cssi/SciSciGPT-SciSciNet huggingface dataset:
Weak Separation, Positivity and Extremal Yangian Invariants

We classify all positive n-particle NkMHV Yangian invariants in $$ \mathcal{N} $$ = 4 YangMills theory with n = 5k, which we call extremal because none exist for n > 5k. We show that this problem is equivalent to that of enumerating plane cactus graphs with k pentagons. We use the known solution of that problem to provide an exact expression for the number of cyclic classes of such invariants for any k, and a simple rule for writing them down explicitly. We provide an alternative (but equivalent) classification by showing that a product of k five-brackets with disjoint sets of indices is a positive Yangian invariant if and only if the sets are all weakly separated.
A cosmological solution of Regge calculus

We revisit the Regge calculus model of the Kasner cosmology first considered by Lewis (1982 Phys. Rev. D 25 306 12). One of the most highly symmetric applications of lattice gravity in the literature, Lewis' discrete model closely matched the degrees of freedom of the Kasner cosmology. As such, it was surprising that Lewis was unable to obtain the full set of Kasner–Einstein equations in the continuum limit. Indeed, an averaging procedure was required to ensure that the lattice equations were even consistent with the exact solution in this limit. We correct Lewis' calculations and show that the resulting Regge model converges quickly to the full set of Kasner–Einstein equations in the limit of very fine discretization. Numerical solutions to the discrete and continuous-time lattice equations are also considered.
Dynamics of zonal flows: failure of wave-kinetic theory, and new geometrical optics approximations

The self-organisation of turbulence into regular zonal flows can be fruitfully investigated with quasi-linear methods and statistical descriptions. A wave-kinetic equation that assumes asymptotically large-scale zonal flows leads to ultraviolet divergence. From an exact description of quasi-linear dynamics emerges two better geometrical optics approximations. These involve not only the mean flow shear but also the second and third derivative of the mean flow. One approximation takes the form of a new wave-kinetic equation, but is only valid when the zonal flow is quasi-static and wave action is conserved.
Air compressor load forecasting using artificial neural network

Abstract Air compressor systems are responsible for approximately 10% of the electricity consumed in United States and European Union industry. As many researches have proven the effectiveness of using Artificial Neural Network in air compressor performance prediction, there is still a need to forecast the air compressor electrical load profile. The objective of this study is to predict compressed air systems' electrical load profile, which is valuable to industry practitioners as well as software providers in developing better practice and tools for load management and look-ahead scheduling programs. Two artificial neural networks, Two-Layer Feed-Forward Neural Network and Long Short-Term Memory were used to predict an air compressors electrical load. Compressors with three different control mechanisms are evaluated with a total number of 11,874 observations. The forecasts were validated using out-of-sample datasets with 5-fold cross-validation. Models produced average coefficient of determination values from 0.24 to 0.94, average root-mean-square errors from 0.05 kW - 5.83 kW, and mean absolute scaled errors from 0.20 to 1.33. The results indicate that both artificial neural networks yield good results for compressors using variable speed drive (average R2 = 0.8 and no naive forecasting), only the long short-term memory model gives acceptable results for compressors using on/off control (average R2 = 0.82 and no naive forecasting), and no satisfactory results are obtained for load/unload type air compressors (models constituting naive forecasting).
Evaluation of kinematic precise point positioning convergence with an incremental graph optimizer

Estimation techniques to precisely localize a kinematic platform with GNSS observables can be broadly partitioned into two categories: differential, or undifferenced. The differential techniques (e.g., real-time kinematic (RTK)) have several attractive properties, such as correlated error mitigation and fast convergence; however, to support a differential processing scheme, an infrastructure of reference stations within a proximity of the platform must be in place to construct observation corrections. This infrastructure requirement makes differential processing techniques infeasible in many locations. To mitigate the need for additional receivers within proximity of the platform, the precise point positioning (PPP) method utilizes accurate orbit and clock models to localize the platform. The autonomy of PPP from local reference stations make it an attractive processing scheme for several applications; however, a current disadvantage of PPP is the slow positioning convergence when compared to differential techniques. In this paper, we evaluate the convergence properties of PPP with an incremental graph optimization scheme (Incremental Smoothing and Mapping (iSAM2)), which allows for real-time filtering and smoothing. The characterization is first conducted through a Monte Carlo analysis within a simulation environment, which allows for the variations of parameters, such as atmospheric conditions, satellite geometry, and intensity of multipath. Then, an example collected data set is utilized to validate the trends presented in the simulation study.
Bag-of-gold spacetimes, Euclidean wormholes, and inflation from domain walls in AdS/CFT

We use Euclidean path integrals to explore the set of bulk asymptotically AdS spacetimes with good CFT duals. We consider simple bottom-up models of bulk physics defined by Einstein-Hilbert gravity coupled to thin domain walls and restrict to solutions with spherical symmetry. The cosmological constant is allowed to change across the domain wall, modeling more complicated Einstein-scalar systems where the scalar potential has multiple minima. In particular, the cosmological constant can become positive in the interior. However, in the above context, we show that inflating bubbles are never produced by smooth Euclidean saddles to asymptotically AdS path integrals. The obstacle is a direct parallel to the well-known obstruction to creating inflating universes by tunneling from flat space. In contrast, we do find good saddles that create so-called “bag-of-gold” geometries which, in addition to their single asymptotic region, also have an additional large semi-classical region located behind both past and future event horizons. Furthermore, without fine-tuning model parameters, using multiple domain walls we find Euclidean geometries that create arbitrarily large bags-of-gold inside a black hole of fixed horizon size, and thus at fixed Bekenstein-Hawking entropy. Indeed, with our symmetries and in our class of models, such solutions provide the unique semi-classical saddle for appropriately designed (microcanonical) path integrals. This strengthens a classic tension between such spacetimes and the CFT density of states, similar to that in the black hole information problem.
On the Inhomogeneity of the Mandelbrot Set

We will show the Mandelbrot set $M$ is locally conformally inhomogeneous: the only conformal map $f$ defined in an open set $U$ intersecting $\partial M$ and satisfying $f(U\cap\partial M)\subset \partial M$ is the identity map. The proof uses the study of local conformal symmetries of the Julia sets of polynomials: we will show in many cases, the dynamics can be recovered from the local conformal structure of the Julia sets.
Blending Brownian motion and heat equation

In this paper we present an original way to couple the Brownian motion and the heat equation. More in general, we suggest a way for coupling the Langevin equation for a particle, which describes a single realization of its trajectory, with the associated Fokker-Plank equation, which instead describes the evolution of the particle’s probability density function. The coupling is obtained blending the micro and the macroscale, which are active always and everywhere in the computational domain. Numerical results show that it is indeed possible to obtain a regularized Brownian motion and a Brownianized heat equation still preserving the global statistical properties of the solutions. The results also suggest that the more macroscale leads the dynamics the more one can reduce the microscopic degrees of freedom. AMS subject classifications: 35Q40, 35R60, 35K05, 60J65, 35Q84.
Electronic structure and magnetism of transition metal dihalides: Bulk to monolayer

Based on first-principles calculations, the evolution of the electronic and magnetic properties of transition metal dihalides $M{X}_{2}\phantom{\rule{4pt}{0ex}}(M=\text{V}$, Mn, Fe, Co, Ni; $X=\text{Cl}$, Br, I) is analyzed from the bulk to the monolayer limit. A variety of magnetic ground states is obtained as a result of the competition between direct exchange and superexchange. The results predict that $\mathrm{Fe}{X}_{2},\mathrm{Ni}{X}_{2},{\mathrm{CoCl}}_{2}$, and ${\mathrm{CoBr}}_{2}$ monolayers are ferromagnetic insulators with sizable magnetocrystalline anisotropies. This makes them ideal candidates for robust ferromagnetism at the single-layer level. Our results highlight the importance of spin-orbit coupling to obtain the correct ground state in these materials.
Experimental Realization of a Reflective Optical Limiter

A typical optical limiter protects sensitive components (such as optoelectronic sensors---or eyes) from a high-power laser by transmitting only low-intensity light, at the cost of absorbing most of the energy itself, which can cause irreversible damage. The authors present a photonic limiter that instead reflects the high-power radiation backward to free space, across a broad frequency range. Their limiter has a much higher damage threshold, and provides much stronger laser suppression.
Black Holes and Beyond

The black hole information paradox forces us into a strange situation: we must find a way to break the semiclassical approximation in a domain where no quantum gravity effects would normally be expected. Traditional quantizations of gravity do not exhibit any such breakdown, and this forces us into a difficult corner: either wemust give up quantum mechanics or we must accept the existence of troublesome ‘remnants’. In string theory, however, the fundamental quanta are extended objects, and it turns out that the bound states of such objects acquire a size that grows with the number of quanta in the bound state. The interior of the black hole gets completely altered to a ‘fuzzball’ structure, and information is able to escape in radiation from the hole. The semiclassical approximation can break at macroscopic scales due to the large entropy of the hole: the measure in the path integral competes with the classical action, instead of giving a subleading correction. Putting this picture of black hole microstates together with ideas about entangled states leads to a natural set of conjectures on many long-standing questions in gravity: the significance of Rindler and de Sitter entropies, the notion of black hole complementarity, and the fate of an observer falling into a black hole.
Three-Dimensional Dynamical Instabilities in Galactic Ionization Fronts

Ionization front instabilities have long been of interest for their suspected role in a variety of phenomena in the Galaxy, from the formation of bright rims and "elephant trunks" in nebulae to triggered star formation in molecular clouds. Numerical treatments of these instabilities have historically been limited in both dimensionality and input physics, leaving important questions about their true evolution unanswered. We present the first three-dimensional radiation hydrodynamical calculations of both R-type (rarefied) and D-type (dense) ionization front instabilities in Galactic environments (i.e., solar-metallicity gas). Consistent with linear stability analyses of planar D-type fronts, our models exhibit many short-wavelength perturbations that grow at early times and later evolve into fewer large-wavelength structures. The simulations demonstrate that both self-consistent radiative transfer and three-dimensional flow introduce significant morphological differences to unstable modes when compared to earlier two-dimensional approximate models. We find that the amplitude of the instabilities in the nonlinear regime is primarily determined by the efficiency of cooling within the shocked neutral shell. Strong radiative cooling leads to long, extended structures with pronounced clumping, while weaker cooling leads to saturated modes that devolve into turbulent flows. These results suggest that expanding H II regions may either promote or provide turbulent support against the formation of later generations of stars, with potential consequences for star formation rates in the Galaxy today.
Photon-dominated region modeling of the [C I], [C II], and CO Line Emission From A Boundary In The Taurus molecular cloud

We present [C I] and [C II] observations of a linear edge region in the Taurus molecular cloud, and model this region as a cylindrically symmetric photon-dominated region (PDR) exposed to a low-intensity UV radiation field. The sharp, long profile of the linear edge makes it an ideal case to test PDR models and determine cloud parameters. We compare observations of the [C I], {sup 3} P {sub 1} → {sup 3} P {sub 0} (492 GHz), [C I] {sup 3} P {sub 2} → {sup 3} P {sub 1} (809 GHz), and [C II] {sup 2} P {sub 3/2} → {sup 2} P {sub 1/2} (1900 GHz) transitions, as well as the lowest rotational transitions of {sup 12}CO and {sup 13}CO, with line intensities produced by the RATRAN radiative transfer code from the results of the Meudon PDR code. We constrain the density structure of the cloud by fitting a cylindrical density function to visual extinction data. We study the effects of variation of the FUV field, {sup 12}C/{sup 13}C isotopic abundance ratio, sulfur depletion, cosmic ray ionization rate, and inclination of the filament relative to the sky-plane on the chemical network of the PDR model and resulting linemore » emission. We also consider the role of suprathermal chemistry and density inhomogeneities. We find good agreement between the model and observations, and that the integrated line intensities can be explained by a PDR model with an external FUV field of 0.05 G {sub 0}, a low ratio of {sup 12}C to {sup 13}C ∼43, a highly depleted sulfur abundance (by a factor of at least 50), a cosmic ray ionization rate (3-6) × 10{sup –17} s{sup –1}, and without significant effects from inclination, clumping or suprathermal chemistry.« less
Exact calculation of stimulated emission driven by pulsed light

Stimulated emission can be defined as the process when an incoming photon stimulates an additional quantum of energy from an atom into the same electromagnetic mode as the impinging photon. Hence, the two outgoing photons are identical. In a waveguide or free space, this intuition is typically found through Fermi’s Golden rule, however, this does not properly account for the wave-like nature of the photons. Here, I present an exact solution to stimulated emission from a quantum two-level atom that properly accounts for the incoming and outgoing electromagnetic modes. This result is valid over a huge range of incident photon numbers. For a single incident photon, it shows how the photon must properly mode match the two-level system to cause stimulated emission. For a Fock state drive with large photon number, the exact solution shows how a two-level system Rabi oscillates with the traveling Fock mode as it passes by. I additionally use the same formalism to show that stimulated emission by a coherent pulse cannot be understood as an additional photon being emitted into the incident coherent state because the two-level system’s state factorizes with the electromagnetic field’s coherent state. Recent advances in superconducting circuits make them an ideal platform to test these predictions.
A microrod-resonator Brillouin laser with 240 Hz absolute linewidth

We demonstrate an ultralow-noise microrod-resonator based laser that oscillates on the gain supplied by the stimulated Brillouin scattering optical nonlinearity. Microresonator Brillouin lasers are known to offer an outstanding frequency noise floor, which is limited by fundamental thermal fluctuations. Here, we show experimental evidence that thermal effects also dominate the close-to-carrier frequency fluctuations. The 6 mm diameter microrod resonator used in our experiments has a large optical mode area of ~100 μm2, and hence its 10 ms thermal time constant filters the close-to-carrier optical frequency noise. The result is an absolute laser linewidth of 240 Hz with a corresponding white-frequency noise floor of 0.1 Hz2 Hz−1. We explain the steady-state performance of this laser by measurements of its operation state and of its mode detuning and lineshape. Our results highlight a mechanism for noise that is common to many microresonator devices due to the inherent coupling between intracavity power and mode frequency. We demonstrate the ability to reduce this noise through a feedback loop that stabilizes the intracavity power.
Holographic Renyi Entropy from Quantum Error Correction

We study Renyi entropies Sn in quantum error correcting codes and compare the answer to the cosmic brane prescription for computing $$ {\tilde{S}}_n\equiv {n}^2{\partial}_n\left(\frac{n-1}{n}{S}_n\right) $$ . We find that general operator algebra codes have a similar, more general prescription. Notably, for the AdS/CFT code to match the specific cosmic brane prescription, the code must have maximal entanglement within eigenspaces of the area operator. This gives us an improved definition of the area operator, and establishes a stronger connection between the Ryu-Takayanagi area term and the edge modes in lattice gauge theory. We also propose a new interpretation of existing holographic tensor networks as area eigenstates instead of smooth geometries. This interpretation would explain why tensor networks have historically had trouble modeling the Renyi entropy spectrum of holographic CFTs, and it suggests a method to construct holographic networks with the correct spectrum.
Galaxy Evolution in the Reddest Possible Filter

We describe an observational programme aimed at understanding the radio emission from distant, rapidly evolving galaxy populations. These observations were carried out at 1.4 and 8.5 GHz with the VLA, centred on the Hubble Deep Field, obtaining limiting flux densities of 40 and 8 μJy respectively. The differential count of the radio sources is marginally sub-Euclidean to the completeness limits(γ = − 2.4 ± 0.1) and fluctuation analysis suggests nearly 60 sources per arcmin2 at the 1 μJy level. Using high-resolution 1.4 GHz observations obtained with MERLIN, we resolve all radio sources detected in the VLA complete sample and measure a median angular size for the microjansky radio population of 1-2". This clue, coupled with the steep spectral index of the 1.4 GHz selected sample, suggests diffuse synchrotron radiation in z ∼ 1 galactic discs. The wide-field HST and ground-based optical exposures show that the radio sources are identified primarily with disc systems composed of irregulars, peculiars, interacting/merging galaxies and a few isolated field spirals. Only 20% of the radio sources can be attributed to AGN – the majority are probably associated with starburst activity. The available redshifts range from 0.1 to 3, with a mean of about 0.8. We are plrobably witnessing a major episode of starburst activity in these luminous (L > L *) systems, occasionallyaccompanied by an embedded AGN.About 20% of the radio sources remain unidentified to I = 26-28 inthe HDF and flanking fields. Several of these objectshave extremely red counterparts. We suggestthat these are high-redshift dusty protogalaxies.
SILICATES ON IAPETUS FROM CASSINI’S COMPOSITE INFRARED SPECTROMETER

We present the first spectral features obtained from Cassini’s Composite Infrared Spectrometer (CIRS) for any icy moon. The spectral region covered by CIRS focal planes (FP) 3 and 4 is rich in emissivity features, but previous studies at these wavelengths have been limited by low signal-to-noise ratios (S/Ns) for individual spectra. Our approach is to average CIRS FP3 spectra to increase the S/N and use emissivity spectra to constrain the composition of the dark material on Iapetus. We find an emissivity feature at ∼855 cm{sup −1} and a possible doublet at 660 and 690 cm{sup −1} that do not correspond to any known instrument artifacts. We attribute the 855 cm{sup −1} feature to fine-grained silicates, similar to those found in dust on Mars and in meteorites, which are nearly featureless at shorter wavelengths. Silicates on the dark terrains of Saturn’s icy moons have been suspected for decades, but there have been no definitive detections until now. Serpentines reported in the literature at ambient temperature and pressure have features near 855 and 660 cm{sup −1}. However, peaks can shift depending on temperature and pressure, so measurements at Iapetus-like conditions are necessary for more positive feature identifications. As a first investigation, wemore » measured muscovite at 125 K in a vacuum and found that this spectrum does match the emissivity feature near 855 cm{sup −1} and the location of the doublet. Further measurements are needed to robustly identify a specific silicate, which would provide clues regarding the origin and implications of the dark material.« less
Data fusion via intrinsic dynamic variables: An application of data-driven Koopman spectral analysis

We demonstrate that the Koopman eigenfunctions and eigenvalues define a set of intrinsic coordinates, which serve as a natural framework for fusing measurements obtained from heterogeneous collections of sensors in systems governed by nonlinear evolution laws. These measurements can be nonlinear, but must, in principle, be rich enough to allow the state to be reconstructed. We approximate the associated Koopman operator using extended dynamic mode decomposition, so the method only requires time series of data for each set of measurements, and a single set of "joint" measurements, which are known to correspond to the same underlying state. We apply this procedure to the FitzHugh-Nagumo PDE, and fuse measurements taken at a single point with principal-component measurements.
Dark matter in 3D

We discuss the relevance of directional detection experiments in the post-discovery era and propose a method to extract the local dark matter phase space distribution from directional data. The first feature of this method is a parameterization of the dark matter distribution function in terms of integrals of motion, which can be analytically extended to infer properties of the global distribution if certain equilibrium conditions hold. The second feature of our method is a decomposition of the distribution function in moments of a model independent basis, with minimal reliance on the ansatz for its functional form. We illustrate our method using the Via Lactea II N-body simulation as well as an analytical model for the dark matter halo. We conclude that $$ \mathcal{O}(1000) $$ events are necessary to measure deviations from the Standard Halo Model and constrain or measure the presence of anisotropies.
Geometric Invariant Theory of Syzygies, with Applications to Moduli Spaces

We define syzygy points of projective schemes, and introduce a program of studying their GIT stability. Then we describe two cases where we have managed to make some progress in this program, that of polarized K3 surfaces of odd genus, and of genus six canonical curves. Applications of our results include effectivity statements for divisor classes on the moduli space of odd genus K3 surfaces, and a new construction in the Hassett-Keel program for the moduli space of genus six curves.
A Privacy-Preserving, Accountable and Spam-Resilient Geo-Marketplace

Mobile devices with rich features can record videos, traffic parameters or air quality readings along user trajectories. Although such data may be valuable, users are seldom rewarded for collecting them. Emerging digital marketplaces allow owners to advertise their data to interested buyers. We focus on geo-marketplaces, where buyers search data based on geo-tags. Such marketplaces present significant challenges. First, if owners upload data with revealed geo-tags, they expose themselves to serious privacy risks. Second, owners must be accountable for advertised data, and must not be allowed to subsequently alter geo-tags. Third, such a system may be vulnerable to intensive spam activities, where dishonest owners flood the system with fake advertisements. We propose a geo-marketplace that addresses all these concerns. We employ searchable encryption, digital commitments, and blockchain to protect the location privacy of owners while at the same time incorporating accountability and spam-resilience mechanisms. We implement a prototype with two alternative designs that obtain distinct trade-offs between trust assumptions and performance. Our experiments on real location data show that one can achieve the above design goals with practical performance and reasonable financial overhead.
Online Ensemble Model Compression Using Knowledge Distillation

This paper presents a novel knowledge distillation based model compression framework consisting of a student ensemble. It enables distillation of simultaneously learnt ensemble knowledge onto each of the compressed student models. Each model learns unique representations from the data distribution due to its distinct architecture. This helps the ensemble generalize better by combining every model’s knowledge. The distilled students and ensemble teacher are trained simultaneously without requiring any pretrained weights. Moreover, our proposed method can deliver multi-compressed students with single training, which is efficient and flexible for different scenarios. We provide comprehensive experiments using state-of-the-art classification models to validate our framework’s effectiveness. Notably, using our framework a 97% compressed ResNet110 student model managed to produce a 10.64% relative accuracy gain over its individual baseline training on CIFAR100 dataset. Similarly a 95% compressed DenseNet-BC (k = 12) model managed a 8.17% relative accuracy gain.
Lift and Relax for PDE-Constrained Inverse Problems in Seismic Imaging

We present lift and relax for waveform inversion (LRWI), an approach that mitigates the local minima issue in seismic full waveform inversion (FWI) via a combination of two convexification techniques. The first technique (Lift) extends the set of unknown variables to their products, arranged as a moment matrix. This algebraic idea is a celebrated way to replace a hard polynomial optimization problem by a semidefinite programming approximation. Concretely, both the model and the wavefield are lifted from vectors to rank-2 matrices. The second technique (Relax) invites to relax the strict wave-equation constraint—a technique known as wavefield reconstruction inversion (WRI), which introduces wave-equation misfits as a weighted penalty term in the objective function. The relaxed penalty formulation enables balancing the data and wave-equation misfits by tuning a penalty parameter. Together, “Lift” and “Relax” help reformulate the inverse problem as a set of constraints on a rank-2 moment matrix. Such a lifting strategy permits good data and wave equation fits throughout the inversion process while leaving the numerical rank of the rank-2 moment matrix to be minimized down to one. Moreover, LRWI does not require adjoint wavefield to compute the gradient, which mitigates computational burdens. Numerical examples indicate that starting with a poor initial model, LRWI can conduct successful inversions with a starting frequency that is higher than that required by FWI and WRI.
Dysfunction by Design: Trumpism as Administrative Doctrine

The administration of President Donald Trump caused widespread damage to administrative capabilities of the American federal government Actions of the administration can be attributed to several causes, including character weaknesses of the President himself, the disadvantages of a political insurgent, and the challenges faced by every president in an era of divided government The actions of the administration also reflect a governing strategy we categorize as Trumpism Important elements of Trumpism will continue to have political force in the coming years Attempts by the Biden administration to restore administrative capabilities will be constrained by these political realities Evidence for PracticeTrumpism was a governing strategy that was associated with a distinctive approach toward the reconstruction of federal administrative capacities Trumpism revived and reinvented old strands in American political thought, such as populism, conspiracism, isolationism, and white nationalism Trumpism as an administrative doctrine included delegitimization of the public service, a politicized and personalized management of the executive branch, a demand for loyalty over competence among public servants, a blurring of roles between Trump and the office of the President, and a disregard for traditional forms of accountability As a means of managing public services, Trumpism could be judged a failure Mismanagement of the COVID pandemic likely cost Trump his re‐election However, his attacks on public service itself drew broad support While Trump is a unique political figure, elements of Trumpism will remain influential in American politics Attempts to reconstruct and expand federal administrative capacities will be constrained by this political reality
Demographics matter: the potentially disproportionate effect of COVID-19 on hospital ratings.

Objective To identify how features of the community in which a hospital serves differentially relate to its patients' experiences based on the quality of that hospital. Design A Finite Mixture Model (FMM) is used to uncover a mix of two latent groups of hospitals that differ in quality. In the FMM, a multinomial logistic equation relates hospital-level factors to the odds of being in either group. And a multiple linear regression relates the characteristics of communities served by hospitals to the patients' expected ratings of their experiences at hospitals in each group. Thus, this association potentially varies with hospital quality. The analysis was conducted via Stata. Setting Hospital Ratings are measured by Hospital Compare using the HCAHPS survey, a patient satisfaction survey required by the Centers for Medicare and Medicaid Services (CMS) for hospitals in the United States. Participants: 2,816 Medicare-certified acute care hospitals across all US states.
Hybrid guided space-time optical modes in unpatterned films.

Light is confined transversely and delivered axially in a waveguide. However, waveguides are lossy static structures whose modal characteristics are fundamentally determined by their boundary conditions. Here we show that unpatterned planar waveguides can provide low-loss two-dimensional waveguiding by using space-time wave packets, which are unique one-dimensional propagation-invariant pulsed optical beams. We observe hybrid guided space-time modes that are index-guided in one transverse dimension and localized along the unbounded dimension. We confirm that these fields enable overriding the boundary conditions by varying post-fabrication the group index of the fundamental mode in a 2-μm-thick, 25-mm-long silica film, achieved by modifying the field’s spatio-temporal structure. Tunability of the group index over an unprecedented range from 1.26 to 1.77 is verified while maintaining a spectrally flat zero-dispersion profile. Our work paves the way to utilizing space-time wave packets in on-chip platforms, and enable phase-matching strategies that circumvent restrictions due to intrinsic material properties. Waveguides typically function by using boundary conditions to contain light. Here, the authors show that by using space-time wavepackets, light can be guided in an unpatterned planar waveguide as the field remains localized along the unbounded dimension.
Real-World Experience of Holmium Laser Enucleation of the Prostate with Patients on Anticoagulation Therapy.

Background: Holmium laser enucleation of the prostate (HoLEP) is a highly effective procedure for benign prostatic hyperplasia that is size independent and has been recommended for patients necessi...
Large-scale Lipschitz estimates for elliptic systems with periodic high-contrast coefficients

This article is concerned with the large-scale regularity in the homogenization of elliptic systems of elasticity with periodic high-contrast coefficients. We obtain the large-scale Lipschitz estim...
Local Statistics, Semidefinite Programming, and Community Detection

We propose a new hierarchy of semidefinite programming relaxations for inference problems. As test cases, we consider the problem of community detection in block models. The vertices are partitioned into $k$ communities, and a graph is sampled conditional on a prescribed number of inter- and intra-community edges. The problem of detection, where we are to decide with high probability whether a graph was drawn from this model or the uniform distribution on regular graphs, is conjectured to undergo a computational phase transition at a point called the Kesten-Stigum (KS) threshold. In this work, we consider two models of random graphs namely the well-studied (irregular) stochastic block model and a distribution over random regular graphs we'll call the Degree Regular Block Model. For both these models, we show that sufficiently high constant levels of our hierarchy can perform detection arbitrarily close to the KS threshold and that our algorithm is robust to up to a linear number of adversarial edge perturbations. Furthermore, in the case of Degree Regular Block Model (DRBM), we show that below the Kesten-Stigum threshold no constant level can do so. In the case of the (irregular) Stochastic Block Model, it is known that efficient algorithms exist all the way down to this threshold, although none are robust to a linear number of adversarial perturbations of the graph when the average degree is small. More importantly, there is little complexity-theoretic evidence that detection is hard below the threshold. In the DRBM with more than two groups, it has not to our knowledge been proven that any algorithm succeeds down to the KS threshold, let alone that one can do so robustly, and there is a similar dearth of evidence for hardness below this point.
Succinate Accumulation Links Mitochondrial MnSOD Depletion to Aberrant Nuclear DNA Methylation and Altered Cell Fate.

Previous studies showed that human cell line HEK293 lacking mitochondrial superoxide dismutase (MnSOD) exhibited decreased succinate dehydrogenase (SDH) activity, and mice lacking MnSOD displayed significant reductions in SDH and aconitase activities. Since MnSOD has significant effects on SDH activity, and succinate is a key regulator of TET enzymes needed for proper differentiation, we hypothesized that SOD2 loss would lead to succinate accumulation, inhibition of TET activity, and impaired erythroid precursor differentiation. To test this hypothesis, we genetically disrupted the SOD2 gene using the CRISPR/Cas9 genetic strategy in a human erythroleukemia cell line (HEL 92.1.7) capable of induced differentiation toward an erythroid phenotype. Cells obtained in this manner displayed significant inhibition of SDH activity and ~10-fold increases in cellular succinate levels compared to their parent cell controls. Furthermore, SOD2-/- cells exhibited significantly reduced TET enzyme activity concomitant with decreases in genomic 5-hmC and corresponding increases in 5-mC. Finally, when stimulated with δ-aminolevulonic acid (δ-ALA), SOD2-/- HEL cells failed to properly differentiate toward an erythroid phenotype, likely due to failure to complete the necessary global DNA demethylation program required for erythroid maturation. Together, our findings support the model of an SDH/succinate/TET axis and a role for succinate as a retrograde signaling molecule of mitochondrial origin that significantly perturbs nuclear epigenetic reprogramming and introduce MnSOD as a governor of the SDH/succinate/TET axis.
Isolation of SAR11 Marine Bacteria from Cryopreserved Seawater.

ABSTRACT While marine microorganisms are frequently studied in their natural environment, isolated strains are invaluable resources that can be used in controlled experiments to expand upon direct observations from natural systems. Here, we sought a means to enhance culture collections of SAR11 marine bacteria by testing the use of seawater cryopreserved with glycerol as an inoculum. Using a raw seawater sample collected from the tropical Pacific Ocean, a subsample was diluted in seawater growth medium to create 576 2-ml dilution cultures containing 5 cells each and incubated for a high-throughput culturing (HTC) experiment, while another portion was cryopreserved in 10% glycerol. After 10 months, a cryopreserved aliquot was thawed and used to create a second cultivation experiment of 480 2-ml cultures containing 5 cells each and 470 cultures containing 105 cells each. The raw seawater cultivation experiment resulted in the successful isolation of 54 monocultures and 29 mixed cultures, while cryopreserved seawater resulted in 59 monocultures and 29 mixed cultures. Combined, the cultures included 51 SAR11 isolates spanning 11 unique 16S rRNA gene amplicon sequence variants (ASVs) from the raw seawater inoculum and 74 SAR11 isolates spanning 13 unique ASVs from cryopreserved seawater. A vast majority (92%) of SAR11 isolates from the two HTC experiments were members of SAR11 subclade Ia, though subclades IIIa and Va were also recovered from cryopreserved seawater and subclade Ib was recovered from both. The four most abundant SAR11 subclade Ia ASVs found in the initial seawater environmental sample were isolated by both approaches. IMPORTANCE High-throughput dilution culture has proved to be a successful approach to bring some difficult-to-isolate planktonic microorganisms into culture, including the highly abundant SAR11 lineage of marine bacteria. While the long-term preservation of bacterial isolates by freezing them in the presence of cryoprotectants, such as glycerol, has been shown to be an effective method of storing viable cells over long time periods (i.e., years), to our knowledge it had not previously been tested for its efficacy in preserving raw seawater for later use as an inoculum for high-throughput cultivation experiments. We found that SAR11 and other abundant marine bacteria could be isolated from seawater that was previously cryopreserved for nearly 10 months at a rate of culturability similar to that of the same seawater used fresh, immediately after collection. Our findings (i) expand the potential of high-throughput cultivation experiments to include testing when immediate isolation experiments are impractical, (ii) allow for targeted isolation experiments from specific samples based on analyses such as microbial community structure, and (iii) enable cultivation experiments across a wide range of other conditions that would benefit from having source inocula available over extended periods of time.
Adversarial Machine Learning-Industry Perspectives

Based on interviews with 28 organizations, we found that industry practitioners are not equipped with tactical and strategic tools to protect, detect and respond to attacks on their Machine Learning (ML) systems. We leverage the insights from the interviews and enumerate the gaps in securing machine learning systems when viewed in the context of traditional software security development. We write this paper from the perspective of two personas: developers/ML engineers and security incident responders. The goal of this paper is to layout the research agenda to amend the Security Development Lifecycle for industrial-grade software in the adversarial ML era.
Web 2.0 chronic disease self-management for older adults: A systematic review

Background: Participatory Web 2.0 interventions promote collaboration to support chronic disease self-management. Growth in Web 2.0 interventions has led to the emergence of e-patient communication tools that enable older adults to (1) locate and share disease management information and (2) receive interactive healthcare advice. The evolution of older e-patients contributing to Web 2.0 health and medical forums has led to greater opportunities for achieving better chronic disease outcomes. To date, there are no review articles investigating the planning, implementation, and evaluation of Web 2.0 chronic disease self-management interventions for older adults. Objective: To review the planning, implementation, and overall effectiveness of Web 2.0 self-management interventions for older adults (mean age ≥ 50) with one or more chronic disease(s). Methods: A systematic literature search was conducted using six popular health science databases. The RE-AIM (Reach, Efficacy, Adoption, Implementation and Maintenance) model was used to organize findings and compute a study quality score (SQS) for 15 reviewed articles. Results: Most interventions were adopted for delivery by multidisciplinary healthcare teams and tested among small samples of white females with diabetes. Studies indicated that Web 2.0 participants felt greater self-efficacy for managing their disease(s) and benefitted from communicating with health care providers and/or website moderators to receive feedback and social support. Participants noted asynchronous communication tools (eg, email, discussion boards) and progress tracking features (eg, graphical displays of uploaded personal data) as being particularly useful for self-management support. Despite high attrition being noted as problematic, this review suggests that greater Web 2.0 engagement may be associated with improvements in health behaviors (eg, physical activity) and health status (eg, HRQoL). However, few studies indicated statistically significant improvements in medication adherence, biological outcomes, or health care utilization. Mean SQS scores were notably low (mean=63%, SD 18%). Studies were judged to be weakest on the Maintenance dimension of RE-AIM; 13 reviewed studies (87%) did not describe any measures taken to sustain Web 2.0 effects past designated study time periods. Detailed process and impact evaluation frameworks were also missing in almost half (n=7) of the reviewed interventions. Conclusions: There is need for a greater understanding of the costs and benefits associated with using patient-centered Web 2.0 technologies for chronic disease self-management. More research is needed to determine whether the long-term effectiveness of these programs is sustainable among larger, more diverse samples of chronically ill patients. The effective translation of new knowledge, social technologies, and engagement techniques will likely result in novel approaches for empowering, engaging, and educating older adults with chronic disease. [J Med Internet Res 2013;15(2):e35]
Structure and contingency determine mutational hotspots for flower color evolution.

Evolutionary genetic studies have uncovered abundant evidence for genomic hotspots of phenotypic evolution, as well as biased patterns of mutations at those loci. However, the theoretical basis for this concentration of particular types of mutations at particular loci remains largely unexplored. In addition, historical contingency is known to play a major role in evolutionary trajectories, but has not been reconciled with the existence of such hotspots. For example, do the appearance of hotspots and the fixation of different types of mutations at those loci depend on the starting state and/or on the nature and direction of selection? Here, we use a computational approach to examine these questions, focusing the anthocyanin pigmentation pathway, which has been extensively studied in the context of flower color transitions. We investigate two transitions that are common in nature, the transition from blue to purple pigmentation and from purple to red pigmentation. Both sets of simulated transitions occur with a small number of mutations at just four loci and show strikingly similar peaked shapes of evolutionary trajectories, with the mutations of the largest effect occurring early but not first. Nevertheless, the types of mutations (biochemical vs. regulatory) as well as their direction and magnitude are contingent on the particular transition. These simulated color transitions largely mirror findings from natural flower color transitions, which are known to occur via repeated changes at a few hotspot loci. Still, some types of mutations observed in our simulated color evolution are rarely observed in nature, suggesting that pleiotropic effects further limit the trajectories between color phenotypes. Overall, our results indicate that the branching structure of the pathway leads to a predictable concentration of evolutionary change at the hotspot loci, but the types of mutations at these loci and their order is contingent on the evolutionary context.
On the Feasibility of Load-Changing Attacks in Power Systems During the COVID-19 Pandemic

The electric power grid is a complex cyberphysical energy system (CPES) in which information and communication technologies (ICT) are integrated into the operations and services of the power grid infrastructure. The growing number of Internet-of-things (IoT) high-wattage appliances, such as air conditioners and electric vehicles, being connected to the power grid, together with the high dependence of ICT and control interfaces, make CPES vulnerable to high-impact, low-probability load-changing cyberattacks. Moreover, the side-effects of the COVID-19 pandemic demonstrate a modification of electricity consumption patterns with utilities experiencing significant net-load and peak reductions. These unusual sustained low load demand conditions could be leveraged by adversaries to cause frequency instabilities in CPES by compromising hundreds of thousands of IoT-connected high-wattage loads. This article presents a feasibility study of the impacts of load-changing attacks on CPES during the low loading conditions caused by the lockdown measures implemented during the COVID-19 pandemic. The load demand reductions caused by the lockdown measures are analyzed using dynamic mode decomposition (DMD), focusing on the March-to-July 2020 period and the New York region as the most impacted time period and location in terms of load reduction due to the lockdowns being in full execution. Our feasibility study evaluates load-changing attack scenarios using real load consumption data from the New York Independent System Operator (NYISO) and shows that an attacker with sufficient knowledge and resources could be capable of producing frequency stability problems, with frequency excursions going up to 60.5 Hz and 63.4 Hz, when no mitigation measures are taken.