cssi/SciSciGPT-SciSciNet huggingface dataset:
Data-Based Receding Horizon Control of Linear Network Systems

We propose a distributed data-based predictive control scheme to stabilize a network system described by linear dynamics. Agents cooperate to predict the future system evolution without knowledge of the dynamics, relying instead on learning a data-based representation from a single sample trajectory. We employ this representation to reformulate the finite-horizon Linear Quadratic Regulator problem as a network optimization with separable objective functions and locally expressible constraints. We show that the controller resulting from approximately solving this problem using a distributed optimization algorithm in a receding horizon manner is stabilizing. We validate our results through numerical simulations.
Dynamical chaos in a simple model of a knuckleball

Abstract The knuckleball is perhaps the most enigmatic pitch in baseball. Relying on the presence of raised seams on the surface of the ball to create asymmetric flow, a knuckleball’s trajectory has proven very challenging to predict compared to other baseball pitches, such as fastballs or curveballs. Previous experimental tracking of large numbers of knuckleballs has shown that they can move in essentially any direction relative to what would be expected from a drag-only trajectory. This has led to speculation that knuckleballs exhibit chaotic motion. Here we develop a relatively simple model of a knuckleball that includes quadratic drag and lift from asymmetric flow which is taken from experimental measurements of slowly rotating baseballs. Our models can indeed exhibit dynamical chaos as long as torque on the ball from the asymmetric flow is included. In contrast, models that omit torques on the ball in flight do not show chaotic behavior. Uncertainties in the phase space position of the knuckleball are shown to grow by factors as large as 106 over the flight of the ball from the pitcher to home plate. We quantify the impact of our model parameters on the chaos realized in our models, specifically showing that maximum Lyapunov exponent is roughly proportional to the square root of the effective lever arm of the torque, and also roughly proportional to the initial velocity of the pitch. We demonstrate the existence of bifurcations that can produce changes in the location of the ball when it reaches the plate of as much as 1.2 m for specific initial conditions similar to those used by professional knuckleball pitchers. As we introduce additional complexity in the form of more faithful representations of the empirical asymmetry force measurements, we find that a larger fraction of the possible initial conditions result in dynamical chaos. The chaotic behavior seen in our simplified model combined with the additional complex and nonlinear effects likely present in real knuckleballs provide strong evidence that knuckleballs are in fact chaotic, and that the chaotic uncertainty is likely a significant factor in the unpredictability of the pitch.
Defoliation-induced compensatory transpiration is compromised in SUT4-RNAi Populus.

The tonoplast sucrose transporter PtaSUT4 is well expressed in leaves of Populus tremula × Populus alba (INRA 717-IB4), and its inhibition by RNA-interference (RNAi) alters leaf sucrose homeostasis. Whether sucrose partitioning between the vacuole and the cytosol is modulated by PtaSUT4 for specific physiological outcomes in Populus remains unexplored. In this study, partial defoliation was used to elicit compensatory increases in photosynthesis and transpiration by the remaining leaves in greenhouse-grown poplar. Water uptake, leaf gas exchange properties, growth and nonstructural carbohydrate abundance in source and sink organs were then compared between wild-type and SUT4-RNAi lines. Partial defoliation increased maximum photosynthesis rates similarly in all lines. There was no indication that source leaf sugar levels changed differently between wild-type and RNAi plants following partial defoliation. Sink levels of hexose (glucose and fructose) and starch decreased similarly in all lines. Interestingly, plant water uptake after partial defoliation was not as well sustained in RNAi as in wild-type plants. While the compensatory increase in photosynthesis was similar between genotypes, leaf transpiration increased less robustly in RNAi than wild-type plants. SUT4-RNAi and wild-type source leaves differed constitutively in their bulk modulus of elasticity, a measure of leaf turgor, and storage water capacitance. The data demonstrate that reduced sucrose partitioning due to PtaSUT4-RNAi altered turgor control and compensatory transpiration capacity more strikingly than photosynthesis and sugar export. The results are consistent with the interpretation that SUT4 may control vacuolar turgor independently of sink carbon provisioning.
Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses

Convolutional neural network based systems have largely failed to be adopted in many high-risk application areas, including healthcare, military, security, transportation, finance, and legal, due to their highly uninterpretable “black-box” nature. Towards solving this deficiency, we teach a novel multi-task capsule network to improve the explainability of predictions by embodying the same high-level language used by human-experts. Our explainable capsule network, X-Caps, encodes high-level visual object attributes within the vectors of its capsules, then forms predictions based solely on these human-interpretable features. To encode attributes, X-Caps utilizes a new routing sigmoid function to independently route information from child capsules to parents. Further, to provide radiologists with an estimate of model confidence, we train our network on a distribution of expert labels, modeling inter-observer agreement and punishing over/under confidence during training, supervised by human-experts’ agreement. X-Caps simultaneously learns attribute and malignancy scores from a multi-center dataset of over 1000 CT scans of lung cancer screening patients. We demonstrate a simple 2D capsule network can outperform a state-of-the-art deep dense dual-path 3D CNN at capturing visually-interpretable high-level attributes and malignancy prediction, while providing malignancy prediction scores approaching that of non-explainable 3D CNNs. To the best of our knowledge, this is the first study to investigate capsule networks for making predictions based on radiologist-level interpretable attributes and its applications to medical image diagnosis. Code is publicly available at https://github.com/lalonderodney/X-Caps.
Online Adaptive Learning for Runtime Resource Management of Heterogeneous SoCs

Dynamic resource management has become one of the major areas of research in modern computer and communication system design due to lower power consumption and higher performance demands. The number of integrated cores, level of heterogeneity and amount of control knobs increase steadily. As a result, the system complexity is increasing faster than our ability to optimize and dynamically manage the resources. Moreover, offline approaches are sub-optimal due to workload variations and large volume of new applications unknown at design time. This paper first reviews recent online learning techniques for predicting system performance, power, and temperature. Then, we describe the use of predictive models for online control using two modern approaches: imitation learning (IL) and an explicit nonlinear model predictive control (NMPC). Evaluations on a commercial mobile platform with 16 benchmarks show that the IL approach successfully adapts the control policy to unknown applications. The explicit NMPC provides 25% energy savings compared to a state-of-the-art algorithm for multi-variable power management of modern GPU sub-systems.
Semantic Discriminability for Visual Communication

To interpret information visualizations, observers must determine how visual features map onto concepts. First and foremost, this ability depends on perceptual discriminability; observers must be able to see the difference between different colors for those colors to communicate different meanings. However, the ability to interpret visualizations also depends on semantic discriminability, the degree to which observers can infer a unique mapping between visual features and concepts, based on the visual features and concepts alone (i.e., without help from verbal cues such as legends or labels). Previous evidence suggested that observers were better at interpreting encoding systems that maximized semantic discriminability (maximizing association strength between assigned colors and concepts while minimizing association strength between unassigned colors and concepts), compared to a system that only maximized color-concept association strength. However, increasing semantic discriminability also resulted in increased perceptual distance, so it is unclear which factor was responsible for improved performance. In the present study, we conducted two experiments that tested for independent effects of semantic distance and perceptual distance on semantic discriminability of bar graph data visualizations. Perceptual distance was large enough to ensure colors were more than just noticeably different. We found that increasing semantic distance improved performance, independent of variation in perceptual distance, and when these two factors were uncorrelated, responses were dominated by semantic distance. These results have implications for navigating trade-offs in color palette design optimization for visual communication.
The World as a Neural Network.

We discuss a possibility that the entire universe on its most fundamental level is a neural network. We identify two different types of dynamical degrees of freedom: “trainable” variables (e.g., bias vector or weight matrix) and “hidden” variables (e.g., state vector of neurons). We first consider stochastic evolution of the trainable variables to argue that near equilibrium their dynamics is well approximated by Madelung equations (with free energy representing the phase) and further away from the equilibrium by Hamilton–Jacobi equations (with free energy representing the Hamilton’s principal function). This shows that the trainable variables can indeed exhibit classical and quantum behaviors with the state vector of neurons representing the hidden variables. We then study stochastic evolution of the hidden variables by considering D non-interacting subsystems with average state vectors, x¯1, …, x¯D and an overall average state vector x¯0. In the limit when the weight matrix is a permutation matrix, the dynamics of x¯μ can be described in terms of relativistic strings in an emergent D+1 dimensional Minkowski space-time. If the subsystems are minimally interacting, with interactions that are described by a metric tensor, and then the emergent space-time becomes curved. We argue that the entropy production in such a system is a local function of the metric tensor which should be determined by the symmetries of the Onsager tensor. It turns out that a very simple and highly symmetric Onsager tensor leads to the entropy production described by the Einstein–Hilbert term. This shows that the learning dynamics of a neural network can indeed exhibit approximate behaviors that were described by both quantum mechanics and general relativity. We also discuss a possibility that the two descriptions are holographic duals of each other.
Semi-Supervised Deep Learning for High-Dimensional Uncertainty Quantification

Conventional uncertainty quantification methods usually lacks the capability of dealing with high-dimensional problems due to the curse of dimensionality. This paper presents a semi-supervised learning framework for dimension reduction and reliability analysis. An autoencoder is first adopted for mapping the high-dimensional space into a low-dimensional latent space, which contains a distinguishable failure surface. Then a deep feedforward neural network (DFN) is utilized to learn the mapping relationship and reconstruct the latent space, while the Gaussian process (GP) modeling technique is used to build the surrogate model of the transformed limit state function. During the training process of the DFN, the discrepancy between the actual and reconstructed latent space is minimized through semi-supervised learning for ensuring the accuracy. Both labeled and unlabeled samples are utilized for defining the loss function of the DFN. Evolutionary algorithm is adopted to train the DFN, then the Monte Carlo simulation method is used for uncertainty quantification and reliability analysis based on the proposed framework. The effectiveness is demonstrated through a mathematical example.
The Special Rapporteur on the Human Rights to Safe Drinking Water and Sanitation: An Assessment of Its First Dozen Years

The Special Rapporteur for Safe Drinking Water and Sanitation is a norm entrepreneur, both as a norm monitor and clarifier, as well as an advocate for reparative action for victims. Two incumbents have identified fundamental principles of these two human rights and many implementation requirements for their protection. Appropriate attention has been placed on various vulnerable groups that require greater efforts at norm compliance through policy responses. However, many countries have tremendous inequalities in access to water and sanitation, which are largely unacknowledged and even unnoticed, for which states have a positive responsibility, but which are not easily noticed because of weak civil society monitoring. Both mandate holders have much of their efforts on country visits with governments interested in improvement—which is desirable for both the countries concerned and for the development of rubrics for institutionalized lessons learned, best practices and methodologies for information collection and analysis. Considerable efforts have also been made on norm development that hopefully encourages emulation. More emphasis is needed to identify and clarify legally-binding, hard law requirements in implementation, not just soft-law non-legally binding recommendations to governments and their public and private partners, as well as specifying the binding rights of the vulnerable. Also needed are more cataloguing of government violations of the human rights to safe drinking water and sanitation, especially outside of Latin America, from where the two mandate holders come. Particular attention should be paid to countries that refuse country visits. Greater use of reliable information concerning pollution of drinking water, poor sanitation, economic development without consultation or impact analysis, exorbitant pricing of water, and inadequate sanitation that allows public defecation. This office should also coordinate generally more often with other Special Procedures on many inter-sectional issues, but above all else, on climate change issues, which present an existential threat to rights protection. While there are many competing claims for resources, important issues regarding access to safe drinking water and sanitation go unnoticed by this office because of its insufficient attention to early warning and urgent action procedures for these violations. However, the contributions of the two mandate holders to norm development has been clear, effective and deserving of praise.
Transient emotions, perceptions of well-being, and mutual fund flows

Abstract Investors’ sentiment is typically proxied by aggregate measures. However, it is composed of distinguishable elements, including impermanent emotions and subjective appraisals of well-being. We show that experiencing transient happiness is associated with flows to mutual funds in the following month. When considering funds’ investment style, heterogeneous effects arise. Happiness and perceived well-being correspond with flows to growth funds but not value funds. Ultimately, broad measures of sentiment may conceal nuances of investor behavior, which can potentially affect asset prices through investment style preferences.
A validated measure of rigidity in Parkinson's disease using alternating finger tapping on an engineered keyboard.

Abstract Introduction Reliable and accurate measures of rigidity have remained elusive in remote assessments of Parkinson's disease (PD). This has severely limited the utility of telemedicine in the care and treatment of people with PD. It has also had a large negative impact on the scope of available outcomes, and on the costs, of multicenter clinical trials in PD. The goal of this study was to determine if quantitative measures from an engineered keyboard were sensitive and related to clinical measures of rigidity. Methods Sixteen participants with idiopathic PD, off antiparkinsonian medications, and eleven age-matched control participants performed a 30 second repetitive alternating finger tapping task on an engineered keyboard and were assessed with the Unified Parkinson's Disease Rating Scale – motor (UPDRS-III). Results The speed of the key release was significantly slower in the PD compared to control cohorts (p Conclusions This validated measure of rigidity complements our previous validation of temporal metrics of the repetitive alternating finger tapping task with the UPDRS III, bradykinesia and with the ability to quantify tremor, arrhythmicity and freezing episodes, and suggests that 30 seconds of alternating finger tapping on a portable engineered keyboard could transform the treatment of PD with telemedicine and the precision of multicenter clinical trials.
Thermal emittance measurements of a cesium potassium antimonide photocathode

Thermal emittance measurements of a CsK2Sb photocathode at several laser wavelengths are presented. The emittance is obtained with a solenoid scan technique using a high voltage dc photoemission gun. The thermal emittance is 0.56±0.03 mm mrad/mm(rms) at 532 nm wavelength. The results are compared with a simple photoemission model and found to be in a good agreement.
Hybrid CMOS detectors for the Lynx x-ray surveyor high definition x-ray imager

X-ray hybrid CMOS detectors (HCDs) are a promising candidate for future x-ray missions requiring high throughput and fine angular resolution along with large field-of-view, such as the high-definition x-ray imager (HDXI) instrument on the Lynx x-ray surveyor mission concept. These devices offer fast readout capability, low power consumption, and radiation hardness while maintaining high detection efficiency from 0.2 to 10 keV. In addition, x-ray hybrid CMOS sensors may be fabricated with small pixel sizes to accommodate high-resolution optics and have shown great improvements in recent years in noise and spectral resolution performance. In particular, 12.5-μm pitch prototype devices that include in-pixel correlated double sampling capability and crosstalk eliminating capacitive transimpedance amplifiers, have been fabricated and tested. These detectors have achieved read noise as low as 5.4 e − , and we measure the best energy resolution to be 148 eV (2.5%) at 5.9 keV and 78 eV (14.9%) at 0.53 keV. We will describe the characterization of these prototype small-pixel x-ray HCDs, and we will discuss their applicability to the HDXI instrument on Lynx.
Chiral Magnetic Effects in Nuclear Collisions

The interplay of quantum anomalies with strong magnetic fields and vorticity in chiral systems could lead to novel transport phenomena, such as the chiral magnetic effect (CME), the chiral magnetic...
LIGHTFRONT HAMILTONIAN STRUCTURES FOR THE NONLINEAR SIGMA MODEL

We derive the Dirac brackets for the O(N) nonlinear sigma model in the lightfront description with and without constraint. We bring out various subtleties that arise including the fact that antiperiodic boundary condition seems to be preferred.
Curvature and torsion in growing actin networks

Intracellular pathogens such as Listeria monocytogenes and Rickettsia rickettsii move within a host cell by polymerizing a comet-tail of actin fibers that ultimately pushes the cell forward. This dense network of cross-linked actin polymers typically exhibits a striking curvature that causes bacteria to move in gently looping paths. Theoretically, tail curvature has been linked to details of motility by considering force and torque balances from a finite number of polymerizing filaments. Here we track beads coated with a prokaryotic activator of actin polymerization in three dimensions to directly quantify the curvature and torsion of bead motility paths. We find that bead paths are more likely to have low rather than high curvature at any given time. Furthermore, path curvature changes very slowly in time, with an autocorrelation decay time of 200 s. Paths with a small radius of curvature, therefore, remain so for an extended period resulting in loops when confined to two dimensions. When allowed to explore a three-dimensional (3D) space, path loops are less evident. Finally, we quantify the torsion in the bead paths and show that beads do not exhibit a significant left- or right-handed bias to their motion in 3D. These results suggest that paths of actin-propelled objects may be attributed to slow changes in curvature, possibly associated with filament debranching, rather than a fixed torque.
Smectic-glass transition in a liquid-crystal cell with a “dirty” substrate

We explore the smectic liquid-crystal order in a cell with a "dirty" substrate imposing random pinnings. Within harmonic elasticity we find a subtle three-dimensional surface disorder-driven transition into a pinned smectic glass, controlled by a three-dimensional Cardy-Ostlund–like fixed line, akin to a super-rough phase of a two-dimensional xy model. We compute the associated random substrate-driven distortions of the smectic-glass state, identify the characteristic length scales on the heterogeneous substrate and in the bulk, and discuss a variety of experimental signatures.
An Extremely Massive Dry Galaxy Merger in a Moderate Redshift Cluster

We have identified perhaps the largest major galaxy merger ever seen. While analyzing Spitzer IRAC images of CL 0958+4702, an X-ray-selected cluster at z = 0.39, we discovered an unusual plume of stars extending 110 h-1 kpc outward from the bright central galaxy (BCG). Three galaxies 1-1.5 mag fainter than the BCG lie within 17 kpc (projected) of the BCG and are probably participating in the merger. The plume is detected in all four IRAC channels and at optical wavelengths in images from the WIYN telescope; the surface brightness is remarkably high (μr ≈ 24.8 mag arcsec-2 at 50 kpc). The optical and infrared colors are consistent with those of other BCGs, suggesting that the plume is composed of old stars and negligible recent star formation (hence a "dry merger"). The luminosity in the plume is at least equivalent to a 4L* galaxy. A diffuse halo extending 110 h-1 kpc from the BCG in one IRAC image suggests the total amount of diffuse light is Lr ~ 1.3 × 1011 h-2 L☉. A Chandra observation shows an X-ray image and spectrum typical of moderate-mass clusters. We use MMT/Hectospec to measure 905 redshifts in a 1 deg2 region around the cluster. The velocities of two of the BCG companions indicate a merger timescale for the companion galaxies of ~110 Myr and ~0.5-1 Gyr for the plume. We conclude that the BCG and intracluster light of CL 0958 is formed by major mergers at moderate redshifts. After the major merger is complete, CL 0958 will likely become a fossil cluster.
A VERSATILE FAMILY OF GALACTIC WIND MODELS

We present a versatile family of model galactic outflows including non-uniform mass and energy source distributions, a gravitational potential from an extended mass source, and radiative losses. The model easily produces steady-state wind solutions for a range of mass-loading factors, energy-loading factors, galaxy mass, and galaxy radius. We find that, with radiative losses included, highly mass-loaded winds must be driven at high central temperatures, whereas low mass-loaded winds can be driven at low temperatures just above the peak of the cooling curve, meaning radiative losses can drastically affect the wind solution even for low mass-loading factors. By including radiative losses, we are able to show that subsonic flows can be ignored as a possible mechanism for expelling mass and energy from a galaxy compared to the more efficient transonic solutions. Specifically, the transonic solutions with low mass loading and high energy loading are the most efficient. Our model also produces low-temperature, high-velocity winds that could explain the prevalence of low-temperature material in observed outflows. Finally, we show that our model, unlike the well-known Chevalier & Clegg model, can reproduce the observed linear relationship between wind X-ray luminosity and star formation rate (SFR) over a large range of SFR from 1–1000 M⊙ yr−1 assuming the wind mass-loading factor is higher for low-mass, and hence, low-SFR galaxies. We also constrain the allowed mass-loading factors that can fit the observed X-ray luminosity versus SFR trend, further suggesting an inverse relationship between mass loading and SFR as explored in advanced numerical simulations.
The Tutte-Potts connection in the presence of an external magnetic field

The classical relationship between the Tutte polynomial of graph theory and the Potts model of statistical mechanics has resulted in valuable interactions between the disciplines. Unfortunately, it does not include the external magnetic fields that appear in most Potts model applications. Here we define the V-polynomial, which lifts the classical relationship between the Tutte polynomial and the zero field Potts model to encompass external magnetic fields. The V-polynomial generalizes Noble and Welsh?s W-polynomial, which extends the Tutte polynomial by incorporating vertex weights and adapting contraction to accommodate them. We prove that the variable field Potts model partition function (with its many specializations) is an evaluation of the V-polynomial, and hence a polynomial with deletion-contraction reduction and Fortuin-Kasteleyn type representation. This unifies an important segment of Potts model theory and brings previously successful combinatorial machinery, including complexity results, to bear on a wider range of statistical mechanics models.
Relativistic linear stability equations for the nonlinear Dirac equation in Bose-Einstein condensates

We present relativistic linear stability equations (RLSE) for quasi-relativistic cold atoms in a honeycomb optical lattice. These equations are derived from first principles and provide a method for computing stabilities of arbitrary localized solutions of the nonlinear Dirac equation (NLDE), a relativistic generalization of the nonlinear Schrodinger equation. We present a variety of such localized solutions: skyrmions, solitons, vortices, and half-quantum vortices, and study their stabilities via the RLSE. When applied to a uniform background, our calculations reveal an experimentally observable effect in the form of Cherenkov radiation.
Lovelock–Brans–Dicke gravity

According to Lovelock’s theorem, the Hilbert–Einstein and the Lovelock actions are indistinguishable from their field equations. However, they have different scalar-tensor counterparts, which correspond to the Brans–Dicke and the Lovelock–Brans–Dicke (LBD) gravities, respectively. In this paper the LBD model of alternative gravity with the Lagrangian density ${{\mathcal{L}}}_{\mathrm{LBD}}=\frac{1}{16\pi }\left[\phi \left(R+\frac{a}{\sqrt{-g}}{}^{*}{RR}+b{ \mathcal G }\right)-\frac{{\omega }_{{\rm{L}}}}{\phi }{{\rm{\nabla }}}_{\alpha }\phi {{\rm{\nabla }}}^{\alpha }\phi \right]$ is developed, where *RR and ${ \mathcal G }$ respectively denote the topological Chern–Pontryagin and Gauss–Bonnet invariants. The field equation, the kinematical and dynamical wave equations, and the constraint from energy–momentum conservation are all derived. It is shown that the LBD gravity reduces to general relativity in the limit ${\omega }_{{\rm{L}}}\to \infty $ unless the ‘topological balance condition’ holds, and in vacuum it can be conformally transformed into the dynamical Chern–Simons gravity and the generalized Gauss–Bonnet dark energy with Horndeski-like or Galileon-like kinetics. Moreover, the LBD gravity allows for the late-time cosmic acceleration without dark energy. Finally, the LBD gravity is generalized into the Lovelock-scalar-tensor gravity, and its equivalence to fourth-order modified gravities is established. It is also emphasized that the standard expressions for the contributions of generalized Gauss–Bonnet dependence can be further simplified.
Collaborative Brain-Computer Interface for Human Interest Detection in Complex and Dynamic Settings

Humans can fluidly adapt their interest in complex environments in ways that machines cannot. Here, we lay the groundwork for a real-world system that passively monitors and merges neural correlates of visual interest across team members via Collaborative Brain Computer Interface (cBCI). When group interest is detected and co-registered in time and space, it can be used to model the task relevance of items in a dynamic, natural environment. Previous work in cBCIs focuses on static stimuli, stimulus-or response-locked analyses, and often within-subject and experiment model training. The contributions of this work are twofold. First, we test the utility of cBCI on a scenario that more closely resembles natural conditions, where subjects visually scanned a video for target items in a virtual environment. Second, we use an experiment-agnostic deep learning model to account for the real-world use case where no training set exists that exactly matches the end-users' task and circumstances. With our approach we show improved performance as the number of subjects in the cBCI ensemble grows, and the potential to reconstruct ground-truth target occurrence in an otherwise noisy and complex environment.
The Computational Complexity of the Lorentz Lattice Gas

The Lorentz lattice gas is studied from the perspective of computational complexity theory. It is shown that using massive parallelism, particle trajectories can be simulated in a time that scales logarithmically in the length of the trajectory. This result characterizes the “logical depth” of the Lorentz lattice gas and allows us to compare it to other models in statistical physics.
A SAMPLE OF OB STARS THAT FORMED IN THE FIELD

We present a sample of 14 OB stars in the Small Magellanic Cloud that meet strong criteria for having formed under extremely sparse star-forming conditions in the field. These stars are a minimum of 28 pc in projection from other OB stars, and they are centered within symmetric, round H II regions. They show no evidence of bow shocks, implying that the targets are not transverse runaway stars. Their radial velocities relative to local H I also indicate that they are not line-of-sight runaway stars. A friends-of-friends analysis shows that nine of the objects present a few low-mass companion stars, with typical mass ratios for the two highest-mass stars of around 0.1. This further substantiates that these OB stars formed in place, and that they can and do form in extremely sparse conditions. This poses strong constraints on theories of star formation and challenges proposed relations between cluster mass and maximum stellar mass.
Drivers of Supplier Participation in Ride-Hailing Platforms

Ride-hailing platforms such as Uber offer service suppliers more flexible work conditions but lower security than permanent jobs. This study examines the preferences of ride-hailing drivers when th...
THE RHIC AZIMUTH QUADRUPOLE: "PERFECT LIQUID" OR GLUONIC RADIATION?

Large elliptic flow at RHIC seems to indicate that ideal hydrodynamics provides a good description of Au–Au collisions, at least at the maximum RHIC energy. The medium formed has been interpreted as a nearly perfect (low-viscosity) liquid, and connections have been made to gravitation through string theory. Recently, claimed observations of large flow fluctuations comparable to participant eccentricity fluctuations seem to confirm the ideal hydro scenario. However, determination of the azimuth quadrupole with 2D angular autocorrelations, which accurately distinguish "flow" (quadrupole) from "nonflow" (minijets), contradicts conventional interpretations. Centrality trends may depend only on the initial parton geometry, and methods used to isolate flow fluctuations are sensitive instead mainly to minijet correlations. The results presented in this paper suggest that the azimuth quadrupole may be a manifestation of gluonic multipole radiation.
Hydrogen-poor Disks in Compact X-Ray Binaries

We show that accretion disks in several compact X-ray binaries with hydrogen-depleted donors are likely subject to a thermal ionization instability, unless they are strongly irradiated. These disks are particularly interesting in that their MHD-turbulent properties in the neutral phase may be quite different from those of standard, hydrogen-rich disks.
COMPARISON OF MILLIMETER-WAVE AND X-RAY EMISSION IN SEYFERT GALAXIES

We compare the emission at multiple wavelengths of an extended Seyfert galaxy sample, including both types of Seyfert nuclei. We use the Caltech Submillimeter Observatory to observe the CO J = 2-1 transition line in a sample of 45 Seyfert galaxies and detect 35 of them. The galaxies are selected by their joint soft X-ray (0.1-2.4 keV) and far-infrared (λ = 60-100 μm) emission from the ROSAT/IRAS sample. Since the CO line widths (W_(CO)) reflect the orbital motion in the gravitational potential of the host galaxy, we study how the kinematics are affected by the central massive black hole (BH), using the X-ray luminosity. A significant correlation is found between the CO line width and hard (0.3-8 keV from Chandra and XMM-Newton) X-ray luminosity for both types of Seyfert nuclei. Assuming an Eddington accretion to estimate the BH mass (M_(BH)) from the X-ray luminosity, the W_(CO)-L_X) relation establishes a direct connection between the kinematics of the molecular gas of the host galaxy and the nuclear activity, and corroborates the previous studies that show that the CO is a good surrogate for the bulge mass. We also find a tight correlation between the (soft and hard) X-ray and the CO luminosities for both Seyfert types. These results indicate a direct relation between the molecular gas (i.e., star formation activity) of the host galaxy and the nuclear activity. To establish a clear causal connection between molecular gas and the fueling of nuclear activity, high-resolution maps (<100 pc) of the CO emission of our sample will be required and provided in a forthcoming Atacama Large Millimeter Array observation.
A Second Law for higher curvature gravity

The Second Law of black hole thermodynamics is shown to hold for arbitrarily complicated theories of higher curvature gravity, so long as we allow only linearized perturbations to stationary black holes. Some ambiguities in Wald’s Noether charge method are resolved. The increasing quantity turns out to be the same as the holographic entanglement entropy calculated by Dong. It is suggested that only the linearization of the higher curvature Second Law is important, when consistently truncating a UV-complete quantum gravity theory.
Modeling Photoionized Turbulent Material in the Circumgalactic Medium. II. Effect of Turbulence within a Stratified Medium

The circumgalactic medium (CGM) of nearby star-forming galaxies shows clear indications of OVI absorption accompanied by little to no detectable NV absorption. This unusual spectral signature, accompanied by highly non-uniform absorption from lower ionization state species, indicates that the CGM must be viewed as a dynamic, multiphase medium, such as occurs in the presence of turbulence. Motivated by previous isotropic turbulent simulations, we carry out chemodynamical simulations of stratified media in a Navarro-Frenk-White (NFW) gravitational potential with a total mass of $10^{12}$ solar masses and turbulence that decreases radially. The simulations assume a metallicity of 0.3 solar, a redshift zero metagalatic UV background, and they track ionizations, recombinations, and species-by-species radiative cooling using the MAIHEM package. We compare a suite of ionic column densities with the COS-Halos sample of low-redshift star-forming galaxies. Turbulence with an average one-dimensional velocity dispersion approximately 40 km/s, corresponding to an energy injection rate of approximately $10^{49}$ erg/yr, produces a CGM that matches many of the observed ionic column densities and ratios. In this simulation, the NVI to OVI ratio is suppressed from its equilibrium value due to a combination of radiative cooling and cooling from turbulent mixing. This level of turbulence is consistent with expectations from observations of better constrained, higher-mass systems, and could be sustained by energy input from supernovae, gas inflows, and dynamical friction from dark matter subhalos. We also conduct a higher resolution run which yields smaller-scale structures, but remains in agreement with observations.
Some Bright Stars with Smooth Continua for Calibrating the Response of High-resolution Spectrographs

When characterizing a high resolution echelle spectrograph, for instance for precise Doppler work, it is useful to observe featureless sources such as quartz lamps or hot stars to determine the response of the instrument. Such sources provide a way to determine the blaze function of the orders, pixel-to-pixel variations in the detector, fringing in the system, and other important characteristics.
Eclipsing Stellar Binaries in the Galactic Center

Compact stellar binaries are expected to survive in the dense environment of the Galactic center. The stable binaries may undergo Kozai–Lidov oscillations due to perturbations from the central supermassive black hole (Sgr A*), yet the general relativistic precession can suppress the Kozai–Lidov oscillations and keep the stellar binaries from merging. However, it is challenging to resolve the binary sources and distinguish them from single stars. The close separations of the stable binaries allow higher eclipse probabilities. Here, we consider the massive star SO-2 as an example and calculate the probability of detecting eclipses, assuming it is a binary. We find that the eclipse probability is ~30%–50%, reaching higher values when the stellar binary is more eccentric or highly inclined relative to its orbit around Sgr A*.
M(atrix)-theory scattering in the noncommutative (2,0) theory

We study the Quantum-Mechanics on the hyper-Kahler manifold that is the blow-up of an A1-singularity. This system is relevant for M(atrix)-theory as it was conjectured to describe scattering in the ``noncommutative'' deformation of a free 5+1D tensor multiplet in the sector with two units of longitudinal light-like momentum.
The hypertoric intersection cohomology ring

We present a functorial computation of the equivariant intersection cohomology of a hypertoric variety, and endow it with a natural ring structure. When the hyperplane arrangement associated with the hypertoric variety is unimodular, we show that this ring structure is induced by a ring structure on the equivariant intersection cohomology sheaf in the equivariant derived category. The computation is given in terms of a localization functor which takes equivariant sheaves on a sufficiently nice stratified space to sheaves on a poset.
Spaces and groups with conformal dimension greater than one

We show that if a complete, doubling metric space is annularly linearly connected, then its conformal dimension is greater than one, quantitatively. As a consequence, we answer a question of Bonk and Kleiner: if the boundary of a one-ended hyperbolic group has no local cut points, then its conformal dimension is greater than one
A Combinatorial Methodology for Optimizing Non-Binary Graph-Based Codes: Theoretical Analysis and Applications in Data Storage

Non-binary (NB) low-density parity-check (LDPC) codes are graph-based codes that are increasingly being considered as a powerful error correction tool for modern dense storage devices. Optimizing NB-LDPC codes to overcome their error floor is one of the main code design challenges facing storage engineers upon deploying such codes in practice. Furthermore, the increasing levels of asymmetry incorporated by the channels underlying modern dense storage systems, e.g., multi-level Flash systems, exacerbate the error floor problem by widening the spectrum of problematic objects that contribute to the error floor of an NB-LDPC code. In a recent research, the weight consistency matrix (WCM) framework was introduced as an effective combinatorial NB-LDPC code optimization methodology that is suitable for modern Flash memory and magnetic recording (MR) systems. The WCM framework was used to optimize codes for asymmetric Flash channels, MR channels that have intrinsic memory, in addition to canonical symmetric additive white Gaussian noise channels. In this paper, we provide an in-depth theoretical analysis needed to understand and properly apply the WCM framework. We focus on general absorbing sets of type two (GASTs) as the detrimental objects of interest. In particular, we introduce a novel tree representation of a GAST called the unlabeled GAST tree, using which we prove that the WCM framework is optimal in the sense that it operates on the minimum number of matrices, which are the WCMs, to remove a GAST. Then, we enumerate WCMs and demonstrate the significance of the savings achieved by the WCM framework in the number of matrices processed to remove a GAST. Moreover, we provide a linear-algebraic analysis of the null spaces of WCMs associated with a GAST. We derive the minimum number of edge weight changes needed to remove a GAST via its WCMs, along with how to choose these changes. In addition, we propose a new set of problematic objects, namely oscillating sets of type two (OSTs), which contribute to the error floor of NB-LDPC codes with even column weights on asymmetric channels, and we show how to customize the WCM framework to remove OSTs. We also extend the domain of the WCM framework applications by demonstrating its benefits in optimizing column weight 5 codes, codes used over Flash channels with additional soft information, and spatially coupled codes. The performance gains achieved via the WCM framework range between 1 and nearly 2.5 orders of magnitude in the error floor region over interesting channels.
Secure Zones: An Attribute-Based Encryption advisory system for safe firearms

This work presents an application of the highly expressive Attribute-Based Encryption to implement Secure Zones for firearms. Within these zones, radio-transmitted local policies based on attributes of the user and the firearm are received by embedded hardware in the firearms, which then advises the user about safe operations. The Secure Zones utilize Attribute-Based Encryption to encode the policies and user attributes, and providing privacy and security through it cryptography. We describe a holistic approach to evolving the firearm to a cyber-physical system to aid in augmenting safety. We introduce a conceptual model for a firearm equipped with sensors and a context-aware software agent. Based on the information from the sensors, the agent can access the context and inform the user of potential unsafe operations. To support Secure Zones and the cyber-physical firearm model, we propose a Key Infrastructure Scheme for key generation, distribution, and management, and a Context-Aware Software Agent Framework for Firearms.
Properties of the electrostatically driven helical plasma state

A novel plasma state has been found [Akcay et al., Phys. Plasmas 24, 052503 (2017)] in the presence of a uniform applied axial magnetic field in periodic cylindrical geometry. This state is driven by external electrostatic fields provided by helical electrodes with a (m=1,n=1) (helical) symmetry where m and n represent the poloidal and axial harmonics. The resulting plasma is a function of the cylinder radius r<rw and helical angle u=mθ−nζ, where θ is the poloidal angle, and ζ=z/R is the normalized axial coordinate in the context of a periodic cylinder. In this reference, the strongly driven form of the state was found to have a strong axial mean current density, with a mean-field line safety factor q0(r) just above the pitch of the electrodes m/n=1 in the interior, where the plasma is nearly force-free. However, at the edge the current density has a component perpendicular to the magnetic field B. This perpendicular current density drives nearly Alfvenic helical plasma flows, a notable feature of these s...
An Estimate of the Yield of Single-transit Planetary Events from the Transiting Exoplanet Survey Satellite

We present a semi-analytic estimate of the expected yield of single-transit planets from the Transiting Exoplanet Survey Satellite (TESS). We use the TESS Candidate Target List 6 (CTL-6) as an input catalog of over 4 million sources. We predict that from the 200,000 stars selected to be observed with the high-cadence postage stamps with the highest CTL-6 priority, there will be 241 single-transit events caused by planets detectable at a signal-to-noise ratio of SNR$\ge7.3$. We find a lower limit of an additional 977 events caused by single-transit planets in the full frame images (FFI); this is a lower limit because the CTL-6 is incomplete below a TESS magnitude of $T>12$. Of the single-transit events from the postage stamps and FFIs, 1091/1218 will have transit depths deeper than 0.1%, and will thus be amenable for photometric follow-up from the ground, and 1195/1218 will have radial velocity signals greater than 1 m/s. We estimate that the periods of 146 single transits will be constrained to better than 10% using the TESS photometry assuming circular orbits. We find that the number of planets detected by TESS in the postage stamps with periods $P>25$ days will be doubled by including single-transiting planets, while the number of planets with $P>250$ days will be increased by an order of magnitude. We predict 79 habitable zone planets from single-transits, with 18 orbiting FGK stars.
A universal coefficient theorem for twisted K-theory

In this paper, we recall the definition of twisted K-theory in various settings. We prove that for a twist $\tau$ corresponding to a three dimensional integral cohomology class of a space X, there exist a "universal coefficient" isomorphism K_{*}^{\tau}(X)\cong K_{*}(P_{\tau})\otimes_{K_{*}(\mathbb{C}P^{\infty})} \hat{K}_{*} where $P_\tau$ is the total space of the principal $\mathbb{C}P^{\infty}$-bundle induced over X by $\tau$ and $\hat K_*$ is obtained form the action of $\mathbb{C}P^{\infty}$ on K-theory.