Hvasta, M. G.; Dudt, D.; Fisher, A. E.; Kolemen, E.
A 'weighted magnetic bearing' has been developed to improve the performance of
rotating Lorentz-force flowmeters (RLFFs). Experiments have shown that the new bearing
reduces frictional losses within a double-sided, disc-style RLFF to negligible levels.
Operating such an RLFF under 'frictionless' conditions provides two major benefits.
First, the steady-state velocity of the RLFF magnets matches the average velocity of the
flowing liquid at low flow rates. This enables an RLFF to make accurate volumetric flow
measurements without any calibration or prior knowledge of the fluid properties. Second,
due to minimized frictional losses, an RLFF is able to measure low flow rates that cannot
be detected when conventional, high-friction bearings are used. This paper provides a
brief background on RLFFs, gives a detailed description of weighted magnetic bearings,
and compares experimental RLFF data to measurements taken with a commercially available
Explosive volcanic eruptions have large climate impacts, and can serve as observable tests of the climatic response to radiative forcing. Using a high resolution climate model, we contrast the climate responses to Pinatubo, with symmetric forcing, and those to Santa Maria and Agung, which had meridionally asymmetric forcing. Although Pinatubo had larger global-mean forcing, asymmetric forcing strongly shifts the latitude of tropical rainfall features, leading to larger local precipitation/TC changes. For example, North Atlantic TC activity over is enhanced/reduced by SH-forcing (Agung)/NH-forcing (Santa Maria), but changes little in response to the Pinatubo forcing. Moreover, the transient climate sensitivity estimated from the response to Santa Maria is 20% larger than that from Pinatubo or Agung. This spread in climatic impacts of volcanoes needs to be considered when evaluating the role of volcanoes in global and regional climate, and serves to contextualize the well-observed response to Pinatubo.
Severe acute respiratory coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is of zoonotic origin. Evolutionary analyses assessing whether coronaviruses similar to SARS-CoV-2 infected ancestral species of modern-day animal hosts could be useful in identifying additional reservoirs of potentially dangerous coronaviruses. We reasoned that if a clade of species has been repeatedly exposed to a virus, then their proteins relevant for viral entry may exhibit adaptations that affect host susceptibility or response. We perform comparative analyses across the mammalian phylogeny of angiotensin-converting enzyme 2 (ACE2), the cellular receptor for SARS-CoV-2, in order to uncover evidence for selection acting at its binding interface with the SARS-CoV-2 spike protein. We uncover that in rodents there is evidence for adaptive amino acid substitutions at positions comprising the ACE2-spike interaction interface, whereas the variation within ACE2 proteins in primates and some other mammalian clades is not consistent with evolutionary adaptations. We also analyze aminopeptidase N (APN), the receptor for the human coronavirus 229E, a virus that causes the common cold, and find evidence for adaptation in primates. Altogether, our results suggest that the rodent and primate lineages may have had ancient exposures to viruses similar to SARS-CoV-2 and HCoV-229E, respectively. Included in this repository are the instructions and corresponding code required to build the dataset and run the analysis in the manuscript.
In this comment, we point out possible critical numerical flaws of recent particle simulation studies (Jiang et al 2016 Nucl. Fusion 56 126017, Peng et al 2018 Nucl. Fusion 58 026007) on the electrical gas breakdown in a simple one-dimensional periodic slab geometry. We show that their observations on the effects of the ambipolar electric fields during the breakdown, such as the sudden reversal of the ion flow direction, could not be real physical phenomena but resulting from numerical artifacts violating the momentum conservation law. We show that an incomplete implementation of the direct-implicit scheme can cause the artificial electric fields and plasma transports resulting in fallacies in simulation results. We also discuss that their simple plasma model without considering poloidal magnetic fields seriously mislead the physical mechanism of the electrical gas breakdown because it cannot reflect important dominant plasma dynamics in the poloidal plane (Yoo et al 2018 Nat. Commun. 9 3523).
A compact and multi-view Solid State Neutral Particle Analyzer (SSNPA) diagnostic based on silicon photodiode arrays has been successfully tested on the National Spherical Torus Experiment-Upgrade (NSTX-U). The SSNPA diagnostic provides spatially, temporally, and pitch-angle resolved measurements of fast-ion distribution by detecting fast neutral flux resulting from charge exchange (CX) reactions. The system consists of three 16-channel subsystems: t-SSNPA viewing the plasma mid-radius and neutral beam (NB) line #2 tangentially, r-SSNPA viewing the plasma core and NB line #1 radially and p-SSNPA with no intersection with any NB lines. Due to the setup geometry, the active CX signals of t-SSNPA and r-SSNPA are mainly sensitive to passing and trapped particles respectively. In addition, both t-SSNPA and r-SSNPA utilize three vertically stacked arrays with different filter thickness to obtain coarse energy information. The experimental data show that all channels are operational. The signal to noise ratio is typically larger than 10 and the main noise is x-ray induced signal. The active and passive CX signals are clearly observed on t-SSNPA and r-SSNPA during NB modulation. The SSNPA data also indicate significant losses of passing particles during sawteeth, while trapped particles are weakly affected. Fluctuations up to 120 kHz, have been observed on SSNPA, and they are strongly correlated with magnetohydrodynamics (MHD) instabilities.
Compact tokamak fusion reactors utilizing advanced high-temperature superconducting magnets for the toroidal field coils have received considerable recent attention due to the promise of more compact devices and more economical fusion energy development. Facilities with combined Fusion Nuclear Science (FNS) and Pilot Plant missions to provide both the nuclear environment needed to develop fusion materials and components while also potentially achieving sufficient fusion performance to generate modest net electrical power are considered. The performance of the tokamak fusion system is assessed using a range of core physics and toroidal field magnet performance constraints to better understand which parameters most strongly influence the achievable fusion performance.
Antony, James W.; Cheng, Larry Y.; Brooks, Paula P.; Paller, Ken A.; Norman, Kenneth A.
Competition between memories can cause weakening of those memories. Here we investigated memory competition during sleep in human participants by presenting auditory cues that had been linked to two distinct picture-location pairs during wake. We manipulated competition during learning by requiring participants to rehearse picture-location pairs associated with the same sound either competitively (choosing to rehearse one over the other, leading to greater competition) or separately; we hypothesized that greater competition during learning would lead to greater competition when memories were cued during sleep. With separate-pair learning, we found that cueing benefited spatial retention. With competitive-pair learning, no benefit of cueing was observed on retention, but cueing impaired retention of well-learned pairs (where we expected strong competition). During sleep, post-cue beta power (16–30 Hz) indexed competition and predicted forgetting, whereas sigma power (11–16 Hz) predicted subsequent retention. Taken together, these findings show that competition between memories during learning can modulate how they are consolidated during sleep.
Complete dataset of pore water chemical parameters measured at the Marsh Resource Meadowlands Mitigation Bank, a tidal marsh within the New Jersey Meadowlands, from March 2011 to April 2012. Analytes measured include dissolved methane, sulfate, dissolved organic carbon, temperature, salinity, and pH. Measurements were conducted using porewater dialysis samplers, and water was sampled from the surface to a depth of 60 cm.
Schwartz, Jacob A.; Ricks, Wilson; Kolemen, Egemen; Jenkins, Jesse D.
Fusion could be a part of future decarbonized electricity systems, but it will need to compete with other technologies.
In particular, pulsed tokamaks plants have a unique operational mode, and evaluating
which characteristics make them economically competitive can help select between design pathways.
Using a capacity expansion and operations model,
we determined cost thresholds for pulsed tokamaks to reach a range of penetration levels in a future decarbonized US Eastern Interconnection.
The required capital cost to reach a fusion capacity of 100 GW varied from $3000 to $7200/kW,
and the equilibrium penetration increases rapidly with decreasing cost.
The value per unit power capacity depends on the variable operational cost and on cost of its competition, particularly fission, much more than on the pulse cycle parameters.
These findings can therefore provide initial cost targets for fusion more generally in the United States.
Zhou, Mi; Peng, Liqun; Zhang, Lin; Mauzerall, Denise L.
This dataset is created for the paper titled 'Environmental Benefits and Household Costs of Clean Heating Options in Northern China' and published on Nature Sustainability. Based on a 2015 regional anthropogenic emission inventory (base case), we propose seven counterfactual scenarios in which all 2015 residential solid fuel heating in northern China switches to one of the following non-district heating options: clean coal with improved stoves (CCIS), natural gas heaters (NGH), resistance heaters (RH), or air-to-air heat pumps (AAHP). This dataset provides the following gridded information for the base case and each clean heating scenario: (1) annual residential heating emissions for PM2.5/NOx/SO2; (2) monthly mean surface PM2.5 concentrations from the WRF-Chem model; (3) annual PM2.5-related premature deaths calculated by the GEMM model; (4) 2015 population in China; (5) mask for provinces in China; (6) longitude and latitude of each grid center.
The dataset contains the model file for the Global Adjoint Tomography Model 25 (GLAD-M25). The model file contains parameters defined on the spectral-element mesh and is recommend to be used in SPECFEM3D GLOBE for seismic wave simulation at the global scale.
Chen, Xu; Li, Zhongshu; Gallagher, Kevin P.; Mauzerall, Denise L.
Power sector decarbonization requires a fundamental redirection of global finance from fossil fuel infrastructure towards low carbon technologies. Bilateral finance plays an important role in the global energy transition to non-fossil energy, but an understanding of its impact is limited. Here, for the first time, we compare the influence of overseas finance from the three largest economies – United States, China, and Japan – on power generation development beyond their borders and evaluate the associated long-term CO2 emissions. We construct a new dataset of Japanese and U.S. overseas power generation finance between 2000-2018 by analyzing their national development finance institutions’ press releases and annual reports and tracking their foreign direct investment at the power plant level. Synthesizing this new data with previously developed datasets for China, we find that the three countries’ overseas financing concentrated in fossil fuel power technologies over the studied period. Financing commitments from China, Japan, and the United States facilitated 101 GW, 95 GW, and 47 GW overseas power capacity additions, respectively. The majority of facilitated capacity additions are fossil fuel plants (64% for China, 87% for Japan, and 66% for the United States). Each of the countries’ contributions to non-hydro renewable generation was less than 15% of their facilitated capacity additions. Together, we estimate that overseas fossil fuel power financing through 2018 from these three countries will lock in 24 Gt CO2 emissions by 2060. If climate targets are to be met, replacing bilateral fossil fuel financing with financing of renewable technologies is crucial.
This dataset contains input and output files to reproduce the results of the manuscript "Homogeneous ice nucleation in an ab initio machine learning model" by Pablo M. Piaggi, Jack Weis, Athanassios Z. Panagiotopoulos, Pablo G. Debenedetti, and Roberto Car (arXiv preprint https://arxiv.org/abs/2203.01376). In this work, we studied the homogeneous nucleation of ice from supercooled liquid water using a machine learning model trained on ab initio energies and forces. Since nucleation takes place over times much longer than the simulation times that can be afforded using molecular dynamics simulations, we make use of the seeding technique that is based on simulating an ice cluster embedded in liquid water. The key quantity provided by the seeding technique is the size of the critical cluster (i.e., a size such that the cluster has equal probabilities of growing or shrinking at the given supersaturation). Using data from the seeding simulations and the equations of classical nucleation theory we compute nucleation rates that can be compared with experiments.
Gartner, Thomas III; Zhang, Linfeng; Piaggi, Pablo; Car, Roberto; Panagiotopoulos, Athanassios; Debenedetti, Pablo
This dataset contains all data related to the publication "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water", by Gartner et al., 2020. In this work, we used neural networks to generate a computational model for water using high-accuracy quantum chemistry calculations. Then, we used advanced molecular simulations to demonstrate evidence that suggests this model exhibits a liquid-liquid transition, a phenomenon that can explain many of water's anomalous properties. This dataset contains links to all software used, all data generated as part of this work, as well as scripts to generate and analyze all data and generate the plots reported in the publication.
This distribution contains experimentally measured data for the extent of retained enzyme activity post thermal stressing for three distinct enzymes: glucose oxidase, lipase, and horseradish peroxidase. The data is used to form conclusions and develop machine learning models as reported in the publication "Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids" by Matthew Tamasi, Roshan Patel, Carlos Borca, Shashank Kosuri, Heloise Mugnier, Rahul Upadhya, N. Sanjeeva Murthy, Michael Webb*, and Adam Gormley. Details regarding the experimental protocols are reported in the aforementioned paper but are briefly discussed in the README.
Data set corresponding to "NAPS: Integrating pose estimation and tag-based tracking." This dataset contains the corresponding videos, tracking scripts, and SLEAP models along with SLEAP, NAPS, and ArUco tracking results.
Pacheco, Diego A; Thiberge, Stephan; Pnevmatikakis, Eftychios; Murthy, Mala
Sensory pathways are typically studied starting at receptor neurons and following postsynaptic neurons into the brain. However, this leads to a bias in analysis of activity towards the earliest layers of processing. Here, we present new methods for volumetric neural imaging with precise across-brain registration, to characterize auditory activity throughout the entire central brain of Drosophila and make comparisons across trials, individuals, and sexes. We discover that auditory activity is present in most central brain regions and in neurons responsive to other modalities. Auditory responses are temporally diverse, but the majority of activity is tuned to courtship song features. Auditory responses are stereotyped across trials and animals in early mechanosensory regions, becoming more variable at higher layers of the putative pathway, and this variability is largely independent of spontaneous movements. This study highlights the power of using an unbiased, brain-wide approach for mapping the functional organization of sensory activity.