internal combustion engine technology, air pollution in most urban areas is still measured at levels determined to be harmful to human health. Throughout the 1990s and beyond, California and France both chose to improve air quality by means of technological innovation, adopting legislation that promoted clean vehicles, prominently among them, electric vehicles (EVs). In California, policymakers chose a technology-forcing approach, setting ambitious goals (e.g., zero emission vehicles), establishing strict deadlines and issuing penalties for non-compliance. The policy process in California called for substantial participation from the public, the media, the academic community and the interest groups affected by the regulation. The automobile and oil industries bitterly contested the regulation, in public and in the courts. In contrast, in France the policy process was non-adversarial, with minimal public participation and negligible debate in academic circles. We argue that California\u27s stringent regulation spurred the development of innovative hybrid and fuel cell vehicles more effectively than the French approach. However, in spite of the differences, both California and France have been unable to put a substantial number of EVs on the road. Our comparison offers some broad lessons about how policy developments within a culture influence both the development of technology and the impact of humans on the environment. © Springer Science+Business Media, LLP 2007