cssi/SciSciGPT-SciSciNet huggingface dataset:
Critical slowing-down as indicator of approach to the loss of stability

We consider stochastic electro-mechanical dynamics of an overdamped power system in the vicinity of the saddle-node bifurcation associated with the loss of global stability such as voltage collapse or phase angle instability. Fluctuations of the system state vector are driven by random variations of loads and intermittent renewable generation. In the vicinity of collapse the power system experiences so-called phenomenon of critical slowing-down characterized by slowing and simultaneous amplification of the system state vector fluctuations. In generic case of a co-dimension 1 bifurcation corresponding to the threshold of instability it is possible to extract a single mode of the system state vector responsible for this phenomenon. We characterize stochastic fluctuations of the system state vector using the formal perturbative expansion over the lowest (real) eigenvalue of the system power flow Jacobian and verify the resulting expressions for correlation functions of the state vector by direct numerical simulations. We conclude that the onset of critical slowing-down is a good marker of approach to the threshold of global instability. It can be straightforwardly detected from the analysis of single-node autostructure and autocorrelation functions of system state variables and thus does not require full observability of the grid.
Topological Entropy and Secondary Folding

A convenient measure of a map or flow’s chaotic action is the topological entropy. In many cases, the entropy has a homological origin: it is forced by the topology of the space. For example, in simple toral maps, the topological entropy is exactly equal to the growth induced by the map on the fundamental group of the torus. However, in many situations the numerically computed topological entropy is greater than the bound implied by this action. We associate this gap between the bound and the true entropy with ‘secondary folding’: material lines undergo folding which is not homologically forced. We examine this phenomenon both for physical rod stirring devices and toral linked twist maps, and show rigorously that for the latter secondary folds occur.
Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

Semidefinite Programming (SDP) and Sums-of-Squ- ares (SOS) relaxations have led to certifiably optimal non-minimal solvers for several robotics and computer vision problems. However, most non-minimal solvers rely on least squares formulations, and, as a result, are brittle against outliers. While a standard approach to regain robustness against outliers is to use robust cost functions, the latter typically introduce other non-convexities, preventing the use of existing non-minimal solvers. In this letter, we enable the simultaneous use of non-minimal solvers and robust estimation by providing a general-purpose approach for robust global estimation, which can be applied to any problem where a non-minimal solver is available for the outlier-free case. To this end, we leverage the Black-Rangarajan duality between robust estimation and outlier processes (which has been traditionally applied to early vision problems), and show that graduated non-convexity ( GNC ) can be used in conjunction with non-minimal solvers to compute robust solutions, without requiring an initial guess. we demonstrate the resulting robust non-minimal solvers in applications, including point cloud and mesh registration, pose graph optimization, and image-based object pose estimation (also called shape alignment ). Our solvers are robust to 70–80% of outliers, outperform RANSAC , are more accurate than specialized local solvers, and faster than specialized global solvers. We also propose the first certifiably optimal non-minimal solver for shape alignment using SOS relaxation.
Gonality of random graphs

The gonality of a graph is a discrete analogue of the similarly named geometric invariant of algebraic curves. Motivated by recent progress in Brill‐Noether theory for graphs, we study the gonality of random graphs. In particular, we show that the gonality of a random graph is asymptotic to the number of vertices.
Gaussianization and eigenvalue statistics for Random quantum channels (III)

In this paper, we present applications of the calculus developed in Collins and Nechita [Comm. Math. Phys. 297 (2010) 345–370] and obtain an exact formula for the moments of random quantum channels whose input is a pure state thanks to Gaussianization methods. Our main application is an in-depth study of the random matrix model introduced by Hayden and Winter [Comm. Math. Phys. 284 (2008) 263–280] and used recently by Brandao and Horodecki [Open Syst. Inf. Dyn. 17 (2010) 31–52] and Fukuda and King [J. Math. Phys. 51 (2010) 042201] to refine the Hastings counterexample to the additivity conjecture in quantum information theory. This model is exotic from the point of view of random matrix theory as its eigenvalues obey two different scalings simultaneously. We study its asymptotic behavior and obtain an asymptotic expansion for its von Neumann entropy.
Existence and non-existence of transition fronts in mixed ignition-monostable media

We study transition fronts for one-dimensional reaction–diffusion equations with compactly-perturbed ignition-monostable reactions. We establish an almost sharp condition on reactions which characterizes the existence and non-existence of fronts. In particular, we prove that a strong inhomogeneity in the reaction prevents formation of transition fronts, while a weak inhomogeneity gives rise to a front. Our work extends the results and methods introduced in Nolen et al 2012 (Arch. Ration. Mech. Anal. 203 217–46), which studied the same question in inhomogeneous KPP media.
A Photometric and Kinematic Study of AWM 7

We have measured redshifts and Kron-Cousins R-band magnitudes for a sample of galaxies in the poor cluster AWM 7. We have measured redshifts for 172 galaxies; 106 of these are cluster members. We determine the luminosity function (LF) from a photometric survey of the central 1.2 × 1.2 h-1 Mpc. The LF has a bump at the bright end and a faint-end slope of α = -1.37 ± 0.16, populated almost exclusively by absorption-line galaxies. The cluster velocity dispersion is lower in the core (~530 km s-1) than at the outskirts (~680 km s-1), consistent with the cooling flow seen in the X-ray. The cold core extends ~150 h-1 kpc from the cluster center. The Kron-Cousins R-band mass-to-light ratio of the system is 650 ± 170 h M⊙/L⊙, substantially lower than previous optical determinations, but consistent with most previous X-ray determinations. We adopt H0 = 100 h km s-1 Mpc-1 throughout this paper; at the mean cluster redshift (5247 ± 76 km s-1), 1 h-1 Mpc subtends 655.
Semantic modeling of analytic-based relationships with Direct Qualification

Successfully modeling state and analytics-based semantic relationships of documents enhances thoroughness of representation, contextualization of importance and relevancy, posterity of provenance, and a delineation of priority for a document. These attributes are the core elements that form the machine-based knowledge representation for documents. However, modeling document relationships that can change over time can be inelegant, limited, complex or overly burdensome for semantic technologies. In this paper, we present Direct Qualification (DQ), an approach for modeling any semantically referenced document, concept, or named graph with results from associated applied analytics. The proposed approach supplements the traditional subject-object relationships by providing a third leg to the relationship; the qualification of how and why the relationship exists. To illustrate, we show a prototype of an event-based system with a realistic use case for applying DQ to relevancy analytics of PageRank and Hyperlink-Induced Topic Search (HITS).
AN ANALYSIS OF JITTER AND TRANSIT TIMING VARIATIONS IN THE HAT-P-13 SYSTEM

If the two planets in the HAT-P-13 system are coplanar, the orbital states provide a probe of the internal planetary structure. Previous analyses of radial velocity and transit timing data for the system suggested that the observational constraints on the orbital states were rather small. We reanalyze the available data, treating the jitter as an unknown MCMC parameter, and find that a wide range of jitter values are plausible, hence the system parameters are less well constrained than previously suggested. For slightly increased levels of jitter (~4.5 m s?1), the eccentricity of the inner planet can be in the range 0 < e inner < 0.07, the period and eccentricity of the outer planet can be 440 days < P outer < 470 days and 0.55 < e outer < 0.85, respectively, while the relative pericenter alignment, ?, of the planets can take essentially any value ?180? < ? < +180?. It is therefore difficult to determine whether e inner and ? have evolved to a fixed-point state or a limit cycle or to use e inner to probe the internal planetary structure. We perform various transit timing variation (TTV) analyses, demonstrating that current constraints merely restrict e outer < 0.85, and rule out relative planetary inclinations within ~2? of i rel = 90?, but that future observations could significantly tighten the restriction on both these parameters. We demonstrate that TTV profiles can readily distinguish the theoretically favored inclinations of i rel = 0? and 45?, provided that sufficiently precise and frequent transit timing observations of HAT-P-13b can be made close to the pericenter passage of HAT-P-13c. We note the relatively high probability that HAT-P-13c transits and suggest observational dates and strategies.
Helium Reionization Simulations. II. Signatures of Quasar Activity on the IGM

We have run a new suite of simulations that solve hydrodynamics and radiative transfer simultaneously to study helium II reionization. Our suite of simulations employs various models for populating quasars inside of dark matter halos, which affect the He II reionization history. In particular, we are able to explore the impact that differences in the timing and duration of reionization have on observables. We examine the thermal signature that reionization leaves on the IGM, and measure the temperature-density relation. As previous studies have shown, we confirm that the photoheating feedback from helium II reionization raises the temperature of the IGM by several thousand kelvin. To compare against observations, we generate synthetic Ly$\alpha$ forest sightlines on-the-fly and match the observed effective optical depth $\tau_{\mathrm{eff}}(z)$ of hydrogen to recent observations. We show that when the simulations have been normalized to have the same values of $\tau_\mathrm{eff}$, the effect that helium II reionization has on observations of the hydrogen Ly$\alpha$ forest is minimal. Specifically, the flux PDF and the one-dimensional power spectrum are sensitive to the thermal state of the IGM, but do not show direct evidence for the ionization state of helium. We show that the peak temperature of the IGM typically corresponds to the time of 90%-95% helium ionization by volume, and is a relatively robust indicator of the timing of reionization. Future observations of helium reionization from the hydrogen Ly$\alpha$ forest should thus focus on measuring the temperature of the IGM, especially at mean density. Detecting the peak in the IGM temperature would provide valuable information about the timing of the end of helium II reionization.
A Class of Series Acceleration Formulae for Catalan's Constant

In this note, we develop transformation formulae and expansions for the log tangent integral, which are then used to derive series acceleration formulae for certain values of Dirichlet L-functions, such as Catalan's constant. The formulae are characterized by the presence of an infinite series whose general term consists of a linear recurrence damped by the central binomial coefficient and a certain quadratic polynomial. Typically, the series can be expressed in closed form as a rational linear combination of Catalan's constant and π times the logarithm of an algebraic unit.
Parallel Toolkit for Measuring the Quality of Network Community Structure

Many networks display community structure which identifies groups of nodes within which connections are denser than between them. Detecting and characterizing such community structure, which is known as community detection, is one of the fundamental issues in the study of network systems. It has received a considerable attention in the last years. Numerous techniques have been developed for both efficient and effective community detection. Among them, the most efficient algorithm is the label propagation algorithm whose computational complexity is O (|E|). Although it is linear in the number of edges, the running time is still too long for very large networks, creating the need for parallel community detection. Also, computing community quality metrics for community structure is computationally expensive both with and without ground truth. However, to date we are not aware of any effort to introduce parallelism for this problem. In this paper, we provide a parallel toolkit to calculate the values of such metrics. We evaluate the parallel algorithms on both distributed memory machine and shared memory machine. The experimental results show that they yield a significant performance gain over sequential execution in terms of total running time, speedup, and efficiency.
Theory of Disk Accretion onto Magnetic Stars

Disk accretion onto magnetic stars occurs in a variety of systems, including accreting neutron stars (with both high and low magnetic fields), white dwarfs, and pro- tostars. We review some of the key physical processes in magnetosphere-disk interaction, highlighting the theoretical uncertainties. We also discuss some applications to the obser- vations of accreting neutron star and protostellar systems, as well as possible connections to protoplanetary disks and exoplanets.
X-Vision: An Augmented Vision Tool with Real-Time Sensing Ability in Tagged Environments

We present the concept of X-Vision, an enhanced Augmented Reality (AR)-based visualization tool, with the realtime sensing capability in a tagged environment. We envision that this type of a tool will enhance the user-environment interaction and improve the productivity in factories, smartspaces, home & office environments, maintenance/facility rooms and operation theatres, etc. In this paper, we describe the design of this visualization system built upon combining the object's pose information estimated by the depth camera and the object's ID & physical attributes captured by the RFID tags. We built a physical prototype of the system demonstrating the projection of 3D holograms of the objects encoded with sensed information like water-level and temperature of common office/household objects. The paper also discusses the quality metrics used to compare the pose estimation algorithms for robust reconstruction of the object's 3D data.
On Polyhedral Product Spaces over Polyhedral Joins

The construction of a simplicial complex given by polyhedral joins (introduced by Anton Ayzenberg), generalizes Bahri, Bendersky, Cohen and Gitler's $J$-construction and simplicial wedge construction. This article gives a cohomological decomposition of a polyhedral product over a polyhedral join for certain families of pairs of simplicial complexes. A formula for the Hilbert-Poincare series is given, which generalizes Ayzenberg's formula for the moment-angle complex.
How Much Information is in a Jet

Machine learning techniques are increasingly being applied toward data analyses at the Large Hadron Collider, especially with applications for discrimination of jets with different originating particles. Previous studies of the power of machine learning to jet physics have typically employed image recognition, natural language processing, or other algorithms that have been extensively developed in computer science. While these studies have demonstrated impressive discrimination power, often exceeding that of widely-used observables, they have been formulated in a non-constructive manner and it is not clear what additional information the machines are learning. In this paper, we study machine learning for jet physics constructively, expressing all of the information in a jet onto sets of observables that completely and minimally span N-body phase space. For concreteness, we study the application of machine learning for discrimination of boosted, hadronic decays of Z bosons from jets initiated by QCD processes. Our results demonstrate that the information in a jet that is useful for discrimination power of QCD jets from Z bosons is saturated by only considering observables that are sensitive to 4-body (8 dimensional) phase space.
MODELS OF OPINION FORMATION: INFLUENCE OF OPINION LEADERS

This paper studies the evolution of the distribution of opinions in a population of individuals in which there exist two distinct subgroups of highly-committed, well-connected opinion leaders endowed with a strong convincing power. Each individual, located at a vertex of a directed graph, is characterized by her name, the list of people she is interacting with, her level of awareness, and her opinion. Various temporal evolutions according to different local rules are compared in order to find under which conditions the formation of strongly polarized subgroups, each adopting the opinion of one of the two groups of opinion leaders, is favored.
Unitarity of the Modular Tensor Categories Associated to Unitary Vertex Operator Algebras, I

This is the first part in a two-part series of papers constructing a unitary structure for the modular tensor category (MTC) associated to a unitary rational vertex operator algebra (VOA). Given a rational VOA, we know that its MTC is constructed using the (finite dimensional) vector spaces of intertwining operators of this VOA. Moreover, the tensor-categorical structures can be described by the monodromy behaviors of the intertwining operators. Thus, constructing a unitary structure for the MTC of a unitary rational VOA amounts to defining an inner product on each (finite dimensional) vector space of intertwining operators, and showing that the monodromy matrices of the intertwining operators (e.g. braiding matrices, fusion matrices) are unitary under these inner products. In this paper, we develop necessary tools and techniques for constructing our unitary structures. This includes giving a systematic treatment of one of the most important functional analytic properties of the intertwining operators: the energy bounds condition. On the one side, we give some useful criteria for proving the energy bounds condition of intertwining operators. On the other side, we show that energy bounded intertwining operators can be smeared to give rise to (unbounded) closed operators. We prove that the (well-known) braid relations and adjoint relations for unsmeared intertwining operators have the corresponding smeared versions. We also give criteria on the strong commutativity between smeared intertwining operators and smeared vertex operators localized in disjoint open intervals of S1 (the strong intertwining property). Besides investigating the energy bounds condition, we also study certain genus 0 geometric properties of intertwining operators. Most importantly, we prove the convergence of certain mixed products-iterations of intertwining operators. Many useful braid and fusion relations will also be discussed.
On the quasi-stationary distribution of the Shiryaev–Roberts diffusion

ABSTRACTWe consider the diffusion generated by the equation with fixed, and where μ≠0 is given, and is standard Brownian motion. We assume that is stopped at with A>0 preset, and obtain a closed-from formula for the quasi-stationary distribution of , i.e., the limit , x∈[0,A]. Further, we also prove QA(x) to be unimodal for any A>0, and obtain its entire moment series. More importantly, the pair with r≥0 and A>0 is the well-known Generalized Shiryaev–Roberts change-point detection procedure, and its characteristics for r∼QA(x) are of particular interest, especially when A>0 is large. In view of this circumstance, we offer an order-three large-A asymptotic approximation of QA(x) valid for all x∈[0,A]. The approximation is rather accurate even if A is lower than what would be considered “large” in practice.
Coherent quantum dynamics in donor–bridge–acceptor systems: beyond the hopping and super-exchange mechanisms

The population transfer dynamics of model donor–bridge–acceptor systems is studied by comparing a recently developed polaron-transformed quantum master equation (PQME) with the well-known Redfield and Forster theories of quantum transport. We show that the PQME approach reduces to these two theories in their respective limits of validity and naturally interpolates between them as a function of the system–bath coupling strength. By exploring the parameter space of our model problem, we identify novel regimes of transport dynamics in bridged systems like those encountered in biological and organic energy transfer problems. Furthermore, we demonstrate that three-level systems like the ones studied herein represent ideal minimal models for the identification of quantum coherent transport as embodied in super-exchange phenomena that cannot be captured by Forster-like hopping approaches.
Advances in the optimization of silicon-based thermoelectrics: a theory perspective

Thermoelectric devices convert temperature gradients into electrical power and vice versa, thus enabling energy scavenging from waste heat, sensing, and cooling. Yet, many of these attractive applications are hindered by the limited efficiency of thermoelectric materials, especially in the low-temperature regime. This review provides a summary of the recent advances in the design of new efficient silicon-based thermoelectric materials through nanostructuring, alloying, and chemical optimization, emphasizing the contribution from theory and atomistic modeling.
Umbral dots observed in photometric images taken with 1.6 m solar telescope

Umbral dots (UDs) were observed using the 1.6 meter solar telescope. Achieved conventional diffraction limit in the TiO 705.68 nm spectral line used was 0.001. The 418 UDs were analysed. Median diameter was 0 .005 and median intensity difference between darkest part of the UD's background and brightest part of the UDs was 37%. Despite the achieved resolution, no UDs substructures were visible. The analysed UDs appeared to be circular.
Comprehensive numerical modeling of filamentary RRAM devices including voltage ramp-rate and cycle-to-cycle variations

The equilibrium ON and OFF states of resistive random access memory (RRAM) are due to formation and destruction of a conducting filament. The laws of thermodynamics dictate that these states correspond to the minimum of free energy. Here, we develop a numerical model that, through the minimization of free energy at a given voltage, determines the filament parameters and thus the electric current. Overall, it simulates the current-voltage (I-V) characteristics of RRAM. The model describes mutual transformations of RRAM states through SET (ON →OFF) and RESET (OFF →ON) processes. From the modeling perspectives, these states and processes constitute four programing modules constructed here in COMSOL multiphysics software tackling the electrodynamic and heat transfer equations and yielding RRAM energy and I-V. Our modeling uniquely reproduces the observed I-V varying with voltage ramp-rates. This is achieved by accounting for the ramp-rate dependent activation energy of conduction. The underlying mechanism is due to the deformation interaction caused by the double well atomic potentials universally present in amorphous materials and having exponentially broad distribution of relaxation times. As another unique feature, our modeling reproduces the observed cycle-to-cycle variations of RRAM parameters attributed to the lack of self-averaging in small ensembles of double well potentials and electronic states in geometrically small (nano-sized) RRAM structures.
Desingularized fiber products of semi-stable elliptic surfaces with vanishing third Betti number

Desingularized fiber products of semi-stable elliptic surfaces with Hetale3=0 are classified. Such varieties may play a role in the study of supersingular threefolds, of the deformation theory of varieties with trivial canonical bundle, and of arithmetic degenerations of rigid Calabi–Yau threefolds.
Membership Inference Attacks on Sequence-to-Sequence Models: Is My Data In Your Machine Translation System?

Data privacy is an important issue for “machine learning as a service” providers. We focus on the problem of membership inference attacks: Given a data sample and black-box access to a model’s API,...
Demand Shaping in Cellular Networks

Demand shaping is a promising way to mitigate the wireless cellular capacity shortfall in the presence of ever-increasing wireless data demand. In this paper, we formulate demand shaping as an optimization problem that minimizes the variation in aggregate traffic. We design a distributed and randomized offline demand shaping algorithm under complete traffic information and prove its almost sure convergence. We further consider a more realistic setting where the traffic information is incomplete but the future traffic can be predicted to a certain degree of accuracy. We design an online demand shaping algorithm that updates the schedules of deferrable applications each time when new information is available, based on solving at each timeslot an optimization problem over a shrinking horizon from the current time to the end of the day. We compare the performance of the online algorithm against the optimal offline algorithm and provide numerical examples to complement the theoretical analysis.
Asymmetric Dark Matter: Theories, Signatures, and Constraints

We review theories of Asymmetric Dark Matter (ADM), their cosmological implications and detection. While there are many models of ADM in the literature, our review of existing models will center on highlighting the few common features and important mechanisms for generation and transfer of the matter–anti-matter asymmetry between dark and visible sectors. We also survey ADM hidden sectors, the calculation of the relic abundance for ADM, and how the DM asymmetry may be erased at late times through oscillations. We consider cosmological constraints on ADM from the cosmic microwave background, neutron stars, the Sun, and brown and white dwarves. Lastly, we review indirect and direct detection methods for ADM, collider signatures, and constraints.
Global Multiclass Classification and Dataset Construction via Heterogeneous Local Experts

In the domains of dataset construction and crowdsourcing, a notable challenge is to aggregate labels from a heterogeneous set of labelers, each of whom is potentially an expert in some subset of tasks (and less reliable in others). To reduce costs of hiring human labelers or training automated labeling systems, it is of interest to minimize the number of labelers while ensuring the reliability of the resulting dataset. We model this as the problem of performing $K$ -class classification using the predictions of smaller classifiers, each trained on a subset of $[K]$ , and derive bounds on the number of classifiers needed to accurately infer the true class of an unlabeled sample under both adversarial and stochastic assumptions. By exploiting a connection to the classical set cover problem, we produce a near-optimal scheme for designing such configurations of classifiers which recovers the well known one-vs.-one classification approach as a special case. Experiments with the MNIST and CIFAR-10 datasets demonstrate the favorable accuracy (compared to a centralized classifier) of our aggregation scheme applied to classifiers trained on subsets of the data. These results suggest a new way to automatically label data or adapt an existing set of local classifiers to larger-scale multiclass problems.
How do I sequence therapy for follicular lymphoma

In the past decade, many new agents have been introduced for the management of follicular lymphoma, and therapeutic strategies have evolved over time. The clinical benefits of the different treatments vary and, at the time of progression, are influenced by patient and disease characteristics, the duration of the interval from last treatment, and the nature of the treatments previously administered. Altogether, this results in a marked heterogeneity of clinical situations encountered during the treatment of these patients. Despite numerous trials performed in the field, there is no single standard of care for patients undergoing second-line treatment or beyond. Furthermore, patients recruited in these studies have characteristics that rarely represent the full spectrum of possible clinical presentations. Therefore, to optimally individualize treatment, all of the risks (short- and long-term) and benefits of the available options should be well known. Discussing the goals of therapy with the patient at each intervention is also critical in providing an optimal sequence of therapy.
Towards Streaming Perception.

Embodied perception refers to the ability of an autonomous agent to perceive its environment so that it can (re)act. The responsiveness of the agent is largely governed by latency of its processing pipeline. While past work has studied the algorithmic trade-off between latency and accuracy, there has not been a clear metric to compare different methods along the Pareto optimal latency-accuracy curve. We point out a discrepancy between standard offline evaluation and real-time applications: by the time an algorithm finishes processing a particular image frame, the surrounding world has changed. To these ends, we present an approach that coherently integrates latency and accuracy into a single metric for real-time online perception, which we refer to as “streaming accuracy”. The key insight behind this metric is to jointly evaluate the output of the entire perception stack at every time instant, forcing the stack to consider the amount of streaming data that should be ignored while computation is occurring. More broadly, building upon this metric, we introduce a meta-benchmark that systematically converts any image understanding task into a streaming perception task. We focus on the illustrative tasks of object detection and instance segmentation in urban video streams, and contribute a novel dataset with high-quality and temporally-dense annotations. Our proposed solutions and their empirical analysis demonstrate a number of surprising conclusions: (1) there exists an optimal “sweet spot” that maximizes streaming accuracy along the Pareto optimal latency-accuracy curve, (2) asynchronous tracking and future forecasting naturally emerge as internal representations that enable streaming image understanding, and (3) dynamic scheduling can be used to overcome temporal aliasing, yielding the paradoxical result that latency is sometimes minimized by sitting idle and “doing nothing”.
Management of acute cardiac tamponade following a transcatheter heart intervention.

I read with interest the manuscript by Masroor and co-authors on the strategy of surgical repair for left atrial appendage perforation following implantation of Watchman device. The authors present the successful management of this complications and they comment on the preferred therapeutic strategy. This is a particular sensitive subject nowadays, since the widespread use and the constant growth of a variety of transcatheter cardiac interventions has inevitably increased the number of patients who are exposed to this type of complication.
Dipolar evaporation of reactive molecules to below the Fermi temperature

The control of molecules is key to the investigation of quantum phases, in which rich degrees of freedom can be used to encode information and strong interactions can be precisely tuned1. Inelastic losses in molecular collisions2–5, however, have greatly hampered the engineering of low-entropy molecular systems6. So far, the only quantum degenerate gas of molecules has been created via association of two highly degenerate atomic gases7,8. Here we use an external electric field along with optical lattice confinement to create a two-dimensional Fermi gas of spin-polarized potassium–rubidium (KRb) polar molecules, in which elastic, tunable dipolar interactions dominate over all inelastic processes. Direct thermalization among the molecules in the trap leads to efficient dipolar evaporative cooling, yielding a rapid increase in phase-space density. At the onset of quantum degeneracy, we observe the effects of Fermi statistics on the thermodynamics of the molecular gas. These results demonstrate a general strategy for achieving quantum degeneracy in dipolar molecular gases in which strong, long-range and anisotropic dipolar interactions can drive the emergence of exotic many-body phases, such as interlayer pairing and p-wave superfluidity. A strongly interacting gas of polar molecules is created by combining an electric field with two-dimensional optical confinement, enabling evaporative cooling and opening up the exploration of low-entropy many-body phases.
Centrality with Diversity

Graph centrality measures use the structure of a network to quantify central or "important" nodes, with applications in web search, social media analysis, and graphical data mining generally. Traditional centrality measures such as the well known PageRank interpret a directed edge as a vote in favor of the importance of the linked node. We study the case where nodes may belong to diverse communities or interests and investigate centrality measures that can identify nodes that are simultaneously important to many such diverse communities. We propose a family of diverse centrality measures formed as fixed point solutions to a generalized nonlinear eigenvalue problem. Our measure can be efficiently computed on large graphs by iterated best response and we study its normative properties on both random graph models and real-world data. We find that we are consistently and efficiently able to identify the most important diverse nodes of a graph, that is, those that are simultaneously central to multiple communities.
Uncommonly accurate energies for the general quartic oscillator

Recent advances in the asymptotic analysis of energy levels of potentials produce relative errors in eigenvalue sums of order $10^{-34}$, but few non-trivial potentials have been solved numerically to such accuracy. We solve the general quartic potential (arbitrary linear combination of $x^2$ and $x^4$ ) beyond this level of accuracy using a basis of several hundred oscillator states. We list the lowest 20 eigenvalues for 9 such potentials. We confirm the known asymptotic expansion for the levels of the pure quartic oscillator, and extract the next 2 terms in the asymptotic expansion. We give analytic formulas for expansion in up to 3 even basis states. We confirm the virial theorem for the various energy components to similar accuracy. The sextic oscillator levels are also given. These benchmark results should be useful for extreme tests of approximations in several areas of chemical physics and beyond.
Keyhole Imaging:Non-Line-of-Sight Imaging and Tracking of Moving Objects Along a Single Optical Path

Non-line-of-sight (NLOS) imaging and tracking is an emerging technology that allows the shape or position of objects around corners or behind diffusers to be recovered from transient, time-of-flight measurements. However, existing NLOS approaches require the imaging system to scan a large area on a visible surface, where the indirect light paths of hidden objects are sampled. In many applications, such as robotic vision or autonomous driving, optical access to a large scanning area may not be available, which severely limits the practicality of existing NLOS techniques. Here, we propose a new approach, dubbed keyhole imaging, that captures a sequence of transient measurements along a single optical path, for example, through a keyhole. Assuming that the hidden object of interest moves during the acquisition time, we effectively capture a series of time-resolved projections of the object's shape from unknown viewpoints. We derive inverse methods based on expectation-maximization to recover the object's shape and location using these measurements. Then, with the help of long exposure times and retroreflective tape, we demonstrate successful experimental results with a prototype keyhole imaging system.
Stiffening transition in asymmetric lipid bilayers: The role of highly ordered domains and the effect of temperature and size

Cellular membranes consist of a large variety of lipids and proteins, with a composition that generally differs between the two leaflets of the same bilayer. One consequence of this asymmetry is thought to be the emergence of differential stress, i.e., a mismatch in the lateral tension of the two leaflets. This can affect a membrane’s mechanical properties; for instance, it can increase the bending rigidity once the differential stress exceeds a critical threshold. Using coarse-grained molecular dynamics simulations based on the MARTINI model, we show that this effect arises due to the formation of more highly ordered domains in the compressed leaflet. The threshold asymmetry increases with temperature, indicating that the transition to a stiffened regime might be restricted to a limited temperature range above the gel transition. We also show that stiffening occurs more readily for larger membranes with smaller typical curvatures, suggesting that the stiffening transition is easier to observe experimentally than in the small-scale systems accessible to simulation.
From Twitter to traffic predictor: Next-day morning traffic prediction using social media data

Abstract The effectiveness of traditional traffic prediction methods, such as autoregressive or spatio-temporal models, is often extremely limited when forecasting traffic dynamics in early morning. The reason is that traffic can break down drastically during the early morning commute, and the time and duration of this break-down vary substantially from day to day. Early morning traffic forecast is crucial to inform morning-commute traffic management, but they are generally challenging to predict in advance, particularly by midnight (called ‘next-day morning traffic prediction’ thereafter). In this paper, we propose to mine Twitter messages as a probing method to understand the impacts of people’s work and rest patterns in the evening/midnight of the previous day to the next-day morning traffic. The model is tested on freeway networks in Pittsburgh as experiments. The resulting relationship is surprisingly simple and powerful. We find that, in general, the earlier people rest as indicated from Tweets, the more congested roads will be in the next morning. The occurrence of big events in the evening before, represented by higher or lower tweet sentiment than normal, often implies lower travel demand in the next morning than normal days. Besides, people’s tweeting activities in the night before and early morning (by 5am) are statistically associated with congestion in morning peak hours. We make use of such relationships to build a predictive framework which forecasts morning commute congestion using people’s tweeting profiles extracted by 5am. In most cases, the tweet information collected by the midnight before is sufficient to make good prediction for next-day morning traffic. The Pittsburgh study supports that this framework can precisely predict morning congestion, particularly for some road segments upstream of roadway bottlenecks with large day-to-day congestion variation, while its prediction performance being no worse than baseline methods on other roads. Through experiments, we demonstrate our approach considerably outperforms those existing methods without Twitter message features, and it can learn meaningful representation of demand from tweeting profiles that offer managerial insights. The proposed social media empowered framework can be a promising tool for real-time traffic management and potentially extended for traffic prediction at other times of day.
Vitamin B12 malabsorption and pseudo- thrombotic microangiopathy in an adolescent

Abstract Thrombotic microangiopathies (TMAs) are a group of rare disorders that can be considered life threatening. The hallmark of this disease is a microangiopathic hemolytic anemia associated with thrombocytopenia which could be congenital or acquired. Acquired vitamin B12 deficiency is overlooked in developed countries but if severe, can mimic a TMA. We report the case of 17-year-old male with celiac disease who presented with a week of fatigue and jaundice. Initial evaluation revealed pancytopenia and hemolysis with a preliminary differential concerning for a myelodysplastic process or a thrombotic microangiopathy. There was no evidence of renal failure, or neurological changes and his hemoglobin stabilized with transfusion therapy. Subsequent bone marrow testing confirmed absence of malignancy or infiltrative processes. B12 levels were found to be undetectable and once replaced his signs and symptoms resolved. Replacement supported the diagnosis of a Vitamin B12 deficiency induced pseudo-thrombotic microangiopathy. When faced with a clinical presentation of a TMA in a child or an adolescent patient, physicians must be aware of the possibility of vitamin B12 deficiency especially in patients at risk for malabsorption.
Towards Totally Asynchronous Primal-Dual Convex Optimization in Blocks

We present a parallelized primal-dual algorithm for solving constrained convex optimization problems. The algorithm is "block-based," in that vectors of primal and dual variables are partitioned into blocks, each of which is updated only by a single processor. We consider four possible forms of asynchrony: in updates to primal variables, updates to dual variables, communications of primal variables, and communications of dual variables. We explicitly construct a family of counterexamples to rule out permitting asynchronous communication of dual variables, though the other forms of asynchrony are permitted, all without requiring bounds on delays. A first-order update law is developed and shown to be robust to asynchrony. We then derive convergence rates to a Lagrangian saddle point in terms of the operations agents execute, without specifying any timing or pattern with which they must be executed. These convergence rates contain a synchronous algorithm as a special case and are used to quantify an "asynchrony penalty." Numerical results illustrate these developments.
Scalable FastMDP for Pre-departure Airspace Reservation and Strategic De-conflict

Pre-departure flight plan scheduling for Urban Air Mobility (UAM) and cargo delivery drones will require on-demand scheduling of large numbers of aircraft. We examine the scalability of an algorithm known as FastMDP which was shown to perform well in deconflicting many dozens of aircraft in a dense airspace environment with terrain. We show that the algorithm can adapted to perform first-come-first-served pre-departure flight plan scheduling where conflict free flight plans are generated on demand. We demonstrate a parallelized implementation of the algorithm on a Graphics Processor Unit (GPU) which we term FastMDP-GPU and show the level of performance and scaling that can be achieved. Our results show that on commodity GPU hardware we can perform flight plan scheduling against 2000-3000 known flight plans and with server-class hardware the performance can be higher. We believe the results show promise for implementing a large scale UAM scheduler capable of performing on-demand flight scheduling that would be suitable for both a centralized or distributed flight planning system
Permanent Employee Attitudes Toward Temporary Employment

The present study investigated the attitudes that a sample of permanent state employees working in the United States (n=100) held toward temporary employment. A simultaneous regression analysis revealed that certain demographic variables differentially predicted attitude scores for the sample. The researchers found that age, level of education, and household size predicted attitudes toward temporary employment. A full inter-item correlation matrix for the attitudinal measure including internal reliability estimates and descriptive statistics for all variables measured used in the study is included, and the simultaneous regression results are reported.
Precautionary Savings and Self-Selection: Evidence from the German Reunification “Experiment”

In the absence of complete insurance, expected future income shocks lead prudent individuals to build up precautionary savings in order to avoid wide fluctuations in the consumption path. The reaction of savings to expected future shocks is stronger, the more risk averse an individual is. Risk aversion might influence not only the savings behavior of an individual facing a stochastic income path, but it can also affect occupational choice in the first place. In particular, risk averse individuals might choose occupations that are associated with less risky income paths, while less risk averse individuals might prefer occupations with higher income risk. Assessing the importance of self-selection of individuals into occupations according to their risk aversion is difficult, since risk aversion is usually unobserved. Yet, failing to control for unobserved risk aversion in regressions of wealth on measures of labor income risk will lead to a bias if selfselection takes place, since measures of labor income risk will be negatively correlated with the error term that is capturing the unobserved risk aversion. This could lead to a rejection of the theory of precautionary savings, even if individuals act according to the theory.
Distributive Justice and Distributed Obligations

Collectivities can have obligations beyond the aggregate of pre-existing obligations of their members. Certain such collective obligations distribute , i.e., become members’ obligations to do their fair share. In incremental good cases, i.e., those in which a member’s fair share would go part way toward fulfilling the collectivity’s obligation, each member has an unconditional obligation to contribute.States are involuntary collectivities that bear moral obligations. Certain states, democratic legal states , are collectivities whose obligations can distribute. Many existing states are democratic legal states, but none satisfies more rigorous requirements of distributive justice. There, citizens who hold assets, in excess of what is just, bear a distributed duty to dedicate that excess toward correcting the injustice. It is an incremental good case not conditioned on the conformity of others who are also wealthier than justice allows, nor on the diligence of the state in meeting its obligations.
Developing a framework to improve retail category management through category captain arrangements

Abstract Manufacturers and retailers have divergent profit objectives. A manufacturer wants to maximize the profits of its own brands. The retailer, on the other hand, wants to maximize the profit of the entire product category. In spite of these apparently diverging profit objectives, both manufacturers and retailers are increasingly realizing that profit margins of both can be increased through cooperation rather than confrontation. Category management is one such cooperative strategy that often involves the appointment of a leading manufacturer as the “category captain”. A category captain advises the retailer on the best way to price, display, and promote products in a category, including those of the competitors. This arrangement, therefore, ensures retail efficiency but raises doubt about possible misuse of power by the category captain to circumvent fair competition. In this paper, we outline the antitrust concerns about this arrangement, and provide a framework that effectively addresses these concerns.