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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]↗
DOE OSTI2026

Secondary-Side Active Rectifier Synchronization and Control in LCC-LC Compensated Inductive Power Transfer Systems

This paper proposes a communication-less synchronization and output power control strategy for LCC-LC compensated inductive power transfer systems with a secondaryside active rectifier. By replacing the passive rectifier with an active bridge, the proposed architecture eliminates the need for a separate secondary-side DC-DC converter and enables direct regulation of battery power. The key challenge in such a system is achieving robust synchronization of the secondary active bridge with the primary inverter without access to primary-side signals. To address this issue, the secondary-side variables are analyzed and the current through the secondary series inductor is identified as a load-independent synchronization variable with a fixed phase relationship to the primary excitation. A fixed-frequency second order generalized (SOGI)-based phase locked loop (PLL) is used to estimate the switching phase and frequency, and a phase-shift-based output power controller is developed using a phasor-transformer model of the active bridges. A modified control formulation is further introduced to remove phase-dependent loop-gain variation and simplify controller design. Simulation results validate the proposed method under both fixed and varying switching-frequency conditions, demonstrating successful frequency tracking from 82 kHz to 88 kHz and accurate output power regulation over a wide operating range. The proposed method offers a compact and effective solution for high-power IPT systems by enabling secondary-side synchronization and control without wireless communication or an additional DC-DC conversion stage.

Fernandes, Arnold Anthony [ORNL] (ORCID:0009000631↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2026

Elongation Factor Tu Acts as a Chaperone to Activate an Antibacterial RNase Toxin

Many Gram-negative bacterial species use contact-dependent growth inhibition (CDI) systems to deliver toxic proteins into neighboring competitors. CDI + strains deploy CdiA effector proteins, which translocate their C-terminal toxin (CT) domains into target bacteria through a receptor-mediated delivery pathway. To protect against auto-intoxication, CDI + bacteria also produce CdiI immunity proteins that neutralize CT toxin activity. Here, we present the crystal structure of the CT·CdiI O32:H37 complex from Escherichia coli O32:H37. CT O32:H37 adopts the same fold as the tRNase domain of colicin D, and the nucleases share similar catalytic centers. However, unlike colicin D, which cleaves the anticodon loops of tRNA Arg isoacceptors, CT O32:H37 exhibits nonspecific RNase activity. Notably, we find that endogenous elongation factor Tu (EF-Tu) co-purifies with the over-produced CT·CdiI O32:H37 complex. Although EF-Tu does not bind stably to CT O32:H37 in the absence of CdiI O32:H37 , the translation factor is required for toxic RNase activity in vitro. AlphaFold 3 modeling and site-directed mutagenesis indicate that CT O32:H37 interacts with the N-terminal GTPase domain of EF-Tu. EF-Tu appears to stabilize residue Trp52 within the hydrophobic core of the toxin, which in turn supports the RNase active site through an unusual hydrogen-bonding interaction with the catalytic His67 residue. Furthermore, EF-Tu is hijacked as an essential co-factor to organize the toxin's catalytic center.

Nhan, Dinh Quan [University of California, Santa B↗
DOE OSTI2023

Microscopic activated dynamics theory of the shear rheology and stress overshoot in ultradense glass-forming fluids and colloidal suspensions

We formulate a particle and force level, activated dynamics-based statistical mechanical theory for the continuous startup nonlinear shear rheology of ultradense glass-forming hard sphere fluids and colloidal suspensions in the context of the elastically collective nonlinear Langevin equation approach and a generalized Maxwell model constitutive equation. Activated structural relaxation is described as a coupled local-nonlocal event involving caging and longer range collective elasticity which controls the characteristic stress relaxation time. Theoretical predictions for the deformation-induced enhancement of mobility, the onset of relaxation acceleration at remarkably low values of stress, strain, or shear rate, apparent power law thinning of the steady-state structural relaxation time and viscosity, a nonvanishing activation barrier in the shear thinning regime, an apparent Herschel–Buckley form of the shear rate dependence of the steady-state shear stress, exponential growth of different measures of a yield or flow stress with packing fraction, and reduced fragility and dynamic heterogeneity under deformation were previously shown to be in good agreement with experiments. The central new question we address here is the defining feature of the transient response—the stress overshoot. In contrast to the steady-state flow regime, understanding the transient response requires an explicit treatment of the coupled nonequilibrium evolution of structure, elastic modulus, and stress relaxation time. We formulate a new quantitative model for this aspect in a physically motivated and computationally tractable manner. Theoretical predictions for the stress overshoot are shown to be in good agreement with experimental observations in the metastable ultradense regime of hard sphere colloidal suspensions as a function of shear rate and packing fraction, and accounting for deformation-assisted activated motion appears to be crucial for both the transient and steady-state responses.

Mechanics↗
DOE OSTI2021

Structure of the phosphoinositide 3-kinase (PI3K) p110γ-p101 complex reveals molecular mechanism of GPCR activation

The class IB phosphoinositide 3-kinase (PI3K), PI3Kγ, is a master regulator of immune cell function and a promising drug target for both cancer and inflammatory diseases. Critical to PI3Kγ function is the association of the p110γ catalytic subunit to either a p101 or p84 regulatory subunit, which mediates activation by G protein–coupled receptors. Here, we report the cryo–electron microscopy structure of a heterodimeric PI3Kγ complex, p110γ-p101. This structure reveals a unique assembly of catalytic and regulatory subunits that is distinct from other class I PI3K complexes. p101 mediates activation through its Gβγ-binding domain, recruiting the heterodimer to the membrane and allowing for engagement of a secondary Gβγ-binding site in p110γ. Mutations at the p110γ-p101 and p110γ–adaptor binding domain interfaces enhanced Gβγ activation. A nanobody that specifically binds to the p101-Gβγ interface blocks activation, providing a novel tool to study and target p110γ-p101–specific signaling events in vivo.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Gating choreography and mechanism of the human proton-activated chloride channel $\mathrm{ASOR}$

The proton-activated chloride channel ASOR (TMEM206/PAC) permeates anions across cellular membranes in response to acidification, thereby enhancing acid-induced cell death and regulating endocytosis. The molecular mechanisms of pH-dependent control are not understood, in part because structural information for an activated conformation of ASOR is lacking. Here, we reconstitute function from purified protein and present a 3.1-Å-resolution cryo–electron microscopy structure of human ASOR at acidic pH in an activated conformation. The work contextualizes a previous acidic pH structure as a desensitized conformation. Combined with electrophysiological studies and high-resolution structures of resting and desensitized states, the work reveals mechanisms of proton sensing and ion pore gating. Clusters of extracellular acidic residues function as pH sensors and coalesce when protonated. Ensuing conformational changes induce metamorphosis of transmembrane helices to fashion an ion conduction pathway unique to the activated conformation. The studies identify a new paradigm of channel gating in this ubiquitous ion channel.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Lytic polysaccharide monooxygenase increases cellobiohydrolases activity by promoting decrystallization of cellulose surface

Efficient depolymerization of crystalline cellulose requires cooperation between multiple cellulolytic enzymes. Through biochemical approaches, molecular dynamics (MD) simulation, and single-molecule observations using high-speed atomic force microscopy (HS-AFM), we quantify and track synergistic activity for cellobiohydrolases (CBHs) with a lytic polysaccharide monooxygenase (LPMO) from Phanerochaete chrysosporium. Increasing concentrations of LPMO (AA9D) increased the activity of a glycoside hydrolase family 6 CBH, Cel6A, whereas the activity of a family 7 CBH (Cel7D) was enhanced only at lower concentrations of AA9D. MD simulation suggests that the result of AA9D action to produce chain breaks in crystalline cellulose can oxidatively disturb the crystalline surface by disrupting hydrogen bonds. HS-AFM observations showed that AA9D increased the number of Cel7D molecules moving on the substrate surface and increased the processivity of Cel7D, thereby increasing the depolymerization performance, suggesting that AA9D not only generates chain ends but also amorphizes the crystalline surface, thereby increasing the activity of CBHs.

09 BIOMASS FUELS↗
DOE OSTI2024

Surface molecular pump enables ultrahigh catalyst activity

The performance of electrocatalysts is critical for renewable energy technologies. While the electrocatalytic activity can be modulated through structural and compositional engineering following the Sabatier principle, the insufficiently explored catalyst-electrolyte interface is promising to promote microkinetic processes such as physisorption and desorption. By combining experimental designs and molecular dynamics simulations with explicit solvent in high accuracy, we demonstrated that dimethylformamide can work as an effective surface molecular pump to facilitate the entrapment of oxygen and outflux of water. Dimethylformamide disrupts the interfacial network of hydrogen bonds, leading to enhanced activity of the oxygen reduction reaction by a factor of 2 to 3. This strategy works generally for platinum-alloy catalysts, and we introduce an optimal model PtCuNi catalyst with an unprecedented specific activity of 21.8 ± 2.1 mA/cm 2 at 0.9 V versus the reversible hydrogen electrode, nearly double the previous record, and an ultrahigh mass activity of 10.7 ± 1.1 A/mg Pt .

Science & Technology - Other Topics↗
DOE OSTI2020

Topological structure and dynamics of three-dimensional active nematics

Topological structures are effective descriptors of the nonequilibrium dynamics of diverse many-body systems. For example, motile, point-like topological defects capture the salient features of two-dimensional active liquid crystals composed of energy-consuming anisotropic units. We dispersed force-generating microtubule bundles in a passive colloidal liquid crystal to form a three-dimensional active nematic. Light-sheet microscopy revealed the temporal evolution of the millimeter-scale structure of these active nematics with single-bundle resolution. The primary topological excitations are extended, charge-neutral disclination loops that undergo complex dynamics and recombination events. Our work suggests a framework for analyzing the nonequilibrium dynamics of bulk anisotropic systems as diverse as driven complex fluids, active metamaterials, biological tissues, and collections of robots or organisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Potent targeted activator of cell kill molecules eliminate cells expressing HIV-1

Antiretroviral therapy inhibits HIV-1 replication but is not curative due to establishment of a persistent reservoir after virus integration into the host genome. Reservoir reduction is therefore an important HIV-1 cure strategy. Some HIV-1 nonnucleoside reverse transcriptase inhibitors induce HIV-1 selective cytotoxicity in vitro but require concentrations far exceeding approved dosages. Focusing on this secondary activity, we found bifunctional compounds with HIV-1–infected cell kill potency at clinically achievable concentrations. These targeted activator of cell kill (TACK) molecules bind the reverse transcriptase–p66 domain of monomeric Gag-Pol and act as allosteric modulators to accelerate dimerization, resulting in HIV-1 + cell death through premature intracellular viral protease activation. TACK molecules retain potent antiviral activity and selectively eliminate infected CD4 + T cells isolated from people living with HIV-1, supporting an immune-independent clearance strategy.

Cell Biology↗
DOE OSTI2021

CD8 Lymphocyte Depletion Enhances the Latency Reversal Activity of the SMAC Mimetic AZD5582 in ART-Suppressed Simian Immunodeficiency Virus-Infected Rhesus Macaques

ABSTRACT Inducing latency reversal to reveal infected cells to the host immune system represents a potential strategy to cure human immunodeficiency virus (HIV) infection. In separate studies, we have shown previously that CD8 + T cells may contribute to the maintenance of viral latency and have identified a novel SMAC (second mitochondrial activator of caspases) mimetic/IAP (inhibitor of apoptosis protein) inhibitor (AZD5582) capable of reversing HIV/simian immunodeficiency virus (SIV) latency in vivo by activating the noncanonical (nc) NF-κB pathway. Here, we use AZD5582 in combination with antibody (Ab)-mediated depletion of CD8α + cells to further evaluate the role of CD8 + T cells in the maintenance of viral latency. Six rhesus macaques (RMs) were infected with SIV mac239 and treated with antiretroviral therapy (ART) starting at week 8 postinfection. After 84 to 85 weeks of ART, all animals received a single dose of the anti-CD8α depleting Ab MT807R1 (50 mg/kg of body weight, administered subcutaneously [s.c.]), followed by five weekly doses of AZD5582 (0.1 mg/kg, administered intravenously [i.v.]). Following combined treatment with CD8α depletion and AZD5582, 100% of RMs experienced on-ART viremia levels above 60 copies per ml of plasma. In comparator groups of SIV-infected, ART-suppressed RMs treated with AZD5582 only or CD8α depletion only, on-ART viremia was experienced by 56% and 57% of the animals, respectively. Furthermore, the increased frequency of viremic episodes during the treatment period was greater in the group treated with CD8α depletion plus AZD5582 than in the other groups. Mathematical modeling of virus reactivation suggested that in addition to viral dynamics during acute infection, CD8α depletion influenced the response to AZD5582. This work suggests that the latency reversal induced by activation of the ncNF-κB signaling pathway with AZD5582 can be enhanced by CD8α + cell depletion. IMPORTANCE A favored approach to curing HIV infection aims at inducing viral expression using latency-reversing agents (LRAs) to allow the elimination of infected cells. Here, we tested a combination of two recently identified LRAs, the SMAC mimetic/IAP inhibitor AZD5582, which activates the noncanonical NF-κB pathway, and the antibody (Ab) MT807R1, which depletes CD8α + cells, in SIV-infected rhesus macaques (RMs) on ART. Latency reversal, as defined by increased on-ART viremia, was observed in all six SIV-infected, ART-treated RMs that received this combined treatment. Furthermore, comparison of viral reactivation between these animals and groups of SIV-infected, ART-treated RMs treated with AZD5582 only or CD8α + cell depletion only showed more frequent increases in viremic episodes when the two treatments were combined. This study provides additional evidence that CD8 + T cells may contribute to the maintenance of HIV/SIV latency on ART and potentially inhibit latency reversal during HIV cure approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Direct Observation of the Dynamics of Single-Cell Metabolic Activity during Microbial Diauxic Growth

Understanding how genetic information is realized as the behavior of individual cells is a long-term goal of biology but represents a significant technological challenge. In clonal microbial populations, variation in gene regulation is often interpreted as metabolic heterogeneity. This follows the central dogma of biology, in which information flows from DNA to RNA to protein and ultimately manifests as activity. At present, DNA and RNA can be characterized in single cells, but the abundance and activity of proteins cannot. Inferences about metabolic activity usually therefore rely on the assumption that transcription reflects activity. By tracking the atoms from which they build their biomass, we make direct observations of growth rate and substrate specialization in individual cells throughout a period of growth in a changing environment. This approach allows the flow of information from DNA to be constrained from the distal end of the regulatory cascade and will become an essential tool in the rapidly advancing field of single-cell metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Heterologous expression of a fully active Azotobacter vinelandii nitrogenase Fe protein in Escherichia coli

ABSTRACT The functional versatility of the Fe protein, the reductase component of nitrogenase, makes it an appealing target for heterologous expression, which could facilitate future biotechnological adaptations of nitrogenase-based production of valuable chemical commodities. Yet, the heterologous synthesis of a fully active Fe protein of Azotobacter vinelandii ( Av NifH) in Escherichia coli has proven to be a challenging task. Here, we report the successful synthesis of a fully active Av NifH protein upon co-expression of this protein with Av IscS/U and Av NifM in E. coli . Our metal, activity, electron paramagnetic resonance, and X-ray absorption spectroscopy/extended X-ray absorption fine structure (EXAFS) data demonstrate that the heterologously expressed Av NifH protein has a high [Fe 4 S 4 ] cluster content and is fully functional in nitrogenase catalysis and assembly. Moreover, our phylogenetic analyses and structural predictions suggest that Av NifM could serve as a chaperone and assist the maturation of a cluster-replete Av NifH protein. Given the crucial importance of the Fe protein for the functionality of nitrogenase, this work establishes an effective framework for developing a heterologous expression system of the complete, two-component nitrogenase system; additionally, it provides a useful tool for further exploring the intricate biosynthetic mechanism of this structurally unique and functionally important metalloenzyme. IMPORTANCE The heterologous expression of a fully active Azotobacter vinelandii Fe protein (AvNifH) has never been accomplished. Given the functional importance of this protein in nitrogenase catalysis and assembly, the successful expression of AvNifH in Escherichia coli as reported herein supplies a key element for the further development of heterologous expression systems that explore the catalytic versatility of the Fe protein, either on its own or as a key component of nitrogenase, for nitrogenase-based biotechnological applications in the future. Moreover, the “clean” genetic background of the heterologous expression host allows for an unambiguous assessment of the effect of certain nif-encoded protein factors, such as AvNifM described in this work, in the maturation of AvNifH, highlighting the utility of this heterologous expression system in further advancing our understanding of the complex biosynthetic mechanism of nitrogenase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Geochemistry and Multiomics Data Differentiate Streams in Pennsylvania Based on Unconventional Oil and Gas Activity

Unconventional oil and gas (UOG) extraction is increasing exponentially around the world, as new technological advances have provided cost-effective methods to extract hard-to-reach hydrocarbons. While UOG has increased the energy output of some countries, past research indicates potential impacts in nearby stream ecosystems as measured by geochemical and microbial markers. Here, we utilized a robust data set that combines 16S rRNA gene amplicon sequencing (DNA), metatranscriptomics (RNA), geochemistry, and trace element analyses to establish the impact of UOG activity in 21 sites in northern Pennsylvania. These data were also used to design predictive machine learning models to determine the UOG impact on streams. We identified multiple biomarkers of UOG activity and contributors of antimicrobial resistance within the order Burkholderiales. Furthermore, we identified expressed antimicrobial resistance genes, land coverage, geochemistry, and specific microbes as strong predictors of UOG status. Of the predictive models constructed (n = 30), 15 had accuracies higher than expected by chance and area under the curve values above 0.70. The supervised random forest models with the highest accuracy were constructed with 16S rRNA gene profiles, metatranscriptomics active microbial composition, metatranscriptomics active antimicrobial resistance genes, land coverage, and geochemistry (n = 23). The models identified the most important features within those data sets for classifying UOG status. These findings identified specific shifts in gene presence and expression, as well as geochemical measures, that can be used to build robust models to identify impacts of UOG development.

16S rRNA↗
DOE OSTI2020

Activities and risk factors associated with fall-related injuries among US Army soldiers

Introduction Falls/near falls are the second leading cause of hospitalisation and outpatient visits among US Army soldiers. While numerous studies have evaluated fall-related or near fall-related injuries among elderly adults, few have evaluated this association among young adults. The objective of this study is to describe the characteristics and risk factors associated with fall-related or near fall-related injuries among male US Army soldiers. Methods This is a cross-sectional study of male US Army Airborne Division soldiers (n=5187). Electronic surveys captured demographic, lifestyle, physical training (PT), fitness and injury data during spring/summer of 2016. Multiple logistic regression was used to identify independent risk factors of fall-related or near fall-related injuries, adjusting for potential confounders. Results Primary findings indicated that activities and risk factors associated with fall-related or near fall-related injuries among soldiers included younger age (≤35 years), holding a job that required minimal lifting activities, slower 2-mile run times and not running during personal PT. Conclusions The findings from this study suggest that male US Army soldiers and other physically active men may benefit from (1) obtaining and/or maintaining higher aerobic endurance and muscular strength, and (2) training focused on preventing fall-related injuries during PT, road marching and sports/recreational activities. Moreover, prevention strategies and education should further target younger soldiers (≤35 years old), as younger age is not modifiable.

General & Internal Medicine↗
DOE OSTI2023

Kinematics reconstruction in solenoidal spectrometers operated in active target mode

Here, we discuss the reconstruction of low-energy nuclear reaction kinematics from charged-particle tracks in solenoidal spectrometers working in Active Target Time Projection Chamber mode. In this operation mode, reaction products are tracked within the active gas medium of the Active Target with a three dimensional space point cloud. We have inferred the reaction kinematics from the point cloud using an algorithm based on a linear quadratic estimator (Kalman filter). The performance of this algorithm has been evaluated using experimental data from nuclear reactions measured with the Active Target Time Projection Chamber (AT-TPC) detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Activity Characterization for Modeling Behavioral-driven Human Mobility in Platial Networks

The population is increasingly becoming tractable as more and more people carry handheld devices as part of their everyday activities. Recent studies have shown that handheld devices' generated traffic share is now more than 50% of total global online traffic. This has created an unprecedented opportunity for modeling human mobility behavior. For example, aggregate check-ins and dwell time can reveal building level occupancies. However, there are clear limits to accurate modeling (e.g. reproducible, repeatable, and realistic), unless we decipher the underlying reason causing typical mobility patterns. We know that human behavior is a reflection of a set of activities, such as going to the gym or work, and which can be seen as a catalyst for humans to move from one location to another. This work envisions the use of activity characterization for modeling human mobility by introducing a context that maps activities to certain mobility patterns. In the end, we highlight the efficacy of the proposed approach by analyzing the impact of public policies surrounding stay at home order on human mobility.

Thakur, Gautam Malviya↗