cssi/SciSciGPT-SciSciNet huggingface dataset:
Data-driven spatiotemporal modal decomposition for time frequency analysis

Abstract We propose a new solution to the blind source separation problem that factors mixed time-series signals into a sum of spatiotemporal modes, with the constraint that the temporal components are intrinsic mode functions (IMF's). The key motivation is that IMF's allow the computation of meaningful Hilbert transforms of non-stationary data, from which instantaneous time-frequency representations may be derived. Our spatiotemporal intrinsic mode decomposition (STIMD) method leverages spatial correlations to generalize the extraction of IMF's from one-dimensional signals, commonly performed using the empirical mode decomposition (EMD), to multi-dimensional signals. Further, this data-driven method enables future-state prediction. We demonstrate STIMD on several synthetic examples, comparing it to common matrix factorization techniques, namely singular value decomposition (SVD), independent component analysis (ICA), and dynamic mode decomposition (DMD). We show that STIMD outperforms these methods at reconstruction and extracting interpretable modes. Next, we apply STIMD to analyze two real-world datasets, gravitational wave data and neural recordings from the rodent hippocampus.
Gamma rays from accretion onto rotating black holes

Ionized matter falling onto an isolated rotating black hole will be heated sufficiently that proton-proton collisions will produce mesons, including neutral pions, which decay into gamma rays. For massive (1000-solar mass) black holes, the resulting gamma-ray luminosity may exceed 10 to the 36th erg/s with a spectrum peaked near 20 MeV.
Data-Driven Modeling of Resource Distribution in Honeybee Swarms

Trophallaxis is the mutual exchange and direct transfer of liquid food among eusocial insects such as ants, termites, wasps, and bees. This process allows efficient dissemination of nutrients and i...
Non-Gaussian Chance-Constrained Trajectory Planning for Autonomous Vehicles Under Agent Uncertainty

Agent behavior is arguably the greatest source of uncertainty in trajectory planning for autonomous vehicles. This problem has motivated significant amounts of work in the behavior prediction community on learning rich distributions of the future states and actions of agents. However, most current works on chance-constrained trajectory planning under agent or obstacle uncertainty either assume Gaussian uncertainty or linear constraints, which is limiting, or requires sampling, which can be computationally intractable to encode in an optimization problem. In this letter, we extend the state-of-the-art by presenting a methodology to upper-bound chance-constraints defined by polynomials and mixture models with potentially non-Gaussian components. Our method achieves its generality by using statistical moments of the distributions in concentration inequalities to upper-bound the probability of constraint violation. With this method, optimization-based trajectory planners can plan trajectories that are chance-constrained with respect to a wide range of distributions representing predictions of agent future positions. In experiments, we show that the resulting optimization problem can be solved with state-of-the-art nonlinear program solvers to plan trajectories fast enough for use online.
Long Short-Term Memory Spiking Networks and Their Applications

Recent advances in event-based neuromorphic systems have resulted in significant interest in the use and development of spiking neural networks (SNNs). However, the non-differentiable nature of spiking neurons makes SNNs incompatible with conventional backpropagation techniques. In spite of the significant progress made in training conventional deep neural networks (DNNs), training methods for SNNs still remain relatively poorly understood. In this paper, we present a novel framework for training recurrent SNNs. Analogous to the benefits presented by recurrent neural networks (RNNs) in learning time series models within DNNs, we develop SNNs based on long short-term memory (LSTM) networks. We show that LSTM spiking networks learn the timing of the spikes and temporal dependencies. We also develop a methodology for error backpropagation within LSTM-based SNNs. The developed architecture and method for backpropagation within LSTM-based SNNs enable them to learn long-term dependencies with comparable results to conventional LSTMs. Code is available on github; https://github.com/AliLotfi92/SNNLSTM
The isomorphism class of the shift map

Abstract The shift map, denoted σ, is the self-homeomorphism of induced by the successor function n ↦ n + 1 on ω. We prove that the isomorphism classes of σ and σ − 1 cannot be separated by a Borel set in H ( ω ⁎ ) , the space of all self-homeomorphisms of ω ⁎ equipped with the compact-open topology. Van Douwen proved it is consistent for σ and σ − 1 not to be isomorphic. Whether it is also consistent for them to be isomorphic is an open problem. The theorem stated above can be thought of as a counterpoint to van Douwen's result: while σ and σ − 1 may not be isomorphic, there is no simple topological property that distinguishes them. As a relatively straightforward consequence of the main theorem, we deduce that OCA + MA implies the set of continuous images of σ fails to be Borel in H ( ω ⁎ ) . (Here a “continuous image” of σ is meant in the sense of topological dynamics: any h ∈ H ( ω ⁎ ) such that q ∘ σ = h ∘ q for some continuous surjection q : ω ⁎ → ω ⁎ .) This contrasts starkly with a recent theorem of the author showing that under CH , the continuous images of σ form a closed subset of H ( ω ⁎ ) .
Comparison of D-Wave Quantum Annealing and Classical Simulated Annealing for Local Minima Determination

Restricted Boltzmann Machines trained with different numbers of iterations were used to provide a large diverse set of energy functions each containing many local valleys (LVs). They were used to confirm the property of the D-Wave quantum annealer (QA) to find potentially important LVs in the energy functions of Markov Random Fields that may be missed by classical searches. Even after a prohibitively long classical search by simulated annealing (SA), as many as 30–50% of the QA-found LVs remained not found by the SA. In order to establish if those LVs represent potentially important regions of the configuration space, they were compared to LVs that were found by both techniques. With respect to most of the important LV parameters, the LVs found only by the QA (missed by SA) were distributed in a wide range of the parameters’ values. In an attempt to explain which LVs could not be found easily by the SA, it was established that for large or small, shallow or deep, wide or narrow LVs, the LVs found only by the QA are distinguished by a few-times smaller size of the LV basin of attraction (BoA). Apparently, the size of the BoA is much less important for QA search compared to the classical search, allowing QA to easily find many potentially important (e.g., wide and deep) LVs missed by even prohibitively lengthy classical searches.
Should competing firms cooperate to reduce congestion

Abstract Consider two profit-maximizing service firms in the presence of congestion-sensitive customers. Firms set their prices and compete to capture market share. We compare cases where the firms can invest either independently (competition) or jointly (co-opetition) in congestion-reduction (CR) activities. Using a stylized analytical model, we find that when the market is covered (that is when everyone buys a product), the firm with a lower marginal CR cost earns more profit under competition than under co-opetition. When the market is uncovered, co-opetition is more profitable if the joint marginal CR cost is less than a threshold. We find that when the market is covered, neither firm makes any CR investment but when the market is uncovered, there will be a CR investment provided the marginal CR cost is lower than a threshold. Our analysis shows that when prices are regulated, firms under competition make CR investments but firms under co-opetition do not. The impact of proximity on each firm’s choice of location under competition and co-opetition are different. We find that if the marginal CR cost under joint investment is larger than a cutoff, then social welfare is also higher under competition than under co-opetition.
Weyl's problem: A computational approach

The distribution of eigenvalues of the wave equation in a bounded domain is known as Weyl's problem. We describe several computational projects related to the cumulative state number, defined as the number of states having wavenumber up to a maximum value. This quantity and its derivative, the density of states, have important applications in nuclear physics, degenerate Fermi gases, blackbody radiation, Bose–Einstein condensation, and the Casimir effect. Weyl's theorem states that, in the limit of large wavenumbers, the cumulative state number depends only on the volume of the bounding domain and not on its shape. Corrections to this behavior are well known and depend on the surface area of the bounding domain, its curvature, and other features. We describe several projects that allow readers to investigate this dependence for three bounding domains—a rectangular box, a sphere, and a circular cylinder. Quasi-one- and two-dimensional systems can be analyzed by considering various limits. The projects have applications in statistical mechanics, but can also be integrated into quantum mechanics, nuclear physics, or computational physics courses.
Student and Teacher Perceptions of Goal Attainment During Intervention With the Self-Determined Learning Model of Instruction:

A major instructional focus of interventions designed to promote self-determination, such as the Self-Determined Learning Model of Instruction (SDLMI), is to engage students in learning to set thei...
Wi-Fringe: Leveraging Text Semantics in WiFi CSI-Based Device-Free Named Gesture Recognition

The lack of adequate training data is one of the major hurdles in WiFi-based activity recognition systems. In this paper, we propose Wi-Fringe, which is a WiFi CSI-based devicefree human gesture recognition system that recognizes named gestures, i.e., activities and gestures that have a semantically meaningful name in English language, as opposed to arbitrary free-form gestures. Given a list of activities (only their names in English text), along with zero or more training examples (WiFi CSI values) per activity, Wi-Fringe is able to detect all activities at runtime. We show for the first time that by utilizing the state-of-the-art semantic representation of English words, which is learned from datasets like the Wikipedia (e.g., Google’s word-to-vector [1]) and verb attributes learned from how a word is defined (e.g, American Heritage Dictionary), we can enhance the capability of WiFi-based named gesture recognition systems that lack adequate training examples per class. We propose a novel cross-domain knowledge transfer algorithm between radio frequency (RF) and text to lessen the burden on developers and end-users from the tedious task of data collection for all possible activities. To evaluate Wi-Fringe, we collect data from four volunteers in a multi-person apartment and an office building for a total of 20 activities. We empirically quantify the trade-off between the accuracy and the number of unseen activities.
On the convergence rate of the quasi- to stationary distribution for the Shiryaev-Roberts diffusion

For the classical Shiryaev-Roberts martingale diffusion considered on the interval [ 0 , A ] , where A > 0 is a given absorbing boundary, it is shown that the rate of convergence of the diffusion’s...
Approximate Identification of the Optimal Epidemic Source in Complex Networks

We consider the problem of identifying the source of a network epidemic from a complete snapshot of the infected nodes. We take a fully statistical approach and derive novel recursions to compute the Bayes optimal solution, under a heterogeneous susceptible-infected (SI) epidemic model. Our analysis is time and rate independent, and holds for general network topologies. We then provide two highly scalable algorithms for solving these recursions, a mean-field approximation and a greedy approach, and evaluate their performance on real and synthetic networks. Previous work on the problem has mostly focused on tree-like network topologies. Real networks are far from tree-like and an emphasis will be given to networks with high transitivity, such as social networks and those with communities. We show that on such networks, our approaches significantly outperform popular geometric and spectral centrality measures, most of which perform no better than random guessing.
THE EMOTIONAL IMPACT OF THE ASRM GUIDELINES ON FERTILITY PATIENTS DURING THE COVID-19 PANDEMIC

Objective: To survey fertility patients’ agreement with ASRM recommendations during the COVID-19 pandemic and the emotional impact on them Design: An online survey was sent to current fertility patients at a New York City academic fertility practice at the epicenter of the COVID-19 pandemic Materials and Methods: Patient agreement with the ASRM recommendations during the COVID-19 pandemic and the emotional impact rated on a Likert scale Ordinal data such as responses rated on a Likert scale were analyzed using Mann-Whitney Wilcoxon testing and responses were compared using Fisher exact or chi-square test as appropriate, with significance at p<0 05 Results: A total of 518 patients completed the survey for a response rate of 17% Fifty percent of respondents had a cycle canceled due to the COVID-19 pandemic Of those who had a cycle cancelled, 85% of respondents found it to be moderately to extremely upsetting with 22% rating it to be equivalent to the loss of a child There was no difference on the emotional impact based on the type of cycle cancelled Fifty-five percent of patients agreed that diagnostic procedures such as hysterosalpingograms should be cancelled while 36% of patients agreed all fertility cycles should be cancelled (22% unsure, 43% disagreed) Patients were slightly more likely to agree with the ASRM guidelines if they have an upcoming cycle cancelled (p = 0 041) Of all respondents 82% would have preferred to have the option to start a treatment cycle in consultation with their doctor Conclusions: Given the severity of the COVID-19 pandemic, the physical, financial and emotional impact of this unprecedented threat cannot be underestimated in our fertility patients
POD-(H)DG Method for Incompressible Flow Simulations

We present a reduced order method based on proper orthogonal decomposition for the viscous Burgers’ equation and the incompressible Navier–Stokes equations discretized using an implicit-explicit hybrid discontinuous Galerkin/discoutinuous Galerkin (IMEX HDG/DG) scheme. A novel closure model, which can be easily computed offline, is introduced. Numerical results are presented to test the proposed POD model and the closure model.
Single-cell secretion analysis reveals a dual role for IL-10 in restraining and resolving the TLR4-induced inflammatory response

Abstract Following TLR4 stimulation of macrophages, negative feedback mediated by the anti-inflammatory cytokine IL-10 limits the inflammatory response. However, extensive cell-to-cell variability in TLR4-stimulated cytokine secretion raises questions about how negative feedback is robustly implemented. To explore this, we characterized the TLR4-stimulated secretion program in primary murine macrophages using a single-cell microwell assay that enabled evaluation of functional autocrine IL-10 signaling. High-dimensional analysis of single-cell data revealed three distinct tiers of TLR4-induced proinflammatory activation based on levels of cytokine secretion. Surprisingly, while IL-10 inhibits TLR4-induced activation in the highest tier, it also contributes to the TLR4-induced activation threshold by regulating which cells transition from non-secreting to secreting states. This role for IL-10 in restraining TLR4 inflammatory activation is largely mediated by intermediate IFN-β signaling, while TNF-a likely mediates response resolution by IL-10. Thus, cell-to-cell variability in cytokine regulatory motifs provides a means to tailor the TLR4-induced inflammatory response.
When Does Domestic Savings Matter for Economic Growth

Can a country grow faster by saving more? The paper addresses this question both theoretically and empirically. In the theoretical model, growth results from innovations that allow local sectors to catch up with frontier technology. In poor countries, catching up requires the cooperation of a foreign investor who is familiar with the frontier technology and a domestic entrepreneur who is familiar with local conditions. In such a country, domestic savings matters for innovation, and therefore growth, because it enables the local entrepreneur to put equity into this cooperative venture, which mitigates an agency problem that would otherwise deter the foreign investor from participating. In rich countries, domestic entrepreneurs are already familiar with frontier technology and therefore do not need to attract foreign investment to innovate, so domestic savings does not matter for growth. A cross-country regression shows that lagged savings is positively associated with productivity growth in poor countries but not in rich countries.
Transient and steady-state temperature rise in three-dimensional anisotropic layered structures in pump-probe thermoreflectance experiments

Recent developments of the pump-probe thermoreflectance methods (such as the beam-offset and elliptical-beam approaches of the time-domain and frequency-domain thermoreflectance techniques) enabled measurements of the thermal conductivities of in-plane anisotropic materials. Estimating the temperature rise of anisotropic layered structures under surface heating is critically important to make sure that the temperature rise is not too high to alias the signals in these experiments. However, a simple formula to estimate the temperature rise in three-dimensional (3D) anisotropic layered systems heated by a non-circular laser beam is not available yet, which is the main problem we aim to solve in this work. We first re-derived general formalisms of the temperature rise of a multilayered structure based on the previous literature work by solving the 3D anisotropic heat diffusion equation in the frequency domain. These general formalisms normally require laborious numerical evaluation; however, they could be reduced to explicit analytical expressions for the case of semi-infinite solids. We then extend the analytical expressions to multilayered systems, taking into account the effect of the top layers. This work not only enhances our understanding of the physics of temperature rise due to surface laser heating but also enables quick estimation of the peak temperature rise of 3D anisotropic layered systems in pump-probe thermoreflectance experiments and thus greatly benefits the thermoreflectance experiments in choosing the appropriate heating power intensity for the experiments.
Triclosan depletes the membrane potential in Pseudomonas aeruginosa biofilms inhibiting aminoglycoside induced adaptive resistance

Biofilm-based infections are difficult to treat due to their inherent resistance to antibiotic treatment. Discovering new approaches to enhance antibiotic efficacy in biofilms would be highly significant in treating many chronic infections. Exposure to aminoglycosides induces adaptive resistance in Pseudomonas aeruginosa biofilms. Adaptive resistance is primarily the result of active antibiotic export by RND-type efflux pumps, which use the proton motive force as an energy source. We show that the protonophore uncoupler triclosan depletes the membrane potential of biofilm growing P. aeruginosa, leading to decreased activity of RND-type efflux pumps. This disruption results in increased intracellular accumulation of tobramycin and enhanced antimicrobial activity in vitro. In addition, we show that triclosan enhances tobramycin effectiveness in vivo using a mouse wound model. Combining triclosan with tobramycin is a new anti-biofilm strategy that targets bacterial energetics, increasing the susceptibility of P. aeruginosa biofilms to aminoglycosides.
Tilings, tiling spaces and topology

To understand on aperiodic tiling (or a quasicrystal modeled on an aperiodic tiling), we construct a space of similar tilings, on which the group of translations acts naturally. This space is then an (abstract) dynamical system. Dynamical properties of the space (such as mixing, or the spectrum of the translation operator) are closely related to bulk properties of individual tilings (such as the diffraction pattern). The topology of the space of tilings, particularly the Cech cohomology, gives information on how original tiling may be deformed. Tiling spaces can be constructed as inverse limits of branched manifolds.
Three-generation neutrino mixing and LSND dark matter neutrinos

The reported signal at the LSND experiment, when interpreted as neutrino mixing with δm 2 = 6 eV 2 , provides evidence for neutrinos with a cosmologically significant mass. However, attempts to reconcile this interpretation of the experiment with other hints about neutrino properties require a (sterile) fourth neutrino and/or an “inverted” neutrino mass hierarchy. An interpretation of the LSND experiment employing δm 2 = 0.3 eV 2 , with three-generation mixing and a “normal” neutrino mass hierarchy, can just barely be reconciled with the negative results of other laboratory neutrino oscillation experiments and the positive hints of neutrino oscillation from the solar and atmospheric neutrino problems. Though subject to test by by future experiments, such a solution allows (but does not demand) neutrino masses relevant for dark matter.
(j, 0) ⊕ (0, j) COVARIANT SPINORS AND CAUSAL PROPAGATORS BASED ON WEINBERG FORMALISM

A pragmatic approach to constructing a covariant phenomenology of the interactions of composite high-spin hadrons is proposed. Because there are no known wave equations without significant problems, we propose to construct the phenomenology without explicit reference to a wave equation. This is done by constructing the individual pieces of a perturbation theory and then utilizing the perturbation theory as the definition of the phenomenology. The covariant spinors for a particle of spin j are constructed directly from Lorentz invariance and the basic precepts of quantum mechanics following the logic put forth originally by Wigner and developed by Weinberg. Explicit expressions for the spinors are derived for j=1, 3/2 and 2. Field operators are constructed from the spinors and the free-particle propagator is derived from the vacuum expectation value of the time-order product of the field operators. A few simple examples of model interactions are given. This provides all the necessary ingredients to treat at a phenomenological level and in a covariant manner particles of arbitrary spin.
ToTTo: A Controlled Table-To-Text Generation Dataset

We present ToTTo, an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description. To obtain generated targets that are natural but also faithful to the source table, we introduce a dataset construction process where annotators directly revise existing candidate sentences from Wikipedia. We present systematic analyses of our dataset and annotation process as well as results achieved by several state-of-the-art baselines. While usually fluent, existing methods often hallucinate phrases that are not supported by the table, suggesting that this dataset can serve as a useful research benchmark for high-precision conditional text generation.
The Averaged Dynamics of the Hydrogen Atom in Crossed Electric and Magnetic Fields as a Perturbed Kepler Problem

We treat the classical dynamics of the hydrogen atom in perpendicular electric and magnetic fields as a celestial mechanics problem. By expressing the Hamiltonian in appropriate action–angle variables, we separate the different time scales of the motion. The method of averaging then allows us to reduce the system to two degrees of freedom, and to classify the most important periodic orbits.
Doubly robust policy evaluation and optimization

We study sequential decision making in environments where rewards are only partially observed, but can be modeled as a function of observed contexts and the chosen action by the decision maker. This setting, known as contextual bandits, encompasses a wide variety of applications such as health care, content recommendation and Internet advertising. A central task is evaluation of a new policy given historic data consisting of contexts, actions and received rewards. The key challenge is that the past data typically does not faithfully represent proportions of actions taken by a new policy. Previous approaches rely either on models of rewards or models of the past policy. The former are plagued by a large bias whereas the latter have a large variance. In this work, we leverage the strengths and overcome the weaknesses of the two approaches by applying the doubly robust estimation technique to the problems of policy evaluation and optimization. We prove that this approach yields accurate value estimates when we have either a good (but not necessarily consistent) model of rewards or a good (but not necessarily consistent) model of past policy. Extensive empirical comparison demonstrates that the doubly robust estimation uniformly improves over existing techniques, achieving both lower variance in value estimation and better policies. As such, we expect the doubly robust approach to become common practice in policy evaluation and optimization.
ARE ACTIVE GALACTIC NUCLEI THE SOLUTION TO THE EXCESS COSMIC RADIO BACKGROUND AT 1.4 GHz

Recently, the ARCADE 2 experiment measured the cosmic radio background (CRB) and found the brightness temperature of the CRB at 1.4 GHz to be ~480 mK. Integrating the flux density from the observed 1.4 GHz radio source count produces a brightness temperature of ~100 mK—less than a quarter of the observed CRB at 1.4 GHz. Radio-quiet active galactic nuclei (AGNs) are a large fraction of the 1.4 GHz μJy sources and typically host significant star formation. Thus, it is possible that AGN and host star formation could be responsible for some fraction of the excess CRB at 1.4 GHz. Here, an X-ray background population synthesis model is used in conjunction with empirical radio to X-ray luminosity ratios to calculate the AGN contribution to the CRB at 1.4 GHz, including the emission from host star formation. It is found that AGN and host star formation contribute 9% of the CRB at 1.4 GHz. When all known 1.4 GHz radio source classes are considered, 60% of the CRB at 1.4 GHz is accounted for; therefore, it is necessary that either known radio sources evolve significantly at flux densities below current survey sensitivity limits or a new population of low flux density radio sources exist.
Global Weak Solution and Large-Time Behavior for the Compressible Flow of Liquid Crystals

The three-dimensional equations for the compressible flow of liquid crystals are considered. An initial-boundary value problem is studied in a bounded domain with large data. The existence and large-time behavior of a global weak solution are established through a three-level approximation, energy estimates, and weak convergence for the adiabatic exponent $${\gamma > \frac{3}{2}}$$ .
Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation

Increasing aggregate diversity (or catalog coverage) is an important system-level objective in many recommendation domains where it may be desirable to mitigate the popularity bias and to improve the coverage of long-tail items in recommendations given to users. This is especially important in multistakeholder recommendation scenarios where it may be important to optimize utilities not just for the end user, but also for other stakeholders such as item sellers or producers who desire a fair representation of their items across recommendation lists produced by the system. Unfortunately, attempts to increase aggregate diversity often result in lower recommendation accuracy for end users. Thus, addressing this problem requires an approach that can effectively manage the trade-offs between accuracy and aggregate diversity. In this work, we propose a two-sided post-processing approach in which both user and item utilities are considered. Our goal is to maximize aggregate diversity while minimizing loss in recommendation accuracy. Our solution is a generalization of the Deferred Acceptance algorithm which was proposed as an efficient algorithm to solve the well-known stable matching problem. We prove that our algorithm results in a unique user-optimal stable match between items and users. Using three recommendation datasets, we empirically demonstrate the effectiveness of our approach in comparison to several baselines. In particular, our results show that the proposed solution is quite effective in increasing aggregate diversity and item-side utility while optimizing recommendation accuracy for end users.
Quantifying the Eddy–Jet Feedback Strength of the Annular Mode in an Idealized GCM and Reanalysis Data

AbstractA linear response function (LRF) that relates the temporal tendency of zonal-mean temperature and zonal wind to their anomalies and external forcing is used to accurately quantify the strength of the eddy–jet feedback associated with the annular mode in an idealized GCM. Following a simple feedback model, the results confirm the presence of a positive eddy–jet feedback in the annular mode dynamics, with a feedback strength of 0.137 day−1 in the idealized GCM. Statistical methods proposed by earlier studies to quantify the feedback strength are evaluated against results from the LRF. It is argued that the mean-state-independent eddy forcing reduces the accuracy of these statistical methods because of the quasi-oscillatory nature of the eddy forcing. Assuming the mean-state-independent eddy forcing is sufficiently weak at the low-frequency limit, a new method is proposed to approximate the feedback strength as the regression coefficient of low-pass-filtered eddy forcing onto the low-pass-filtered an...
Spaced Repetition and Mnemonics Enable Recall of Multiple Strong Passwords

Abstract—We report on a user study that provides evidencethat spaced repetition and a speciﬁc mnemonic technique enableusers to successfully recall multiple strong passwords over time.Remote research participants were asked to memorize 4 Person-Action-Object (PAO) stories where they chose a famous personfrom a drop-down list and were given machine-generated randomaction-object pairs. Users were also shown a photo of a scene andasked to imagine the PAO story taking place in the scene (e.g.,Bill Gates—swallowing—bike on a beach). Subsequently, theywere asked to recall the action-object pairs when prompted withthe associated scene-person pairs following a spaced repetitionschedule over a period of 127+ days. While we evaluated severalspaced repetition schedules, the best results were obtained whenusers initially returned after 12 hours and then in 1:5 increasingintervals: 77% of the participants successfully recalled all 4stories in 10 tests over a period of ˇ 158 days. Much of theforgetting happened in the ﬁrst test period (12 hours): 89%of participants who remembered their stories during the ﬁrsttest period successfully remembered them in every subsequentround. These ﬁndings, coupled with recent results on naturallyrehearsing password schemes, suggest that 4 PAO stories couldbe used to create usable and strong passwords for 14 sensitiveaccounts following this spaced repetition schedule, possibly witha few extra upfront rehearsals. In addition, we ﬁnd statisticallysigniﬁcant evidence that with 8 tests over 64 days users whowere asked to memorize 4 PAO stories outperform users whoare given 4 random action-object pairs, but with 9 tests over 128days the advantage is not signiﬁcant. Furthermore, there is aninterference effect across multiple PAO stories: the recall rate of100% (resp. 90%) for participants who were asked to memorize1 PAO story (resp. 2 PAO stories) is signiﬁcantly better than therate for participants who were asked to memorize 4 PAO stories.These ﬁndings yield concrete advice for improving constructionsof password management schemes and future user studies.
On macroscopic dimension of rationally essential manifolds

We construct a counterexamples in dimensions $n>3$ to Gromov's conjecture \cite{Gr1} that the macroscopic dimension of rationally essential $n$-dimensional manifolds equals $n$.
The Freund–Rubin coset, textures and group theory*

Contribution to the Peter Freund Memorial volume: a glossary of group-theoretic facts that may relate the seven-dimensional Freund-Rubin coset to Yukawa textures.
Optical parametric oscillation in silicon carbide nanophotonics

Silicon carbide (SiC) is rapidly emerging as a leading platform for the implementation of nonlinear and quantum photonics. Here, we find that commercial SiC, which hosts a variety of spin qubits, possesses low optical absorption that can enable SiC integrated photonics with quality factors exceeding 107. We fabricate multimode microring resonators with quality factors as high as 1.1 million, and observe low-threshold (8.5±0.5mW) optical parametric oscillation using the fundamental mode as well as optical microcombs spanning 200 nm using a higher-order mode. Our demonstration is an essential milestone in the development of photonic devices that harness the unique optical properties of SiC, paving the way toward the monolithic integration of nonlinear photonics with spin-based quantum technologies.
BCJ relations from a new symmetry of gauge-theory amplitudes

We introduce a new set of symmetries obeyed by tree-level gauge-theory amplitudes involving at least one gluon. The symmetry acts as a momentum-dependent shift on the color factors of the amplitude. Using the radiation vertex expansion, we prove the invariance under this color-factor shift of the n-gluon amplitude, as well as amplitudes involving massless or massive particles in an arbitrary representation of the gauge group with spin zero, one-half, or one. The Bern-Carrasco-Johansson relations are a direct consequence of this symmetry. We also introduce the cubic vertex expansion of an amplitude, and use it to derive a generalized-gauge-invariant constraint on the kinematic numerators of the amplitude. We show that the amplitudes of the bi-adjoint scalar theory are invariant under the color-factor symmetry, and use this to derive the null eigenvectors of the propagator matrix. We generalize the color-factor shift to loop level, and prove the invariance under this shift of one-loop n-gluon amplitudes in any theory that admits a color-kinematic-dual representation of numerators. We show that the one-loop color-factor symmetry implies known relations among the integrands of one-loop color-ordered amplitudes.
Comparing and Combining Measurement-Based and Driven-Dissipative Entanglement Stabilization

Error correction by feedback is crucial in quantum computation, and an experiment now shows that two such methods can be integrated in a nested feedback protocol to obtain the best properties of both.
Atomistic potentials for palladium-silver hydrides

New embedded-atom method potentials for the ternary palladium–silver–hydrogen system are developed by extending a previously developed palladium–hydrogen potential. The ternary potentials accurately capture the heat of mixing and structural properties associated with solid solution alloys of palladium–silver. Stable hydrides are produced with properties that smoothly transition across the compositions. Additions of silver to palladium are predicted to alter the properties of the hydrides by decreasing the miscibility gap and increasing the likelihood of hydrogen atoms occupying tetrahedral interstitial sites over octahedral interstitial sites.
D’Alembert’s Direct and Inertial Forces Acting on Populations: The Price Equation and the Fundamental Theorem of Natural Selection

I develop a framework for interpreting the forces that act on any population described by frequencies. The conservation of total frequency, or total probability, shapes the characteristics of force. I begin with Fisher's fundamental theorem of natural selection. That theorem partitions the total evolutionary change of a population into two components. The first component is the partial change caused by the direct force of natural selection, holding constant all aspects of the environment. The second component is the partial change caused by the changing environment. I demonstrate that Fisher's partition of total change into the direct force of selection and the forces from the changing environmental frame of reference is identical to d'Alembert's principle of mechanics, which separates the work done by the direct forces from the work done by the inertial forces associated with the changing frame of reference. In d'Alembert's principle, there exist inertial forces from a change in the frame of reference that exactly balance the direct forces. I show that the conservation of total probability strongly shapes the form of the balance between the direct and inertial forces. I then use the strong results for conserved probability to obtain general results for the change in any system quantity, such as biological fitness or energy. Those general results derive from simple coordinate changes between frequencies and system quantities. Ultimately, d'Alembert's separation of direct and inertial forces provides deep conceptual insight into the interpretation of forces and the unification of disparate fields of study.
Domain-Wall Standard Model in non-compact 5D and LHC phenomenology

We propose a framework to construct “Domain-Wall Standard Model” in a non-compact 5-dimensional spacetime, where all the Standard Model (SM) fields are localized in certain domains of the 5th dimension and the SM is realized as a 4-dimensional effective theory without any compactification for the 5th dimension. In this context, we investigate the collider phenomenology of the Kaluza–Klein (KK) modes of the SM gauge bosons and the current constraints from the search for a new gauge boson resonance at the Large Hadron Collider Run-2. The couplings of the SM fermions with the KK-mode gauge bosons depend on the configuration of the SM fermions in the 5-dimensional bulk. This “geometry” of the model can be tested at the future Large Hadron Collider experiment, once a KK-mode of the SM gauge boson is discovered.
OPTICAL BVRI PHOTOMETRY OF COMMON PROPER MOTION F/G/K+M WIDE SEPARATION BINARIES

We present optical (BVRI) photometric measurements of a sample of 76 common proper motion wide separation main-sequence binary pairs. The pairs are composed of a F-, G-, or K-type primary star and an M-type secondary. The sample is selected from the revised NLTT catalog and the LSPM catalog. The photometry is generally precise to 0.03 mag in all bands. We separate our sample into two groups, dwarf candidates and subdwarf candidates, using the reduced proper motion diagram constructed with our improved photometry. The M subdwarf candidates in general have larger V – R colors than the M dwarf candidates at a given V – I color. This is consistent with an average metallicity difference between the two groups, as predicted by the PHOENIX/BT-Settl models. The improved photometry will be used as input into a technique to determine the metallicities of the M-type stars.
Defying Inertia: How Rotating Superconductors Generate Magnetic Fields

I discuss the process of magnetic field generation in rotating superconductors in simply connected and multiply connected geometries. In cooling a normal metal into the superconducting state while it is rotating, electrons slow down or speed up depending on the geometry and their location in the sample, apparently defying inertia. I argue that the conventional theory of superconductivity does not explain these processes. Instead, the theory of hole superconductivity does. Its predictions agree with experimental observations of Hendricks, King and Rohrschach for solid and hollow cylinders.
A note on subfactor projections

We extend some results of Bestvina and Feighn [4] on subfactor projections to show that the projection of a free factor B to the free factor complex of the free factor A is well defined with uniformly bound diameter, unless either A is contained in B or A and B are vertex stabilizers of a single splitting of Fn , ie, they are disjoint. These projections are shown to satisfy properties analogous to subsurface projections, and we give as an application a construction of fully irreducible outer automorphisms using the bounded geodesic image theorem. 20F65; 57M07
Linear preservers and representations with a 1-dimensional ring of invariants

We determine the group of linear transformations on a vector space V that preserve a polynomial function f on V for several interesting pairs (V,f), using the theory of semisimple algebraic groups. In an 1897 paper (Fro97), Frobenius proved that every linear transformation of the n-by-n real matrices that preserves the determinant is of the form X 7→AXB or X 7→AX t B for some A,B ∈ GLn(R) such that det(AB) = 1. This is the basic example of a linear preserver problem (LPP): one is given a finite-dimensional vector space V over a field K and a polynomial function f : V → K and one wants to determine the linear transformations of V that preserve f. Since Frobenius, many such prob- lems have been solved, see for example the surveys (LP01), (PLL + 92), (LT92), and (Mar62). We develop here a general method that solves several new problems, see Examples 3.14 and 3.15 and Corollaries 7.10, 8.3, 8.7, 8.5, 8.8, and 8.11. Our method is to introduce an auxiliary group G ⊂ GL(V ) that is semisimple and such that V is an irreducible representation or Weyl module of G. In section 2, we determine the normalizer NGL(V )(G) of G in GL(V ). We prove in Theorem 3.2 that this subgroup equals the stabilizer of a closed G-orbit O in the projective space P(V ), i.e., StabGL(V )(O) = NGL(V )(G). Using this result, in sections 7 and 8, we solve two families of LPPs by reducing the problems in each family to determining this stabilizer. These two families consist of representations V with a 1-dimensional ring of G-invariant functions generated by f and are examples of prehomogenous vector spaces of parabolic type; the two families correspond to the cases where the unipotent radical U of the parabolic subgroup is abelian (i.e., (U,U) = 0) or (U,U) is 1-dimensional respectively, and we use the general results on representations in these families from (RRS92), (Roh93), and (Hel12). Besides obtaining new results, we also recover many known solutions to linear preserver problems. The generality of our method is in contrast to many of the proofs in the literature, which typically are highly dependent on the particular choice of V and f. (The arguments in (PD95) and (Gur97) are notable exceptions.) Further, we require only very weak assumptions about the field K (at most we require that the characteristic is 6 2,3) and determine the preserver precisely (and not just its identity component or Lie algebra).
The star-formation relation for regions in the galactic plane: The effect of spatial resolution

We examined the relations between molecular gas surface density and star-formation rate surface density in an 11 deg2 region of the Galactic plane. Dust continua at 1.1 mm from the Bolocam Galactic Plane Survey and 22 μm emission from the Wide-field Infrared Survey Explorer (WISE) all-sky survey were used as tracers of molecular gas and the star-formation rate, respectively, across the Galactic longitude of 31.5 ≥ l ≥ 20.5 and Galactic latitude of 0.5 ≥ b ≥ –0.5. The relation was studied over a range of resolutions from 33'' to 20' by convolving images to larger scales. The pixel-by-pixel correlation between 1.1 mm and 22 μm increases rapidly at small scales and levels off at the scale of 5'-8'. We studied the star-formation relation based on a pixel-by-pixel analysis and on an analysis of the 1.1 mm and 22 μm peaks. The star-formation relation was found to be nearly linear with no significant changes in the form of the relation across all spatial scales, and it lies above the extragalactic relation from Kennicutt. The average gas-depletion time is ≈200 Myr and does not change significantly at different scales, but the scatter in the depletion time decreases as the scale increases.
Submillimeter Atmospheric Transparency at Maunakea, at the South Pole, and at Chajnantor

For a systematic assessment of submillimeter observing conditions at different sites, we constructed tipping radiometers to measure the broad band atmospheric transparency in the window around 350 μm wavelength. The tippers were deployed on Maunakea, Hawaii, at the South Pole, and in the vicinity of Cerro Chajnantor in northern Chile. Identical instruments permit direct comparison of these sites. Observing conditions at the South Pole and in the Chajnantor area are better than on Maunakea. Simultaneous measurements with two tippers demonstrate conditions at the summit of Cerro Chajnantor are significantly better than on the Chajnantor plateau.
The Starburst in the Central Kiloparsec of Markarian 231

We present VLBA observations at 0.33 and 0.61 GHz, and VLA observations between 5 and 22 GHz, of subkiloparsec-scale radio emission from Mrk 231. In addition to jet components clearly associated with the active galzctic nucleus, we also find a smooth extended component of size 100-1000 pc most probably related to the purported massive star-forming disk in Mrk 231. The diffuse radio emission from the disk is found to have a steep spectrum at high frequencies, characteristic of optically thin synchrotron emission. The required relativistic particle density in the disk can be produced by a star formation rate of 220 M☉ yr-1 in the central kiloparsec. At low frequencies the disk is absorbed, most likely by ionized gas with an emission measure of 8 × 105 pc cm-6. We have also identified four candidate radio supernovae that, if confirmed, represent direct evidence for ongoing star formation in the central kiloparsec.
Nuclear Spin Relaxation within Interstellar Grains

We identify a new mechanism of internal dissipation of rotational kinetic energy in spinning dust grains, arising from the reorientation of nuclear angular momentum, e.g., spins of protons. Grain rotation induces magnetization of the nuclear spin system, with net alignment of nuclear spins parallel to the grain angular velocity. When the grain does not rotate around a principal axis, the nuclear magnetization vector precesses in grain-body coordinates, resulting in dissipation of energy. The analogous process involving electron spins was discovered by E. M. Purcell and termed "Barnett relaxation." We revisit the physics of the Barnett relaxation process and correct the estimate for the Barnett relaxation rate. We show that nuclear relaxation can be orders of magnitude more important than Barnett relaxation. This finding implies that the processes of "thermal flipping" and "thermal trapping" are important for a broad range of grain sizes.
GLOBAL CALCULATIONS OF DENSITY WAVES AND GAP FORMATION IN PROTOPLANETARY DISKS USING A MOVING MESH

We calculate the global quasi-steady state of a thin disk perturbed by a low-mass protoplanet orbiting at a fixed radius using extremely high resolution numerical integrations of Euler's equations in two dimensions. The calculations are carried out using a moving computational domain, which greatly reduces advection errors and allows for much longer time steps than a fixed grid. We calculate the angular momentum flux and the torque density as a function of radius and compare them with analytical predictions. We discuss the quasi-steady state after 100 orbits and the prospects for gap formation by low-mass planets.