Asymmetric drug binding in an ATP-loaded inward-facing state of an ABC transporter
Not provided.
Biochemistry & Molecular Biology↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Allosteric binding properties of a 1,3-alternate thiacalix[4]arene-based receptor having phenylthiourea and 2-pyridylmethyl moieties on opposite faces
The synthesis of three new heteroditopic receptors (5a–c) which are based on thiacalix[4]arenes in the 1,3-alternate conformation is reported herein. These new receptors each have two thiourea moieties linking phenyl groups, two of which are substituted with electron-withdrawing groups at their para-positions, and at the opposite side of the thiacalix[4]arene cavity, with two 2-pyridylmethyl groups. One example (5a) was also characterized by X-ray crystallography. A limited 1 H-NMR and UV-vis anion complexation study was conducted. DFT computational determinations indicated that 5c, which has strongly electron-withdrawing NO 2 groups, had the most effective recognition ability towards the selected anions. The binding of Ag + at the 2-pyridyl moieties, and the binding of the anions at the two thiourea NH groups of the p-substituted phenylthioureido moieties, respectively, was also investigated. The appearance of a positive allosteric effect with receptor 5b was also found using 1 H-NMR titration experiments.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learned interatomic potential for dispersion strengthened plasma facing components
Tungsten (W) is a material of choice for the divertor material due to its high melting temperature, thermal conductivity, and sputtering threshold. However, W has a very high brittle-to-ductile transition temperature, and at fusion reactor temperatures (≥1000 K), it may undergo recrystallization and grain growth. Dispersion-strengthening W with zirconium carbide (ZrC) can improve ductility and limit grain growth, but much of the effects of the dispersoids on microstructural evolution and thermomechanical properties at high temperatures are still unknown. We present a machine learned Spectral Neighbor Analysis Potential for W–ZrC that can now be used to study these materials. In order to construct a potential suitable for large-scale atomistic simulations at fusion reactor temperatures, it is necessary to train on ab initio data generated for a diverse set of structures, chemical environments, and temperatures. Further accuracy and stability tests of the potential were achieved using objective functions for both material properties and high temperature stability. Additionally, validation of lattice parameters, surface energies, bulk moduli, and thermal expansion is confirmed on the optimized potential. Tensile tests of W/ZrC bicrystals show that although the W(110)–ZrC(111) C-terminated bicrystal has the highest ultimate tensile strength (UTS) at room temperature, observed strength decreases with increasing temperature. At 2500 K, the terminating C layer diffuses into the W, resulting in a weaker W–Zr interface. Meanwhile, the W(110)–ZrC(111) Zr-terminated bicrystal has the highest UTS at 2500 K.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A Software Package for Plasma-Facing Component Analysis and Design: The Heat Flux Engineering Analysis Toolkit (HEAT)
Not Available
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Stronger weld than base metal in face-centered cubic alloy through multi-scale heterogeneity
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Shin, Dongwon [ORNL] (ORCID:0000000257973423)↗
Ion beam analysis of fusion plasma-facing materials and components: facilities and research challenges
Following the IAEA Technical Meeting on 'Advanced Methodologies for the Analysis of Materials in Energy Applications Using Ion Beam Accelerators', our work reviews the current status of ion beam analysis (IBA) techniques and some aspects of ion-induced radiation damage in materials for the field of materials relevant to fusion. Available facilities, apparatus development, future research options and challenges are presented and discussed. The analysis of beryllium and radioactivity-containing samples from future experiments in JET or ITER represents not only an analytical but also a technical challenge. A comprehensive list of the facilities, their current status, and analytical capabilities comes alongside detailed descriptions of the labs. A discussion of future issues of sample handling and the current status of facilities at JET complete the technical section. To prepare the international IBA community for these challenges, the IAEA technical meeting finalizes the necessity for determining new nuclear reaction cross-sections and improving the inter-laboratory comparability by defining international standards and testing these via a round-robin test.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Corrigendum and Addendum: Helium flux effects on bubble growth and surface morphology in plasma-facing tungsten from large-scale molecular dynamics simulations (2019 Nucl. Fusion 59 066035)
Two of the simulations discussed in a prior article (Hammond et al 2019 Nucl. Fusion 59 066035) were affected by a simulation glitch. We repeated the affected calculations and discuss them here. Here, the overall conclusions are essentially unchanged, though the details are different. In particular, observations that we referred to as ‘concerted bursting’ were caused primarily by non-physical heating and cooling applied by the thermostat after most atoms’ velocities were deleted (for reasons that are not known for certain). The phenomenon of one bubble bursting and causing another nearby bubble to burst does exist, though its effects are much less spectacular in the absence of non-physical driving forces. The observation of an interconnected network of sub-surface cavities formed by burst bubbles is real, and the observation of holes on the surface 1–2 nm in diameter is also confirmed.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Modern Senicide in the Face of a Pandemic: An Examination of Public Discourse and Sentiment About Older Adults and COVID-19 Using Machine Learning
Objectives This study examined public discourse and sentiment regarding older adults and COVID-19 on social media and assessed the extent of ageism in public discourse. Methods Twitter data (N = 82,893) related to both older adults and COVID-19 and dated from January 23 to May 20, 2020, were analyzed. We used a combination of data science methods (including supervised machine learning, topic modeling, and sentiment analysis), qualitative thematic analysis, and conventional statistics. Results The most common category in the coded tweets was “personal opinions” (66.2%), followed by “informative” (24.7%), “jokes/ridicule” (4.8%), and “personal experiences” (4.3%). The daily average of ageist content was 18%, with the highest of 52.8% on March 11, 2020. Specifically, more than 1 in 10 (11.5%) tweets implied that the life of older adults is less valuable or downplayed the pandemic because it mostly harms older adults. A small proportion (4.6%) explicitly supported the idea of just isolating older adults. Almost three-quarters (72.9%) within “jokes/ridicule” targeted older adults, half of which were “death jokes.” Also, 14 themes were extracted, such as perceptions of lockdown and risk. A bivariate Granger causality test suggested that informative tweets regarding at-risk populations increased the prevalence of tweets that downplayed the pandemic. Discussion Ageist content in the context of COVID-19 was prevalent on Twitter. Information about COVID-19 on Twitter influenced public perceptions of risk and acceptable ways of controlling the pandemic. Finaly, public education on the risk of severe illness is needed to correct misperceptions.
60 APPLIED LIFE SCIENCES↗
Theoretical antiferromagnetism of ordered face-centered cubic Cr-Ni alloys
Contrary to prior calculations, the Ni-rich ordered structures of the Cr-Ni alloy system are found to be antiferromagnetic under semilocal density-functional theory. The optimization of local magnetic moments significantly increases the driving force for the formation of CrNi 2 , the only experimentally observed intermetallic phase. This structure's ab initio magnetism appears well described by a Heisenberg Hamiltonian with longitudinal spin fluctuations; itinerant Cr moments are induced only by the strength of exchange interactions. The role of magnetism at temperature is less clear and several scenarios are considered based on a review of experimental literature, specifically a failure of the theory, the existence of an overlooked magnetic phase transition, and the coupling of antiferromagnetism to chemical ordering. In conclusion, implications for related commercial and high-entropy alloys are discussed for each case.
36 MATERIALS SCIENCE↗
Janus skyrmion: Interfacial quasiparticle with two-faced helicity
Janus particles are functional particles with at least two surfaces showing asymmetric properties. Here, we show at the interface between two magnetic regions with different antisymmetric exchange interactions, an alternative species of two-dimensional topological quasiparticles can emerge, in which different helicity structures can coexist. We name such an interfacial quasiparticle a “Janus skyrmion,” in analogy to the Janus particle. As the Janus skyrmion shows helicity asymmetry, its size could vary with both the in-plane and out-of-plane magnetic fields. A vertical spin current could drive the Janus skyrmion into one-dimensional motion along the interface without showing the skyrmion Hall effect, at a speed which depends on both the in-plane spin-polarization direction and current density. Thermal fluctuations could also lead to one-dimensional random walk of a Brownian Janus skyrmion. This work uncovers unique dynamics intrinsic to interfacial quasiparticles with exotic helicity, which may be realized in interface-engineered magnetic layers.
36 MATERIALS SCIENCE↗
Investigation of Materials for Radio Frequency Antenna Plasma Facing Components
Here, the interaction of radio frequency (RF) sheaths with fusion reactor relevant materials (e.g., tungsten and titanium diboride) is being studied on the RF Plasma Interaction Experiment (RF PIE). The RF PIE consists of an electron cyclotron resonance (ECR) plasma source (2.45 GHz, 5 kW) with a biased and heated RF electrode that is used to simulate antenna surfaces in contact with the edge plasma. Helium plasmas (density of ~1e18/m 3 , electron temperature of 4–5 eV) are being used to explore sheath formation on material surfaces with biases up to 500 V. The erosion of a tungsten surface is being studied spectroscopically using a mirror-linked 1 m Czerny-Turner UV imaging spectrometer with a spectral resolution of 0.012 nm for measuring plasma emission in and near the sheath. Tungsten line emission intensity is higher for RF versus dc biasing for similar plasma conditions and average ion energy. RF biasing causes a broadening of the ion energy distribution function (IEDF) due to the RF sheath, as determined from the hPIC2 code, and results in enhanced sputtering. Calculations of the expected sputtering yield for dc and RF biasing are consistent with experimental observations of changes in the 400.9 nm tungsten line emission intensity as a function of ion energy.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
FOXO3 targets are reprogrammed as Huntington's disease neural cells and striatal neurons face senescence with p16 INK4a increase
Neurodegenerative diseases (ND) have been linked to the critical process in aging-cellular senescence. However, the temporal dynamics of cellular senescence in ND conditions is unresolved. Here, we show senescence features develop in human Huntington's disease (HD) neural stem cells (NSCs) and medium spiny neurons (MSNs), including the increase of p16 INK4a , a key inducer of cellular senescence. We found that HD NSCs reprogram the transcriptional targets of FOXO3, a major cell survival factor able to repress cell senescence, antagonizing p16 INK4a expression via the FOXO3 repression of the transcriptional modulator ETS2. Additionally, p16 INK4a promotes cellular senescence features in human HD NSCs and MSNs. These findings suggest that cellular senescence may develop during neuronal differentiation in HD and that the FOXO3-ETS2-p16 INK4a axis may be part of molecular responses aimed at mitigating this phenomenon. Our studies identify neuronal differentiation with accelerated aging of neural progenitors and neurons as an alteration that could be linked to NDs.
59 BASIC BIOLOGICAL SCIENCES↗
Acoustic effects of medical, cloth, and transparent face masks on speech signals
Not Available
Corey, Ryan M.↗
Building water resilience in the face of cascading wildfire risks
Severe wildfire is altering the natural and the built environment and posing risks to environmental and societal health and well-being, including cascading impacts to water systems and built water infrastructure. Research on wildfire-resilient water systems is growing but not keeping pace with the scale and severity of wildfire impacts, despite their intensifying threat. In this study, we evaluate the state of knowledge regarding wildfire-related hazards to water systems. We propose a holistic framework to assess interactions and feedback loops between water quality, quantity, and infrastructure hazards as determinants of post-fire water availability and access. Efforts to address the evolving threat of wildfires to water systems will require more interdisciplinary research on the complex relationships shaping wildfire’s threat to water availability and access. To support this, we need reliable long-term data availability, consistent metrics, greater research in shared contexts, more extensive research beyond the burn area, and multistakeholder collaboration on wildfire risks to water systems.
54 ENVIRONMENTAL SCIENCES↗
Architecture of the cytoplasmic face of the nuclear pore
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Bley, Christopher J.↗
Parameter Estimation for Electrode Degradation: Learning in the Face of Model-Experiment Discrepancies
Use of physics-based models to interpret battery degradation data over the course of cycling can provide deeper physical insight into the internal states of the system and how they evolve. We present a neural network trained on simulations generated by a previously published physics-based model for a lithium trivanadate (LVO) cathode to estimate parameters that evolve over the course of cycling. We focus on the robustness of the neural network through two case studies that probe different kinds of discrepancies between model and experiment: nonideal data and imperfect model. In the former, the experimental protocols do not meet the assumption made in the training data generated by the physics-based model, while in the latter, the physics-based model fails to describe all of the measured cathode behavior even under ideal conditions. When there is total model-experiment agreement, a neural network estimates parameters with improved accuracy compared to a maximum likelihood analysis using the same set of simulations. However, in both types of model-experiment discrepancy, the neural network returned biased parameter estimates. We introduce a data augmentation procedure into the neural network training to mitigate these effects and improve robustness, and employ it to estimate parameters for a cycling LVO cathode.
Mayilvahanan, Karthik S. (ORCID:0000000316282332)↗
TECHNOLOGY: A Lesson In LED Adoption: Understanding the hurdles faced by K–12 schools
PK-12 schools lag in upgrading fluorescent lighting. Surprised? So were we; spurring a journey to understand the reasons for lagging adoption of LED. During conversations with school facility managers and other lighting professionals the reasons became clearer. What follows is a synopsis of what has been uncovered so far, yet there remains much to learn. Here, these stories are not the product of imagination; they represent real experiences, real decisions, and real concerns from 9 school districts in 7 states from coast to coast.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Partner with a Third-Party Delivery Service or Not? A Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic
Amidst the COVID-19 pandemic, restaurants become more reliant on no-contact pick-up or delivery ways for serving customers. As a result, they need to make tactical planning decisions such as whether to partner with online platforms, to form their own delivery team, or both. In this paper, we develop an integrated prediction-decision model to analyze the profit of combining the two approaches and to decide the needed number of drivers under stochastic demand. We first use the susceptible-infected-recovered (SIR) model to forecast future infected cases in a given region and then construct an autoregressive-moving-average (ARMA) regression model to predict food-ordering demand. Using predicted demand samples, we formulate a stochastic integer program to optimize food delivery plans. We conduct numerical studies using COVID-19 data and food-ordering demand data collected from local restaurants in Nuevo Leon, Mexico, from April to October 2020, to show results for helping restaurants build contingency plans under rapid market changes. Our method can be used under unexpected demand surges, various infection/vaccination status, and demand patterns. Here, our results show that a restaurant can benefit from partnering with third-party delivery platforms when (i) the subscription fee is low, (ii) customers can flexibly decide whether to order from platforms or from restaurants directly, (iii) customers require more efficient delivery, (iv) average delivery distance is long, or (v) demand variance is high.
97 MATHEMATICS AND COMPUTING↗