Secondary organic aerosol formation from in-use motor vehicle emissions using a potential aerosol mass reactor.

Secondary organic aerosol (SOA) formation from in-use vehicle emissions was investigated using a potential aerosol mass (PAM) flow reactor deployed in a highway tunnel in Pittsburgh, Pennsylvania. Experiments consisted of passing exhaust-dominated tunnel air through a PAM reactor over integrated hydroxyl radical (OH) exposures ranging from ∼ 0.3 to 9.3 days of equivalent atmospheric oxidation. Experiments were performed during heavy traffic periods when the fleet was at least 80% light-duty gasoline vehicles on a fuel-consumption basis. The peak SOA production occurred after 2-3 days of equivalent atmospheric oxidation. Additional OH exposure decreased the SOA production presumably due to a shift from functionalization to fragmentation dominated reaction mechanisms. Photo-oxidation also produced substantial ammonium nitrate, often exceeding the mass of SOA. Analysis with an SOA model highlight that unspeciated organics (i.e., unresolved complex mixture) are a very important class of precursors and that multigenerational processing of both gases and particles is important at longer time scales. The chemical evolution of the organic aerosol inside the PAM reactor appears to be similar to that observed in the atmosphere. The mass spectrum of the unoxidized primary organic aerosol closely resembles ambient hydrocarbon-like organic aerosol (HOA). After aging the exhaust equivalent to a few hours of atmospheric oxidation, the organic aerosol most closely resembles semivolatile oxygenated organic aerosol (SV-OOA) and then low-volatility organic aerosol (LV-OOA) at higher OH exposures. Scaling the data suggests that mobile sources contribute ∼ 2.9 ± 1.6 Tg SOA yr(-1) in the United States, which is a factor of 6 greater than all mobile source particulate matter emissions reported by the National Emissions Inventory. This highlights the important contribution of SOA formation from vehicle exhaust to ambient particulate matter concentrations in urban areas

Evaluating the impact of new observational constraints on P-S/IVOC emissions, multi-generation oxidation, and chamber wall losses on SOA modeling for Los Angeles, CA

Secondary organic aerosol (SOA) is an important contributor to fine particulate matter (PM) mass in polluted regions, and its modeling remains poorly constrained. A box model is developed that uses recently published literature parameterizations and data sets to better constrain and evaluate the formation pathways and precursors of urban SOA during the CalNex 2010 campaign in Los Angeles. When using the measurements of intermediate-volatility organic compounds (IVOCs) reported in Zhao et al. (2014) and of semivolatile organic compounds (SVOCs) reported in Worton et al. (2014) the model is biased high at longer photochemical ages, whereas at shorter photochemical ages it is biased low, if the yields for VOC oxidation are not updated. The parameterizations using an updated version of the yields, which takes into account the effect of gas-phase wall losses in environmental chambers, show model–measurement agreement at longer photochemical ages, even though some low bias at short photochemical ages still remains. Furthermore, the fossil and non-fossil carbon split of urban SOA simulated by the model is consistent with measurements at the Pasadena ground site. Multi-generation oxidation mechanisms are often employed in SOA models to increase the SOA yields derived from environmental chamber experiments in order to obtain better model–measurement agreement. However, there are many uncertainties associated with these aging mechanisms. Thus, SOA formation in the model is compared to data from an oxidation flow reactor (OFR) in order to constrain SOA formation at longer photochemical ages than observed in urban air. The model predicts similar SOA mass at short to moderate photochemical ages when the aging mechanisms or the updated version of the yields for VOC oxidation are implemented. The latter case has SOA formation rates that are more consistent with observations from the OFR though. Aging mechanisms may still play an important role in SOA chemistry, but the additional mass formed by functionalization reactions during aging would need to be offset by gasphase fragmentation of SVOCs. All the model cases evaluated in this work show a large majority of the urban SOA (70–83 %) at Pasadena coming from the oxidation of primary SVOCs (P-SVOCs) and primary IVOCs (P-IVOCs). The importance of these two types of precursors is further supported by analyzing the percentage of SOA formed at long photochemical ages (1.5 days) as a function of the precursor rate constant. The P-SVOCs and P-IVOCs have rate constants that are similar to highly reactive VOCs that have been previously found to strongly correlate with SOA formation potential measured by the OFR. Finally, the volatility distribution of the total organic mass (gas and particle phase) in the model is compared against measurements. The total SVOC mass simulated is similar to the measurements, but there are important differences in the measured and modeled volatility distributions. A likely reason for the difference is the lack of particle-phase reactions in the model that can oligomerize and/or continue to oxidize organic compounds even after they partition to the particle phase

Cell Pattern in Adult Human Corneal Endothelium

A review of the current data on the cell density of normal adult human endothelial cells was carried out in order to establish some common parameters appearing in the different considered populations. From the analysis of cell growth patterns, it is inferred that the cell aging rate is similar for each of the different considered populations. Also, the morphology, the cell distribution and the tendency to hexagonallity are studied. The results are consistent with the hypothesis that this phenomenon is analogous with cell behavior in other structures such as dry foams and grains in polycrystalline materials. Therefore, its driving force may be controlled by the surface tension and the mobility of the boundaries

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)