cssi/SciSciGPT-SciSciNet huggingface dataset:
Delay-coordinate maps, coherence, and approximate spectra of evolution operators

The problem of data-driven identification of coherent observables of measure-preserving, ergodic dynamical systems is studied using kernel integral operator techniques. An approach is proposed whereby complex-valued observables with approximately cyclical behavior are constructed from a pair of eigenfunctions of integral operators built from delay-coordinate mapped data. It is shown that these observables are $$\varepsilon $$ -approximate eigenfunctions of the Koopman evolution operator of the system, with a bound $$\varepsilon $$ controlled by the length of the delay-embedding window, the evolution time, and appropriate spectral gap parameters. In particular, $$ \varepsilon $$ can be made arbitrarily small as the embedding window increases so long as the corresponding eigenvalues remain sufficiently isolated in the spectrum of the integral operator. It is also shown that the time-autocorrelation functions of such observables are $$\varepsilon $$ -approximate Koopman eigenvalues, exhibiting a well-defined characteristic oscillatory frequency (estimated using the Koopman generator) and a slowly decaying modulating envelope. The results hold for measure-preserving, ergodic dynamical systems of arbitrary spectral character, including mixing systems with continuous spectrum and no non-constant Koopman eigenfunctions in $$L^2$$ . Numerical examples reveal a coherent observable of the Lorenz 63 system whose autocorrelation function remains above 0.5 in modulus over approximately 10 Lyapunov timescales.
The structure of the human cell cycle

ABSTRACT The human cell cycle is conventionally depicted as a five-phase model consisting of four proliferative phases (G1, S, G2, M) and a single state of arrest (G0). However, recent studies show that individual cells can take different paths through the cell cycle and exit into distinct arrest states, thus necessitating an update to the canonical model. We combined time lapse microscopy, highly multiplexed single cell imaging and manifold learning to determine the underlying “structure” of the human cell cycle under multiple growth and arrest conditions. By visualizing the cell cycle as a complete biological process, we identified multiple points of divergence from the proliferative cell cycle into distinct states of arrest, revealing multiple mechanisms of cell cycle exit and re-entry and the molecular routes to senescence, endoreduplication and polyploidy. These findings enable the visualization and comparison of alternative cell cycles in development and disease. One-sentence summary A systems-level view of single-cell states reveals the underlying architecture of the human cell cycle
Ultrasonic thickness measurement of nonporous membranes with long wavelengths.

Abstract A new thickness measurement technique is described in which air-coupled ultrasound is used to interrogate nonporous membranes at relatively long wavelengths. The thru-transmission technique compares a reference signal taken with the membrane absent to a material signal acquired when the membrane is present in the transducer’s wave field. The technique uses both amplitude and phase information from the signals’ frequency spectra to find the membrane’s thickness along with its surface density. No a priori knowledge of the membrane’s material properties is needed. The technique is experimentally verified by estimating the thicknesses of a number of metallic and non-metallic sheet-like materials. Thicknesses are typically measured to within 6% of their nominal values and the technique spans a range of roughly 10–100 μm.
Constraints on a massive double-copy and applications to massive gravity

We propose and study a BCJ double-copy of massive particles, showing that it is equivalent to a KLT formula with a kernel given by the inverse of a matrix of massive bi-adjoint scalar amplitudes. For models with a uniform non-zero mass spectrum we demonstrate that the resulting double-copy factors on physical poles and that up to at least 5-particle scattering, color-kinematics duality satisfying numerators always exist. For the scattering of 5 or more particles, the procedure generically introduces spurious singularities that must be cancelled by imposing additional constraints. When massive particles are present, color-kinematics duality is not enough to guarantee a physical double-copy. As an example, we apply the formalism to massive Yang-Mills and show that up to 4-particle scattering the double-copy construction generates physical amplitudes of a model of dRGT massive gravity coupled to a dilaton and a two-form with dilaton parity violating couplings. We show that the spurious singularities in the 5-particle double-copy do not cancel in this example, and the construction fails to generate physically sensible amplitudes. We conjecture sufficient constraints on the mass spectrum, which in addition to massive BCJ relations, guarantee the absence of spurious singularities.
Full structural ensembles of intrinsically disordered proteins from unbiased molecular dynamics simulations.

Molecular dynamics (MD) simulation is widely used to complement ensemble-averaged experiments of intrinsically disordered proteins (IDPs). However, MD often suffers from limitations of inaccuracy. Here, we show that enhancing the sampling using Hamiltonian replica-exchange MD (HREMD) led to unbiased and accurate ensembles, reproducing small-angle scattering and NMR chemical shift experiments, for three IDPs of varying sequence properties using two recently optimized force fields, indicating the general applicability of HREMD for IDPs. We further demonstrate that, unlike HREMD, standard MD can reproduce experimental NMR chemical shifts, but not small-angle scattering data, suggesting chemical shifts are insufficient for testing the validity of IDP ensembles. Surprisingly, we reveal that despite differences in their sequence, the inter-chain statistics of all three IDPs are similar for short contour lengths (< 10 residues). The results suggest that the major hurdle of generating an accurate unbiased ensemble for IDPs has now been largely overcome. Shrestha et al. show that enhancing the sampling using Hamiltonian replica exchange molecular simulation (HREMD) leads to accurate unbiased ensembles of intrinsically disordered proteins. They find that standard molecular simulation cannot reproduce small-angle scattering data as well as HREMD, highlighting the utility of the suggested approach.
Olfactory Impairment Is Related to Tau Pathology and Neuroinflammation in Alzheimer's Disease.

BACKGROUND Olfactory impairment is evident in Alzheimer's disease (AD); however, its precise relationships with clinical biomarker measures of tau pathology and neuroinflammation are not well understood. OBJECTIVE To determine if odor identification performance measured with the University of Pennsylvania Smell Identification Test (UPSIT) is related to in vivo measures of tau pathology and neuroinflammation. METHODS Cognitively normal and cognitively impaired participants were selected from an established research cohort of adults aged 50 and older who underwent neuropsychological testing, brain MRI, and amyloid PET. Fifty-four participants were administered the UPSIT. Forty-one underwent 18F-MK-6240 PET (measuring tau pathology) and fifty-three underwent 11C-PBR28 PET (measuring TSPO, present in activated microglia). Twenty-three participants had lumbar puncture to measure CSF concentrations of total tau (t-tau), phosphorylated tau (p-tau), and amyloid-β (Aβ42). RESULTS Low UPSIT performance was associated with greater18F-MK-6240 binding in medial temporal cortex, hippocampus, middle/inferior temporal gyri, inferior parietal cortex, and posterior cingulate cortex (p < 0.05). Similar relationships were seen for 11C-PBR28. These relationships were primarily driven by amyloid-positive participants. Lower UPSIT performance was associated with greater CSF concentrations of t-tau and p-tau (p < 0.05). Amyloid status and cognitive status exhibited independent effects on UPSIT performance (p < 0.01). CONCLUSION Olfactory identification deficits are related to extent of tau pathology and neuroinflammation, particularly in those with amyloid pathophysiology. The independent association of amyloid-positivity and cognitive impairment with odor identification suggests that low UPSIT performance may be a marker for AD pathophysiology in cognitive normal individuals, although impaired odor identification is associated with both AD and non-AD related neurodegeneration.NCT Registration Numbers: NCT03373604; NCT02831283.
Native point defects from stoichiometry-linked chemical potentials in cubic boron arsenide

The presence of a point defect typically breaks the stoichiometry in a semiconductor. For example, a vacancy on an A-site in an AB compound makes the crystal B-rich. As the stoichiometry changes, so do the chemical potentials. While the prevalent first-principles methods have provided significant insight into characters of point defects in a transparent manner, the crucial connection between crystal stoichiometry and chemical potentials is usually not made. However, ad hoc choices for chemical potentials can lead to nonphysical negative formation energies in some Fermi level ranges, along with questions about charge balance. Herein, we formulate a canonical framework describing how the chemical potential of each element is directly linked to the composition of the crystal under (off-)stoichiometric conditions instead of the ad hoc assumption that the chemical potential is the elemental limit under a certain growth condition. Consequently, the chemical potential changes with the Fermi level within the bandgap and the formation energies are positive. Using such an approach, we present ab initio results for native point defects in BAs, a semiconductor with ultrahigh room-temperature thermal conductivity. We find that antisites are the constitutional defects in off-stoichiometric material, while B As antisites and B vacancies dominate in the stoichiometric material. We further discuss the thermodynamic equilibrium and charge neutrality point in BAs in light of our stoichiometry-determined chemical potentials. As discussed, our work offers a more applicable and accessible approach to tackle defect formation energies in semiconductors, especially the ones with wide gap where negative formation energies are commonly seen.
Taking Access Seriously

Copyright is conventionally understood as serving the dual purposes of providing incentives for the creation of new works and access to the resulting works. In most analysis of copyright, however, creation takes priority. When access is considered, it is often in the context of how access relates back to the creation of new works. Largely missing is an account of the value of access on its own terms. So what is the place of access in copyright law and policy? A set of cases dealing with copyright owners’ attempts to enjoin the markets created by new playback and distribution technologies is instructive. These decisions—where the courts refused to enforce copyright where the owners attempted to shut down a market rather than participate in it—have been criticized for their unclear policy guidance and lack of doctrinal grounding. We can reconcile these cases with copyright policy by focusing on access. These cases provide rich examples showing how expanded access advances copyright’s higher-order goals of promoting a more democratic and participatory culture. Focusing on access also provides a means for bringing doctrinal coherence to these cases through the fair-use defense. The courts permitted the use of copyrighted works in new markets despite the copyright owners’ objections because these markets could expand public access without diminishing the copyright industries’ creative incentives. Indeed, copyright owners often found the markets profitable after being forced to enter them. Copyright owners’ market refusal in these scenarios is a distinct type of market failure, and fairuse doctrine allows courts to correct it.
Raf promotes dimerization of the Ras G-domain with increased allosteric connections.

Ras dimerization is critical for Raf activation. Here we show that the Ras binding domain of Raf (Raf-RBD) induces robust Ras dimerization at low surface densities on supported lipid bilayers and, to a lesser extent, in solution as observed by size exclusion chromatography and confirmed by SAXS. Community network analysis based on molecular dynamics simulations shows robust allosteric connections linking the two Raf-RBD D113 residues located in the Galectin scaffold protein binding site of each Raf-RBD molecule and 85 A apart on opposite ends of the dimer complex. Our results suggest that Raf-RBD binding and Ras dimerization are concerted events that lead to a high-affinity signaling complex at the membrane that we propose is an essential unit in the macromolecular assembly of higher order Ras/Raf/Galectin complexes important for signaling through the Ras/Raf/MEK/ERK pathway.
Bang the Can Slowly: An Investigation into the 2017 Houston Astros

This article is a statistical investigation into the 2017 Major League Baseball scandal involving the Houston Astros, the World Series championship winner that the same year. The Astros were allege...
Skin in the Game: Comparing the Private and Public Regulation of Isotretinoin

This paper engages in a comparative-institutional analysis of the private and public risk-management programs of the drug isotretinoin, which are designed to prevent the undesired effects isotretinoin has on fetal development. This case study sheds light on the comparative effectiveness of private and public regulation in the pharmaceutical and healthcare markets. A range of evidence indicates that the private risk management program successful in reducing pregnancies and educating patients about the harmful effects isotretinoin can have on a fetus. These findings challenge a consensus found in the medical literature that the private program needed to be supplanted and contain implications for future risk-management policy in healthcare.
Approximating Orbifold Spectra Using Collapsing Connected Sums

For a closed Riemannian orbifold O, we compare the spectra of the Laplacian, acting on functions or differential forms, to the Neumann spectra of the orbifold with boundary given by a domain U in O whose boundary is a smooth manifold. Generalizing results of several authors, we prove that the metric of O can be perturbed to ensure that the first N eigenvalues of U and O are arbitrarily close to one another. This involves a generalization of the Hodge decomposition to the case of orbifolds with manifold boundary. Using these results, we study the behavior of the Laplace spectrum on functions or forms of a connected sum of two Riemannian orbifolds as one orbifold in the pair is collapsed to a point. We show that the limits of the eigenvalues of the connected sum are equal to those of the noncollapsed orbifold in the pair. In doing so, we prove the existence of a sequence of orbifolds with singular points whose eigenvalue spectra come arbitrarily close to the spectrum of a manifold, and a sequence of manifolds whose eigenvalue spectra come arbitrarily close to the eigenvalue spectrum of an orbifold with singular points. We also consider the question of prescribing the first part of the spectrum of an orientable orbifold.
RANS-Based Aerodynamic Shape Optimization of a Wing Considering Propeller–Wing Interaction

The recent growth of interest in hybrid-electric and fully electric aircraft has led to a renewed focus on the design and optimization of propeller aircraft. Considering propeller–wing interaction ...
Lumbosacral interspinous ligament rupture associated with acute intrinsic spinal muscle degeneration.

Objective: To demonstrate lumbosacral interspinous ligament rupture, with or without related paraspinal muscle degeneration. Subjects and Methods: This study consisted of a prospective imaging analysis of 100 consecutive MRI studies in adult patients (mean age: 56 years) presenting with low back pain. Alterations from the normal in the inter- and perispinal structures of the spine and perispinal soft tissues (e.g. spinal ligaments, perispinal muscles) were sought based upon studies on young volunteers without low back pain (n = 10; mean age: 23 years). Results: Compared to the group without low back pain, many index cases (n = 71: 71%) demonstrated hyperintensity (i.e., sprain or frank ligamentous rupture) of the interspinous ligament(s) on T2-weighted, fat suppressed MRI studies at one (n = 20/71:28%) or multiple (n = 51/71:72%) levels. Associated paraspinal muscle (e.g., interspinalis, multifidus muscles) degeneration was observed in a minority of cases overall (n = 7: 7%), but was only seen in association with cases also demonstrating interspinous ligament degeneration/rupture (n = 7/71:10%). Conclusion: Lumbosacral interspinous ligament sprain or frank rupture, as well as related acute-subacute autotraumatic paraspinal muscle rupture/degeneration, may be overlooked by many observers if fat suppressed, T2-weighted MRI is not acquired. These musculoligamentous alterations are on occasion the only abnormalities recognized on MRI of the lumbosacral spine and may theoretically be sources of low back morbidity that potentially may respond to specific therapy. Because this study was an observational one, based solely upon medical imaging, future research must focus upon the correlation of the relevance of these findings with an age-matched asymptomatic control group and longitudinal clinicoradiologic therapeutic trials.
Copyright infringement and Peer-to-peer Technology

In this article, I will analyze the activities of peer-to-peer ("P2P") users to determine more precisely which, if any, of their actions infringe copyright. In Part II, I will describe the process of copyright lawmaking and the recent evolution of copyright law in response to technology. This discussion will include a brief description of conventional and P2P network technology. A copyright analysis of user activities on P2P networks follows in Part III, where I argue that the nature of copyright legislation requires courts to be especially careful and precise in determining the contours of infringing noncommercial conduct by members of the public. The analysis in Part II will lead to the conclusion that copying by P2P users does not infringe copyright, but distribution does. In Part IV, I address some strategic considerations affecting copyright enforcement and P2P networks, including some speculation about why the Napster case turned out the way it did, and why that is a problem. Finally, I propose the reinvigoration of Sony as a way to preserve the public benefit of P2P technology.
When is greenwashing an easy fix

Greenwashing has long been considered a viable strategy in the literature and academic research has explored its drivers from an institutional viewpoint. This paper extends the literature by consid...
Digital Health Passes in the Age of COVID-19: Are "Vaccine Passports" Lawful and Ethical?

As COVID-19 vaccination rates in high-income countries increase, governments are proposing or implementing digital health passes (DHPs) (vaccine “passports” or “certificates”). Israel uses a “green pass” smartphone application permitting vaccinated individuals’ access to public venues (eg, gyms, hotels, entertainment). The European Union plans a “Digital Green Certificate” enabling free travel within the bloc (see eTable in the Supplement). New York is piloting an IBM “Excelsior Pass,” confirming vaccination or negative SARS-CoV-2 test status through confidential data transfers to fast-track business reopenings. This paper examines the benefits of DHPs, scientific challenges, and whether they are lawful and ethical.
Fault-Tolerant Control of Degrading Systems with On-Policy Reinforcement Learning

Abstract We propose a novel adaptive reinforcement learning control approach for fault tolerant control of degrading systems that is not preceded by a fault detection and diagnosis step. Therefore, a priori knowledge of faults that may occur in the system is not required. The adaptive scheme combines online and offline learning of the on-policy control method to improve exploration and sample efficiency, while guaranteeing stable learning. The offline learning phase is performed using a data-driven model of the system, which is frequently updated to track the system’s operating conditions. We conduct experiments on an aircraft fuel transfer system to demonstrate the effectiveness of our approach.
Estimation of rheological parameters for unstained living cells

In video-records, objects moving in intracellular regions are often hardly detectable and identifiable. To squeeze the information on the intracellular flows, we propose an automatic method of reconstruction of intracellular flow velocity fields based only on a recorded video of an unstained cell. The basis of the method is detection of speeded-up robust features (SURF) and assembling them into trajectories. Two components of motion—direct and Brownian—are separated by an original method based on minimum covariance estimation. The Brownian component gives a spatially resolved diffusion coefficient. The directed component yields a velocity field, and after fitting the vorticity equation, estimation of the spatially distributed effective viscosity. The method was applied to videos of a human osteoblast and a hepatocyte. The obtained parameters are in agreement with the literature data.
A note on an asymptotic expansion related to the Dickman function

In this paper we refine an asymptotic expansion given by Soundararajan (Ramanujan J 29(1–3):25–30 2012) for a family of multiple integrals related to the Dickman function. The result suggests a relatively simple approach to computing these integrals numerically.
Debt is Not Free

With public debt soaring across the world, a growing concern is whether current debt levels are a harbinger of fiscal crises, thereby restricting the policy space in a downturn. The empirical evidence to date is however inconclusive, and the true cost of debt may be overstated if interest rates remain low. To shed light into this debate, this paper re-examines the importance of public debt as a leading indicator of fiscal crises using machine learning techniques to account for complex interactions previously ignored in the literature. We find that public debt is the most important predictor of crises, showing strong non-linearities. Moreover, beyond certain debt levels, the likelihood of crises increases sharply regardless of the interest-growth differential. Our analysis also reveals that the interactions of public debt with inflation and external imbalances can be as important as debt levels. These results, while not necessarily implying causality, show governments should be wary of high public debt even when borrowing costs seem low.
Semantic and phonological false memory: A review of theory and data

Abstract False memories typically share semantic or surface features with actual experiences, sometimes both. However, it is unclear whether false memories that are rooted in semantic versus surface resemblance obey the same laws. The Deese/Roediger/McDermott (DRM) illusion offers an attractive testbed for comparing semantic and surface false memories under closely matched conditions, owing to parallel semantic and phonological versions of the illusion. We review three lines of evidence in which semantic and phonological DRM illusions have been compared: (a) studies in which the two illusions were tracked in populations with different semantic or surface memory abilities; (b) studies that investigated the effects of manipulations that target semantic content or surface content or both; and (c) studies that examined hybrid forms of the illusion in which there was both semantic and surface resemblance between false memories and actual experiences. The three lines of evidence showed that semantic and phonological DRM illusions display dissociative patterns in most instances, indicating that they are two distinct types of false memories. The two major theories of the DRM illusion, fuzzy-trace theory and the activation/monitoring framework, have different views of the underlying mechanisms for the semantic and phonological illusions. We discuss the implications of this literature for the two theories.
SPARC: Simulation Package for Ab-initio Real-space Calculations

Abstract We present SPARC: Simulation Package for Ab-initio Real-space Calculations. SPARC can perform Kohn–Sham density functional theory calculations for isolated systems such as molecules as well as extended systems such as crystals and surfaces, in both static and dynamic settings. It is straightforward to install/use and highly competitive with state-of-the-art planewave codes, demonstrating comparable performance on a small number of processors and increasing advantages as the number of processors grows. Notably, SPARC brings solution times down to a few seconds for systems with O ( 100 – 500 ) atoms on large-scale parallel computers, outperforming planewave counterparts by an order of magnitude and more.
A Multi-Stage Stochastic Programming Approach to Epidemic Resource Allocation with Equity Considerations

Existing compartmental models in epidemiology are limited in terms of optimizing the resource allocation to control an epidemic outbreak under disease growth uncertainty. In this study, we address this core limitation by presenting a multi-stage stochastic programming compartmental model, which integrates the uncertain disease progression and resource allocation to control an infectious disease outbreak. The proposed multi-stage stochastic program involves various disease growth scenarios and optimizes the distribution of treatment centers and resources while minimizing the total expected number of new infections and funerals. We define two new equity metrics, namely infection and capacity equity, and explicitly consider equity for allocating treatment funds and facilities over multiple time stages. We also study the multi-stage value of the stochastic solution (VSS), which demonstrates the superiority of the proposed stochastic programming model over its deterministic counterpart. We apply the proposed formulation to control the Ebola Virus Disease (EVD) in Guinea, Sierra Leone, and Liberia of West Africa to determine the optimal and fair resource-allocation strategies. Our model balances the proportion of infections over all regions, even without including the infection equity or prevalence equity constraints. Model results also show that allocating treatment resources proportional to population is sub-optimal, and enforcing such a resource allocation policy might adversely impact the total number of infections and deaths, and thus resulting in a high cost that we have to pay for the fairness. Our multi-stage stochastic epidemic-logistics model is practical and can be adapted to control other infectious diseases in meta-populations and dynamically evolving situations.
Sigma-invariants and tropical varieties

The Bieri–Neumann–Strebel–Renz invariants $$\Sigma ^q(X,\mathbb {Z})\subset H^1(X,\mathbb {R})$$ of a connected, finite-type CW-complex X are the vanishing loci for Novikov–Sikorav homology in degrees up to q, while the characteristic varieties $$\mathcal {V}^q(X) \subset H^1(X,\mathbb {C}^{\times })$$ are the nonvanishing loci for homology with coefficients in rank 1 local systems in degree q. We show that each BNSR invariant $$\Sigma ^q(X,\mathbb {Z})$$ is contained in the complement of the tropical variety associated to the algebraic variety $$\mathcal {V}^{\le q}(X)$$ , and provide applications to several classes of groups and spaces.
Ordinal UNLOC: Target Localization With Noisy and Incomplete Distance Measures

A main challenge in target localization arises from the lack of reliable distance measures. This issue is especially pronounced in indoor settings due to the presence of walls, floors, furniture, and other dynamically changing conditions, such as the movement of people and goods, varying temperature and air flows. Here, we develop a new computational framework to estimate the location of a target without the need for reliable distance measures. The method, which we term Ordinal UNLOC, uses only ordinal data obtained from comparing the signal strength from anchor pairs at known locations to the target. Our estimation technique utilizes rank aggregation, function learning as well as proximity-based unfolding optimization. As a result, it yields accurate target localization for common transmission models with unknown parameters and noisy observations that are reminiscent of practical settings. Our results are validated by both numerical simulations and hardware experiments.
Hurdles to Progress in Long-form Question Answering

The task of long-form question answering (LFQA) involves retrieving documents relevant to a given question and using them to generate a paragraph-length answer. While many models have recently been proposed for LFQA, we show in this paper that the task formulation raises fundamental challenges regarding evaluation and dataset creation that currently preclude meaningful modeling progress. To demonstrate these challenges, we first design a new system that relies on sparse attention and contrastive retriever learning to achieve state-of-the-art performance on the ELI5 LFQA dataset. While our system tops the public leaderboard, a detailed analysis reveals several troubling trends: (1) our system’s generated answers are not actually grounded in the documents that it retrieves; (2) ELI5 contains significant train / validation overlap, as at least 81% of ELI5 validation questions occur in paraphrased form in the training set; (3) ROUGE-L is not an informative metric of generated answer quality and can be easily gamed; and (4) human evaluations used for other text generation tasks are unreliable for LFQA. We offer suggestions to mitigate each of these issues, which we hope will lead to more rigorous LFQA research and meaningful progress in the future.
NASA Stennis Space Center test technology branch activities

This paper provides a short history of NASA Stennis Space Center's Test Technology Laboratory and briefly describes the variety of engine test technology activities and developmental project initiatives. Theoretical rocket exhaust plume modeling, acoustic monitoring and analysis, hand held fire imaging, heat flux radiometry, thermal imaging and exhaust plume spectroscopy are all examples of current and past test activities that are briefly described. In addition, recent efforts and visions focused on accomodating second, third, and fourth generation flight vehicle engine test requirements are discussed.
Hovering Dual-Spin Vehicle Groundwork for Bias Momentum Sizing Validation Experiment

Angular bias momentum offers significant stability augmentation for hovering flight vehicles. The reliance of the vehicle on thrust vectoring for agility and disturbance rejection is greatly reduced with significant levels of stored angular momentum in the system. A methodical procedure for bias momentum sizing has been developed in previous studies. This current study provides groundwork for experimental validation of that method using an experimental vehicle called the Dual-Spin Test Device, a thrust-levitated platform. Using measured data the vehicle's thrust vectoring units are modeled and a gust environment is designed and characterized. Control design is discussed. Preliminary experimental results of the vehicle constrained to three rotational degrees of freedom are compared to simulation for a case containing no bias momentum to validate the simulation. A simulation of a bias momentum dominant case is presented.
Experimental and Computational Study of Tones Occurring with a Coaxial Nozzle

Tones were encountered in large-scale, multi-stream nozzle tests in the Aeoacoustics Propulsion Laboratory (AAPL). A different coaxial nozzle used in a past experiment also produced tones. In this paper, we present experimental and COMSOL results addressing the tone mechanism in the latter nozzle.
Graph Neural Networks with Heterophily.

Graph Neural Networks (GNNs) have proven to be useful for many different practical applications. However, many existing GNN models have implicitly assumed homophily among the nodes connected in the graph, and therefore have largely overlooked the important setting of heterophily, where most connected nodes are from different classes. In this work, we propose a novel framework called CPGNN that generalizes GNNs for graphs with either homophily or heterophily. The proposed framework incorporates an interpretable compatibility matrix for modeling the heterophily or homophily level in the graph, which can be learned in an end-to-end fashion, enabling it to go beyond the assumption of strong homophily. Theoretically, we show that replacing the compatibility matrix in our framework with the identity (which represents pure homophily) reduces to GCN. Our extensive experiments demonstrate the effectiveness of our approach in more realistic and challenging experimental settings with significantly less training data compared to previous works: CPGNN variants achieve state-of-the-art results in heterophily settings with or without contextual node features, while maintaining comparable performance in homophily settings.
Propulsion requirements for communications satellites

The concept of characteristics thrust is introduced herein as a means of classifying propulsion system tasks related particularly to geosynchronous communications spacecraft. Approximate analytical models are developed to permit estimation of characteristic thrust for injection error corrections, orbit angle re-location, north-south station keeping, east-west station keeping, spin axis precession control, attitude rate damping, and orbit raising applications. Performance assessment factors are then outlined in terms of characteristic power, characteristic weight, and characteristic volume envelope, which are related to the characteristic thrust. Finally, selected performance curves are shown for power as a function of spacecraft weight, including the influence of duty cycle on north-south station keeping, a 90 degree orbit angle re-location in 14 days, and finally comparison of orbit raising tasks from low and intermediate orbits to a final geosynchronous station. Power requirements range from less than 75 watts for north-south station keeping on small payloads up to greater than 15 KW for a 180 day orbit raising mission including a 28.5 degree plane change.
Widespread Race and Class Disparities in Surface Urban Heat Extremes Across the United States

Here we use 1000-m satellite land surface temperature anomaly measurements to explore the distribution of the United States' urban heating burden, both at high resolution (within cities or counties) and at scale (across the whole contiguous United States). While a rich literature has documented neighborhood-level disparities in urban heat exposures in individual cities, data constraints have precluded comparisons across locations. Here, drawing on extreme summer urban heat measurements from all 1056 U.S. counties with more than 10 developed census tracts, we find that the poorest tracts (and those with lowest average education levels) within a county are significantly hotter than the richest (and more educated) neighborhoods for 76% of these counties (54\% for education); we also find that neighborhoods with higher Black, Hispanic, and Asian population shares are hotter than the more White, non-Hispanic areas in each county. This holds in counties with both large and small spreads in these population shares, and for 71% of all counties the significant racial urban heat disparities persist even when adjusting for income. Although individual locations have different histories that have contributed to race- and class-based geographies, we find that the physical features of the urban environments driving these heat exposure gradients are fairly uniform across the country. Systematically, the disproportionate heat exposures faced by minority communities are due to higher population density, more built-up neighborhoods, and less vegetation.
Data-Driven Safety-Critical Control: Synthesizing Control Barrier Functions with Koopman Operators

Control barrier functions (CBFs) are a powerful tool to guarantee safety of autonomous systems, yet they rely on the computation of control invariant sets, which is notoriously difficult. A backup strategy employs an implicit control invariant set computed by forward integrating the system dynamics. However, this integration is prohibitively expensive for high dimensional systems, and inaccurate in the presence of unmodelled dynamics. We propose to learn discrete-time Koopman operators of the closed-loop dynamics under a backup strategy. This approach replaces forward integration by a simple matrix multiplication, which can mostly be computed offline. We also derive an error bound on the unmodeled dynamics in order to robustify the CBF controller. Our approach extends to multi-agent systems, and we demonstrate the method on collision avoidance for wheeled robots and quadrotors.
Knowledge Annotation for Intelligent Textbooks

With the increased popularity of electronic textbooks, there is a growing interest in developing a new generation of “intelligent textbooks,” which have the ability to guide readers according to their learning goals and current knowledge. Intelligent textbooks extend regular textbooks by integrating machine-manipulable knowledge, and the most popular type of integrated knowledge is a list of relevant concepts mentioned in the textbooks. With these concepts, multiple intelligent operations, such as content linking, content recommendation, or student modeling, can be performed. However, existing automatic keyphrase extraction methods, even supervised ones, cannot deliver sufficient accuracy to be practically useful in this task. Manual annotation by experts has been demonstrated to be a preferred approach for producing high-quality labeled data for training supervised models. However, most researchers in the education domain still consider the concept annotation process as an ad-hoc activity rather than a carefully executed task, which can result in low-quality annotated data. Using the annotation of concepts for the Introduction to Information Retrieval textbook as a case study, this paper presents a knowledge engineering method to obtain reliable concept annotations. As demonstrated by the data we collected, the inter-annotator agreement gradually increased along with our procedure, and the concept annotations we produced led to better results in document linking and student modeling tasks. The contributions of our work include a validated knowledge engineering procedure, a codebook for technical concept annotation, and a set of concept annotations for the target textbook, which could be used as a gold standard in further intelligent textbook research.
Techno-economic analysis of long-duration energy storage and flexible power generation technologies to support high-variable renewable energy grids

Summary As variable renewable energy penetration increases beyond 80%, clean power systems will require long-duration energy storage or flexible, low-carbon generation. Here, we provide a detailed techno-economic evaluation and uncertainty analysis of applicable technologies and identify challenges and opportunities to support electric grid planning. We show that for a 120-h storage duration rating, hydrogen systems with geologic storage and natural gas with carbon capture are the least-cost low-carbon technologies for both current and future capital costs. These results are robust to uncertainty for the future capital cost scenario, but adiabatic compressed air and pumped thermal storage could be the least-cost technologies in the current capital cost scenario under uncertainty. Finally, we present a new storage system using heavy-duty vehicle fuel cells that could reduce the levelized cost of energy by 13%–20% compared with the best previously considered storage technology and, thus, could help enable very high (>80%) renewable energy grids.
Synthesizing safe and efficient kernel extensions for packet processing

Extended Berkeley Packet Filter (BPF) has emerged as a powerful method to extend packet-processing functionality in the Linux operating system. BPF allows users to write code in high-level languages (like C or Rust) and execute them at specific hooks in the kernel, such as the network device driver. To ensure safe execution of a user-developed BPF program in kernel context, Linux uses an in-kernel static checker. The checker allows a program to execute only if it can prove that the program is crash-free, always accesses memory within safe bounds, and avoids leaking kernel data. BPF programming is not easy. One, even modest-sized BPF programs are deemed too large to analyze and rejected by the kernel checker. Two, the kernel checker may incorrectly determine that a BPF program exhibits unsafe behaviors. Three, even small performance optimizations to BPF code (e.g., 5% gains) must be meticulously hand-crafted by expert developers. Traditional optimizing compilers for BPF are often inadequate since the kernel checker's safety constraints are incompatible with rule-based optimizations. We present K2, a program-synthesis-based compiler that automatically optimizes BPF bytecode with formal correctness and safety guarantees. K2 produces code with 6--26% reduced size, 1.36%--55.03% lower average packet-processing latency, and 0--4.75% higher throughput (packets per second per core) relative to the best clang-compiled program, across benchmarks drawn from Cilium, Facebook, and the Linux kernel. K2 incorporates several domain-specific techniques to make synthesis practical by accelerating equivalence-checking of BPF programs by 6 orders of magnitude.
Multiple Modes of Regulation Control Dynamic Transcription Patterns During the Mitosis-G1 Transition

Following cell division, genomes must reactivate gene expression patterns that reflect the identity of the cell. Here, we use PRO-seq to examine the mechanisms that reestablish transcription patterns after mitosis. We uncover regulation of transcription cycle at multiple steps including initiation, promoter-proximal pause positioning and escape, poly-A site cleavage and termination during the mitotic-G1 transition. During mitosis, RNA polymerase activity is retained at initiation sites, albeit shifted in position relative to non-mitotic cells. This activity is strongly linked to maintenance of local chromatin architecture during mitosis and is more predictive of rapid gene reactivation than histone modifications previously associated with bookmarking. These molecular bookmarks, combined with sequence-specific transcription factors, direct expression of select cell growth and cell specific genes during mitosis followed by reactivation of functional gene groups with distinct kinetics after mitosis. This study details how dynamic regulation of transcription at multiple steps contributes to gene expression during the cell cycle.
Software-hardware co-optimization for computational chemistry on superconducting quantum processors

Computational chemistry is the leading application to demonstrate the advantage of quantum computing in the near term. However, large-scale simulation of chemical systems on quantum computers is currently hindered due to a mismatch between the computational resource needs of the program and those available in today’s technology. In this paper we argue that significant new optimizations can be discovered by co-designing the application, compiler, and hardware. We show that multiple optimization objectives can be coordinated through the key abstraction layer of Pauli strings, which are the basic building blocks of computational chemistry programs. In particular, we leverage Pauli strings to identify critical program components that can be used to compress program size with minimal loss of accuracy. We also leverage the structure of Pauli string simulation circuits to tailor a novel hardware architecture and compiler, leading to significant execution overhead reduction by up to 99%. While exploiting the high-level domain knowledge reveals significant optimization opportunities, our hardware/software framework is not tied to a particular program instance and can accommodate the full family of computational chemistry problems with such structure. We believe the co-design lessons of this study can be extended to other domains and hardware technologies to hasten the onset of quantum advantage.
Compressive time-lapse seismic monitoring of carbon storage and sequestration with the joint recovery model

Time-lapse seismic monitoring of carbon storage and sequestration is often challenging because the time-lapse signature of the growth of CO2 plumes is weak in amplitude and therefore difficult to detect seismically. This situation is compounded by the fact that the surveys are often coarsely sampled and not replicated to reduce costs. As a result, images obtained for different vintages (baseline and monitor surveys) often contain artifacts that may be attributed wrongly to time-lapse changes. To address these issues, we propose to invert the baseline and monitor surveys jointly. By using the joint recovery model, we exploit information shared between multiple time-lapse surveys. Contrary to other time-lapse methods, our approach does not rely on replicating the surveys to detect time-lapse changes. To illustrate this advantage, we present a numerical sensitivity study where CO2 is injected in a realistic synthetic model. This model is representative of the geology in the southeast of the North Sea, an area currently considered for carbon sequestration. Our example demonstrates that the joint recovery model improves the quality of time-lapse images allowing us to monitor the CO2 plume seismically.
Liquid-Crystalline Lipid Phase Transitions in Lipid Droplets Selectively Remodel the Ld Proteome

Lipid droplets (LDs) are reservoirs for triglycerides (TGs) and sterol-esters (SEs). How lipids are organized within LDs and influence the LD proteome remains unclear. Using in situ cryo-electron tomography, we show that glucose restriction triggers lipid phase transitions within LDs generating liquid-crystalline lattices inside them. Mechanistically, this requires TG lipolysis, which alters LD neutral lipid composition and promotes SE transition to a liquid-crystalline phase. Fluorescence imaging and proteomics further reveal that LD liquid-crystalline lattices selectively remodel the LD proteome. Some canonical LD proteins including Erg6 re-localize to the ER network, whereas others remain on LDs. Model peptide LiveDrop also redistributes from LDs to the ER, suggesting liquid-crystalline-phases influence ER-LD inter-organelle transport. Proteomics also indicates glucose restriction elevates peroxisome lipid oxidation, suggesting TG mobilization provides fatty acids for cellular energetics. This suggests glucose restriction drives TG mobilization, which alters the phase properties of LD lipids and selectively remodels the LD proteome.
Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application

Search and experience goods, as well as vertical and horizontal differentiation, are fundamental concepts of great importance to business operations and strategy. In our paper, we propose a set of ...