cssi/SciSciGPT-SciSciNet huggingface dataset:
A haplotype-phased genome of wheat stripe rust pathogen Puccinia striiformis f. sp. tritici, race PST-130 from the Western USA.

More virulent and aggressive races of Puccinia striiformis f. sp. tritici (Pst), the pathogen causing wheat stripe rust, have been spreading around the world since 2000 causing large grain yield losses. A better understanding of the genome and genetic diversity of these new Pst races will be useful to develop new strategies to ameliorate these losses. In this study, we generated an improved genome assembly of a post-2000 virulent race from the Western USA designated as PST-130. We implemented a haplotype phasing strategy using the diploid-aware assembler, Falcon-Unzip and new long-read technology from PacBio to phase the two genomes of this dikaryotic organism. The combination of these new technologies resulted in an improved PST-130 assembly with only 151 contigs (85.4 Mb, N50 of 1.44 Mb), and a complementary assembly (haplotigs) with 458 contigs (65.9 Mb, N50 of 0.235 Mb, PRJNA650506). This new assembly improved gene predictions resulting in 228 more predicted complete genes than in the initial Illumina assembly (29,178 contigs, N50 of 5 kb). The alignment of the non-repetitive primary and haplotig contigs revealed and average of 5.22 SNP/kb, with 39.1% showing 10 SNP/kb. This large divergent regions may represent introgressions of chromosome segments from more divergent Pst races in regions where a complete sexual cycle and recombination are possible. We hypothesize that some of the divergent regions in PST-130 may be related to the European "Warrior" race PST-DK0911 because this genome is more similar to PST-130 (3.18 SNP/kb) than to the older European race PST-104E (3.75 SNP/kb). Complete phasing of additional Pst genomes or sequencing individual nuclei will facilitate the tracing of the haploid genomes introduced by the new Pst races into local populations.
RE-INTERPRETATION OF SUPRA-ARCADE DOWNFLOWS IN SOLAR FLARES

Following the eruption of a filament from a flaring active region, sunward-flowing voids are often seen above developing post-eruption arcades. First discovered using the soft X-ray telescope aboard Yohkoh, these supra-arcade downflows (SADs) are now an expected observation of extreme ultra-violet and soft X-ray coronal imagers and spectrographs (e.g, TRACE, SOHO/SUMER, Hinode/XRT, SDO/AIA). Observations made prior to the operation of AIA suggested that these plasma voids (which are seen in contrast to bright, high-temperature plasma associated with current sheets) are the cross-sections of evacuated flux tubes retracting from reconnection sites high in the corona. The high temperature imaging afforded by AIA's 131, 94, and 193 A channels coupled with the fast temporal cadence allows for unprecedented scrutiny of the voids. For a flare occurring on 2011 October 22, we provide evidence suggesting that SADs, instead of being the cross-sections of relatively large, evacuated flux tubes, are actually wakes (i.e., trailing regions of low density) created by the retraction of much thinner tubes. This re-interpretation is a significant shift in the fundamental understanding of SADs, as the features once thought to be identifiable as the shrinking loops themselves now appear to be "side effects" of the passage of the loops through the supra-arcade plasma. In light of the fact that previous measurements have attributed to the shrinking loops characteristics that may instead belong to their wakes, we discuss the implications of this new interpretation on previous parameter estimations and on reconnection theory.
ALEX: An Updatable Adaptive Learned Index

Recent work on "learned indexes" has changed the way we look at the decades-old field of DBMS indexing. The key idea is that indexes can be thought of as "models" that predict the position of a key in a dataset. Indexes can, thus, be learned. The original work by Kraska et al. shows that a learned index beats a B+ tree by a factor of up to three in search time and by an order of magnitude in memory footprint. However, it is limited to static, read-only workloads. In this paper, we present a new learned index called ALEX which addresses practical issues that arise when implementing learned indexes for workloads that contain a mix of point lookups, short range queries, inserts, updates, and deletes. ALEX effectively combines the core insights from learned indexes with proven storage and indexing techniques to achieve high performance and low memory footprint. On read-only workloads, ALEX beats the learned index from Kraska et al. by up to 2.2X on performance with up to 15X smaller index size. Across the spectrum of read-write workloads, ALEX beats B+ trees by up to 4.1X while never performing worse, with up to 2000X smaller index size. We believe ALEX presents a key step towards making learned indexes practical for a broader class of database workloads with dynamic updates.
Replication or Exploration? Sequential Design for Stochastic Simulation Experiments

We investigate the merits of replication, and provide methods for optimal design (including replicates), with the goal of obtaining globally accurate emulation of noisy computer simulation experime...
Spitzer, Gaia, and the Potential of the Milky Way

Near-future data from ESA's Gaia mission will provide precise, full phase-space information for hundreds of millions of stars out to heliocentric distances of ~10 kpc. This "horizon" for full phase-space measurements is imposed by the Gaia parallax errors degrading to worse than 10%, and could be significantly extended by an accurate distance indicator. Recent work has demonstrated how Spitzer observations of RR Lyrae stars can be used to make distance estimates accurate to 2%, effectively extending the Gaia, precise-data horizon by a factor of 10 in distance and a factor of 1000 in volume. This Letter presents one approach to exploit data of such accuracy to measure the Galactic potential using small samples of stars associated with debris from satellite destruction. The method is tested with synthetic observations of 100 stars from the end point of a simulation of satellite destruction: the shape, orientation, and depth of the potential used in the simulation are recovered to within a few percent. The success of this simple test with such a small sample in a single debris stream suggests that constraints from multiple streams could be combined to examine the Galaxy's dark matter halo in even more detail—a truly unique opportunity that is enabled by the combination of Spitzer and Gaia with our intimate perspective on our own Galaxy.
A simulations approach for meta-analysis of genetic association studies based on additive genetic model.

Abstract Meta-analysis of genetic association studies is being increasingly used to assess phenotypic differences between genotype groups. When the underlying genetic model is assumed to be dominant or recessive, assessing the phenotype differences based on summary statistics, reported for individual studies in a meta-analysis, is a valid strategy. However, when the genetic model is additive, a similar strategy based on summary statistics will lead to biased results. This fact about the additive model is one of the things that we establish in this paper, using simulations. The main goal of this paper is to present an alternate strategy for the additive model based on simulating data for the individual studies. We show that the alternate strategy is far superior to the strategy based on summary statistics.
Metaplectic Whittaker functions and crystal bases

We study Whittaker functions on nonlinear coverings of simple algebraic groups over a nonarchimedean local field. We produce a recipe for expressing such a Whittaker function as a weighted sum over a crystal graph and show that in type A, these expressions agree with known formulae for the prime-power-supported coefficients of multiple Dirichlet series.
Temporal Self-organization in Galaxy Formation

We report on the discovery of a relation between the number of star formation (SF) peaks per unit time, νpeak, and the size of the temporal smoothing window function, Δt, used to define the peaks: νpeak∝Δt 1 – ( ~ 1.618). This relation holds over the range of Δt = 10-1000 Myr that can be reliably computed here, using a large sample of galaxies obtained from a state-of-the-art cosmological hydrodynamic simulation. This means that the temporal distribution of SF peaks in galaxies as a population is fractal with a Hausdorff fractal dimension equal to – 1. This finding reveals, for the first time, that the superficially chaotic process of galaxy formation is underlined by temporal self-organization up to at least one gigayear. It is tempting to suggest that, given the known existence of spatial fractals (such as the power-law two-point function of galaxies), there is a joint spatio-temporal self-organization in galaxy formation. From an observational perspective, it will be urgent to devise diagnostics to probe the SF histories of galaxies with good temporal resolution to facilitate a test of this prediction. If confirmed, it would provide unambiguous evidence for a new picture of galaxy formation that is interaction driven, cooperative, and coherent in and between time and space. Unravelling its origin may hold the key to understanding galaxy formation.
High Visibility Time-Energy Entangled Photons from a Silicon Nanophotonic Chip

Advances in quantum photonics have shown that chip-scale quantum devices are translating from the realm of basic research to applied technologies. Recent developments in integrated photonic circuits and single photon detectors indicate that the bottleneck for fidelity in quantum photonic processes will ultimately lie with the photon sources. We present and demonstrate a silicon nanophotonic chip capable of emitting telecommunication band photon pairs that exhibit the highest raw degree of time-energy entanglement from a micro/nanoscale source, to date. Biphotons are generated through cavity-enhanced spontaneous four-wave mixing (SFWM) in a high-Q silicon microdisk resonator, wherein the nature of the triply resonant generation process leads to a dramatic Purcell enhancement, resulting in highly efficient pair creation rates as well as extreme suppression of the photon noise background. The combination of the excellent photon source and a new phase locking technique allow for the observation of a nearly pe...
Similarity between Kaluza-Klein and open-string amplitudes in diphoton production

We calculate the tree-level open-string amplitudes for the scattering of four massless particles with diphoton final states. These amplitudes are required to reproduce those of standard model at the tree level in the low energy limit. After low energy stringy corrections, we found that they have similar form to the same processes induced by exchange of the Kaluza-Klein(KK) excitations of graviton in ADD scenario. Using this similarity, we apply constraints on the KK mass scale MD to the string scale MS. The results are consistent with constraints from the 4-fermion scattering, about 0.6-0.9 TeV.
On Achieving Size-Independent Stability Margin of Vehicular Lattice Formations With Distributed Control

We study the stability margin of a vehicular formation with distributed control, in which the control at each vehicle only depends on the information from its neighbors in an information graph. We consider a D-dimensional lattice as information graph, of which the 1-D platoon is a special case. The stability margin is measured by the real part of the least stable eigenvalue of the closed-loop state matrix, which quantifies the rate of decay of initial errors. In [1], it was shown that with symmetric control, in which two neighbors put equal weight on information received from each other, the stability margin of a 1-D vehicular platoon decays to 0 as 0(1/N2), where N is the number of vehicles. Moreover, a perturbation analysis was used to show that with vanishingly small amount of asymmetry in the control gains, the stability margin scaling can be improved to 0(1/N). In this technical note, we show that, with judicious choice of nonvanishing asymmetry in control, the stability margin of the closed loop can be bounded away from zero uniformly in N. Asymmetry in control gains thus makes the control architecture highly scalable. The results are also generalized to D-dimensional lattice information graphs that were studied in [2], and the correspondingly stronger conclusions than those derived in [2] are obtained. In addition, we show that the size-independent stability margin can be achieved with relative position and relative velocity (RPRV) feedback as well as relative position and absolute velocity (RPAV) feedback, while the analysis in [1], [2] was only for the RPAV case.
A novel reflectometer for relative reflectance measurements of CCDs

The high quantum efficiencies (QE) of backside illuminated charge coupled devices (CCD) has ushered in the age of the large scale astronomical survey. The QE of these devices can be greater than 90%, and is dependent upon the operating temperature, device thickness, backside charging mechanisms, and anti-reflection (AR) coatings. But at optical wavelengths the QE is well approximated as one minus the reflectance, thus the measurement of the backside reflectivity of these devices provides a second independent measure of their QE. We have designed and constructed a novel instrument to measure the relative specular reflectance of CCD detectors, with a significant portion of this device being constructed using a 3D fused deposition model (FDM) printer. This device implements both a monitor and measurement photodiode to simultaneously collect in- cident and reflected measurements reducing errors introduced by the relative reflectance calibration process. While most relative reflectometers are highly dependent upon a precisely repeatable target distance for accurate measurements, we have implemented a method of measurement which minimizes these errors. Using the reflectometer we have measured the reflectance of two types of Hamamatsu CCD detectors. The first device is a Hamamatsu 2k x 4k backside illuminated high resistivity p-type silicon detector which has been optimized to operate in the blue from 380 nm - 650 nm. The second detector being a 2k x 4k backside illuminated high resistivity p-type silicon detector optimized for use in the red from 640 nm - 960 nm. We have not only been able to measure the reflectance of these devices as a function of wavelength we have also sampled the reflectance as a function of position on the device, and found a reflection gradient across these devices.
Twin Vector Fields and Independence of Spectra for Quadratic Vector Fields

The object of this paper is to address the following question: when is a polynomial vector field on $\mathbb {C}^{2}$ completely determined (up to affine equivalence) by the spectra of its singularities? We will see that for quadratic vector fields, this is not the case: given a generic quadratic vector field there is, up to affine equivalence, exactly one other vector field which has the same spectra of singularities. Let us say that two distinct vector fields are twin vector fields if they have the same singular locus and the same spectrum at each singularity. Our main result is as follows: any two generic quadratic vector fields with the same spectra of singularities (yet possibly different singular locus) can be transformed by suitable affine maps to be either the same vector field or a pair of twin vector fields. Moreover, a generic quadratic vector field has exactly one twin vector field. We later analyze the case of quadratic Hamiltonian vector fields in more detail and find necessary and sufficient conditions for a collection of non-zero complex numbers to arise as the spectra of singularities of a quadratic Hamiltonian vector field. Lastly, we show that a generic quadratic vector field is completely determined (up to affine equivalence) by the spectra of its singularities together with the characteristic numbers of its singular points at infinity.
Measuring the Allan variance by sinusoidal fitting.

The Allan variance of signal and reference frequencies is measured by a least-square fit of the output of two analog-to-digital converters to ideal sine waves. The difference in the fit phase of the two channels generates the timing data needed for the Allan variance. The fits are performed at the signal frequency (≈10 MHz) without the use of heterodyning. Experimental data from a modified digital oscilloscope yield a residual Allan deviation of 3 × 10−13/τ, where τ is the observation time in s. This corresponds to a standard deviation in time of <300 fs or 20 μrad in phase. The experimental results are supported by statistical theory and Monte Carlo simulations which suggest that optimized devices may have one or two orders of magnitude better performance.
CP-violating phases in the MSSM

We combine experimental bounds on the electric dipole moments of the neutron and electron with cosmological limits on the relic density of a gaugino-type LSP neutralino to constrain certain CP-violating phases appearing in the MSSM. We find that in the Constrained MSSM, the phase |θμ| ≲ π/10, while the phase θA remains essentially unconstrained.
A Possible Supernova Remnant High Above the Galactic Disk

We present the analysis of three Suzaku observations of a bright arc in the ROSAT All-Sky Survey 1/4 keV maps at l {approx} 247 deg., b {approx} -64 deg. In particular, we have tested the hypothesis that the arc is the edge of a bubble blown by an extraplanar supernova. One pointing direction is near the brightest part of the arc, one is toward the interior of the hypothesized bubble, and one is toward the bubble exterior. We fit spectral models generated from one-dimensional hydrodynamical simulations of extraplanar supernova remnants (SNRs) to the spectra. The spectra and the size of the arc (radius {approx} 5 deg.) are reasonably well explained by a model in which the arc is the bright edge of a {approx}100,000 yr old SNR located {approx}1-2 kpc above the disk. The agreement between the model and the observations can be improved if the metallicity of the X-ray-emitting gas is {approx}1/3 solar, which is plausible, as the dust which sequesters some metals is unlikely to have been destroyed in the lifetime of the SNR. The width of the arc is larger than that predicted by our SNR model; this discrepancy is also seen with the Vela SNR, andmore » may be due to the one-dimensional nature of our simulations. If the arc is indeed the edge of an extraplanar SNR, this work supports the idea that extraplanar supernovae contribute to the heating of the {approx}million degree gas in the halo.« less
CANDIDATE X-RAY-EMITTING OB STARS IN THE CARINA NEBULA IDENTIFIED VIA INFRARED SPECTRAL ENERGY DISTRIBUTIONS

We report the results of a new survey of massive, OB stars throughout the Carina Nebula using the X-ray point source catalog provided by the Chandra Carina Complex Project (CCCP) in conjunction with infrared (IR) photometry from the Two Micron All-Sky Survey and the Spitzer Space Telescope Vela-Carina survey. Mid-IR photometry is relatively unaffected by extinction, hence it provides strong constraints on the luminosities of OB stars, assuming that their association with the Carina Nebula, and hence their distance, is confirmed. We fit model stellar atmospheres to the optical (UBV) and IR spectral energy distributions (SEDs) of 182 OB stars with known spectral types and measure the bolometric luminosity and extinction for each star. We find that the extinction law measured toward the OB stars has two components: AV = 1-1.5?mag produced by foreground dust with a ratio of total-to-selective absorption RV = 3.1 plus a contribution from local dust with RV > 4.0 in the Carina molecular clouds that increases as AV increases. Using X-ray emission as a strong indicator of association with Carina, we identify 94 candidate OB stars with L bol 104 L ? by fitting their IR SEDs. If the candidate OB stars are eventually confirmed by follow-up spectroscopic observations, the number of cataloged OB stars in the Carina Nebula will increase by ~50%. Correcting for incompleteness due to OB stars falling below the L bol cutoff or the CCCP detection limit, these results potentially double the size of the young massive stellar population.
Breaking time reversal symmetry in topological insulators

A wide class of materials that were discovered to carry a topologically protected phase order has led to a highly active area of research called topological insulators (TIs). This phenomenon has radically changed our thinking because of the robust quantum coherent behavior showing two-dimensional Dirac-type metallic surface states (SSs) and simultaneously insulating bulk states. The Dirac SSs are induced by the strong spin–orbit coupling as well as protected by time reversal symmetry (TRS). Breaking TRS in a TI with ferromagnetic perturbation can lead to many exotic quantum phenomena, such as the quantum anomalous Hall effect, topological magnetoelectric effect, as well as image magnetic monopole. This article presents an overview of the current status of TRS breaking in TIs and outlines the prospects for future studies.
Specht modules decompose as alternating sums of restrictions of Schur modules

Schur modules give the irreducible polynomial representations of the general linear group $\mathrm{GL}_t$. Viewing the symmetric group $\mathfrak{S}_t$ as a subgroup of $\mathrm{GL}_t$, we may restrict Schur modules to $\mathfrak{S}_t$ and decompose the result into a direct sum of Specht modules, the irreducible representations of $\mathfrak{S}_t$. We give an equivariant Mobius inversion formula that we use to invert this expansion in the representation ring for $\mathfrak{S}_t$ for $t$ large. In addition to explicit formulas in terms of plethysms, we show the coefficients that appear alternate in sign by degree. In particular, this allows us to define a new basis of symmetric functions whose structure constants are stable Kronecker coefficients and which expand with alternating signs into the Schur basis.
Minimax lower bounds for Kronecker-structured dictionary learning

Dictionary learning is the problem of estimating the collection of atomic elements that provide a sparse representation of measured/collected signals or data. This paper finds fundamental limits on the sample complexity of estimating dictionaries for tensor data by proving a lower bound on the minimax risk. This lower bound depends on the dimensions of the tensor and parameters of the generative model. The focus of this paper is on second-order tensor data, with the underlying dictionaries constructed by taking the Kronecker product of two smaller dictionaries and the observed data generated by sparse linear combinations of dictionary atoms observed through white Gaussian noise. In this regard, the paper provides a general lower bound on the minimax risk and also adapts the proof techniques for equivalent results using sparse and Gaussian coefficient models. The reported results suggest that the sample complexity of dictionary learning for tensor data can be significantly lower than that for unstructured data.
Heliospheric Transport of Neutron-Decay Protons

We report on new simulations of the transport of energetic protons originating from the decay of energetic neutrons produced in solar flares. Because the neutrons are fast-moving but insensitive to the solar wind magnetic field, the decay protons are produced over a wide region of space, and they should be detectable by current instruments over a broad range of longitudes for many hours after a sufficiently large gamma-ray flare. Spacecraft closer to the Sun are expected to see orders-of-magnitude higher intensities than those at the Earth-Sun distance. The current solar cycle should present an excellent opportunity to observe neutron-decay protons with multiple spacecraft over different heliographic longitudes and distances from the Sun.
Photonic temporal-mode multiplexing by quantum frequency conversion in a dichroic-finesse cavity

Photonic temporal modes (TMs) form a field-orthogonal basis set representing a continuous-variable degree of freedom that is in principle infinite dimensional, and create a promising resource for quantum information science and technology. The ideal quantum pulse gate (QPG) is a device that multiplexes and demultiplexes temporally orthogonal optical pulses that have the same carrier frequency, spatial mode, and polarization. The QPG is the chief enabling technology for usage of orthogonal temporal modes as a basis for high-dimensional quantum information storage and processing. The greatest hurdle for QPG implementation using nonlinear-optical, parametric processes with time-varying pump or control fields is the limitation on achievable temporal mode selectivity, defined as perfect TM discrimination combined with unity efficiency. We propose the use of pulsed nonlinear frequency conversion in an optical cavity having greatly different finesses for different frequencies to implement a nearly perfectly TM-selective QPG in a low-loss integrated-optics platform.
Dyson-Schwinger calculations of meson form factors

The ladder-rainbow truncation of the set of Dyson-Schwinger equations is used to study the pion and kaon electromagnetic form factors and the γ7π0γ transition form factor in impulse approximation. With model parameters previously fixed by the pseudoscalar meson masses and decay constants, the obtained form factors are in good agreement with the data.
Quantum limited super-resolution of an unequal-brightness source pair in three dimensions

This paper extends our previous quantum Fisher information (QFI) based analysis of the problem of separating a pair of equal-brightness incoherent point sources in three dimensions to the case of a pair of sources that are unequally bright. When the pair's geometric center is perfectly known in advance, QFI with respect to the estimation of the three separation coordinates remains independent of the degree of brightness asymmetry. For the experimentally more relevant case of perfect prior knowledge of the pair's brightness centroid, however, such QFI becomes dependent on the pair separation vector in a way that is controlled by the degree of its brightness asymmetry. This study yields potentially useful insights into the analysis of a more general superresolution imaging problem involving extended incoherent sources with nontrivial brightness distributions.
Global solutions of the Navier–Stokes equations for isentropic flow with large external potential force

We prove the global-in-time existence of weak solutions to the Navier–Stokes equations of compressible isentropic flow in three space dimensions with adiabatic exponent γ ≥ 1. Initial data and solutions are small in L2 around a non-constant steady state with densities being positive and essentially bounded. No smallness assumption is imposed on the external forces when γ = 1. A great deal of information about partial regularity and large-time behavior is obtained.
Posterior convergence rates for estimating large precision matrices using graphical models

We consider Bayesian estimation of a $p\times p$ precision matrix, when $p$ can be much larger than the available sample size $n$. It is well known that consistent estimation in such ultra-high dimensional situations requires regularization such as banding, tapering or thresholding. We consider a banding structure in the model and induce a prior distribution on a banded precision matrix through a Gaussian graphical model, where an edge is present only when two vertices are within a given distance. For a proper choice of the order of graph, we obtain the convergence rate of the posterior distribution and Bayes estimators based on the graphical model in the $L_{\infty}$-operator norm uniformly over a class of precision matrices, even if the true precision matrix may not have a banded structure. Along the way to the proof, we also compute the convergence rate of the maximum likelihood estimator (MLE) under the same set of condition, which is of independent interest. The graphical model based MLE and Bayes estimators are automatically positive definite, which is a desirable property not possessed by some other estimators in the literature. We also conduct a simulation study to compare finite sample performance of the Bayes estimators and the MLE based on the graphical model with that obtained by using a Cholesky decomposition of the precision matrix. Finally, we discuss a practical method of choosing the order of the graphical model using the marginal likelihood function.
Characteristic Variability Timescales in the Gamma-Ray Power Spectra of Blazars

Characteristic variability timescales in blazar gamma-ray light curves can provide insight into the physical processes responsible for the gamma-ray variability. The power spectral density (PSD) is capable of revealing such timescales, which may appear as breaks or periodicities. Continuous-time autoregressive moving-average (CARMA) models can be used to accurately estimate a light curve's PSD. Through a lightcurve simulation study, we develop a methodology to identify PSD breaks using CARMA models. Using this methodology, we study the gamma-ray light curves of 13 bright blazars observed with the Fermi Large Area Telescope in the 0.1-300 GeV band over 9.5 years. We present the blazar gamma-ray PSDs, which provide evidence for low-frequency breaks on timescales ~1 year in four sources, and an additional high-frequency break on a timescale ~9 days in one source.
Lower bounds for multicolor Ramsey numbers

Abstract We give an exponential improvement to the lower bound on diagonal Ramsey numbers for any fixed number of colors greater than two.
Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes

Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disruption of operation, financial losses, and equipment damage. In particular, false data attacks initiated during power systems transients caused due to abrupt changes in load and generation can fool the conventional model-based detection methods relying on thresholds comparison to trigger an anomaly. In this paper, we propose a Koopman mode decomposition (KMD) based algorithm to detect and identify false data attacks in real-time. The Koopman modes (KMs) are capable of capturing the nonlinear modes of oscillation in the transient dynamics of the power networks and reveal the spatial embedding of both natural and anomalous modes of oscillations in the sensor measurements. The Koopman-based spatio-temporal nonlinear modal analysis is used to filter out the false data injected by an attacker. The performance of the algorithm is illustrated on the IEEE 68-bus test system using synthetic attack scenarios generated on GridSTAGE, a recently developed multivariate spatio-temporal data generation framework for simulation of adversarial scenarios in cyber-physical power systems.
Bayesian Update with Importance Sampling: Required Sample Size.

Importance sampling is used to approximate Bayes’ rule in many computational approaches to Bayesian inverse problems, data assimilation and machine learning. This paper reviews and further investigates the required sample size for importance sampling in terms of the χ2-divergence between target and proposal. We illustrate through examples the roles that dimension, noise-level and other model parameters play in approximating the Bayesian update with importance sampling. Our examples also facilitate a new direct comparison of standard and optimal proposals for particle filtering.
Identifying Overlapping Successive Events Using a Shallow Convolutional Neural Network

Real-time identification of successive events in power systems is crucial to avoid cascading failures. Existing identification methods are mainly designed for single events and may not accurately identify a subsequent event that occurs when the system is undergoing the disturbance of a previous event. Since overlapping successive events do not frequently happen in power systems, insufficient multi-event datasets exist for training. We develop a data-driven event identification method that can accurately identify the types of overlapping events. Our approach only requires a small number of recorded Phasor Measurement Unit (PMU) data of single events to train a two-layer convolutional neural network (CNN) classifier offline. We extract the dominant eigenvalues and singular values as features instead of training on time series directly. That reduces the required number of training datasets and enhances the robustness to measurement inaccuracy. In real time, our method first predicts and subtracts the impact of previous events. It then extracts the dominant features from the residual measurements and applies the classifier. We evaluate the method on simulated events in the IEEE 68-bus power system. Our classifier is demonstrated to be more accurate and stable than a direct application of CNN on time series. The robustness of the proposed method to the delay in event detection and noise is validated.
Deep neural networks for collaborative learning analytics: Evaluating team collaborations using student gaze point prediction

Automatic assessment and evaluation of team performance during collaborative tasks is key to the research on learning analytics and computer-supported cooperative work. There is growing interest in the use of gaze-oriented cues for evaluating the collaboration and cooperativeness of teams. However, collecting gaze data using eye-trackers is not always feasible due to time and cost constraints. In this paper, we introduce an automated team assessment tool based on gaze points and joint visual attention (JVA) information drawn from computer vision solutions. We evaluated team collaborations in an undergraduate anatomy learning activity (N = 60, 30 teams) as a test user study. The results indicate that higher JVA was positively associated with student learning outcomes (r(30) = 0.50, p < 0.005). Moreover, teams who participated in two experimental groups and used interactive 3D anatomy models, had higher JVA (F(1,28) = 6.65, p < 0.05) and better knowledge retention (F(1,28) = 7.56, p < 0.05) than those in the control group. Also, no significant difference was observed based on JVA for different gender compositions of teams. The findings from this work have implications in learning sciences and collaborative computing by providing a novel joint attention-based measure to objectively evaluate team collaboration dynamics. Implications for practice or policy: Student learning outcomes can be improved by receiving constructive feedback about team performances using our gaze-based collaborative learning method. Underrepresented and underserved minorities of science, technology, engineering and mathematics disciplines can be engaged in more collaborative problem-solving and team-based learning activities since our method offers a broader reach by automating collaboration assessment process. Course leaders can assess the quality of attention and engagement among students and can monitor or assist larger numbers of students simultaneously.
Balancing Wildfire Risk and Power Outages Through Optimized Power Shut-Offs

Electric grid faults can ignite catastrophic wildfires, particularly in regions with high winds and low humidity. In real-time operations, electric utilities have few options for wildfire risk mitigation, leading to use of disruptive measures such as proactive de-energization of equipment, frequently referred to as public safety power shut-offs. Such power shut-offs have significant impacts on customers, who experience power cuts in an attempt to protect them from fires. This work proposes the optimal power shut-off problem, an optimization model to support short-term operational decision making in the context of extreme wildfire risk. Specifically, the model optimizes grid operations to maximize the amount of power that can be delivered, while proactively minimizing the risk of wildfire ignitions by selectively de-energizing components in the grid. This is the first optimization model to consider how preventive wildfire risk measures impact both wildfire risk and power systems reliability at a short-term, operational time-frame. The effectiveness of the method is demonstrated on an augmented version of the RTS-GMLC test case, located in Southern California, and compared against two approaches based on simple risk thresholds. The proposed optimization-based model reduces both wildfire risk and lost load shed relative to the benchmarks.