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Overlooked glassy polymer attributes illustrated by asymmetric polyimide hollow fibers
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A simulation pipeline for fast neutron imaging and spectroscopy using quantified detector attributes
Radiation imaging capabilities, essential in the nuclear nonproliferation regime, facilitate source localization and, in certain cases, spectroscopy. Scatter-based neutron cameras, which can measure the neutron signatures from special nuclear material, hold particular interest. Systems incorporating organic scintillators can extract neutron energy spectra, potentially distinguishing fission neutron sources from others, such as alpha-neutron sources. The development and testing of a scatter-based neutron imager, however, can be challenging without having an accurate simulation model or first constructing a prototype. This work describes a simulation pipeline that takes output from MCNPX-PoliMi simulations and creates the expected back-projection neutron images and neutron energy spectra. This pipeline was developed to improve the modeling of fast neutron imagers and bridge the current gap in literature, which predominantly focuses on gamma-ray Compton imager models. This work also reports on the significance of various real-world system considerations and their effects on the simulated detector responses. The pipeline was verified and validated with experimental data collected using a 252 Cf spontaneous fission source using a fast neutron scattering imager developed at the University of Michigan.
Analysis of barriers to perceived service quality in Ghana: Students’ perspectives on bus mobility attributes
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Localized enzymolysis and sonochemically modified sunflower protein: Physical, functional and structure attributes
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Mechanistic Analysis of Microstructural Attributes to Lithium Plating in Fast Charging
Metallic lithium deposition on graphite anodes is a critical degradation mode in lithium-ion batteries, which limits safety and fast charge capability. A conclusive strategy to mitigate lithium deposition under fast charging yet remains elusive. Herein, we examine the role of electrode microstructure in mitigating lithium plating behavior under various operating conditions, including fast charging. The multilength scale characteristics of the electrode microstructure lead to a complex interaction of transport and kinetic limitations that significantly governs the cell performance and the occurrence of Li plating. We demonstrate, based on a comprehensive mesoscale analysis, that the performance and degradation can be significantly modulated via systematic design improvements at the hierarchy of length scales. It is found that the improvement in kinetic and transport characteristics achievable at disparate scales can dramatically affect Li plating propensity.
Attribution-Driven Explanation of the Deep Neural Network Model via Conditional Microstructure Image Synthesis
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Quantifying Carbon Cycle Extremes and Attributing Their Causes Under Climate and Land Use and Land Cover Change From 1850 to 2300
The increasing atmospheric carbon dioxide (CO 2 ) mole fraction affects global climate through radiative (trapping longwave radiation) and physiological effects (reduction of plant transpiration). We use the simulations of the Community Earth System Model (CESM1-BGC) forced with Representative Concentration Pathway 8.5 to investigate climate-vegetation feedbacks from 1850 to the year 2300. Human-induced land use and land cover change (LULCC), through biogeochemical and biogeophysical processes, alter the climate and modify photosynthetic activity. The changing characteristics of extreme anomalies in photosynthesis, referred to as carbon cycle extremes, increase the uncertainty of terrestrial ecosystems to act as a net carbon sink. However, the role of LULCC in altering carbon cycle extremes under business-as-usual (continuously rising) CO 2 emissions is unknown. Here we show that LULCC magnifies the intensity, frequency, and extent of carbon cycle extremes, resulting in a net reduction in expected photosynthetic activity in the future. We found that large temporally contiguous negative carbon cycle extremes are due to a persistent decrease in soil moisture, which is triggered by declines in precipitation. With LULCC and global warming, vegetation exhibits increased vulnerability to hot and dry environmental conditions, increasing the frequency of fire events and resulting in considerable losses in photosynthetic activity. While most regions show strengthening of negative carbon cycle extremes, a few locations show a weakening effect driven by declining vegetation cover or benign climate conditions for photosynthesis. Increasing hot, dry, and fire-driven carbon cycle extremes are essential for improving carbon cycle modeling and estimation of ecosystem responses to LULCC and rising CO 2 mole fractions. Moreover, large aberrations in vegetation productivity represent potential and growing threats to human lives, wildlife, and food security.
Attribution of 2020 hurricane season extreme rainfall to human-induced climate change
Abstract The 2020 North Atlantic hurricane season was one of the most active on record, causing heavy rains, strong storm surges, and high winds. Human activities continue to increase the amount of greenhouse gases in the atmosphere, resulting in an increase of more than 1 °C in the global average surface temperature in 2020 compared to 1850. This increase in temperature led to increases in sea surface temperature in the North Atlantic basin of 0.4–0.9 °C during the 2020 hurricane season. Here we show that human-induced climate change increased the extreme 3-hourly storm rainfall rates and extreme 3-day accumulated rainfall amounts during the full 2020 hurricane season for observed storms that are at least tropical storm strength (>18 m/s) by 10 and 5%, respectively. When focusing on hurricane strength storms (>33 m/s), extreme 3-hourly rainfall rates and extreme 3-day accumulated rainfall amounts increase by 11 and 8%, respectively.
Observed changes in dry-season water availability attributed to human-induced climate change
Human-induced climate change impacts the hydrological cycle and thus the availability of water resources. However, previous assessments of observed warming-induced changes in dryness have not excluded natural climate variability and show conflicting results due to uncertainties in our understanding of the response of evapotranspiration. Here in this paper, we employ data-driven and land-surface models to produce observation-based global reconstructions of water availability from 1902 to 2014, a period during which our planet experienced a global warming of approximately 1°C. Our analysis reveals a spatial pattern of changes in average water availability during the driest month of the year over the past three decades compared with the first half of the twentieth century, with some regions experiencing increased and some decreased water availability. The global pattern is consistent with climate model estimates that account for anthropogenic effects, and it is not expected from natural climate variability, supporting human-induced climate change as the cause. There is regional evidence of drier dry seasons predominantly in extratropical latitudes and including Europe, western North America, northern Asia, southern South America, Australia and eastern Africa. We also find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.
Spatial patterns of historical crop yields reveal soil health attributes in US Midwest fields
Abstract Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers’ fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ.
Structural attributes of mammalian prion infectivity: Insights from studies with synthetic prions
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Lost in translation: What we have learned from attributes that do not translate from Arabidopsis to other plants
Abstract Research in Arabidopsis thaliana has a powerful influence on our understanding of gene functions and pathways. However, not everything translates from Arabidopsis to crops and other plants. Here, a group of experts consider instances where translation has been lost and why such translation is not possible or is challenging. First, despite great efforts, floral dip transformation has not succeeded in other species outside Brassicaceae. Second, due to gene duplications and losses throughout evolution, it can be complex to establish which genes are orthologs of Arabidopsis genes. Third, during evolution Arabidopsis has lost arbuscular mycorrhizal symbiosis. Fourth, other plants have evolved specialized cell types that are not present in Arabidopsis. Fifth, similarly, C4 photosynthesis cannot be studied in Arabidopsis, which is a C3 plant. Sixth, many other plant species have larger genomes, which has given rise to innovations in transcriptional regulation that are not present in Arabidopsis. Seventh, phenotypes such as acclimation to water stress can be challenging to translate due to different measurement strategies. And eighth, while the circadian oscillator is conserved, there are important nuances in the roles of circadian regulators in crop plants. A key theme emerging across these vignettes is that even when translation is lost, insights can still be gained through comparison with Arabidopsis.
SPARSITY IMPROVES UNSUPERVISED ATTRIBUTE DISCOVERY IN STYLEGAN
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A Study of Imbalance Levels Attributed to Photovoltaic Penetration in Distribution Systems
Abstract— The number of renewable sources, namely photovoltaics (PV), continues to grow within distribution systems. How placements impact a system’s performance remains a concern within both the research and the utility communities. Beyond system node voltages and real power losses, this work looks to industry standard imbalance metrics and the changes experienced on these values with varied levels of PV. Specifically, four imbalance metrics are presented and studied for an actual 906-bus distribution system. Multiple loading conditions and photovoltaic placement schemes are explored to compare the changes seen on these metrics across a variety of scenarios experienced by the network.
High-throughput feature extraction for measuring attributes of deforming open-cell foams
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DETECTING COMMUNITIES AND ATTRIBUTING PURPOSE TO HUMAN MOBILITY DATA.
Abstract not provided.