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At least 973 records · Page 54

Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study

Background: Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging, is also important for minimizing long-term effects of an outbreak. Objective: We used social media data from Twitter to identify human behaviors relevant to COVID-19 transmission, as well as the perceived impacts of COVID-19 on individuals, as a first step toward real-time monitoring of public perceptions to inform public health communications. Methods: We developed a coding schema for 6 categories and 11 subcategories, which included both a wide number of behaviors as well codes focused on the impacts of the pandemic (eg, economic and mental health impacts). We used this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that performed adequately were applied to our remaining corpus, and temporal and geospatial trends were assessed. We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. Results: We applied our labeling schema to approximately 7200 tweets. The worst-performing classifiers had F1 scores of only 0.18 to 0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, were much stronger, with F1 scores of 0.64 to 0.66. We applied the social distancing classifiers to over 228 million tweets. We showed temporal patterns consistent with real-world events, and we showed correlations of up to –0.5 between social distancing signals on Twitter and ground truth mobility throughout the United States. Conclusions: Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior, as well as for informing public health communication strategies by describing awareness of and compliance with suggested behaviors.

60 APPLIED LIFE SCIENCES↗

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗

Nematic Order, Plasmonic Switching and Self-Patterning of Colloidal Gold Bipyramids

Dispersing inorganic colloidal nanoparticles within nematic liquid crystals provides a versatile platform both for forming new soft matter phases and for predefining physical behavior through mesoscale molecular-colloidal self-organization. However, owing to formation of particle-induced singular defects and complex elasticity-mediated interactions, this approach has been implemented mainly just for colloidal nanorods and nanoplatelets, limiting its potential technological utility. Here, orientationally ordered nematic colloidal dispersions are reported of pentagonal gold bipyramids that exhibit narrow but controlled polarization-dependent surface plasmon resonance spectra and facile electric switching. Bipyramids tend to orient with their C 5 rotation symmetry axes along the nematic director, exhibiting spatially homogeneous density within aligned samples. Topological solitons, like heliknotons, allow for spatial reorganization of these nanoparticles according to elastic free energy density within their micrometer-scale structures. With the nanoparticle orientations slaved to the nematic director and being switched by low voltages ≈1 V within a fraction of a second, these plasmonic composite materials are of interest for technological uses like color filters and plasmonic polarizers, as well as may lead to the development of unusual nematic phases, like pentatic liquid crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Orbital Angular Momentum from Self‐Assembled Concentric Nanoparticle Rings

Abstract Ring‐shaped nanostructures can focus, filter, and manipulate electromagnetic waves, but are challenging to incorporate into devices using standard nanofabrication techniques. Directed self‐assembly (DSA) of block copolymers (BCPs) on lithographically patterned templates has successfully been used to fabricate concentric rings and spirals as etching masks. However, this method is limited by BCP phase behavior and material selection. Here, a straightforward approach to generate ring‐shaped nanoparticle assemblies in thin films of supramolecular nanocomposites is demonstrated. DSA is used to guide the formation of concentric rings with radii spanning 150–1150 nm and ring widths spanning 30–60 nm. When plasmonic nanoparticles are used, ring nanodevice arrays can be fabricated in one step, and the completed devices produce high‐quality orbital angular momentum (OAM). Nanocomposite DSA simplifies and streamlines nanofabrication by producing metal structures without etching or deposition steps; it also introduces interparticle coupling as a new design axis. Detailed analysis of the nanoparticle ring assemblies confirms that the supramolecular system self‐regulates the spatial distribution of its components, and thus exhibits a degree of flexibility absent in DSA of BCPs alone, where structures are determined by polymer‐pattern incommensurability. The present studies also provide guidelines for developing self‐regulating DSA as an alternative to incommensurability‐driven methods.

Vargo, Emma↗

Curvature-controlled geometrical lensing behavior in self-propelled colloidal particle systems

In many biological systems, the curvature of the surfaces cells live on influences their collective properties. Curvature should likewise influence the behavior of active colloidal particles. We show using molecular simulation of self-propelled active particles on surfaces of Gaussian curvature (both positive and negative) how curvature sign and magnitude can alter the system's collective behavior. Curvature acts as a geometrical lens and shifts the critical density of motility-induced phase separation (MIPS) to lower values for positive curvature and higher values for negative curvature, which we explain theoretically by the nature of parallel lines in spherical and hyperbolic space. Curvature also fluidizes dense MIPS clusters due to the emergence of defect patterns disrupting the crystalline order inside the clusters. Using our findings, we engineer three confining surfaces that strategically combine regions of different curvature to produce a host of novel dynamical behaviors, including cyclic MIPS on spherocylinders, directionally biased cyclic MIPS on spherocones, and position dependent cluster fluctuations on metaballs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of Quaternary Structure Transitions in R-State Carbonmonoxyhemoglobin Unveiled in Time-Resolved X-ray Scattering Patterns Following a Temperature Jump

It is well-known that tetrameric hemoglobin binds ligands cooperatively by undergoing a ligand-induced T → R quaternary structure transition, a structure-function relationship that has long served as a model system for understanding allostery in proteins. However, kinetic studies of the reverse, R → T quaternary structure transition following photolysis of carbonmonoxyhemoglobin (HbCO) reveal complex behavior that may be better explained by the presence of two different R quaternary structures coexisting in thermal equilibrium. Indeed, we report here time-resolved small- and wide-angle X-ray scattering (SAXS/WAXS) patterns of HbCO following a temperature jump that not only provide unambiguous evidence for more than one R state, but also unveil the time scale for interconversion between them. Since the time scale for the photolysis-induced R → T transition is likely different for different R-states, this structural heterogeneity must be accounted for to properly explain the kinetic heterogeneity observed in time-resolved spectroscopic studies following photolysis of HbCO.

Cho, Hyun Sun↗

The behavior of the Mg II lines near 2800 A in A, B, and O stars

The equivalent widths of the Mg II resonance doublet and their subordinate lines near 2800 A have been determined in ten stars of spectral types A through O. By combining the current results with previously published results for four F stars, it is found that the total equivalent widths of the Mg II lines follow a pattern and that the maximum in absorption strength occurs in late-A spectral type. Evidence of mass flow has been found in the Algol spectrum together with some other peculiarities. The general behavior of the Mg II lines in stars in this spectral range is also discussed.

Kondo, Y.↗

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗

Smoothed Particle Hydrodynamics pore-scale simulations of unstable immiscible flow in porous media

We have conducted a series of high-resolution numerical experiments using the Pair-Wise Force Smoothed Particle Hydrodynamics (PF-SPH) multiphase flow model. First, we derived analytical expressions relating parameters in the PF-SPH model to the surface tension and static contact angle. Next, we used the model to study viscous fingering, capillary fingering, and stable displacement of immiscible fluids in porous media for a wide range of capillary numbers and viscosity ratios. We demonstrated that the steady state saturation profiles and the boundaries of viscous fingering, capillary fingering, and stable displacement regions compare favorably with micromodel laboratory experimental results. For displacing fluid with low viscosity, we observed that the displacement pattern changes from viscous fingering to stable displacement with increasing injection rate. When a high viscosity fluid is injected, transition behavior from capillary fingering to stable displacement occurred as the flow rate was increased. These observation also agree with the results of the micromodel laboratory experiments.

Environmental Molecular Sciences Laboratory↗

Learning-based CO 2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

There have been increasing concerns over the air quality inside buildings as high levels of bio-effluents can cause nausea, dizziness, headaches, and fatigue to the people working in those spaces. First published in 2004 as Standard 62.1, ASHRAE Standard 62.2-2019 requires highly occupied spaces to implement heating, ventilation, and air conditioning (HVAC) that can dilute contaminants produced by occupants. In this regard, occupant-centric ventilation control has been regarded as an effective practice to maintain a satisfactory indoor air quality (IAQ) when dealing with highly variable occupancy environments. However, few established models in current literature and practice consider dynamic occupancy behavior and adaptive IAQ control. To address this gap, a dynamic indoor CO2 model is constructed using machine learning algorithms to forecast CO2concentrations across a range of forecasting horizons. Herein, we tuned and compared six state-of-the-algorithms—including Support Vector Machine, Ada Boost, Random Forest, Gradient Boosting, Logistic Regression, and Multilayer Perceptron. The algorithms’ performances are validated using CO 2 and historical meteorological data collected from a campus classroom with a variable occupancy rate. Simulation results showed that Multilayer Perceptron can strongly predict the volatile CO 2 behavior and also outperforms other algorithms in terms of accuracy. Furthermore, a control strategy capable of modeling and detecting dynamic patterns of CO 2 level is utilized to modulate the ventilation rate in real-time and also reduce the energy consumption. The proposed controller reduced the HVAC fan’s energy consumption by 51.4% and provide ventilation as needed per the ASHRAE standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Microfracture-pore structure characterization and water-rock interaction in three lithofacies of the Lower Eagle Ford Formation

The microfracture-pore structures and water-rock interactions of eight samples of three typical lithofacies (three limestone, three wackestone, and two mudstone) from the Lower Eagle Ford Formation have been investigated using an integrated methodology. The methods used were X-ray diffraction (XRD), total organic carbon (TOC) content, pyrolysis, thin-section petrography, scanning electron microscopy (SEM), mercury intrusion porosimetry (MIP), spontaneous water imbibition, and water vapor & nitrogen physisorption. Petrophysical properties such as organic richness, maturity, mineral composition, types and patterns of microfractures and pores, porosity, pore-throat size distribution, pore size distribution, pore connectivity, water adsorption and desorption behavior were determined from these methods, and the results compared among the three lithofacies. For example, the three limestone EAS samples and three wackestone DM samples show a low porosity range from 2.02–3.35%, whereas the two mudstone VRU samples exhibit a much large average porosity of 11.7% by MIP results. Nitrogen physisorption results show that pore size distributions have a good similarity in N2 adsorption volume for the samples with similar lithology. Microfractures are morphologically divided into seven types, with their definitions & pictorial examples presented and possible formation mechanisms proposed. In addition, the water vapor physisorption behavior and their controlling factors are discussed. Here, the water adsorption capacity shows a positive relationship (R 2 = 0.90) with clay content and a negative relationship (R 2 = 0.99) with carbonate content. In general, this integrated study of microfracture-pore structure characterization and water-rock interaction provides some insights of water vapor adsorption behavior in different lithofacies and whether microfractures could be an important pathway for fluid flow.

58 GEOSCIENCES↗

Hardenability and microstructural evolution of a precipitation strengthened Ni 50 Ti 21 Hf 25 Al 4 alloy

NiTi-based quaternary alloys are used in a variety of mechanical components, such as bearings, actuators, and dampers, owing to their good hardenability, wear resistance, and corrosion resistance. Additionally, one of the most notable characteristics of NiTi-based alloys is their shape memory effect and pseudoelastic properties. Connecting the macroscopic processing parameters employed in the design of new intermetallic alloys to the nanoscale structural characteristics dictating their behavior is crucial for improving their mechanical properties and expanding the spectrum of potential applications. Here, in this work, an arc melted Ni 50 Ti 21 Hf 25 Al 4 (at%) alloy was solution treated at 1050 °C followed by quenching and aging at 600 °C to investigate the effect of aging time on the microstructure and mechanical properties. Two types of nano-sized precipitates were observed and determined as face-centered orthorhombic H-phase (TiHf)Ni and L2 1 Heusler precipitates Ni 2 TiAl. The morphology and orientation of the H-phase were investigated using scanning and transmission electron microscopy (SEM and TEM), elucidating the coarsening kinetics and strengthening contribution of that phase to the intermetallic mechanical behavior. Following coarsening, the presence of Heusler nanoprecipitates was detected under overaged conditions through TEM imaging and nanobeam electron diffraction patterns. A peak hardness condition of 756 HV was achieved after 70 h of aging, indicating that the co-precipitation of H-phase and Heusler precipitates through a well-designed aging treatment can lead to optimal mechanical performance, thus elevating the alloy’s potential as a viable material for industrial applications.

36 MATERIALS SCIENCE↗

Understanding the effect of friction stir processing on electrical steel: Microstructural changes and mechanical transformations

Raising Si beyond 3.5 wt% reduces core loss but embrittles electrical steels, constraining processing and application. Here we assess friction stir processing (FSP) as a solid‑state route to enable Fe–4.0 wt% Si with improved mechanical performance. Temperature‑controlled FSP with a PcBN tool produced a defect‑free processed zone. SEM/EBSD revealed dynamic recrystallization and grain refinement from an average 110 μm in the base material to ∼20 μm in the processed region, with ∼ 80% of grains < 40 μm and a reduction in high‑angle boundary fraction to ∼65% (vs >85% in the base). Comparative mechanical property analysis shows a moderate increase in yield strength in FSP samples relative to the base material, with a significant improvement in ductility (∼35–50%). Post‑fracture EBSD identified 60° twin boundaries in the base while sub-grain formation with elevated KAM in the FSP sample. Fractography revealed a shift from quasi‑cleavage in the Base-faceted planes with river patterns, steps, and occasional secondary cracks—to ductile micro void coalescence after FSP. Following FSP, the material retains soft‑magnetic behavior, with modest shifts in saturation magnetization consistent with grain refinement and stored strain, accompanied by a clear gain in formability. These results indicate that FSP provides a viable route to deploy higher‑Si electrical steels with concurrent gains in strength and ductility.

Electrical steel↗

Complex Dependence of Calcite Crack Kinetics on Salinity: The Role of DLVO and Hydration Forces

Abstract Subcritical crack growth (SCG) plays an important role in many geological processes such as delayed earth rupture and rock weathering. The complex dependency of SCG on the in‐crack fluid chemistry, however, is still poorly understood. In this study, we utilize the newly developed surface force‐based fracture theory (SFFT) to elucidate the relative contributions of surface forces and solute transport to the crack growth kinetics of calcite in NaCl solutions. Expanding on Barenblatt's cohesive crack model, SFFT introduces an effective stress intensity at the crack tip that encompasses all the relevant intermolecular forces across the crack in addition to the external far‐field stresses. The nonlinear system of equations portraying the crack opening profile, the solute distribution in a propagating crack, and the crack growth velocity are numerically solved via an implicit scheme. After carefully calibrating the model for calcite‐water systems, the SFFT is used to predict the SCG response of calcite at different NaCl concentrations, based on various hypotheses. These predictions are then compared to existing SCG data from the literature. We demonstrate that the experimentally observed variation of SCG rate with NaCl concentration cannot be explained solely by DLVO forces (electrostatic and Van der Waals interactions). This can be remediated by introducing an exponentially decaying hydration force with a nonlinear, nonmonotonic dependence on NaCl concentration. Furthermore, we demonstrate that accounting for both diffusive and advective transport of ions is important in explaining the absence of a stage‐II SCG response for calcite in electrolyte solutions. Plain Language Summary Subcritical crack growth (SCG) refers to the slow propagation of cracks in materials under a stress below the threshold for catastrophic failure. SCG is a key process in many geological events, for example, delayed earth ruptures and rock weathering. New initiatives such as underground CO 2 and H 2 storage in carbonate reservoirs further call for better understanding of SCG in carbonate minerals subjected to varying fluid chemistry. This study examines the SCG of calcite, a key mineral found in carbonate rocks, intergranular cement in sandstones, and filling material in mineral veins and faults, determining their deformation and strength. A mathematical model is developed to describe how the crack opens and propagates, how solutes (like salts) distribute within the crack, and how the crack surfaces interact with each other. We used the model to predict calcite SCG in water at different salt concentrations and compared it with experimental data. Our results revealed that the hydration force is the dominating factor in determining the complex, non‐linear dependency of SCG on salinity. We also found that both the movement of ions by diffusion and by bulk water flow are crucial for explaining the SCG rates, especially when the cracks grow quickly. Key Points Surface Force‐Based Fracture Theory predicts the complex subcritical crack growth patterns of calcite crystals immersed in NaCl solutions Results highlight the dominant role of hydration forces in altering the fracture behavior of calcite compared to VdW and electric double‐layer forces Advective solute transport explains the absence of stages‐II and ‐III subcritical crack growth responses in solid‐liquid systems

DLVO↗

Nanoscopy reveals surface-metallic black phosphorus

Black phosphorus (BP) is an emerging two-dimensional material with intriguing physical properties. It is highly anisotropic and highly tunable by means of both the number of monolayers and surface doping. Here, we experimentally investigate and theoretically interpret the near-field properties of a-few-atomic-monolayer nanoflakes of BP. We discover near-field patterns of bright outside fringes and a high surface polarizability of nanofilm BP consistent with its surface-metallic, plasmonic behavior at mid-infrared frequencies <1176 cm -1 . We conclude that these fringes are caused by the formation of a highly polarizable layer at the BP surface. This layer has a thickness of ~1 nm and exhibits plasmonic behavior. We estimate that it contains free carriers in a concentration of n≈1.1 × 10 20 cm -3 . Surface plasmonic behavior is observed for 10–40 nm BP thicknesses but absent for a 4-nm BP thickness. This discovery opens up a new field of research and potential applications in nanoelectronics, plasmonics and optoelectronics.

36 MATERIALS SCIENCE↗

FeCoSiBNbCu bulk metallic glass with large compressive deformability studied by time-resolved synchrotron X-ray diffraction

By adding 0.5 at. % Cu to the strong but brittle [(Fe{sub 0.5}Co{sub 0.5}){sub 0.75}Si{sub 0.05}B{sub 0.20}]{sub 96}Nb{sub 4} bulk metallic glass, fully amorphous rods with diameters up to 2 mm were obtained. The monolithic samples with 1 mm diameter revealed a fracture strain of 3.80% and a maximum stress of 4143 MPa upon compression, together with a slight work-hardening behavior. SEM micrographs of fractured samples did neither reveal any shear bands on the lateral surface nor the typical vein patterns which characterize ductile fracture. However, some layers appear to have flowed and this phenomenon took place before the brittle final fracture. An estimate of the temperature rise ΔT in the shear plane gives 1039 K, which is large enough to melt a layer of 120 nm. The overall performance and the macroscopic plastic strain depend on the interaction between cleavage-like and viscous flow-like features. Mechanical tests performed in-situ under synchrotron radiation allowed the calculation of the strain tensor components, using the reciprocal-space data and analyzing the shift of the first (the main) and the second broad peak positions in the X-ray diffraction patterns. The results revealed that each atomic shell may have a different stiffness, which may explain the macroscopic compressive plastic deformation. Also, there were no signs of (nano) crystallization induced by the applied stress, but the samples preserve a monolithic amorphous structure until catastrophic failure occurs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗